Archives of General Psychiatry

Barton, David A.;Esler, Murray D.;Dawood, Tye;Lambert, Elisabeth A.;Haikerwal, Deepak;Brenchley, Celia;Socratous, Florentia;Hastings, Jacqueline;Guo, Ling;Wiesner, Glen;Kaye, David M.;Bayles, Richard;Schlaich, Markus P.;Lambert, Gavin W.

doi: 10.1001/archgenpsychiatry.2007.11pmid: 18180427

Abstract Context The biological basis for the development of major depressive disorder (MDD) remains incompletely understood. Objective To quantify brain serotonin (5-hydroxytryptamine [5-HT]) turnover in patients with MDD. Design Patients with depression were studied both untreated and during administration of a selective serotonin reuptake inhibitor (SSRI) in an unblinded study of sequential design. Healthy volunteers were examined on only 1 occasion. Direct internal jugular venous blood sampling was used to directly quantify brain serotonin turnover. The effect of serotonin transporter (5-HTT) genotype on brain serotonin turnover was evaluated and the influence of SSRI therapy on serotonin turnover was investigated. Setting Participants were recruited from the general community following media advertisement. Experimental procedures were performed in the research catheterization laboratory of a major training hospital and medical research institute. Participants Studies were performed in 21 patients fulfilling the DSM-IV and International Statistical Classification of Diseases, 10th Revision diagnostic criteria for MDD and in 40 healthy volunteers. Interventions Treatment for patients consisted of SSRI administration for approximately 12 weeks. Main Outcome Measures Brain serotonin turnover before and after SSRI therapy. Results Brain serotonin turnover was significantly elevated in unmedicated patients with MDD compared with healthy subjects (mean [SD] internal jugular venoarterial 5-hydroxyindoleacetic acid plasma concentration difference, 4.4 [4.3] vs 1.6 [2.4] nmol/L, respectively; P = .003). Analysis of the influence of the 5-HTT genotype in MDD indicated that carriage of the s allele compared with the l allele was associated with greater than a 2-fold increase in brain serotonin turnover (mean [SD] internal jugular venoarterial 5-hydroxyindoleacetic acid plasma concentration difference, 6.5 [4.7] vs 2.7 [2.9] nmol/L, respectively; P = .04). Following SSRI therapy, brain serotonin turnover was substantially reduced (mean [SD] internal jugular venoarterial 5-hydroxyindoleacetic acid plasma concentration difference, 6.0 [4.0] nmol/L prior to treatment vs 2.0 [3.3] nmol/L following therapy; P = .008). Conclusions Brain serotonin turnover is elevated in unmedicated patients with MDD and is influenced by the 5-HTT genotype. The marked reduction in serotonin turnover following SSRI treatment and the accompanying improvement in symptoms suggest that high brain serotonin turnover may be a biological substrate of MDD. The etiology of major depressive disorder (MDD) has been linked to brain monoaminergic neuronal dysfunction.1,2 Of particular interest is the role of brain serotonin (5-hydroxytryptamine [5-HT]) in MDD. The diversity of roles played by serotonin coupled with the lack of a demonstrated relationship between different clinical presentations and biochemical abnormalities has hampered the development of sensitive markers of the disease. Indeed, brain serotonin-releasing neurons subserve diverse although incompletely understood functions related to emotions and behavior, feeding and adiposity,3 and light stimulation.4 We have previously demonstrated influences of obesity and feeding5 and season and sunlight6 on brain serotonin turnover in humans. The principal means of intraneuronal metabolism of serotonin is via oxidative deamination by monoamine oxidase resulting in formation of 5-hydroxyindoleacetic acid (5-HIAA) (Figure 1). Deamination followed by reduction, conjugation with sulfate or glucuronide, and N-acetylation represent minor metabolic pathways of serotonin.10,11 Brain serotonin turnover, where turnover refers to the rate of synthesis of the transmitter, is difficult to assess in humans. The brain is the source of less than 10% of 5-HIAA found in plasma and urine,12 rendering peripheral venous plasma measurements and urine collections unsuitable for studying brain serotonin turnover. Given our group's longstanding expertise in direct intravenous catheterization techniques, we used a method originally described by Maas et al13-15 with percutaneously placed venous sampling catheters positioned high in an internal jugular vein in order to quantify the turnover of central nervous system monoamine neurotransmitters. Earlier investigations from our group documenting similar cerebral norepinephrine and metabolite internal jugular venous overflows in healthy subjects and in patients with autonomic failure in whom there was existing biochemical evidence of almost complete postganglionic sympathetic denervation16 provided the justification that our internal jugular venous metabolites measured emanate from central neurons and not from cerebrovascular sympathetic nerves.17 In previous articles, we documented the importance of subcortical norepinephrine in the regulation of sympathetic activity in patients with heart failure18 and hypertension19 and reported reduced brain norepinephrine and dopamine turnover in patents with treatment-refractory depression.20 In this study, we examined brain serotonin turnover in healthy subjects and in unmedicated patients with MDD. To facilitate interpretation of brain serotonin turnover measurements in the patients with MDD, serotonin transporter (5-HTT) genotyping was also performed. The 5-HTT gene (GenBank accession No. SLC6A4) is subject to a 44–base pair deletion-insertion promoter region polymorphism that may influence gene activity.21 We hypothesized that the presence of the short form of the gene might increase serotonin turnover rates through impairment of neuronal serotonin reuptake. In addition, in 11 patients with MDD, jugular venous sampling was performed twice, first while patients were untreated and then during treatment with a selective serotonin reuptake inhibitor (SSRI). This was done to ascertain whether treatment response under SSRI dosing was associated with normalization of any abnormality in brain serotonin turnover that might be present. Methods Participants Data were obtained from 21 patients (9 men and 12 women; mean [SD] age, 45 [12] years) fulfilling the DSM-IV and International Statistical Classification of Diseases, 10th Revision diagnostic criteria for MDD and from 40 healthy volunteers (31 men and 9 women; mean [SD] age, 41 [19] years). Patients with MDD and healthy volunteers were recruited through media advertisements. Patients were either newly diagnosed or currently untreated after a relapse and had not been receiving antidepressants or benzodiazepines for at least 4 weeks prior to the study (5 weeks if they had been receiving fluoxetine hydrochloride). Eight of the patients had never been treated with antidepressants prior to this trial. The remaining patients had previously received antidepressant medications; 10 of them had stopped receiving medication more than 12 months prior to the investigation (2 of whom had previously been receiving fluoxetine), 1 of them had stopped 9 months prior, and 2 of them had stopped 6 weeks prior. Following initial telephone screening, patients were interviewed by a psychiatrist (D.A.B.) using a structured clinical interview (Mini International Neuropsychiatric Interview [MINI]22). The 17-item Hamilton Depression Scale (HAM-D),23 Spielberger's State and Trait Anxiety Inventories,24,25 and the Beck Depression Inventory (BDI)26 were used to assess severity and monitor response to treatment. Patients were eligible for inclusion if they fulfilled criteria for MDD on the MINI, had HAM-D and BDI scores of 18 or higher, and were assessed as having MDD as the primary illness at psychiatric interview. Patient selection attempted to minimize psychiatric comorbidity. Possible comorbidity was evaluated with the Anxiety Disorders Interview Schedule for DSM-IV,27 which allows for discrimination between anxiety disorders as well as for the determination of primary and secondary diagnoses based on the participant's responses and severity scores on measures of symptoms. Ratings were considered to be clinically significant with a score of 4 or higher on the 8-point Likert-type scale, where 2 is mild, 4 is moderate, 6 is severe, and 8 is very severe. Patients with comorbid panic or anxiety disorders were included in the study if the primary diagnosis was depression and any panic or anxiety was secondary to their depression. All of the participants had a clinical examination to exclude any previously undiagnosed medical conditions. Patients were excluded if they had coexisting heart disease, diabetes, medicated hypertension, alcohol or drug abuse or dependence, or infectious disease; had a comorbid psychotic disorder, eating disorder, mental retardation, personality disorder, or epilepsy; or had a current high suicide risk. Suicide risk was assessed using the MINI, the BDI (question 9), and evaluation of current risk by a psychiatrist (D.A.B.) during the initial clinical interview. Patients having previously failed to respond to SSRI treatment at the maximum tolerated dose for at least 4 weeks were excluded from the study. Four of the patients with MDD were current smokers and none in the control group were smokers. Initial research studies were performed within 10 days of a confirmed diagnosis of MDD. Following the initial investigation, 11 patients commenced treatment with an SSRI (citalopram hydrobromide, n = 7; sertraline hydrochloride, n = 2; fluoxetine, n = 2). The choice of SSRI was based on clinical grounds and was made by the psychiatrist in consultation with the participant. The dosage was determined according to clinical response. No structured psychotherapy was provided to the patient either within or external to the study. Repeat research studies with blood sampling from the same internal jugular vein were performed after approximately 12 weeks of therapy (mean [SD] duration of therapy, 98 [7] days). Patients were examined weekly for the purposes of the study or more frequently if required on clinical grounds. Significant clinical improvement was defined as a decrease of more than 50% in HAM-D scores and remission was defined as a HAM-D score lower than 8. By appropriate selection and matching of a healthy reference population, with matching of healthy subjects and patients with MDD in terms of body mass index (calculated as the weight in kilograms divided by the height in meters squared) and sunlight hours on the study day, we were able to avoid a confounding effect of serotonergic neuronal systems activated by sunlight6 and in obesity.5 The mean (SD) body mass index was 25 (1) in patients with MDD and 24 (1) in healthy subjects. With the assistance of the Melbourne Bureau of Meteorology,6 healthy volunteers were chosen from a large pool of subjects to achieve matching for sunlight hours on the day of the catheter sampling study (mean [SD] sunlight hours, 6.6 [0.8] hours in patients with MDD and 6.0 [0.6] hours in the reference population). Healthy subjects were studied on only 1 occasion. Central venous catheterization procedure All of the catheter studies were performed with subjects in the supine position according to previously described methods.17,20 Caffeinated beverages, alcohol, and tobacco smoking were prohibited for the 12 hours preceding the catheter study. Under local anesthesia, the radial artery was cannulated for arterial pressure monitoring and blood sampling. A venous introducer sheath was placed in the antecubital fossa. Subsequently, a 6F coronary sinus angiographic catheter (Cordis Europa, Roden, the Netherlands) was introduced via the antecubital venous sheath and placed under fluoroscopic control in the right (n = 19 patients with MDD, n = 28 control subjects) or left (n = 2 patients with MDD, n = 12 control subjects) internal jugular vein. The antecubital access on the same side as the sampled jugular vein was used in each case. The face and scalp have a rich blood supply and the venous drainage into the internal jugular vein is typically via the supratrochlear and supraorbital veins, which combine to form the facial vein.28 Given that the facial vein enters the internal jugular vein near the greater cornu of the hyoid bone, the internal jugular venous catheter was advanced beyond the mandibular angle upstream to points of entry of veins draining the face and neck to minimize any contamination of the cerebral venous effluent.28 The catheter was used for sampling internal jugular vein blood. Thirty milliliters of blood was simultaneously obtained from the arterial and internal jugular catheters. Measurement of brain serotonin turnover The metabolism of serotonin is achieved almost exclusively via the actions of monoamine oxidase and aldehyde dehydrogenase, resulting in the formation of 5-HIAA. Venoarterial plasma 5-HIAA concentration gradients were used as indicators of brain serotonin turnover.12 Plasma 5-HIAA concentrations were determined by high-performance liquid chromatography coupled with coulometric detection as previously described.12 The interassay and intra-assay coefficients of variation for 5-HIAA were ±6% and ±2%, respectively. The assay was linear within the physiological range, with a sensitivity (signal to noise ratio of 3) of 50 pg. 5-htt genotyping The human 5-HTT, encoded by a single gene on chromosome 17q11.2, is expressed in both the brain and peripheral blood cells. A 5-HTT–linked gene promoter region (5-HTTLPR) insertion-deletion polymorphism with long (l) and short (s) forms has been demonstrated to influence expression and function of the 5-HTT.21,29,30 Genomic DNA was isolated from whole blood using the Flexigene DNA Kit (Qiagen, Hilden, Germany). Genotyping for the 5-HTTLPR was performed after amplification by polymerase chain reaction using sense and antisense primers as previously described.21,30 The polymerase chain reaction products were resolved and the bands visualized by UV illumination. The identity of each band was confirmed by automated DNA sequencing. Plasma catecholamine determinations Given that activation of the sympathetic nervous system may be responsible for stress-related increases in brain tryptophan concentration,31 arterial norepinephrine and epinephrine concentrations were used as a marker of sympathetic nervous and sympathoadrenal activation. Plasma concentrations of norepinephrine and epinephrine were determined by high-performance liquid chromatography with electrochemical detection.32 Ethics considerations Given that this study involved the percutaneous placement of a central venous catheter and an arterial cannula in participants for whom this was not clinically indicated, comment on research ethics is in order. The central issues in clinical research ethics are the following: (1) the quality of the research, (2) the potential for harm to an individual from the experiment, and (3) the degree of safeguarding of the participants' autonomy. In this study, we investigated aspects of brain serotonergic function in patients with MDD that are potentially of clinical importance using well-established research methods. There is no less invasive method for validly doing this than we applied. In our extensive research experience with central venous catheters6,20,33-35 involving in excess of 2000 studies performed over more than 20 years, we have found the procedure to be invariably associated with negligible risk. Cardiologists who are experts in the technique always perform the procedures. The process of written consent, to which an honest, open, and explicit participant information sheet was central, conformed to the standards expected to preserve the autonomy of the participants. The research protocol conformed to the relevant guidelines of the National Health and Medical Research Council of Australia and was approved by the Alfred Hospital ethics review committee. Written informed consent was obtained from each subject prior to the study. Patients with MDD were not paid. Healthy subjects were reimbursed US $100. Statistical analyses All of the results unless otherwise specified are expressed as mean (standard deviation). Tests of significance were carried out using analysis of variance (1-way analysis of variance for comparison between patients with MDD and control subjects and repeated-measures analysis of variance for the effect of therapy) or distribution-free nonparametric tests. The possible relationship between variables was evaluated using least squares linear regression analysis. All of the statistical tests were 2-tailed and statistical significance was set at a probability level of .05. Results Patients with MDD were moderately to severely depressed with a mean (SD) HAM-D score of 25 (4) and a mean (SD) BDI score of 29 (8). They also had high levels of both state (mean [SD] score, 57 [12]) and trait (mean [SD] score, 62 [7]) anxiety. Approximately half of the patients had a positive family history of depression. On average, patients had experienced 2.3 previous episodes of depression, with 64% having had 2 or more previous episodes. In 3 patients this was their first episode. Eighteen percent of the population had a current episode duration shorter than 3 months, whereas 59% had a current episode duration longer than 12 months. In all of the patients, the primary disorder was MDD. Seven of the patients with MDD had comorbid (secondary) panic disorder and 10 had social phobia. No patients had generalized anxiety disorder or obsessive-compulsive disorder. Clinician-rated suicide risk (assessed during the clinical interview from the MINI) indicated that 14 of the patients were considered to be at low risk, 6 were at medium risk, and 1 was at high risk. The 1 patient at high risk was rated high on the MINI due to a previous suicide attempt but was felt not to be currently at significant risk by the psychiatrist at the initial interview. Analysis of the hemodynamic data and arterial plasma norepinephrine and epinephrine concentrations revealed no difference between patients with MDD and healthy subjects (Table). The arterial 5-HIAA plasma concentration did not differ between groups (mean [SD], 46 [21] nmol/L in patients with MDD vs 42 [19] nmol/L in control subjects; P = .48). Indicative of elevated brain serotonin turnover, the internal jugular venoarterial 5-HIAA plasma concentration gradient was significantly elevated in unmedicated patients with MDD as compared with control subjects (Figure 2) (mean [SD], 4.4 [4.3] vs 1.6 [2.4] nmol/L, respectively; P = .003). In patients with MDD, there was a trend only for the internal jugular venous 5-HIAA concentration gradient to be related to the severity of depression as indicated by the HAM-D rating (r = 0.35; P = .12). No effect of sex occurred on the internal jugular 5-HIAA concentration gradient in patients with MDD (mean [SD], 4.2 [4.9] nmol/L for women vs 4.6 [3.9] nmol/L for men; P = .82). The internal jugular venous 5-HIAA concentration gradient was not quantitatively linked to the assessed risk of suicide (P = .54). The mean (SD) internal jugular 5-HIAA concentration gradient was 5.6 (3.8) nmol/L in patients with comorbid panic disorder, whereas it was 3.5 (4.2) nmol/L in patients with comorbid social phobia. This difference was not significant (P = .32). In all of the subjects combined, there was no relationship between the internal jugular 5-HIAA concentration gradient and arterial norepinephrine (P = .18) or epinephrine (P = .91) level, systolic (P = .77) or diastolic (P = .25) blood pressure, or heart rate (P = .88). Analysis of the influence of the 5-HTT genotype in MDD indicated that carriage of the s allele compared with the l allele was associated with greater than a 2-fold increase in brain serotonin turnover (Figure 3) (mean [SD] internal jugular venoarterial 5-HIAA plasma concentration difference, 6.5 [4.7] vs 2.7 [2.9] nmol/L, respectively; P = .04). Nine patients had the ll genotype, 7 had the sl genotype, and 4 had the ss genotype. In 1 patient we were unable to amplify and resolve a fragment of appropriate size. Three of the 4 current smokers carried the s allele; hence, there was a trend for the current smokers to have a greater serotonin turnover than the nonsmokers (mean [SD] internal jugular venoarterial 5-HIAA plasma concentration difference, 7.5 [3.6] vs 3.7 [4.2] nmol/L, respectively; P = .08). In the 11 patients in whom we obtained matching post–SSRI treatment internal jugular vein blood samples, SSRI treatment resulted in a marked improvement in clinician- and patient-rated symptoms (during treatment: mean[SD] HAM-D score, 7 [5], P < .001; mean [SD] BDI score, 9 [5], P < .001; mean [SD] Trait and State Anxiety Inventory scores, 42 [12] and 40 [11], respectively, both P < .001). Brain serotonin turnover was substantially reduced in all but 1 patient following SSRI therapy (Figure 4) (mean [SD] internal jugular venoarterial 5-HIAA plasma concentration difference, 6.0 [4.0] nmol/L prior to treatment vs 2.0 [3.3] nmol/L following therapy; P = .008). Comment In this study, we used direct internal jugular venous blood sampling to examine brain serotonin turnover in patients with MDD. Perhaps surprisingly, brain serotonin turnover was substantially elevated in unmedicated patients with MDD, with serotonin turnover being particularly prominent in those patients who carried the short allele of the serotonin transporter. Given that arterial norepinephrine and epinephrine levels, blood pressure, and heart rate were not elevated during testing in the patients with MDD as well as the lack of an association between brain serotonin turnover and these parameters, it would seem that the difference between groups is not due to elevated situational stress in the patients with MDD. Following effective therapy with an SSRI, brain serotonin turnover was reduced to the level observed in healthy subjects. Recent data linking fenfluramine-stimulated serotonin release and diminished dysfunctional attitudes as well as showing an association between dysfunctional attitudes and an up-regulation of cortical serotonin 2A binding potential in patients with MDD36,37 support the conventional view that MDD is caused by a relative reduction in brain monoaminergic neuronal activity. While our combined observations of elevated internal jugular venous 5-HIAA concentration in unmedicated patients and reduced serotonin turnover following SSRI therapy appear to run counter to this thesis, an elevated rate of serotonin metabolism could represent a process by which the availability of serotonin to be released neuronally is lowered. Interestingly, Gjerris et al7 in their initial cerebrospinal fluid (CSF) study actually documented elevated serotonin levels in lumbar CSF in patients with depression. More recently, Sullivan and colleagues38 documented elevated CSF 5-HIAA levels in patients with MDD with comorbid panic disorder. While the study by Sullivan and colleagues was confined to examinations in female patients, we found no difference in internal jugular 5-HIAA concentrations between sexes. Consistent with elevated serotonin turnover in MDD, in an experimental model of depression, chronic stress was associated with an up-regulation of tryptophan hydroxylase expression in the dorsal raphe nucleus.39 Cerebrospinal fluid 5-HIAA levels are typically normal in nonsuicidal depressed patients but low in patients with a predisposition to violent suicide.40,41 Normal CSF 5-HIAA concentration in patients with MDD42-44 and in suicide attempters has also been described.45 Rosa-Neto and colleagues46 recently estimated serotonin synthesis using α-[11C]methyl-L-tryptophan, a synthetic analog of tryptophan taken up by serotonergic neurons, and concluded that reduced serotonin synthesis occurs in some parts of the brain in patients with MDD. These conflicting results may reflect diagnostic heterogeneity of the patients examined or the imprecision of using lumbar CSF as an index of brain neurotransmitter turnover. Lumbar CSF concentrations reflect only a small portion of total 5-HIAA production by the central nervous system.47 Moreover, there exists a substantial rostrocaudal 5-HIAA concentration gradient in CSF,48 with serotonin in lumbar CSF being derived from both the brain and the terminals of descending serotonergic neuronal projections to the spinal cord.49,50 Applying positron emission tomographic scanning methods in parallel with the jugular venous technique would be instructive. Positron emission tomographic studies, ideally using a variety of serotonergic ligands, should provide regional measures of receptor occupancy that would be complementary to the measures of serotonin turnover based on jugular venous sampling. Indicative of the complexity of serotonergic regulation in the brain, positron emission tomographic examinations have revealed influences of sex51 and age52 on binding potential of various radiolabeled ligands. While serotonin 2 binding potential is not increased in untreated depressed subjects who have not made recent suicide attempts,53 recent articles36,37 have documented elevated cortical serotonin 2 receptor binding potential in patients with dysfunctional attitudes. To appropriately interpret our results, one must appreciate the mechanisms involved in neurotransmitter turnover. The terms release, spillover, and turnover are often used interchangeably but do refer to distinct processes (Figure 1). To maintain neuronal stores of neurotransmitter under steady-state conditions, the rate of serotonin synthesis must equal the rate of serotonin turnover, where turnover specifically denotes the depletion of previously synthesized stores of serotonin. Hence, in the brain, cerebral serotonin turnover may be estimated from the sum of differences in rates at which serotonin and its metabolites enter and leave the cerebral circulation. In CSF, 5-HIAA concentrations are approximately 200 times that of serotonin,7 thereby rendering 5-HIAA levels an approximation of serotonin turnover. Given that 5-HIAA is effectively a terminal metabolite, the prime determinants of outward flux at steady state are the brain concentration and production rate. Infusion of radiolabeled 5-HIAA would have allowed a more formal application of the Fick principle with measurement of the outward flux of the metabolite from the brain based on isotope dilution. 5-Hydroxyindoleacetic acid is produced by intraneuronal deamination (via monoamine oxidase A) of serotonin after either leakage of transmitter into the axoplasm from storage vesicles or reuptake of transmitter after exocytotic release; the contribution of the latter process is reflected by the decrease in 5-HIAA production after neuronal uptake blockade. Using carbon 11–labeled harmine and positron emission tomography, Meyer et al54 demonstrated a substantial elevation in monoamine oxidase A density in patients with MDD. Given the dependence of serotonin turnover on intraneuronal deamination, this observation is consistent with our data showing a substantial elevation in internal jugular venous 5-HIAA overflow in patients with MDD. It is important to point out that elevated monoamine oxidase A activity and a concomitant increase in serotonin turnover in the brain do not necessarily translate to a reduction in brain serotonin release. Increased metabolism without a concomitant elevation in the synthesis rate would lead to a rapid depletion of neurotransmitter stores. Elevated internal jugular 5-HIAA overflow in patients with MDD could occur as a result of augmented neuronal firing or secondary to either increased vesicular leakage or reduced capacity of vesicular uptake and subsequent intraneuronal metabolism. This latter explanation would be consistent with the proposal of reduced serotonergic activity being of primary importance in the etiology of MDD. Decreased vesicular monoamine transporter 2 protein expression in the brain in an animal model of depression has been described.55 Evidence implicating a role for vesicular monoamine transporter 2 in clinical MDD is scant. Given that serotonin may be accumulated into, metabolized, and released (as 5-HIAA) from sympathetic nerves in cerebral blood vessels56 and by uptake and metabolism by endothelial cells of the skeletal muscle vascular bed,57,58 it is important to consider possible extracerebral sources of 5-HIAA in plasma. Previous studies have demonstrated that up to 50% of intra-arterially infused serotonin is removed in a single passage through the hind limb of anesthetized dogs.57 Shepro and Hechtman57 proposed that it reflected uptake and metabolism by the endothelial cells of the skeletal muscle vascular bed. Moreover, tritium-labeled serotonin may be incorporated into nerve endings and subsequently released, spontaneously or by electrical stimulation,59 with the radioactivity being predominantly associated with 5-HIAA.56 This indicates that serotonin taken up into sympathetic nerves is subjected to intraneuronal oxidative deamination by monoamine oxidase A. While possible, we think it is unlikely that either the cerebrovascular sympathetic nerves or the vascular endothelium contributed markedly to the determined internal jugular 5-HIAA concentration gradients or accounted for the difference between values in healthy subjects and patients with MDD. Using regional blood sampling from a variety of vascular beds coupled with radiotracer-derived measurements of the rate of spillover of norepinephrine to plasma, we have previously demonstrated a significant relationship between regional sympathetic activity and 5-HIAA overflow only from the hepatosplanchnic bed.12 There was no relationship between sympathetic activity and 5-HIAA overflow from the skeletal muscle vascular bed. Importantly, with regard to a possible endothelial source of 5-HIAA, while studies using animal preparations57,59 have documented marked uptake of serotonin, 2 studies60,61 using human vascular preparations have demonstrated only a minor capacity of the human vascular endothelium to take up serotonin. The development of molecular, biochemical, and imaging techniques has yielded significant insights into the functioning of the serotonin transporter. Our finding of elevated internal jugular 5-HIAA overflow in depressed patients carrying the s allele of the 5-HTT gene is in agreement with the recent findings by Kishida and colleagues,62 who observed elevated 5-HIAA levels in the CSF of patients with MDD carrying the s allele. While it has been observed that 5-HTT expression and serotonin uptake are impaired with the presence of the short-form haplotype,21,30 studies in postmortem brain tissue demonstrated no relationship between 5-HTT binding potential and genotype in suicide victims.63 Moreover, using positron emission tomography, Shioe et al64 failed to reveal an association between 5-HTT binding and genotype in healthy individuals. This discrepancy in findings may be owing to the fact that functional single nucleotide variants exist in the s and l alleles.65 Indeed, a single-nucleotide variant (A to G) of the l allele has been shown to influence transporter function, with the long G (LG) variant being functionally similar to the s allele.66 Indeed, Praschak-Rieder and colleagues67 recently demonstrated that the long A/A variant was associated with elevated serotonin transporter binding density in the putamen compared with subjects who carried the LG allele. While we did not take into account the possibility of variation in the l allele, given that we observed elevated internal jugular 5-HIAA levels in patients who carried the s allele, further consideration of whether the ll patients carried the LG or LA allele may have strengthened our association. Our observation that current smokers, most of whom carried the s allele, tended to have higher serotonin turnover than nonsmokers is difficult to interpret given that tobacco smoking is associated with a diminution in brain monoamine oxidase A68 activity. On balance, the 5-HTT promoter polymorphism seems not to be associated with smoking behavior.69 The mechanisms underpinning the therapeutic effect of SSRIs remain incompletely understood. The knowledge that neuronal uptake blockade following antidepressant administration occurs rapidly but therapeutic effects may take from 2 to 6 weeks to occur70 has been difficult to reconcile both in terms of the etiology of the disease and the therapeutic mechanism of SSRIs. In agreement with our results documenting a reduction in internal jugular venous overflow of 5-HIAA following SSRI administration, improvement in symptoms coupled with a reduction in CSF 5-HIAA levels in patients with MDD following therapy with citalopram,71,72 venlafaxine hydrochloride,73 fluvoxamine, and fluoxetine43,74 have previously been described. Citalopram administration in chronically stressed rats normalizes the elevated expression of tryptophan hydroxylase.39 The commonly held view that desensitization of inhibitory presynaptic serotonin 1A autoreceptors is implicit in the therapeutic effect of SSRIs is not consistent with these data documenting a reduction in indices of brain serotonergic activity following long-term SSRI treatment. Given that serotonin 1A autoreceptors on the cell body do retain the capacity to inhibit serotonin release even after long-term SSRI administration (for review, see the article by Hjorth et al75), the reduction in internal jugular venous 5-HIAA levels that we have documented following treatment with SSRIs may reflect a long-term activation of serotonin 1A autoreceptors leading to a reduction in neuronal firing and serotonin release. Perhaps contrary to this view, Parsey and colleagues,76 using positron emission tomography, demonstrated a reduced serotonin 1A binding potential in patients with MDD who were previously exposed to antidepressant medications compared with drug-naive patients. Given the recent demonstration that serotonergic neurons may be heterogeneous with respect to their susceptibility to serotonin 1A–induced inhibition,77 the integration of these results may be more complicated than previously thought. In this study, using direct internal jugular venous sampling, we have demonstrated that brain serotonin turnover is elevated in unmedicated patients with MDD. Interestingly and consistent with the hypothesis that the activity of the 5-HTT is influenced by genotype, carriage of the 5-HTT s allele was associated with an approximately 2-fold increase in serotonin turnover. Whether elevated brain serotonin turnover occurs as a result of increased neuronal activity or enhanced vesicular leakage and subsequent intraneuronal metabolism remains unknown. Correspondence: Gavin W. Lambert, PhD, Human Neurotransmitters Laboratory, Baker Heart Research Institute, PO Box 6492, St Kilda Road Central, Melbourne, Victoria 8008, Australia ([email protected]). Submitted for Publication: March 1, 2007; final revision received May 31, 2007; accepted June 20, 2007. Author Contributions: Dr G. W. Lambert takes responsibility for the integrity of the data and the accuracy of the data analysis. Financial Disclosure: Drs Barton, Esler, and G. W. Lambert have given presentations and received honoraria from Servier, Solvay Pharmaceuticals, Wyeth Pharmaceuticals, and Pfizer. Dr Esler serves on the scientific advisory boards of Servier and Solvay Pharmaceuticals. Funding/Support: This study was supported by project grant 225121 from the National Health and Medical Research Council of Australia and by the Rotary Health Research Fund of Australia. Drs Esler, E. A. Lambert, Schlaich, and G. W. Lambert are supported by National Health and Medical Research Council career awards. Dr Dawood was supported by a postgraduate research scholarship from the National Heart Foundation of Australia. Lundbeck Australia provided cipramil for use in this study. Role of the Sponsor: The funding organizations played no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. References 1. 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Perlis, Roy H.;Purcell, Shaun;Fagerness, Jesen;Kirby, Andrew;Petryshen, Tracey L.;Fan, Jinbo;Sklar, Pamela

doi: 10.1001/archgenpsychiatry.2007.15pmid: 18180429

Abstract Context Association studies in bipolar disorder have been focused on a relatively narrow pool of candidate genes based on a limited understanding of the underlying pathophysiologic features. Recent developments suggest that a broader pool of genes may be associated with this disorder. Objective To examine the association between genes related to the lithium mechanism of action, as well as other positional and functional candidates, with bipolar I disorder. Design We examined a dense set of haplotype-tagging single-nucleotide polymorphisms using a gene-based test of association. Participants Three hundred seventy-nine parent-affected offspring trios. Results No genes specifically chosen to probe the action of lithium were associated with bipolar disorder. However, gene-based analysis of sialyltransferase 4A (SIAT4A), tachykinin receptor 1 (TACR1), and γ-aminobutyric acidA β2 receptor subunit (GABRB2) yielded evidence of association (empirical P value, <.005). Among 3 genes associated with schizophrenia or bipolar disorder in multiple previous studies, including dysbindin (DTNBP1), neuregulin (NRG1), and disrupted-in-schizophrenia 1 (DISC1), only DISC1 showed evidence of association in this cohort. In a secondary analysis of these 6 genes among parent-proband trios with a history of psychosis, evidence of the association with SIAT4A was strengthened. Conclusions These results suggest novel candidates and 1 gene (DISC1) previously associated with schizophrenia that merit further study in bipolar disorder. However, polymorphisms in major lithium-signaling genes do not appear to contribute substantially to bipolar liability. Bipolar disorder is common and disabling.1-3 Although environmental factors influence disease course,4 family and twin studies suggest it is highly heritable.5,6 A recent meta-analysis identified regions on chromosomes 6q and 8q with evidence of linkage to bipolar disorder, although individual linkage studies have generally yielded inconsistent results.7 Likewise, although multiple candidate genes have been reported to be associated with bipolar disorder, these genes frequently do not show evidence of association in independent cohorts. A primary obstacle to further candidate gene–based studies is the limited understanding of the pathophysiologic features of bipolar disorder at a cellular or molecular level, which hinders the selection of candidate genes with adequate prior probability of association. Some insight into the pathophysiologic features may come from consideration of the mechanism of action of an effective therapy for bipolar disorder such as lithium carbonate, which remains a first-line treatment.8-10 By analogy, genes involved in the mechanism of action of hypoglycemic agents in diabetes mellitus have been shown to confer risk for that disorder.11-13 Likewise, in major depressive disorder, the serotonergic mechanism of action of many antidepressants focused attention on the serotonin transporter gene, which was subsequently associated with risk for major depressive disorder.14 As indirect support of this approach in bipolar disorder, lithium treatment responsiveness has been associated with greater family loading for bipolar disorder,15,16 although not all studies observe this effect.17-19 Thus, genes associated with the lithium mechanism of action represent candidates for association with bipolar disorder itself. Although lithium's mechanisms of therapeutic action are not fully understood, the enzymatic pathways with which it interacts are increasingly well studied. Lithium interacts with 2 major cell-signaling pathways. In the first pathway, lithium inhibits recycling of inositol at multiple steps, thereby altering inositol 1,4,5-triphosphate– dependent second-messenger signaling.20-22 In the second pathway, lithium acts as a selective inhibitor of glycogen synthesis kinase 3β (GSK3B),22-25 influencing several downstream pathways including activation of the Wnt-signaling pathway.26-30 Perhaps most compellingly, mice that are haploinsufficient for GSK3B display behaviors similar to those of mice receiving long-term treatment with lithium.29 The GSK3B pathway has also been postulated to contribute to the observed neuroprotective effects of lithium.31 The 2 hypotheses are not mutually exclusive; for example, both pathways appear to converge on the serine/threonine kinase Akt-1 region.22 Genes in either of these 2 signaling pathways are therefore candidates for association with the risk for bipolar disorder. Three other lines of evidence implicate additional candidate genes in bipolar disorder. First, messenger RNA expression studies or similar paradigms have identified additional genes32-34 not belonging to 1 of the 2 pathways noted. Some of these are differentially regulated by lithium or by other traditional mood stabilizers, differentially expressed in the brains of patients with bipolar disorder (hereinafter referred to as bipolar patients), or yield proteins that are otherwise implicated in the mechanism of action of mood stabilizers. For example, genes related to oligodendrocyte differentiation or function exhibited differential expression in a postmortem study of bipolar patients,33 whereas the traditional mood stabilizer valproate sodium appears to influence histone deacetylation.34 Second, a small number of genes known to be expressed in the central nervous system lie under bipolar linkage peaks on 6q and 8q.7 Finally, a small number of genes have been shown in multiple studies to be associated with schizophrenia, including disrupted-in-schizophrenia 1 (DISC1),35,36 neuregulin (NRG1),37-39 and dysbindin (DTNBP1),40-44 and an overlap in liability with bipolar disorder has been suggested.39 Several other genes have also been associated with the risk of, or the pathways implicated in, schizophrenia or affective illness.14,45,46 Therefore, to identify genes associated with bipolar disorder liability, we conducted a family-based association study examining a select panel of candidate genes based on these hypotheses. Methods Sample description Patient samples were selected from the National Institute of Mental Health [NIMH] Genetics Collaborative Study of Bipolar Disorder waves 1 through 4, details of which have been previously reported.47 In brief, that study ascertained subjects in the following 2 ways: (1) first-degree probands with bipolar I disorder (BPI) and at least 1 first-degree relative with BPI or schizoaffective disorder, bipolar type (SAB), and (2) 2 first- or second-degree relatives with BPI or SAB, with at least 2 additional members of the extended family with BPI, SAB, bipolar II disorder (BPII), or recurrent major depressive disorder. In either approach, subjects with 2 parents with BPI or SAB were excluded. Diagnosis was determined using the Diagnostic Interview for Genetic Studies48 with best-estimate diagnosis assigned by 2 independent psychiatrists based on the Diagnostic Interview for Genetic Studies result, family informants, and review of medical records.47 For the present study, we initially identified all complete affected parent-proband trios for whom DNA was available from the Rutgers University repository (http://www.nimhgenetics.org) using a broad definition that included BPI, BPII, or SAB probands; from these, BPI parent-proband trios were selected for primary analyses, based on the most current phenotypic data available to us (NIMH release 3.05 [http://www.nimhgenetics.org]). Gene and single-nucleotide polymorphism selection Genes were selected from the following 3 broad categories based on a review of the literature: (1) implication in lithium signaling (n = 91, including 17 related primarily to inositol 1,4,5-triphosphate, 39 related primarily to GSK3B/Wnt signaling, and 35 others implicated by messenger RNA expression data or related approaches); (2) location under a bipolar disorder linkage peak (n = 10); and (3) previous evidence of association with or involvement in schizophrenia or mood disorders (n = 23, including 3 with replicated association in schizophrenia [DISC1, DTNBP1, and NRG1]). A fourth gene previously associated with schizophrenia, G72, was omitted because it had previously been studied in the NIMH cohort.49 In all, 124 genes spanning 11.8 megabases were selected with this approach (eTable 1). The single-nucleotide polymorphisms (SNPs) within the candidate genes were selected using a haplotype-tagging (or locus variation–tagging) approach. This approach identifies a set of nonredundant “tag” SNPs that capture common genetic variation in the designated region, allowing a more efficient screen than typing all SNPs in a region. The tagging approach has been shown to be efficient and powerful for association studies.50 In selecting tags, priority was given to known or putative functional SNPs, including exonic SNPs or promoter-region SNPs. First, genotypic data for all SNPs in regions encompassing each gene (including 10-kilobase [kb] 5′ and 10-kb 3′ flanking regions) were obtained from the International HapMap Project phase Ic public database (http://www.hapmap.org/). The bioinformatics software TAMAL51 was also used to identify putative functional SNPs in the same gene regions. The SNPs selected from the HapMap and TAMAL databases were submitted to the program Tagger50 to identify the subset to be used for tagging; parameters included a minimum coefficient of determination (r2) threshold of 0.8 and minimum minor allele frequency of 0.05. The SNPs selected using TAMAL for their functional importance were forced into the final SNP set, regardless of their tagging performance. For 2 genes previously reported to be associated with schizophrenia, NRG1 and the ionotropic/kainate glutamate receptor 2 (GRIK2), the tagging approach was not applied because the large gene size and low linkage disequilibrium would have required a prohibitive number of SNPs to be genotyped; rather, SNPs were selected on the basis of those previously showing evidence of association with schizophrenia. Genotyping was performed using a gene expression platform (Illumina BeadArray at the Center for Genotyping and Analysis of the Broad Institute52). In total, 1536 SNPs were genotyped in 1302 samples; 1 control sample from the Centre d’Étude du Polymorphisme Humain set was also included on each 96-well plate. After data cleaning (eTable 2), the final sample included 1261 autosomal SNPs genotyped in 829 individuals from 225 families and yielded 379 affected-offspring parent-proband trios. Resulting genotype success rates for these SNPs were in excess of 99%, and mean genotyping rates were greater than 99% for all individuals (minimum, 94%). For the analyzable duplicate samples, interplate concordance was greater than 99.9% and concordance with published Centre d’Étude du Polymorphisme Humain genotypes was 100% (n = 1025 genotypes in total). To determine the informativeness of the resulting SNPs for the gene panel, Tagger was rerun with the same parameters but including only the passing SNPs. Although these SNPs were identified using HapMap phase Ic data, the informativeness for the 1180 HapMap SNPs meeting quality control criteria was estimated using phase II data, released subsequent to our initial genotyping assay development (eTable 1). Of a total of 7762 HapMap phase II SNPs in the tagged genes, 77% were captured with r2 ≥ 0.8, with mean r2 = 0.83. For the individual genes, 67 were captured with mean r2 ≥ 0.8 and 108 with mean r2 ≥ 0.5, suggesting that the tag SNPs adequately captured the common variation in these genes. Analysis As suggested by Neale and Sham,53 we considered the natural unit of analysis to be the single gene rather than the single SNP or haplotype. We therefore used a gene-based framework to aggregate the single SNP statistics and correct for multiple testing up to the level of the individual gene. Specifically, primary analysis screened for association among the 379 BPI trios using the set-based test implemented in the PLINK association analysis toolset (http://pngu.mgh.harvard.edu/~purcell/plink/) for all 124 genes.54 This test is similar to that described and shown to be highly efficient by Ott and Hoh55: it computes the test statistic (χ2 from the single-SNP transmission disequilibrium test in this case) for each individual SNP within a gene, then calculates the average test statistic for the best single SNP per region, for the best 2 SNPs per region, for the best 3 SNPs per region, and so forth.54 The significance of these set statistics is then estimated by permutation, which allows a determination of genewise significance, allowing for correlation between SNPs and tests while controlling for type I error at the single-gene level. For these analyses, the significance of the SNP combinations including 1 to 5 SNPs were estimated, using 50 000 permutations. Although it would be possible to sum over all SNPs within 1 gene, rather than the best 5, this approach would tend to obscure associations if only 1 or a few SNPs show evidence of association, as we would expect. The transmission disequilibrium test is problematic as a test for association in multiplex families in the presence of linkage56,57 because transmissions to affected offspring are not independent. However, the determination of P values by permutation allows transmissions to multiple affected siblings to be analyzed while taking into account this relatedness. We chose to correct for testing multiple genes for association, within the constraints of available power, by setting a more stringent permuted genewise P < .005 as the threshold for significance in the gene-based test. This value was selected according to examination of thresholds for 70% power to detect association in the single-SNP transmission disequilibrium test. Anticipating the need for replication of any suggestive finding, and recognizing the possibility of more than 1 true-positive association given the nature of the hypotheses under study, we elected not to choose a more stringent threshold. Tests of DISC1, NRG1, and DTNBP1, which we considered to have greater prior probability of association based on previous reports, used a less stringent threshold for statistical significance (P < .05) than the other genes. For any gene with evidence of association in the gene-based test, we then examined 3-marker haplotypes within the gene using a sliding-window approach for illustrative purposes.58 For graphical illustration of SNP location within a subset of genes, the Haploview (http://www.broad.mit.edu/mpg/haploview/)59 and Locusview 2.0 (http://www.broad.mit.edu/mpg/locusview/) packages were used. Finally, given emerging evidence of overlap between bipolar disorder and primary psychotic disorders, we performed a follow-up analysis of only those genes with evidence of association with BPI in our primary analysis, as well as the 3 replication genes (DTNBP1, NRG1, and DISC1). For this analysis, affection status was determined by psychosis (SAB or BPI with psychotic features in the proband) rather than BPI diagnosis, yielding 294 affected trios drawn from the larger cohort. To aid in the interpretation of results, the power for single-marker analyses was estimated using the Genetic Power Calculator60 for 379 trios assuming a discrete trait analyzed by means of the transmission disequilibrium test. For α = .005 and an additive model with a genotypic risk ratio of 1.5, power was at least 75% for minor allele frequency of 25% or greater and at least 70% for minor allele frequency of 20% or greater. For α = .05, as applied to the replication genes, and an additive model with a genotypic risk ratio of 1.4, power was at least 75% for a minor allele frequency of 20% or greater and at least 70% for a minor allele frequency of 15% or greater. These estimates do not consider the nonindependence of trios in multiplex families, although comparison of asymptotic and permuted P values suggested little influence of nonindependence here. True power is likely to be substantially greater because of the use of the set-based test. Results Three genes (SIAT4A, TACR1, and GABRB2) yielded permuted P < .005 in gene-based association tests, corrected for all tests within the gene; the 5 SNPs in each gene that contribute to this association are listed in the Table (eTable 3 shows all gene-based results). Likewise, the 5 SNPs that contribute to the gene-based tests for 3 replication genes (DISC1, DTNBP1, and NRG1) are listed in the Table; only DISC1 yielded P < .05. The association between BPI and SIAT4A, TACR1, GABRB2, and DISC1 was further characterized using 3-marker sliding-window haplotypes because the set-based test does not localize association within a gene (Figure). In GABRB2, multiple haplotypes were differentially transmitted to bipolar offspring; the strongest association was observed with an overtransmitted 3-marker haplotype of rs6556547, rs967771, and rs10515828 (transmitted to untransmitted [T:NT] ratio, 203:139; χ2 = 11.98; P < .001). In SIAT4A, the strongest association was observed with a 3-marker haplotype of rs2075823, rs6986303, and rs9643297, which was undertransmitted (T:NT ratio, 76.7:118.1 [these numbers are not integers because of ambiguous phasing]; χ2 = 8.81; P = .003). In TACR1, a 3-marker combination of rs3771809, rs6546952, and rs3771811 was undertransmitted (T:NT ratio, 190.5:249.7; χ2 = 7.96; P = .005). Finally, for DISC1, an overtransmitted haplotype of rs10495308, rs2793091, and rs2793085 (T:NT ratio, 98:65; χ2 = 6.67; P = .01) showed the greatest evidence of association. (To aid in the comparison of these results with previous studies and to facilitate future ones, the odds ratios and P values [in terms of −log (P)] from single-SNP tests are also presented in the eFigure and supplemental eTable 4). Notably, the gene-based test explicitly considers the single-SNP results (ie, single-SNP transmission disequilibrium test; see SNP 1 in the Table) and thus does not require further correction for these single-SNP tests. Because of the reported overlap in schizophrenia and bipolar liability,39 we performed a secondary analysis examining gene-based associations using the lifetime presence or absence of psychotic symptoms, regardless of diagnosis, as the phenotype. This analysis included 294 affected-offspring trios drawn from the larger cohort, including BPI and SAB offspring. For SIAT4A, the gene-based test yielded P < 4 × 10−5; for the other genes, results were essentially unchanged from the primary analysis of the bipolar phenotype (eTable 5). Three-marker sliding-window results for this gene are shown in the Figure (top half of SIAT4A panel [A]). Comment In this large-scale family-based association study of bipolar disorder, we identified evidence of association using a gene-based test for 3 genes from a panel of 124. One gene, SIAT4A, is in a region of chromosome 8 implicated in a meta-analysis of linkage data in bipolar disorder7; a second, TACR1, was identified in an expression study of bipolar disorder32; and a third, GABRB2, was previously implicated in 2 association studies of schizophrenia.61,62 None of the genes related to lithium signaling demonstrated evidence of association. Sialyltransferase 4a Sialyltransferase 4A (Online Mendelian Inheritance in Man *607187), also referred to as ST3 β-galactoside α-2,3-sialyltransferase 1 (ST3GAL1), codes for one of a family of proteins that transfer sialic acid to glycoprotein or glycolipid carbohydrate groups.63 It was included herein because of its location under a bipolar disorder linkage peak on 8q identified in a pooled analysis of linkage data7 and prioritized among positional candidates because nerve cell adhesion molecules, key to cell-cell interaction in the developing brain,64 are modified by the addition of polysialic acid by sialyltransferases. Changes in the expression of nerve cell adhesion molecule 1 have been noted in the hippocampus in postmortem studies of bipolar patients.65 The gene coding for another glycosyltransferase, a mannosyltransferase at 11q23, was shown to be disrupted by a translocation break point cosegregating with bipolar disorder in one family.66 Finally, a recent report described an association between another sialyltransferase, SIAT8B, and schizophrenia risk.67 Sialyltransferase 4A is known to be expressed in brain and many other tissues68 but is otherwise not well characterized. Our finding that the association is strongest among psychotic patients, particularly in the context of the SIAT8B association, suggests that SIAT4A should be studied among schizophrenia cohorts as well. Tachykinin receptor 1 Substance P, alternately referred to as neurokinin and tachykinin, and its primary receptor tachykinin receptor 1 (TACR1) (Online Mendelian Inheritance in Man *162323) have previously been associated with pain and more broadly with stress response, as well as motivation and reward/aversion circuits.69 Studies in mood disorders are limited, but a neuropathology study found differences in the expression pattern of TACR1 among unipolar but not bipolar subjects.70 Substance P antagonists are also known to have antidepressant and anxiolytic effects in animal models,71,72 although human studies remain inconclusive.73 Tachykinin receptor 1 itself was initially reported to be one of a subset of genes regulated by lithium in cultured lymphoblastoid cells.74 After an examination of messenger RNA expression data suggested the gene coding for substance P as a high-priority target in bipolar disorder,32 a small population-based association study failed to find an association in 20 SNPs in 4 genes related to substance P with affective illness, although coverage of TACR1 itself was limited and the cohort was quite small.75 Otherwise, to our knowledge, this gene has not been studied in mood disorder cohorts, and no studies have examined the effects of substance P in bipolar disorder itself. GABAA β2 RECEPTOR The γ-aminobutyric acidA (GABAA) β2 receptor subunit gene (Online Mendelian Inheritance in Man *600232) is located in a region of chromosome 5q identified in a previous meta-analysis76 of linkage data in schizophrenia; linkage has also been reported in studies of families of Portuguese descent77 and those of Colombian and Costa Rican descent.78 One study62 reported the association of GABRB2 with schizophrenia in a cohort of Chinese patients with schizophrenia, and a subsequent family-based study61 identified a single overtransmitted SNP (rs168697) in GABRB2 in 2 independent cohorts, 1 of Portuguese and 1 of German descent. Our result does not directly replicate either of the schizophrenia findings. Of the SNPs associated in the Chinese cohort62 (rs1816071, rs194072, rs252944, and rs187269), none was associated in the present study. For rs194072 and rs252944, the T:NT ratio was 101:97 (P > .5); for rs187269, 154:158 (P > .5). Although rs1816071 was not directly genotyped, a 2-marker haplotype (rs1644454 and rs187269) served as a proxy with r2 > 0.6; again, no significant evidence of association (for all comparisons, P > .5) was identified. The single SNP associated in the Portuguese and German cohorts61 was not successfully genotyped in our study, nor could a tagging SNP be identified in HapMap. Although abnormalities in GABAergic neurotransmission have been best described in schizophrenia,79-85 differences have also been reported in affective illness. Changes in the expression of multiple GABA receptor subunits were noted in a cohort of individuals with major depressive disorder,86 particularly in suicides; similar changes were noted in another postmortem study.87 Increased immunolabeling of GABAA β2/3 subunits was increased in bipolar patients compared with control subjects.88 Finally, another BPI postmortem study found a change in the GABAA receptor subunit composition in the hippocampus, with an increase in the GABA α5 receptor subunit compared with controls.89 Pharmacotherapies with known efficacy in bipolar disorder appear to influence GABAergic neuron development or GABAergic neurotransmission. Antipsychotics that antagonize the dopamine D2 receptor lead to up-regulation of glutamic acid decarboxylase 67, the rate-limiting step in GABA synthesis.90 Valproic acid stimulates GABAergic neurogenesis in rat forebrain.91 In rat hippocampus, lithium treatment appears to enhance the firing of GABAergic interneurons.92 In bipolar patients, lithium (although not valproate) treatment was associated with decreases in a measure of glutamate and GABA levels on magnetic resonance spectroscopy; elevated levels of this measure had been observed in bipolar patients not receiving medication.93 Finally, 2 sets of clinical observations in bipolar disorder implicate GABAergic neurotransmission. First, drugs such as benzodiazepines that act primarily on the GABA receptor are widely used adjunctively in mania, and a recent meta-analysis94 suggests efficacy for at least 1 of them. Second, studies of bipolar patients indicate extremely high rates of anxiety comorbidity.95 Confining our analysis to individuals with psychotic disorders yielded minimal change in the evidence of association for GABRB2. This suggests that reports of association in schizophrenia and bipolar disorder may not simply indicate that this gene is a psychosis risk gene per se. Genes with prior replicated evidence of association with schizophrenia The DISC region on 1q42.1 was first identified in a Scottish family in which a chromosome break point translocation segregated with mood and psychotic disorders.96 Multiple positive linkage studies in schizophrenia or schizoaffective disorder97-100 and bipolar disorder101-103 followed. The SNPs in the DISC1 region have since been associated with such disorders, and particularly psychosis, in multiple cohorts.35,36,97,98,104 Unfortunately, the extent to which the haplotypes examined in these studies overlap has not been fully defined35 (J.Fan, unpublished data, May 23, 2007). As has been noted, studies reported as replication often assess different markers or report different risk haplotypes.105 Although we did not assess all SNPs included in previous DISC1 publications, of the 37 SNPs showing prior evidence of association across published studies, 20 were directly genotyped or have proxies with r2 ≥ 0.8 in our cohort. Only 1 SNP, rs1015101 (associated with schizoaffective disorder in the work of Hodgkinson and colleagues36) was nominally associated in our cohort, with P = .04. This SNP also tags 1 SNP of a 4-marker haplotype (block 4; rs9432024-rs999710-rs11122359-rs821723) associated with bipolar disorder but not schizophrenia in the same study.36 Two of the other SNPs in this 4-marker block are tagged with r2 ≥ 0.8 and show no evidence of association, while a third is not well-captured with our SNPs. Two additional SNPs in our sample that appear to lie within or adjacent to this block, rs11577215 and rs10864702, also show modest evidence of association (nominal P = .01 and P = .02, respectively). Thus, although our results cannot be construed as replicating the earlier finding, they are at least consistent with it. Our coverage of other haplotypes associated with bipolar disorder was less complete, but there was no evidence of an association with single SNPs in these regions. Among the SNPs in the region 2 and 3 blocks of Thomson and colleagues,35 for example, none was associated with P < .1 in our study. In disorders such as diabetes mellitus, targets of drugs known to be effective as treatments have proved to be risk genes for the disorder itself.106 Notably, then, none of the genes associated with lithium signaling showed significant evidence of association, despite extensive support for the efficacy of lithium in the treatment of bipolar disorder8—suggestive evidence that lithium responsiveness may be associated with familial bipolar disorder107-109 and isolated positive studies of lithium-related candidate genes.110 This may simply indicate that the primary genes involved in lithium's mechanism of action are not those that contribute to liability for bipolar disorder (ie, are dysregulated or dysfunctional in bipolar disorder); instead, lithium may act upstream or downstream of these genes. Alternatively, although our pathway-based approach was as comprehensive as possible based on review of the literature in 2006, other known or unknown genes in these pathways that were not investigated may contribute risk; for example, understanding of GSK3B signaling continues to evolve rapidly.111 Indeed, a very recent report described association between SNPs in diacylglycerol kinase-eta (DGKH) and bipolar disorder.112 The diacylglycerol kinases play a role in phosphatidylinositol signaling but were not included in the present study becauseb of space constraints. We identified no evidence of association for upstream or downstream genes in that pathway. Finally, although the SNP tagging approach was generally informative for most genes, we cannot exclude the possibility that rarer variation in these genes, or SNPs that were not adequately tagged, are those that confer bipolar risk. We were unable to detect any significant evidence of association for 2 other genes implicated first in schizophrenia and later as bipolar candidates, NRG135,39,113 and DTNBP1,114 in the gene-based test. In DTNBP1, we directly genotyped or captured by tagging (r2 = 1) 8 of the 11 SNPs with evidence of association in schizophrenia, including all of the haplotype-tagging SNPs identified by Mutsuddi et al.105 In this our results are consistent with negative results from other groups.105,115 We also did not detect an association with the set-based test for other genes previously implicated in bipolar disorder, including brain-derived neurotrophic factor (BDNF), the dopamine transporter (SLC6A3), and the serotonin transporter (SLC6A4).116-121 We note 2 primary limitations in this study. First, although it represents one of the larger reported cohorts of bipolar patients, the power to detect moderate effects is still only fair; thus, the possibility of type II error must be considered. Second, all of the reported associations will require replication because, even where the genes implicated overlap with previous reports, the specific SNPs or haplotypes conferring risk apparently do not. Nonetheless, if replicated, these genes may represent novel targets for the development of treatments and diagnostic tools in bipolar disorder. Correspondence: Pamela Sklar, MD, PhD, Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, 185 Cambridge St, Boston, MA 02114 ([email protected]). Submitted for Publication: February 13, 2007; final revision received July 20, 2007; accepted July 24, 2007. Financial Disclosure: None reported. Funding/Support: This study was supported by grants MH062137 (Dr Sklar) and MH067060 (Dr Perlis) from the National Institute of Mental Health and by Independent Investigator (Dr Sklar) and Sidney R. Baer Jr Foundation (Dr Sklar) awards from NARSAD. References 1. 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Frasure-Smith, Nancy;Lespérance, François

doi: 10.1001/archgenpsychiatry.2007.4pmid: 18180430

Abstract Context Anxiety and depression are associated with mechanisms that promote atherosclerosis. Most recent studies of emotional disturbances in coronary artery disease (CAD) have focused on depression only. Objective To assess the 2-year cardiac prognostic importance of the DSM-IV–based diagnoses of major depressive disorder (MDD) and generalized anxiety disorder (GAD) and self-report measures of anxiety and depression and their co-occurrence. Design, Setting, and Patients Two-year follow-up of 804 patients with stable CAD (649 men) assessed using the Beck Depression Inventory II (BDI-II), the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A), and the Structured Clinical Interview for DSM-IV (masked to self-reports) 2 months after acute coronary syndromes. Main Outcome Measures Major adverse cardiac events (MACEs) (cardiac death, myocardial infarction, cardiac arrest, or nonelective revascularization) in the 2 years after baseline. Results Of the 804 patients, 57 (7.1%) met the criteria for MDD and 43 (5.3%) for GAD (11 [1.4%] had comorbidity); 220 (27.4%) had elevated BDI-II scores (≥14), and 333 (41.4%) had elevated HADS-A scores (≥8), with 21.1% overlap. Major depressive disorder (odds ratio [OR], 2.55; 95% confidence interval [CI], 1.38-4.73), GAD (OR, 2.47; 95% CI, 1.23-4.97), elevated BDI-II (OR, 1.81; 95% CI, 1.20-2.73), elevated HADS-A score (OR, 1.66; 95% CI, 1.12-2.47), and continuous standardized scores on the BDI-II (OR, 1.31; 95% CI, 1.05-1.62) and the HADS-A (OR, 1.43; 95% CI, 1.19-1.73) all predicted MACEs. After covariate control, only the P value associated with the continuous BDI-II score increased to above .10. Most of the risk associated with elevated symptoms was in patients with psychiatric disorders. However, patients with comorbid MDD and GAD or elevated anxiety and depression symptoms were not at greater MACE risk than those with only 1 factor. Conclusion Anxiety and depression predict greater MACE risk in patients with stable CAD, supporting future research into common genetic, environmental, and pathophysiologic pathways and treatments. Several of the pathophysiologic correlates of anxiety and depression may contribute to atherosclerosis,1,2 but many recent studies3 of patients with coronary artery disease (CAD) have focused only on depression. Furthermore, most of the existing literature on anxiety as a predictor of prognosis in patients with CAD has involved self-report measures.4 Although some attention has been given to panic disorder,5 to our knowledge, the potential importance of anxiety disorders, in particular generalized anxiety disorder (GAD), has been ignored, as has the question of whether the co-occurrence of anxiety and depression has prognostic importance. The overlap between anxiety and depression has long been discussed by theoreticians and health care professionals alike,6 and it is well known that self-report measures of these concepts are highly interrelated.7 Although the diagnosis of GAD is based on the presence of continuous and excessive worry, and the diagnosis of major depressive disorder (MDD) requires depressed mood or loss of interest, these conditions have much in common. The DSM-IV criteria for MDD and GAD share 4 symptoms (restlessness/agitation, fatigue, concentration difficulties, and sleep problems),8 with a fifth GAD symptom (irritability) often used clinically as a substitutive symptom9 for diagnosing MDD in medically ill patients. Estimates of comorbidity between anxiety and mood disorders vary from 25% to 50% or more.10 Research11,12 in non–medically ill patients suggests that those with dual diagnoses may be particularly difficult to treat and are likely to experience a chronic course. A recent report13 from the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) project indicated that close to half of the patients had anxious depression (MDD with high levels of anxiety symptoms) and that they had more severe depressions of longer duration than patients with MDD alone. Although some previous research14 suggested that GAD often precedes the development of MDD, a recent prospective study15 following up individuals from age 11 to 32 years observed that in approximately one-third of patients, MDD preceded GAD, with GAD preceding MDD approximately as often. Thus, the 2 disorders may follow a fluctuating and alternating pattern across time. In fact, several studies16,17 have observed a common genetic component. Finally, antidepressant agents have demonstrated efficacy in both conditions.18,19 Suls and Bunde4 reviewed 17 studies published before 2003 that considered the long-term prognostic impact of anxiety in patients with CAD. They concluded that the evidence linking anxiety symptoms to cardiac outcomes was sparse. All the studies used self-report measures, with most administering the State-Trait Anxiety Inventory.20 Most studies observed no relationship between anxiety and prognosis. One large study21 of more than 2000 patients with CAD assessed before routine stress tests found that anxiety, measured using the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A),22 was associated with lower mortality rates. The researchers speculated that anxiety might be related to increased tendencies to seek medical attention or alter risk factors. Another study23 that administered the HADS to 344 patients after myocardial infarction (MI) reported no relationship between either anxiety or depression and 1-year mortality. However, the mortality rate was low (4%). In fact, only 3 of the studies24-26 reviewed by Suls and Bunde4 showed that anxiety symptoms predicted worse long-term prognosis. All 3 studies administered the State-Trait Anxiety Inventory. Two of these studies25,26 assessed patients who participated in cardiac rehabilitation programs with psychological treatment components during follow-up, making it difficult to interpret the results. There were also relatively few cardiac events, limiting the ability to control covariates. In the third study,24 we examined 222 patients during hospitalization for MI who received usual care for 1 year. There was an increase in risk associated with anxiety symptoms that was independent of depression symptoms (assessed using the Beck Depression Inventory I [BDI-I]27), history of major depression, previous MI, and prescription of angiotensin-converting enzyme inhibitors.24 With an expanded cohort of 896 usual-care patients followed up for 5 years, we performed more extensive control for cardiac disease severity. Covariates entirely explained the long-term impact of anxiety symptoms, whereas the impact of depression symptoms continued to remain significant.28 Recently a few other publications have appeared,29-33 but differences in the measures used, timing of measurement, variations in sample sizes, and consequent ability to control covariates, as well as publication bias in favor of small studies with positive findings, mean that the prognostic value of self-reports of anxiety remains unclear. Furthermore, to our knowledge, there is no information about the role of GAD or the cardiac prognostic importance of co-occurring MDD and GAD. Two of the aims of the Epidemiological Study of Acute Coronary Syndromes and the Pathophysiology of Emotions (ESCAPE) study,34,35 the subject of this article, were to evaluate the prognostic importance of DSM-IV diagnoses in patients with stable CAD and to assess the relative predictive value of self-report symptom scales and diagnoses based on structured interviews. In this article we (1) examine the relationship between DSM-IV–based diagnoses and self-report measures of anxiety and depression assessed approximately 2 months after hospital discharge for an acute coronary syndrome (ACS) and the occurrence of major adverse cardiac events (MACEs) during the subsequent 2 years and (2) explore whether the combination of anxiety and depression confers an increased risk of 2-year MACEs compared with that conferred by only 1 of the 2 factors. Methods The ESCAPE study has been described previously.34,35 With previous ethics approval, we recruited patients from the Montreal Heart Institute and Hôpital du Sacré-Coeur de Montréal (Montreal, Quebec, Canada) who had cardiac catheterizations during ACS admissions. The ACSs included acute Q-wave MI (electrocardiographic evidence of new Q waves in 2 consecutive leads), non–Q-wave MI (peak creatine kinase [CK] enzyme level ≥1.5 times the hospital norm, or a CK-MB value greater than 5% of a simultaneous CK value greater than normal before revascularization; after angioplasty, the lower limit CK-MB mass level was at least 3 times greater than the reference range, and after coronary artery bypass graft surgery, the lower limit was at least 10 times greater than the reference range), or an episode of unstable angina with elevated troponin T levels (according to each hospital's norms). Exclusion criteria included ACS secondary to noncardiac conditions, likely survival less than 2 years due to another illness, living too far away to return for baseline evaluation, and inability to speak and read English or French. Eligible patients received letters about the project containing a telephone number to call if they did not want additional information about the study. Between August 31, 1999, and August 2, 2001, 1577 patients were contacted by telephone, and 965 agreed to attend appointments for baseline interviews. Of these patients, 811 (55.3% of eligible men and 40.4% of eligible women) signed informed consent forms and completed baseline assessments. Measures of depression and anxiety Approximately 2 months after hospital discharge, participants arrived at the research center after an overnight fast, had their vital signs measured, and had baseline blood samples collected. They brought all current medications with them for recording purposes. Other baseline medical variables were abstracted from hospital medical records. We used the definition of metabolic syndrome from the Adult Treatment Panel III of the National Cholesterol Education Program.36 Participants completed the 21-item BDI-II37 and the 7-item HADS-A.22 The HADS-A was included because of its brevity, item content (tension, fear, worry, apprehension, agitation, and panic feelings), and psychometric properties.38 The depression subscale of the HADS was not administered because of inclusion of the BDI-II. After the self-reports, a trained psychologist, masked to self-report results, administered the Structured Clinical Interview for DSM-IV,39 including modules for current and past mood disorders, panic disorder with and without agoraphobia, social phobia, GAD, and alcohol and substance abuse and dependence. The full DSM-IV criteria for MDD were applied, including requiring at least a 2-week duration for depression symptoms and functional impairment. Cardiac events Patients received biannual telephone calls assessing hospital readmissions for the subsequent 2 years. With written permission from patients or next of kin, records for admissions outside of study hospitals were obtained from archives departments. Study hospital records were reviewed for the 2-year period, and we obtained Quebec Medicare data for hospitalizations, procedures, and last dates of physician contacts (to establish 2-year survival status) for all participants. Cardiac events were blindly and independently coded by a cardiologist and a psychiatrist (F.L.) with extensive cardiac experience. Disagreements were resolved by discussion. The primary outcome was the occurrence of 1 or more MACEs (cardiac death, survived MI, survived cardiac arrest, or nonelective revascularization) in the 730 days after the baseline interview. Cardiac deaths were classified as ischemic, arrhythmic, due to pump failure, or due to cardiac procedure complications.40 The MIs were defined by elevation of the CK-MB level accompanied by chest pain lasting longer than 30 minutes or by ST-T changes (any of the following in 2 contiguous leads: new persistent or transient ST-segment depression > 0.1 mV or T-wave inversion or transient [<20-minute] ST-segment elevation > 0.1 mV). Nonelective revascularizations included coronary artery bypass graft surgery and angioplasty during admissions directly after emergency department visits. Nonelective revascularizations during hospital admissions with other MACE diagnoses were not counted separately. Statistical analyses A software program (SPSS for Windows version 15.0; SPSS Inc, Chicago, Illinois) was used for all analyses. Statistical tests were 2-sided. We performed receiver operating characteristic curve analyses to assess the sensitivity and specificity for each self-report measure in predicting each DSM-IV diagnosis. The relationships between background factors and measures of anxiety and depression were assessed using Pearson product moment correlations for pairs of continuous variables and between continuous and dichotomous variables. Contingency coefficients were calculated for pairs of dichotomous variables. Logistic regression was used to evaluate the odds ratios (ORs) for experiencing 1 or more MACEs during the 2-year follow-up associated with each measure of anxiety and depression. Because of skewness, BDI-II scores were analyzed using natural log transformations. The ORs for the HADS-A and log-transformed BDI-II were calculated per standard deviation increase. For comparability with previous research and to allow assessment of comorbidity using the self-reports, both scales were dichotomized using cutoff points suggested in the literature. Scores of 14 or greater on the BDI-II were considered indicative of at least mild to moderate symptoms of depression (elevated depression symptoms),37 and scores of 8 or greater on the HADS-A defined elevated anxiety symptoms.22 The limiting factor for the number of covariates in studies with dichotomous outcomes is the smaller of the outcome frequencies,41 in this case the number of MACEs, with the rule-of-thumb limit being approximately 8 to 10 events per covariate.42 With 115 MACEs, we were able to use the approach recommended by Steyerberg et al43 to select covariates. Baseline variables were entered together into a logistic regression analysis to predict MACEs. Those with adjusted P <.50 were retained as covariates. These variables were entered together in the first step of a logistic regression analysis, followed by the measure being evaluated. The likelihood ratio test was used to assess the covariate-adjusted P value. Body mass index and blood pressure measurements were missing for 1 participant, and owing to technical problems, baseline blood test results were not available for 11 patients. We substituted the overall mean values for the missing variables in the covariate modeling, and we also used a regression model based on the complete cases to estimate values for the missing data. The 2 approaches yielded almost identical results, and the analyses substituting mean values are presented in this article. Results Sample Only 7 of the 811 participants (<1%, including 1 with GAD and none with MDD) were lost to follow-up or died of noncardiac causes without having 1 or more MACEs in 2 years, resulting in a final sample of 804. Overall, 110 (13.7%) of the patients in the final sample met the DSM-IV criteria for 1 or more current mood, anxiety, or substance abuse or dependence disorders. This included 57 (7.1%) who met the criteria for current MDD (22 [2.7%] with past depression), whereas GAD was diagnosed in 43 (5.3%) (17 [2.1%] with past depression). Other diagnoses occurring in more than 1% of the sample included past MDD (not currently depressed, n=123; 15.3%), bipolar disorder (n=21; 2.6%), panic disorder (n=16; 2.0%), and alcohol abuse or dependence (n=23; 2.9%). Using the cutoff score of at least 14 on the BDI-II, 220 (27.4%) had elevated depression symptoms, and 333 (41.4%) had HADS-A scores of 8 or greater. Table 1 includes participants' background characteristics. Psychometrics Internal consistency was acceptable for both self-reports (BDI-II: α = .90; HADS-A: α = .83). Both showed some departure from normality. The BDI-II showed more pronounced skewness (1.35) and kurtosis (2.13) than the HADS-A (skewness = 0.64; kurtosis = −0.07). Analyses for the continuous BDI-II score were based on natural log-transformed data (skewness = −0.69; kurtosis = 0.17). Log-transformed continuous BDI-II and HADS-A scores were moderately highly correlated (r = 0.61; P < .001). This degree of interrelationship is approximately in the middle of the range reported previously (r = 0.45-0.83).38,44,45 We performed receiver operating characteristic curve analyses to compare the ability of each self-report measure to predict the DSM-IV diagnoses of MDD and GAD (Table 2). The area under the curve (AUC) for the BDI-II for predicting MDD was greater than its AUC for GAD, indicating that the BDI-II is a better screening tool for depression than for anxiety. This is also reflected in the higher sensitivity of elevated BDI-II scores for detecting MDD than GAD. The AUC for MDD predicted by the HADS-A, although lower than that for the BDI-II, was approximately the same as the AUC for the HADS-A as a predictor for GAD. Although the sensitivity of the HADS-A for detecting GAD was as high as that of the BDI-II for detecting MDD, the cutoff score of at least 8 on the HADS-A had a specificity of 84.2% for detecting MDD. In this sample, the HADS-A was more likely to reflect both depression and anxiety than was the BDI-II, which is a more pure index of depression. Baseline variables associated with depression and anxiety Table 1 shows the correlations between baseline characteristics and measures of depression and anxiety. The only baseline variables not significantly related to any psychological measures were left ventricular ejection fraction less than 45%, coronary angioplasty at baseline, high-density lipoprotein cholesterol level, systolic and diastolic blood pressure, and prescription of aspirin, β-blockers, angiotensin-converting enzyme inhibitors, and statins. Measures of depression and anxiety were higher in younger participants. Women were more likely to meet the criteria for MDD (5.5% of men and 13.5% of women; P < .001) and had higher scores on the BDI-II and the HADS-A, but they did not differ from men in their prevalence of GAD (5.4% of men and 5.2% of women; P = .91). Metabolic syndrome was related to measures of depression but not anxiety. Most measures of anxiety and depression were significantly linked to smoking, triglyceride levels, and use of antidepressants and benzodiazepines. Long-acting nitrates were linked to self-report measures but not to the diagnostic categories. Predictors of cardiac events During the 2 years after the baseline interview, 115 participants (14.3%) experienced at least 1 MACE (11 cardiac deaths, 54 survived MIs, 3 survived cardiac arrests, and 47 nonelective revascularizations). All diagnostic and self-report symptom measures of anxiety and depression significantly predicted MACEs (Table 3). Although the ORs associated with psychological factors were numerically higher for men than for women, none of the interactions between sex and baseline anxiety and depression were significant in predicting MACEs (P ≥ .25 for all depression measures; P ≥ .13 for all anxiety measures). However, the number of women was too small to reliably detect sex-related differences. For example, with a prevalence of 50% for elevated anxiety symptoms and a 17% event rate, the sample of 155 women had a power of less than 25% to detect a doubling in risk associated with this factor. Other significant predictors of MACEs included older age, previous cardiac history, higher systolic and diastolic blood pressure, and more prescribed medications, plus several variables reflecting ischemic risk, including having 1 or more major cardiac vessels remaining blocked after index revascularization procedures and being prescribed long-acting nitrates (Table 4). Covariate control The method suggested by Steyerberg et al43 was used to select covariates. Table 2 includes multivariate-adjusted ORs for MACEs associated with each measure of depression and anxiety. The final multivariate model is illustrated in Table 5 using the standardized HADS-A score. Although the final covariates included age, left ventricular ejection fraction less than 45%, coronary artery bypass graft surgery at index, having 1 or more coronary vessels with 50% or greater blockage after index revascularization, diastolic blood pressure, triglyceride levels, and several other variables, most results remained statistically significant after covariate adjustment. The only P value increasing to >.10 was for the log-transformed BDI-II score. Comparative prognostic importance of diagnoses and self-reports In Table 3, the ORs associated with DSM-IV diagnoses are numerically greater than those associated with elevated self-report scores. We wondered whether there was an increased risk of MACEs in patients with elevated self-report symptoms who did not fulfill the criteria for MDD or GAD. Two 3-category variables were created, 1 for depression and 1 for anxiety. The highest category included patients meeting the criteria for the DSM-IV diagnosis. The middle category included those with elevated self-report scores not meeting the DSM-IV criteria, and the lowest category included those with low self-report scores who also did not meet the diagnostic criteria. The ORs for MACEs associated with each of these 3-category variables appear in Table 6 before and after covariate control. After covariate adjustment, the ORs for MACES remained significant only for patients meeting diagnostic criteria vs those in the lowest category. Those with elevated symptoms who did not meet the diagnostic criteria were not at significantly increased risk compared with those with a low level of symptoms. With the observed group sizes and event rates, we had greater than 80% power to detect ORs of approximately 1.7 associated with elevated symptoms without DSM-IV diagnoses compared with a low level of symptoms. Thus, the increase in MACE risk in patients who have elevated symptoms only is not likely to be greater than this. Comorbid anxiety and depression Although 19.3% of patients with MDD and 25.6% of those with GAD met the criteria for the other disorder (κ = 0.17; P < .001), there were only 11 patients with comorbid diagnoses (1.4% of the total sample). The dichotomized self-report scores showed a greater degree of overlap (κ = 0.43; P < .001), with 21.1% of the sample (n = 170) having elevated scores on both self-reports. Approximately 77.3% of patients with elevated BDI-II scores had HADS-A scores of 8 or greater, and 51.1% of the patients with anxiety also had elevated BDI-II scores. To determine whether patients with comorbid depression and anxiety experienced an increased risk of MACEs compared with those with only 1 condition, we performed logistic regression analyses comparing the ORs for MACES for patients with both conditions, those having only depression, and those having only anxiety. As illustrated in the Figure, approximately the same percentage of patients with both GAD and MDD experienced MACEs as those with only 1 diagnosis (comparison of 3 groups: P = .99). Although we had 80% power to detect an increase in risk of approximately 2.6 associated with comorbid DSM-IV disorders in contrast to a single disorder, results from the self-report scales corroborate these findings, with greater than 80% power for detecting a doubling in risk. Patients with elevated depression and anxiety symptoms did not experience a doubling in risk compared with those with elevated scores on only 1 measure (comparison of 3 groups: P = .68). Thus, this sample provided little evidence that co-occurring anxiety and depression lead to an augmentation in MACE risk across 2 years above that conferred by either anxiety or depression alone. Given the lack of increased risk in patients with co-occurring anxiety and depression, we considered the ORs associated with having 1 or more diagnoses or with having elevated symptoms on 1 or more of the self-report scales (Table 6). Patients with either DSM-IV diagnosis were at significantly greater risk than those with elevated symptoms of either type who did not meet the diagnostic criteria, a difference that remained significant after covariate control. The sample size was large enough to conclude that patients with elevated symptoms without diagnoses did not experience an increase in the OR of MACEs of more than approximately 1.7 compared with those with a low level of symptoms. Comment We found that in patients with stable CAD, diagnostic and dichotomous self-report measures of anxiety and depression predict increased odds of experiencing MACEs across 2 years, even after adjustment for multiple background and cardiac disease severity measures. Although before covariate adjustment there was evidence of increased risk with elevated self-report symptoms, even in the absence of meeting DSM-IV criteria, after covariate control only the increased risks associated with MDD and GAD remained significant. Most of the increased risk associated with elevated depression and anxiety symptoms occurred in those meeting the diagnostic criteria. The results suggest that medical and background factors play a greater confounding role in self-report data than in diagnostic assessments. This may in part account for the inconsistent results in the literature on the prognostic importance of anxiety in patients with CAD and underscore the importance of covariate adjustment. The use of diagnostic measures is likely to produce larger and more robust risk estimates for anxiety and depression. We observed 20% to 25% comorbidity between MDD and GAD, on the low side of estimates from cross-sectional community studies.10 However, patients with comorbid diagnoses were not at greater risk for MACEs than those with only 1 of these factors. Results were the same when comorbidity was defined by the self-reports. It is possible that patients with comorbid conditions were less likely to survive the index ACS episode or may not even have survived to be hospitalized. However, the distinction between the conditions may not matter much in terms of cardiac prognosis in patients with established CAD. Approximately 40% of those with each diagnosis had past episodes of depression. This is similar to data recently reported15 in a much younger cohort followed up prospectively since childhood. For some patients, the presentation of emotional difficulties may vary between anxiety and depression across their lifetimes. In others, anxiety or depression may remain the predominant observable negative emotion, but both may share common genetic, environmental, and pathophysiologic bases. It has been suggested that because of their overlap, MDD and GAD should probably be considered as part of the same broad diagnostic classification in the DSM-V, perhaps as part of a “distress disorder” category.46 This may be particularly true for patients with CAD. Receiver operating characteristic curve analyses of the BDI-II and the HADS-A for predicting diagnoses of MDD and GAD also supported the overlapping nature of anxiety and depression in patients with CAD. The HADS-A was almost as good at predicting MDD as GAD. The BDI-II was a more psychometrically pure measure of depression but did as well at detecting GAD as many screening indices. When considered as continuous measures, the HADS-A, but not the BDI-II, remained a significant predictor of increasing MACE risk after covariate control. This likely reflects its ability to tap both factors and thus better identify patients for whom emotional symptoms increase the risk of cardiac events. Although most recent research on pathophysiologic links between negative emotions and CAD has involved depression, evidence indicates that anxiety is also related to several mechanisms involved in CAD events,1 including increased catecholamine levels,47 indicators of autonomic dysfunction (increased heart rate, decreased heart rate variability, and decreased baroreceptor sensitivity),48-51 increased platelet activity,52 and subacute chronic inflammation.53 It has also been suggested that depression and anxiety have common genetic predispositions16,17 and that the biological mechanisms linking depression with CAD may result from shared genetic factors.54 For example, dysregulation of the serotonin system,55,56 which is likely to be partially determined by genetic factors, may predispose to depression or anxiety or CAD, with the predominant clinical phenotype(s) being the result of multiple genetic-environmental interactions yet to be determined. In the present sample, assessed approximately 2 months after hospital discharge for ACS, the rate of MDD was only 7.1%, approximately one-third of that reported for patients interviewed during hospitalization for MI.57 Previous studies have varied in the proportion of women, and evidence suggests that female cardiac patients are approximately twice as likely to be depressed as their male counterparts. In the ESCAPE study, 13.5% of women but only 5.5% of men met the criteria for MDD, and only 19.3% of the patients were women. A more probable explanation for the low prevalence of depression is that some patients who meet the criteria for MDD during hospitalization have an adjustment disorder or a less severe mood disorder that is no longer present 2 months later. Most structured interview studies in patients with CAD have administered the Diagnostic Interview Schedule58 or the Depression Interview and Structured Hamilton.59 In contrast, ESCAPE study psychologists administered the Structured Clinical Interview for DSM-IV.39 To qualify for MDD, ESCAPE study patients had to note sadness or loss of interest “most of the day, nearly every day” for 2 weeks or more during the past month and have experienced significant social, occupational, or other impairment. The Diagnostic Interview Schedule requires sadness or loss of interest most days and, when administered in the hospital, has often been modified to exclude the impairment criterion and to require less than 2 weeks of symptoms. Thus, the stricter application of the DSM-IV criteria in the ESCAPE study is at least partially responsible for the lower prevalence of MDD. This study has other limitations. We do not know the refusal rates in patients with DSM-IV diagnoses or elevated self-report symptoms. Depression and anxiety were assessed at baseline only. We do not know whether patients with co-occurring anxiety and depression had different psychological outcomes than those with a single condition. There were 68 patients (8.5%) taking antidepressant agents, and 212 (26.4%) had benzodiazepine prescriptions. However, neither was related to MACEs. Despite the 2-year follow-up, the number of cardiac events was lower than in earlier studies, likely a positive consequence of improvements in medical treatment coupled with the fact that patients were recruited 2 months after an ACS episode rather than during hospitalization. The outcome, MACEs, was a composite of cardiac deaths, MIs, survived cardiac arrests, and emergency revascularizations, all events signaling a worsening cardiovascular condition and associated with major health care costs and long-term prognostic burden. However, this sample was not large enough to assess the separate components and ensure adequate covariate adjustment. Anxiety and depression have prognostic importance in patients with stable CAD, and the risks are fairly equivalent. At first glance, the inclusion of patients with elevated anxiety or depression symptoms seems to be a good strategy for recruitment in clinical trials aimed at preventing the cardiac consequences of psychological risks. However, we found that most of the increased risk of cardiac events associated with self-report symptoms is in those with either GAD or MDD. Because there is evidence that 2 selective serotonin reuptake inhibitor antidepressants (sertraline60 and citalopram61) are efficacious and safe for patients with CAD and MDD, randomization to placebo use for long periods is not likely to be ethically acceptable. In addition, although there are no specific trial data supporting their use for GAD in patients with CAD, several selective serotonin reuptake inhibitors have demonstrated efficacy for medically healthy patients with GAD.62 Thus, long-term randomization to placebo therapy is also questionable in patients with CAD and GAD. Placebo treatment is probably acceptable for patients with CAD and elevated symptoms who do not meet the criteria for a disorder, but their rate of cardiac events is likely to be low, requiring a substantially larger sample size. This adds yet another challenge to designing a cardiac prevention trial based on reduction of risks linked to psychiatric factors and suggests that efforts would be better placed at improving the efficacy of existing treatments. Back to top Article Information Correspondence: Nancy Frasure-Smith, PhD, Departement de Psychiatrie, Centre Hospitalier de l’Université de Montréal, Hôpital Notre Dame, Pavillon Mailloux (7° étage, porte K 7211), 1560 rue Sherbrooke Est, Montreal, QC H2L 4M1, Canada ([email protected]). Submitted for Publication: April 20, 2007; final revision received July 31, 2007; accepted August 23, 2007. Financial Disclosure: Dr Frasure-Smith has received grant support from IsodisNatura and GlaxoSmithKline and honoraria from Solvay and Tromsdorff. Drs Frasure-Smith and Lespérance have received placebo and active medication from Lundbeck Canada for an investigator-initiated, peer-reviewed, funded trial. Dr Lespérance has received honoraria from GlaxoSmithKline, Lundbeck, Pfizer, Biovail, and Wyeth and grant support from IsodisNatura and GlaxoSmithKline and is a consultant for Servier. Funding/Support: This study was supported by the Medical Research Council of Canada, unrestricted grant POP-37744 from GlaxoSmithKline, the Charles A. Dana Foundation, the Foundation of the Montreal Heart Institute, the Pierre David Fund, and the Fondation du Centre Hospitalier de l'Université de Montréal. Role of the Sponsors: The funding bodies had no role in the design or conduct of the study; the data collection, management, analyses, or interpretation; or the preparation, review, or approval of the manuscript. Additional Contributions: The Régie de l’assurance maladie du Québec and the Ministère de la santé et des services sociaux du Québec provided Medicare data; Ginette Gravel, MSc, Elaine Kennedy, MPs, Johanne Lalancette, Joanne Lavoignat, RN, Marie-Pierre Leduc, MPs, Aline Masson, MSc, and Isabelle Ménard, MPs, performed data collection and database preparation; Martine Habra, PhD, critically reviewed and edited the final manuscript; Jacques Lespérance, MD, coded baseline angiograms; and Claude Sauvé, MD, performed event adjudication. This article was corrected for errors on May 29, 2015. References 1. Grippo AJ, Johnson AK. Biological mechanisms in the relationship between depression and heart disease. Neurosci Biobehav Rev. 2002;26(8):941-962. PubMedGoogle ScholarCrossref 2. Januzzi JL, Stern TA, Pasternak RC, DeSanctis RW. The influence of anxiety and depression on outcomes of patients with coronary artery disease. Arch Intern Med. 2000;160(13):1913-1921. 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Holman, E. Alison;Silver, Roxane Cohen;Poulin, Michael;Andersen, Judith;Gil-Rivas, Virginia;McIntosh, Daniel N.

doi: 10.1001/archgenpsychiatry.2007.6pmid: 18180431

Abstract Context The terrorist attacks of 9/11 (September 11, 2001) present an unusual opportunity to examine prospectively the physical health impact of extreme stress in a national sample. Objective To examine the degree to which acute stress reactions to the 9/11 terrorist attacks predict cardiovascular outcomes in a national probability sample over the subsequent 3 years. Design, Setting, and Participants A national probability sample of 2729 adults (78.1% participation rate), 95.0% of whom had completed a health survey before 9/11 (final health sample, 2592), completed a Web-based assessment of acute stress responses approximately 9 to 14 days after the terrorist attacks. Follow-up health surveys reassessed physician-diagnosed cardiovascular ailments 1 (n = 1923, 84.3% participation rate), 2 (n = 1576, 74.2% participation rate), and 3 (n = 1950, 78.9% participation rate) years following the attacks. Main Outcome Measures Reports of physician-diagnosed cardiovascular ailments over the 3 years following the attacks. Results Acute stress responses to the 9/11 attacks were associated with a 53% increased incidence of cardiovascular ailments over the 3 subsequent years, even after adjusting for pre-9/11 cardiovascular and mental health status, degree of exposure to the attacks, cardiovascular risk factors (ie, smoking, body mass index, and number of endocrine ailments), total number of physical health ailments, somatization, and demographics. Individuals reporting high levels of acute stress immediately following the attacks reported an increased incidence of physician-diagnosed hypertension (rate ratios, 2.15 at 1 year and 1.75 at 2 years) and heart problems (rate ratios, 2.98 at 1 year and 3.12 at 2 years) over 2 years. Among individuals reporting ongoing worry about terrorism post-9/11, high 9/11-related acute stress symptoms predicted increased risk of physician-diagnosed heart problems 2 to 3 years following the attacks (rate ratios, 4.67 at 2 years and 3.22 at 3 years). Conclusion Using health data collected before 9/11 as a baseline, acute stress response to the terrorist attacks predicted increased reports of physician-diagnosed cardiovascular ailments over 3 years following the attacks. On 9/11 (September 11, 2001), the US public experienced a terrorist event of extraordinary scope and traumatic impact. Studies have documented substantial short-term psychological response to 9/11,1-4 but its effect on physical health has received limited attention.5 Extremely stressful events may precipitate biological processes that increase one's risk of developing cardiovascular ailments.6-11 Indeed, during the weeks following 9/11, rates of cardiovascular events increased significantly in New York City and surrounding areas.12-14 Comparable findings were reported in Florida,15 suggesting the possibility that direct exposure may not have been necessary for the development of 9/11 stress-related health problems. These provocative findings imply that, for some individuals, indirect exposure to extreme stress may produce physiologic responses that contribute to cardiovascular ailments. Extreme stress may also initiate psychological processes (eg, acute stress reactions) that parallel physiologic stress reactions. Acute stress16-18 and early physiologic arousal (heart rate)19,20 are known risk factors for subsequent development of posttraumatic stress disorder (PTSD). While recognizing that the acute stress disorder (ASD) diagnosis has come under recent scrutiny,21 we suggest that acute stress responses may have value beyond their potential for predicting PTSD. To the extent that acute stress reactions represent the psychological parallel to complex psychophysiological responses to extreme stress, they may help identify individuals whose responses to stress place them at greater risk for developing physical illness. Although extreme stress can affect cardiovascular health through the subsequent development of PTSD,22 it is unknown whether early assessment of stress-related symptoms might enhance our ability to identify individuals whose responses to extreme events increase the risk for experiencing cardiovascular ailments over time. While acute stress may trigger immediate potentially lethal cardiovascular responses,23-25 acute, subacute, and chronic stress can gradually increase cardiovascular risk through neurohormonal arousal.10 This physiologic reactivity may be easily rekindled by trauma reminders, leaving individuals vulnerable to the detrimental effects of arousal over time.26 Perseverative cognition (eg, worry) may serve as a cognitive mechanism that fuels or prolongs stress-related activation before and after stress, increasing the risk for subsequent stress-related health problems.27,28 Indeed, fear or worry about terror has been linked to low-grade inflammatory processes associated with cardiovascular disease.29 We sought to examine the relationship between 9/11-related acute stress and cardiovascular health in a nationwide, 3-year, prospective, longitudinal study. We expected acute stress responses to be prospectively associated with reports of cardiovascular ailments over time, especially among those who continued to worry about terrorism. Methods Overview and design We conducted a longitudinal study of mental and physical health following the 9/11 attacks with a national probability sample of the US population in collaboration with Knowledge Networks, Inc (KN), a Web-based survey research company.30 Knowledge Networks, Inc recruits, maintains, and conducts surveys with a nationally representative Web-enabled panel using an anonymous Web-based method. The KN panel was developed using traditional probability methods for creating national survey samples and was recruited using stratified random-digit-dial telephone sampling. The random-digit-dial method provides a known nonzero probability of selection for every household having a telephone. The recruitment rate for this study was approximately 53%, and the overall KN panel recruitment response rate, based on American Association for Public Opinion Research standards, averaged 41% when this study began.31 To ensure representation of population segments that would not otherwise have Internet access, KN provides panel households with Internet connections and appliances that use televisions (TVs) as monitors (Web TV). Panel members participate in brief Web-based surveys 3 to 4 times monthly in exchange for free Internet access or other compensation if the household is already Web enabled. The KN panel closely tracks the distribution of census counts for the US population on age, sex, race, Hispanic ethnicity, educational level, annual income, geographical region, and employment status.32 To correct for possible nonresponse bias from panel recruitment and attrition, representative samples are selected for panel surveys using poststratification weights that weight panel distributions to match benchmarks from the most recent government statistics for sex, age, race, ethnicity, educational level, and geographic region. Samples are drawn with probabilities proportional to panel weights using a systematic sample applied to the eligible panel members. Distributions for panel samples resemble, within sampling error, US population distributions for key demographic variables. Panel members are notified in password-protected e-mail accounts that an assigned survey is available. Surveys are confidential, self-administered, and accessible any time of day for a designated period; participants can complete a survey only once. Members may leave the panel at any time, and receipt of the Web TV and Internet access is not contingent on completion of any particular survey. Comparison of KN panelists' demographic, attitudinal, and behavioral responses to random-digit-dial samples strongly suggests that they do not respond as “professional” respondents.33 Early responses to the terrorist attacks were assessed shortly after 9/11, with follow-up assessments of psychosocial responses to 9/11 conducted at 12, 18, 24, and 36 months post-9/1130; health assessments were completed in separate surveys before 9/11 and approximately 1 and 2 years after 9/11. The 36-month (3-year) survey combined health and post-9/11 psychosocial assessments. The institutional review boards of the University of California, Irvine, and the University of Denver approved the design and procedures. Measures Pre-9/11 Health Survey Between June 17, 2000, and September 9, 2001, 45 938 adult panelists completed an online health survey, modified from the Centers for Disease Control and Prevention's National Center for Health Statistics annual National Health Interview Survey.34 Respondents were asked, “Has a medical doctor ever diagnosed you as suffering from any of the following ailments?” with prompts for 35 physical and mental health ailments. When estimates from the 2000 National Health Interview Survey were compared with a sample of 25 000 KN health surveys on various outcomes, the average difference was less than 1.5% for current smoking, heart problems, cancer, diabetes mellitus, hypertension, ulcer, migraine, and stroke, supporting the validity of these data35 (Table 1). Items from this survey provided the baseline assessments for our respondents (2592 of the 45 938 panelists). A physician used the International Classification of Diseases, Ninth Revision, Clinical Modification36 standards to classify the 35 health survey ailments into International Classification of Diseases, Ninth Revision, Clinical Modification disease system categories (eg, circulatory, nervous, and respiratory systems). Physician-diagnosed “heart problems,” “hypertension,” and “stroke” were coded as “circulatory” (henceforth, cardiovascular) ailments. The total number of cardiovascular ailments (range, 0-3) reported before 9/11 served as the baseline premeasure. Cardiac risk factors, including International Classification of Diseases, Ninth Revision Clinical Modification endocrine ailments (high cholesterol level and diabetes mellitus), smoking, and body mass index (BMI), and an index (range, 0-2) representing pre-9/11 physician-diagnosed mental health ailments (none, anxiety disorder or depression, or both) were also recorded. Demographics Knowledge Networks, Inc, provided data on age, sex, marital status, ethnicity, educational level, and household income, and imputed missing values for annual income with mean income scores for respondent's census block. Early Response to the Terrorist Attacks Between September 20 and October 4, 2001, a random sample of 2729 adults (78.1% of the 3496 sampled) from the KN panel completed a modified Stanford Acute Stress Reaction Questionnaire; more than 75% did so 9 to 14 days after the attacks.37 Items were revised to a 6.5-grade Kincaid reading level, and respondents reported whether they “experienced” or “did not experience” 9/11 stress-related symptoms. Of these respondents, 2592 (95.0% of 2729) had also completed the pre-9/11 health survey, and this group served as the final health sample for the present report. Individuals whose symptoms met the DSM-IV criteria B, C, D, and E for ASD (≥3 dissociative symptoms, ≥1 reexperiencing or intrusive symptom, ≥1 avoidance symptom, and ≥1 arousal or anxiety symptom) were classified as having “high” acute stress.38 Because most respondents did not meet DSM-IV criterion A (direct exposure) and we did not assess symptom duration, respondents were not assumed to have ASD. Post-9/11 Health Surveys comparable to the pre-9/11 health survey were readministered annually over the next 3 years to all available respondents from the original pool of 2592 who had completed the pre-9/11 health and early response surveys. Respondents who left the KN panel were allowed to complete the survey online or by mail. Type of survey completed was unrelated to cardiovascular ailments in all assessments. Online survey completion times ranged from 12 to 15 minutes. Between October 10 and December 6, 2002, 1923 of 2281 available respondents completed the health survey online (84.3% of those fielded and 74.2% of the 2592 respondents who completed the pre-9/11 health and early response surveys). Between October 10, 2003, and March 31, 2004, 1576 of 2123 available respondents completed the health survey (1491 online and 85 by mail; 74.2% of those fielded and 60.8% of respondents who completed the pre-9/11 health and early response surveys). Around the 3-year 9/11 anniversary (September 12 to November 2, 2004), 1950 of 2471 available respondents completed the health survey (1296 online and 654 by mail; 78.9% of those fielded and 75.2% of respondents who had completed the pre-9/11 health and early response surveys). The pre-9/11 and 1-, 2-, and 3-year post-9/11 health surveys were missing physician-diagnosed ailments for approximately 8% to 9%, 6% to 7%, less than 1%, and less than 1% of respondents, respectively. Patterns of missing data were evaluated using the methods of Little and Rubin39 (missing at random). Because these tests were nonsignificant (P > .10), missing data were imputed within age groups using the expectation maximization method for pre-9/11 and 1-year post-9/11 health data. Variables identical to baseline pre-9/11 health indices were created representing total number (range, 0-3) of physician-diagnosed cardiovascular ailments reported 1, 2, and 3 years after the attacks. Cardiac risk factors (endocrine ailments and BMI) were also computed for each year. Somatization Subjects' tendency to report physical symptoms was assessed 2 ways. First, because somatization is associated with symptoms from multiple systems,40,41 total number of physician-diagnosed physical health ailments each year (including pre-9/11) was considered a proxy for somatization. Second, subjects completed the somatization subscale from the 18-item Brief Symptom Inventory,42 a standardized scale with a valid reliable somatization subscale. Reliability was excellent for all assessments (α = .81). Stressful Life Event Exposure Lifetime exposure to stressful events was assessed during the year after 9/11 by asking participants whether they had ever experienced each of 37 negative events (eg, natural disaster, child abuse) and the age(s) at which they occurred.30 Ongoing exposure was reassessed with each survey. This measure was modified from the Diagnostic Interview Schedule trauma section,43 was expanded to include a wider variety of stressful events using primary care patients' reports of lifetime stress,44 and has provided rates of specific events comparable to those in other community samples.45,46 Continuous variables were computed representing the number of pre-9/11 childhood (≤17 years) and adulthood stressors. Stressful events directly related to physical health (eg, had a serious accident or illness) were excluded from analyses to avoid confounding stress and health outcomes. A continuous count of events that occurred following the attacks was also computed. Exposure to the 9/11 Attacks Items modified from prior research on disaster exposure47,48 assessed respondents' 9/11-related exposure (degree of exposure to and loss from the attacks, including hours of daily television coverage watched). Individuals were categorized into 1 of 3 levels of exposure: direct exposure (ie, being in the World Trade Center [WTC] or Pentagon, seeing or hearing the attacks in person, or having a close relationship with someone in the targeted buildings or airplanes [ie, meeting criterion A1 for ASD and PTSD]), live media exposure (ie, watching the attacks on television live as they occurred), and no live exposure (ie, seeing videotaped replay or learning of the attacks only after they occurred). US Postal Service residential zip codes were used to compute azimuth distance from the WTC to measure the degree of impact (similar to earthquakes, with lessening impact as distance from the “epicenter” increases). Residency in New York City or Washington, DC, at the time of the attacks was also recorded. Worries About Terrorism Each annual 9/11-related survey included 2 items assessing ongoing worries about terrorism (eg, “I worry that an act of terrorism [bioterrorism, hijacking, etc] will personally affect me or someone in my family in the future”). Items were scored on a 5-point Likert scale (1 indicates never; and 5, all the time) and combined as an index of ongoing worry. Reliability was excellent (α = .82 to .84 for all). Overview of analyses A computer program (Stata 7.0; Stata Corp, College Station, Texas) designed to handle weighted analysis of complex longitudinal survey data was used, and it provided necessary adjustments of standard errors. Weighted data were adjusted for differences in probabilities of selection and nonresponse within and between households. Poststratification weights were calculated by deriving weighted sample distributions along combinations of demographics and regional status. Similar distributions were calculated using recent US Census Bureau Current Population Survey and KN panel data. Cell-by-cell adjustments over various univariate and bivariate distributions were calculated to make weighted sample cells match those of the US census and KN panel.49,50 This process was repeated iteratively to reach convergence between the weighted sample and benchmark distributions from the 2001 Current Population Survey.51 All statistics calculated from the KN panel are subject to sampling variability and nonsampling error. Quality control and edit procedures ensure that the effects of these errors on final survey estimates are minimal. Preliminary analyses examined time, demographics, pre-9/11 mental health and cardiac ailments, pre- and post-9/11 cardiac risk factors, 9/11 exposure, pre-9/11 lifetime and post-9/11 stressful event exposure, pre- and post-9/11 somatization, and acute stress responses as predictors of cardiovascular ailments over 3 years after the attacks. Nonsignificant variables (P > .05) were removed from analyses, and multivariate models were estimated, adjusting for significant variables. The final, most parsimonious, models were obtained by trimming nonsignificant variables from the multivariate model. Effect sizes are presented as adjusted incident rate ratios and adjusted relative risk ratios. Longitudinal generalized estimating equations (GEEs) for Poisson distributions provided incidence rates over time. Cases missing demographics, 9/11 exposure, and stressful event data and those who had not completed at least 3 of 4 health assessments were excluded, leaving 1760 cases for the final GEE analyses. Because Poisson techniques may violate assumptions about dispersion of residuals (eg, overdispersion), inflate goodness-of-fit tests, and erroneously reduce standard errors, generalized linear modeling (Stata 7.0) was used to adjust for overdispersion.52 The generalized linear modeling and GEE findings reported later were comparable. A multinomial logistic regression procedure (Stata 7.0) then identified predictors of cardiac ailments annually. Because few individuals reported strokes, and most of these individuals also reported having hypertension or heart problems, the categorical outcome for these analyses compared individuals with hypertension only, heart problems only, and 2 or more cardiac conditions (ie, any combination of hypertension, heart problems, and stroke) with individuals reporting no cardiac conditions during the 3-year period. Interactions examined whether the relationship between post-9/11 cardiovascular ailments and acute stress symptoms depended on time, age, sex, lifetime stress, or ongoing worries about terrorism. Interactions were initially tested using the full sample—only ongoing worry was significant. The 2- and 3-year ongoing worry scores were then dichotomized using a median split; multinomial logistic regression analyses were conducted within low- and high-worry groups separately. Results Sample The sample was 52.2% female, 61.3% married, 80.0% white, and 10.6% Hispanic. Of the sample, 24.0% had completed some college and 24.0% had a bachelor's degree. For 3 years following 9/11, our sample consistently compared favorably with US Census Bureau annual statistics on age, sex, ethnicity, marital status, and educational level, suggesting that our sample remained demographically similar to the US population.51 Most weighted differences are within sampling error, although low- to middle-income households were overrepresented (eTable). Analysis of nonparticipants Individuals who completed the early response survey (n = 2729) did not differ from nonresponders (n = 767) in terms of education or marital status. However, responders were older than nonresponders (mean age, 47 vs 39 years; t3494 = 12.12, P < .001), reported a slightly lower annual income ($35 000-$40 000 vs $40 000-$50 000; t2886 = 2.61, P < .009), and were more likely to be white than black or Hispanic (χ23 = 51.98, P < .001). Individuals who completed the early response survey and the pre-9/11 health survey (n = 2592) did not differ significantly from nonrespondents (n = 904) on age, sex, marital status, ethnicity, educational level, or income (P = .29). Attrition analyses conducted for each annual follow-up survey revealed no differences between respondents and nonrespondents on pre-9/11 cardiovascular or mental health, acute stress symptoms, sex, ethnicity, marital status, or income. Respondents at each follow-up were older than nonrespondents (1 year: mean, 50 vs 42 years [t2719 = −11.75, P < .001]; 2 years: mean, 51 vs 42 years [t2717 = −14.51, P < .001]; and 3 years: mean, 50 vs 42 years [t2717 = −13.05, P < .001]) and had completed more years of education than nonrespondents at each year (1 year: χ24 = 13.95, P < .01; 2 years: χ24 = 18.76, P < .001; and 3 years: χ24 = 35.18, P < .001). Individuals included in GEE analyses (n = 1760) were not significantly different from excluded individuals in terms of pre-9/11 cardiovascular (P = .087) or mental health (P = .21) status, acute stress symptoms (P = .74), sex (P = .64), marital (P = .74) or educational (P = .42) status, or income (P = .31). Complete cases were, however, older than those excluded (mean, 50 vs 42 years; t2717 = −11.45, P < .001) and less likely to be black than white (χ23 = 17.47, P < .001). 9/11-related exposure and early response Most respondents watched the attacks live on television (1393 [63.2%]), one-third reported no live or direct exposure to the attacks (731 [33.2%]), and a few reported direct exposure (79 [3.6%]). On 9/11, 39 of the respondents (1.6%) lived in Washington, DC; 97 (4.1%) lived within 40 km of the WTC; 144 (6.0%) lived between 41 and 160 km of the WTC; 504 (21.1%) lived between 161 and 800 km of the WTC; 684 (28.7%) lived between 801 and 1600 km of the WTC; and 958 (40.1%) lived more than 1600 km from the WTC. High levels of acute stress symptoms were reported by 10.7% of respondents (unweighted) (weighted, 12.3% of respondents). Cardiovascular ailments post-9/11 Rates of reported physician-diagnosed cardiovascular ailments increased during the 3-year period from 21.5% pre-9/11 (weighted, 18.7%) to 30.5% at 3 years post-9/11 (weighted, 27.3%). Within-subject analyses indicated an increased incidence of cardiac ailments each year following 9/11 (overall, χ23 = 126.30, P < .001), even after adjusting for pre- and post-9/11 cardiac risk factors (endocrine ailments, BMI, and smoking), somatization, and demographics. Pre-9/11 mental health, 9/11-related exposure, and residential proximity to the attacks (New York City or Washington, DC) were unrelated to cardiac ailments during the 3 years following 9/11, after adjusting for pre-9/11 cardiac ailments. Although pre-9/11 cardiac ailments strongly predicted subsequent cardiovascular ailments, they did not predict acute stress responses (ie, no reverse causation). Table 2 presents findings from weighted GEE analyses predicting the number of cardiovascular ailments reported over 3 years following 9/11. High 9/11-related acute stress symptoms predicted increased incidence of cardiovascular ailments over 3 years following the attacks, even after adjusting for pre-9/11 cardiovascular ailments and mental health, age, ethnicity, pre- and post-9/11 cardiac risk factors (endocrine ailments, smoking, and BMI), pre- and post-9/11 somatization, and lifetime or ongoing stressful event exposure. Individuals meeting criteria B, C, and D of DSM-IV for ASD at the early assessment had a 53% higher incidence of reporting physician-diagnosed cardiovascular ailments over 3 years following 9/11 when compared with respondents with low acute stress symptoms. Individuals older than 35 years (P < .005 for all) and those with preexisting cardiovascular ailments (P < .001) had the highest adjusted incidence rates for subsequent cardiovascular ailments. Separate GEE analyses conducted for heart problems, stroke, and hypertension individually revealed a comparable pattern for each ailment. Multinomial logistic regression clarified which cardiac ailments were associated with acute stress symptoms for each annual follow-up survey (Table 3). Individuals who reported high acute stress symptoms immediately following 9/11 were nearly twice as likely to report being diagnosed as having hypertension and approximately 3 times more likely to report being diagnosed as having heart problems 1 and 2 years following the attacks. A similar trend appeared for 2 or more cardiac ailments 1 year after the attacks (P < .06). Interactions demonstrated that, over time, acute stress symptoms predicted reports of cardiac ailments 2 and 3 years post-9/11, especially among respondents reporting ongoing worries about terrorism. Although acute stress symptoms had no direct relationship with cardiac ailments 3 years post-9/11, they predicted increased reports of heart problems among individuals who reported ongoing worry about terrorism at both 2 and 3 years following the attacks (Table 4). Other ailments post-9/11 Pre-9/11 physician-diagnosed mental health disorders were significantly associated with the total number of physical health ailments reported over 3 years following the attacks (P = .005), although they were not specifically associated with an increased risk for cardiovascular ailments (P = .11). Rates of other noncardiovascular ailments (respiratory, gastrointestinal, genitourinary, and musculoskeletal) also increased over time post-9/11. However, after controlling for pre-9/11 levels of each ailment and total number of physical health ailments reported over time, acute stress responses were significantly associated only with cardiovascular ailments (P = .03). Comment The 9/11 terrorist attacks have been indirectly linked to increased rates of cardiovascular problems (arrhythmias) in small studies12-15 of high-risk patients during the early months following 9/11. In this study, the use of a large, representative, national sample and the longitudinal collection of health ailments before and after the 9/11 attacks provided a unique opportunity to examine the role of acute stress response and health outcomes on a national scale over time. To our knowledge, this is the first study to demonstrate that acute psychological responses to 9/11 predicted increased incidence in reports of physician-diagnosed cardiovascular ailments for 3 years in adults, most of whom did not have known preexisting cardiac disease. Moreover, ongoing worries about terrorism seemed to exacerbate the risk of physician-diagnosed heart problems 2 and 3 years later among individuals with high 9/11-related acute stress. Other research6,22 addressing the relationship between extreme stress and physical health has often assumed that direct exposure and subsequent development of PTSD are necessary preconditions linking these experiences with health conditions. A recent study5 found that adults who survived in collapsed or seriously damaged buildings during the WTC attacks reported new onset of physical health ailments, including respiratory, gastrointestinal, neurologic, and dermatologic problems. Our data further suggest the importance of considering the potential public health impact of indirect exposure to extreme stress because most of our respondents were exposed to the attacks only by watching television. Mass media coverage of these attacks likely expanded their impact geographically,53 and the unexpected, uncontrollable, and unique nature of the attacks enhanced their impact as well. To our knowledge, this is also the first study with baseline health status documented before a specific stressor, early assessment of stress responses following the event, and health status reassessed annually for 3 years. Our prospective longitudinal design allowed rigorous testing of the stress–response–health outcome relationship. Timing of the acute stress response assessment was critical because rapid assessment allowed us to evaluate early predictors of long-term health outcomes. This is unlike many studies54,55 that interview respondents many years after the initial stressor, leaving unknown the impact of time and ongoing life experience on reports of stress-related symptoms and health. Several theories help explain how acute stress reactions to highly stressful events might contribute to the development of cardiovascular ailments. Because acute stress reactions often accompany underlying stress-related physiologic arousal initially,19,20 they may mark the onset of physiologic processes that ultimately affect cardiovascular health. The allostatic load theory56 posits that activation of the sympathetic nervous system and hypothalamic-pituitary-adrenal axis sets off a neurohormonal cascade that supports coping initially but threatens health if it persists after the event has passed. Following 9/11, 2 wars, economic downturn, job loss, and subsequent terrorist attack warnings may have perpetuated the stress response and increased the allostatic load on individuals over time. Persistent physiologic responses associated with chronic stress exposure are likely to be detrimental to cardiovascular health.22,56 Ongoing exposure to stress increases blood pressure; promotes atherosclerosis, hypercoagulation, and arrhythmias10; and increases the risk of myocardial infarction through neurohormonal arousal.57 Our finding that high acute stress increased risk of cardiovascular events among individuals with ongoing worries about terrorism suggests that chronic reminders of the threat (eg, terrorism alerts, worrying, or both) may have prolonged the physiologic arousal in some people, rendering them vulnerable to cardiovascular ailments. This transition from acute to chronic stress may explain why acute stress did not directly predict ailments 3 years post-9/11—by that time, the impact of 9/11 may have manifested through ongoing stress, as indexed by ongoing worry about subsequent terrorism. Several physiologic pathways have been implicated in biological theories of PTSD.6,22,56 To the extent that acute stress reactions represent an early form of posttraumatic stress that parallels neurohormonal stress processes, they may help identify individuals whose immediate psychophysiological responses place them at greater risk for subsequent PTSD and cardiovascular ailments. While prior research has evaluated the utility and validity of using acute stress symptoms to predict PTSD, our research extends this work by suggesting the need to consider how acute reactions influence physical health as well. Moreover, acute stress responses may be an early independent risk factor for cardiovascular disease. We found that although pre-9/11 mental health problems predicted acute stress symptoms,3 they did not predict increased risk for cardiovascular ailments. The specificity of acute stress symptoms in their ability to predict cardiovascular ailments, but not other types of health ailments, suggests that this may be an important area for further study. It is also plausible that preexisting physical health problems render individuals vulnerable to acute stress following trauma or terrorism, which then predicts subsequent health problems. Although we found no supporting evidence for reverse causation in our data, this remains an important area for future study. This study has several strengths. Its prospective and longitudinal design allowed identification of predictors of reports of physician-diagnosed cardiovascular ailments over 3 years following 9/11. By studying a national sample of individuals exposed to the same event, we did not limit our investigation to specialized populations. We controlled for ongoing stress that may have contributed to subsequent health problems by including the number of post-9/11 stressors as a covariate in our analyses. Our health measure had been benchmarked against the National Health Interview Survey, which itself has been validated against medical records.58 Finally, all analyses controlled for cardiac risk factors, such as pre- and post-9/11 endocrine ailments (high cholesterol levels and diabetes mellitus), BMI, and smoking, and the individual's tendency to report physical and somatic symptoms. Nevertheless, self-report measures of physician diagnoses may be influenced by recall biases and are open to interpretation by respondents. Because acute stress did not directly predict 3-year cardiovascular ailments, it is possible that our respondents interpreted “heart problems” to include benign ailments (eg, palpitations) that differ in nature and duration from serious cardiac conditions. Without medical record corroboration, we cannot assume that all individuals reporting physician-diagnosed heart problems had true cardiovascular disease. Variability also existed in the timing of the pre-9/11 health survey. However, we found no significant differences in the number of ailments reported by early (first 2 months) vs late (last 2 months) responders. Although our initial sample closely paralleled the US population census, small but significant trends to lose younger (aged < 35 years), black, and less educated respondents over time makes generalization of our findings to these populations difficult. Finally, although attrition over time could introduce response bias (eg, illness behavior, help seeking) that might also explain our results, research has demonstrated that KN panelists are comparable to National Health Interview Survey respondents on prior year physician and emergency department visits and hospitalizations.35 Because no substantial differences emerged on markers of health care use, this is not a likely explanation for our results. In conclusion, many advances have been made in understanding the mental and physical health effects of extreme stress. We extend this work by linking acute stress responses to increases in physician-diagnosed cardiovascular ailments in a national sample of individuals following the 9/11 attacks, most of whom did not report preexisting cardiac disease. These findings highlight the possibility that acute stress reactions may indicate subsequent vulnerability to potentially serious health problems. Correspondence: E. Alison Holman, FNP, PhD, Program in Nursing Science, College of Health Sciences, 205B Irvine Hall, University of California, Irvine, CA 92697-3959 ([email protected]). Submitted for Publication: November 16, 2006; final revision received April 13, 2007; accepted June 5, 2007. Financial Disclosure: None reported. Funding/Support: This study was supported by grant SF03-09 from The Josiah Macy, Jr. Foundation (Dr Holman); and grants BCS-9910223, BCS-0211039, and BCS-0215937 from the US National Science Foundation (Dr Silver). Additional Contributions: The KN government, academic, and nonprofit research team of J. Michael Dennis, William McCready, Kathy Dykeman, Rick Li, and Vicki Pineau granted access to the data collected on KN panelists, provided pre-9/11 health data, prepared the Web-based versions of our questionnaires, created the data files, provided general guidance on their method, and provided survey research and sampling expertise; Jodie Ullman, PhD, and JoAnn Prause, PhD, provided expert statistical advice; Peter Scheid, MD, assisted with the International Classification of Diseases, Ninth Revision, Clinical Modification coding; and Sheldon Greenfield, MD, provided comments on an earlier version of the manuscript. References 1. Schuster MAStein BDJaycox LCollins RLMarshall GNElliott MNZhou AJKanouse DEMorrison JLBerry SH A national survey of stress reactions after the September 11, 2001, terrorist attacks. N Engl J Med 2001;345 (20) 1507- 1512PubMedGoogle ScholarCrossref 2. Galea SAhern JResnick HKilpatrick DBucuvalas MGold JVlahov D Psychological sequelae of the September 11 terrorist attacks in New York City. N Engl J Med 2002;346 (13) 982- 987PubMedGoogle ScholarCrossref 3. Silver RCHolman EAMcIntosh DNPoulin MGil-Rivas V Nationwide longitudinal study of psychological responses to September 11. JAMA 2002;288 (10) 1235- 1244PubMedGoogle ScholarCrossref 4. Schlenger WECaddell JMEbert LJordan BKRourke KMWilson DThalji LDennis JMFairbank JAKulka RA Psychological reactions to terrorist attacks: findings from the National Study of Americans' Reactions to September 11. JAMA 2002;288 (5) 581- 588PubMedGoogle ScholarCrossref 5. Brackbill RMThorpe LEDiGrande LPerrin MSapp JH 2ndWu DCampolucci SWalker DJCone JPulliam PThalji LFarfel MRThomas P Surveillance for World Trade Center disaster health effects among survivors of collapsed and damaged buildings. MMWR Surveill Summ 2006;55 (2) 1- 18PubMedGoogle Scholar 6. Schnurr PPGreen BL Trauma and Health: Physical Health Consequences of Exposure to Extreme Stress. Washington, DC American Psychological Association2004; 7. Qureshi EAMerla VSteinberg JRozanski A Terrorism and the heart: implications for arrhythmogenesis and coronary artery disease. Card Electrophysiol Rev 2003;7 (1) 80- 84PubMedGoogle ScholarCrossref 8. Krantz DSSheps DCarney RMNatelson BH Effects of mental stress in patients with coronary artery disease: evidence and clinical implications. JAMA 2000;283 (14) 1800- 1802PubMedGoogle ScholarCrossref 9. Blascovich JedKatkin ESed Cardiovascular Reactivity to Psychological Stress and Disease. Washington, DC American Psychological Association1993; 10. Rozanski ABlumenthal JAKaplan J Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation 1999;99 (16) 2192- 2217PubMedGoogle ScholarCrossref 11. Pizarro JSilver RCPrause J Physical and mental health costs of traumatic war experiences among Civil War veterans. Arch Gen Psychiatry 2006;63 (2) 193- 200PubMedGoogle ScholarCrossref 12. Lampert RBaron SJMcPherson CALee FA Heart rate variability during the week of September 11, 2001. JAMA 2002;288 (5) 575PubMedGoogle ScholarCrossref 13. Feng JWLenihan DJJohnson MMReddy CVR Cardiac sequelae in Brooklyn after the September 11 terrorist attacks. Clin Cardiol 2006;29 (1) 13- 17Google ScholarCrossref 14. Steinberg JSArshad AKowalski MKukar ASuma VVloka MEhlert FHerweg BDonnelly JPhilip JReed GRozanski A Increased incidence of life-threatening ventricular arrhythmias in implantable defibrillator patients after the World Trade Center attack. J Am Coll Cardiol 2004;44 (6) 1261- 1264PubMedGoogle ScholarCrossref 15. Shedd OLSears SF JrHarvill JLArshad AConti JBSteinberg JSCurtis AB The World Trade Center attack: increased frequency of defibrillator shocks for ventricular arrhythmias in patients living remotely from New York City. J Am Coll Cardiol 2004;44 (6) 1265- 1267PubMedGoogle ScholarCrossref 16. Ozer EJBest SRLipsey TLWeiss DS Predictors of posttraumatic stress disorder and symptoms in adults: a meta-analysis. Psychol Bull 2003;129 (1) 52- 73PubMedGoogle ScholarCrossref 17. Birmes PBrunet ACarreras DDucassé JLCharlet JPLauque DSztulman HSchmitt L The predictive power of peritraumatic dissociation and acute stress symptoms for posttraumatic stress symptoms: a three-month prospective study. Am J Psychiatry 2003;160 (7) 1337- 1339PubMedGoogle ScholarCrossref 18. Brewin CRAndrews BRose S Diagnostic overlap between acute stress disorder and PTSD in victims of violent crime. Am J Psychiatry 2003;160 (4) 783- 785PubMedGoogle ScholarCrossref 19. 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American Association for Public Opinion Research, Standard definitions: final dispositions of case codes and outcome rates for surveys. http://www.aapor.org/uploads/standarddefs_4.pdf. Accessed April 6, 2007 32. Dennis JMKrotki K Probability-based survey research on the Internet. Paper presented at: Conference of the International Statistical Institute August 29, 2001 Seoul, South Korea 33. Krosnick JAChang LC A comparison of the random digit dialing telephone survey methodology with Internet survey methodology as implemented by Knowledge Networks and Harris Interactive. Paper presented at: Conference of the American Association for Public Opinion Research May 19, 2001 Montreal, Quebec, Canada 34. National Center for Health Statistics, US Department of Health and Human Services, National Health Interview Survey Questionnaire. Hyattsville, MD National Center for Health Statistics2000; 35. Baker LCBundorf MKSinger SWagner TH Validity of the Survey of Health and Internet and Knowledge Network's Panel and Sampling. Stanford, CA Stanford University2003; 36. World Health Organization, International Classification of Diseases, 9th Revision, Clinical Modification. 5th ed. Los Angeles, CA Practice Management Information Corp1999; 37. Cardeña EKoopman CClassen CWaelde LCSpiegel D Psychometric properties of the Stanford Acute Stress Reaction Questionnaire (SASRQ): a valid and reliable measure of acute stress. J Trauma Stress 2000;13 (4) 719- 734PubMedGoogle ScholarCrossref 38. American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC American Psychiatric Association1994; 39. Little RARubin DB Statistical Analysis With Missing Data. New York, NY John Wiley & Sons Inc1987; 40. Fink P Physical complaints and symptoms of somatizing patients. J Psychosom Res 1992;36 (2) 125- 136PubMedGoogle ScholarCrossref 41. Gregory RJ Characteristics of patients assigned multiple nonthreatening medical diagnoses. Prim Care Companion J Clin Psychiatry 2001;3 (4) 164- 167PubMedGoogle ScholarCrossref 42. Derogatis LRSavitz K The SCL-90-R and Brief Symptom Inventory in primary care settings. Marvish ME Handbook of Psychological Assessment in Primary Care Settings. Mahwah, NJ Lawrence A Erlbaum Associates2000;297- 334Google Scholar 43. Robins LNHelzer JECroughan JRatcliff KS National Institute of Mental Health Diagnostic Interview Schedule: its history, characteristics, and validity. Arch Gen Psychiatry. 1981;38 (4) 381- 389 44. Holman EASilver RCWaitzkin H Traumatic life events in primary care patients: a study in an ethnically-diverse sample. Arch Fam Med 2000;9 (9) 802- 811PubMedGoogle ScholarCrossref 45. Breslau NKessler RCChilcoat HDSchultz LRDavis GCAndreski P Trauma and posttraumatic stress disorder in the community: the 1996 Detroit Area Survey of Trauma. 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Mahwah, NJ Lawrence A Erlbaum Associates2003; 53. Wright KMUrsano RJBartone PTIngraham LH The shared experience of catastrophe: an expanded classification of the disaster community. Am J Orthopsychiatry 1990;60 (1) 35- 42PubMedGoogle ScholarCrossref 54. Boscarino JA Diseases among men 20 years after exposure to severe stress: implications for clinical research and medical care. Psychosom Med 1997;59 (6) 605- 614PubMedGoogle ScholarCrossref 55. Schnurr PPSpiro A IIIParis AH Physician-diagnosed medical disorders in relation to PTSD symptoms in older male military veterans. Health Psychol 2000;19 (1) 91- 97PubMedGoogle ScholarCrossref 56. McEwen BS Protective and damaging effects of stress mediators. N Engl J Med 1998;338 (3) 171- 179PubMedGoogle ScholarCrossref 57. Muller JETofler GHStone PH Circadian variation and triggers of onset of acute cardiovascular disease. Circulation 1989;79 (4) 733- 743PubMedGoogle ScholarCrossref 58. US Department of Health and Human Services, Vital and Health Statistics: Evaluation of National Health Interview Survey Diagnostic Reporting. Hyattsville, MD US Dept of Health and Human Services, Public Health Service1994;DHHS publication 94-1394, series 2, No. 120

Chen, Jen-Kai;Johnston, Karen M.;Petrides, Michael;Ptito, Alain

doi: 10.1001/archgenpsychiatry.2007.8pmid: 18180432

Abstract Context Depressed mood is frequently reported by individuals who have sustained cerebral concussion but little is known about the nature of this alteration in mood state. Objective To investigate whether the symptoms of depression reflect an ongoing pathophysiological change following concussion. Design Cohort study with male athletes using functional and structural neuroimaging. Setting Hospital laboratory and imaging facility. Participants Fifty-six male athletes with and without concussion were divided into (1) a no depression symptom, concussed group, (2) a mild depression symptom, concussed group, (3) a moderate depression symptom, concussed group, and (4) a healthy control group. Interventions All athletes filled out a postconcussive symptoms checklist and the Beck Depression Inventory II and underwent a magnetic resonance imaging session, which included T1, T2, and fluid-attenuated inversion recovery sequences, as well as functional magnetic resonance imaging (fMRI), during which they performed a working memory task. Main Outcome Measures (1) Behavioral: response speed and accuracy on the working memory task performed during the fMRI session; (2) functional imaging: brain activation patterns associated with the working memory task obtained using blood oxygen level–dependent fMRI; and (3) structural imaging: voxel-based morphometry examining gray matter concentration. Results (1) Behavioral: there was no performance difference between the groups; and (2) imaging: athletes with concussion with depression symptoms showed reduced activation in the dorsolateral prefrontal cortex and striatum and attenuated deactivation in medial frontal and temporal regions. The severity of symptoms of depression correlated with neural responses in brain areas that are implicated in major depression. Voxel-based morphometry confirmed gray matter loss in these areas. Conclusions The results suggest that depressed mood following a concussion may reflect an underlying pathophysiology consistent with a limbic-frontal model of depression. Given that depression is associated with considerable functional disability, this finding has important clinical implications for the management of individuals with a cerebral concussion. Mild traumatic brain injury and concussion account for as many as 90% of all cases of head injury.1 After a cerebral concussion, individuals often report a cluster of symptoms referred to as postconcussive symptoms (PCS). In addition to somatic symptoms, such as headaches and fatigue, these include cognitive deficits (eg, problems with memory, concentration, planning, and organization) as well as psychiatric complications, such as anxiety, irritability, and depression. Most studies on concussion have focused on the somatic and cognitive aspects, with the psychiatric dimension of PCS remaining largely unexplored. The psychiatric issue is particularly relevant in sport concussion2 because symptoms of depression in athletes with concussion have often been attributed to the loss of position on the team, lack of teammate support, poorly defined timeline to recovery, and the fact that this injury, being “invisible,” raises issues of treatment compliance or malingering. An acknowledgment of the importance of affective symptoms associated with concussion injury and recovery was raised at the most recent International Conference on Concussion in Sport.3 In addition, the anecdotal success of treatment with antidepressants in isolated sport concussion cases raises awareness of the importance of the evaluation of symptoms of depression following concussion. Previous functional imaging studies have suggested an association between prefrontal dysfunction and major depression.4-7 Because the prefrontal cortex is often implicated following head injury, the question arises as to whether the symptoms of depression are reflecting a pathophysiological change due to the concussion. The present study was designed to examine neural responses associated with a working memory task in athletes with concussion who complained of symptoms of depression, athletes with concussion who did not report symptoms of depression, and noninjured control athletes. The primary objective was to understand the underlying neural mechanisms of depression symptoms expressed by athletes following a cerebral concussion. Methods Participants Fifty-six right-handed male athletes were studied: 40 with concussion and 16 healthy controls. The concussion group consisted of athletes involved in contact sports at recreational, amateur, and professional levels. They were referred to the McGill Sports Medicine Clinic for consultation related to their concussive injury from sports. Their concussions were, in general, observed and verified by the team medical personnel present during the game; the athletes then agreed to report to the research team. Subjects in the control group were recruited from McGill varsity hockey and football teams. They were screened before the study to ensure that they had no neurological or psychiatric disorders and that they did not have a concussion in at least the 12 months preceding the study. A detailed description of the sample is provided in Table 1. The severity of the PCS in each participant at the time of the study was assessed using a 21-item checklist adapted from the Postconcussive Symptom Scale–Revised.8 The presence of symptoms of depression was evaluated using the Beck Depression Inventory II (BDI-II).9 Athletes with concussion were subdivided according to Spreen and Strauss10 into 3 groups based on their BDI-II score: (1) no depression symptom group, consisting of athletes with a BDI-II score ranging from 0 to 9, (2) mild depression symptom group, consisting of athletes with a BDI-II score ranging from 10 to 19, and (3) moderate depression symptom group, consisting of athletes with a BDI-II score ranging from 20 to 29. None of the athletes had a history of mood disorder, required a referral to a psychiatrist, or were taking psychotropic medication at the time of the study. All subjects gave informed, written consent for their participation in the study, which was approved by the Research Ethics Board of the Montreal Neurological Institute and Hospital, McGill University. Working memory task An externally ordered working memory task using pseudowords as stimuli (ie, experimental condition) and a control task (ie, baseline condition) were used for the functional magnetic resonance imaging (fMRI) studies. Briefly, the format of stimulus presentation, mode of response, and the timing of events were identical in both conditions, except that they differed in terms of working memory requirements. The working memory task was adapted from the Petrides externally ordered task,11,12 which requires the subjects to keep track of the serial presentation of 4 items selected randomly from a set of 5 items and to make a decision as to whether the test item, presented after a short delay, was among the 4 previously presented items or whether it was the item not presented. The subjects made their response by pressing the appropriate mouse key. In the baseline control task condition, 1 item was presented 4 times successively followed by a short delay, after which 1 of 2 items associated with either a left or a right mouse button press was presented and the subjects had to make the appropriate response. The subjects learned prior to scanning which one of these 2 items was associated with a left mouse button press and which one, with a right button press. The baseline task was introduced to obtain baseline activation and to “subtract out” any activation related to the motor and perceptual components of the working memory task. Imaging procedures Scanning was carried out using a 1.5-T Siemens Sonata scanner (Siemens AG, Erlangen, Germany). Functional Each scanning session started with the acquisition of high-resolution (1-mm3), T1-weighted, 3-dimensional structural images for anatomical localization of the functional data. Changes in neural activity were then measured using blood oxygenation level–dependent (BOLD) fMRI, by means of a T2*-weighted, gradient-echo echo planar imaging sequence (repetition time [TR], 3000 milliseconds; echo time [TE], 51 milliseconds; flip angle [FA], 90). A total of 120 acquisitions were collected in each functional scan. Twenty oblique, contiguous slices covering the entire brain (7-mm thickness, −35° relative to the anterior commissure–posterior commissure line, interleaved signal order) were taken during each acquisition. Each functional scan consisted of 6 alternating blocks (60 seconds each) of working memory and baseline conditions. All stimuli were presented via an LCD projector to a screen placed in front of the scanner, then to the subject via a mirror mounted on the head coil. The subjects' responses were recorded by a magnetic resonance imaging (MRI)–compatible mouse. Structural All subjects underwent routine MRI examination, including axial T2-weighted turbo spin echo (TR, 3910 milliseconds; TE, 81 milliseconds; FA, 150) and axial fluid-attenuated inversion recovery (TR, 9000 milliseconds; TE, 66 milliseconds; FA, 180) sequences. These MRIs, as well as the T1-weighted, 3-dimensional gradient echo images acquired as part of the functional scans, were evaluated by an expert clinical neuroradiologist for obvious signs of axonal injury and/or abnormal signal intensity, size, and location in the brain. fMRI DATA PROCESSING AND ANALYSIS Before statistical analyses, all frames in each functional scan were first realigned to the third frame in that run to correct transient head movements due to breathing and swallowing during data acquisition. The images were then spatially smoothed with a 6-mm full-width-at-half-maximum gaussian filter to increase the signal-to-noise ratio of the data and the tolerance of the subsequent analysis steps to residual motion in the scans and to minimize resampling artifacts. The motion-corrected data were analyzed statistically using fmristat13 (available at http://www.math.mcgill.ca/keith/fmristat). The BOLD data were first converted to a percentage of the whole volume. Significant BOLD change percentages were determined at each voxel, based on a linear model with correlated errors. The mean parametric t maps were constructed for each individual by averaging functional data across scans using linear regression analyses. To obtain the average group t maps, all individual data were first normalized to the Montreal Neurological Institute template (MNI305) constructed from the average stereotaxic MRI of 305 normal subjects, then combined using a mixed-effects linear model.14 The resulting t statistic images were thresholded using the minimum given by a Bonferroni correction and random field theory to correct for multiple comparisons. Each set of fMRI data was then coregistered to the corresponding anatomical MRI, which was corrected for intensity nonuniformity, and normalized to MNI305 standard space. Voxel-based morphometry analysis Voxel-based morphometry was carried out using the T1-weighted images of each subject. The analysis steps included (1) nonuniformity correction15 to remove variations in signal intensity related to radio-frequency inhomogeneity; (2) linear transformation of images into the standardized Montreal Neurological Institute 305 average template (MNI305) to normalize the images for between-subject differences in brain size and shape; (3) classification of brain tissue into white matter, gray matter, and cerebrospinal fluid using an automatic tissue-classification algorithm16; (4) blurring of the binary gray matter map extracted from the classified image using a gaussian smoothing kernel of 10 mm full width at half maximum. This step converts binary data into continuous data, which is necessary for statistical analysis. It also weighs the signal at each voxel according to the signal in neighboring voxels, thus reflecting the amount of gray matter within the smoothing kernel, and it reduces the effect of between-subject differences in the exact spatial location of gyri and sulci; and (5) voxelwise comparisons of group differences in gray matter concentration were performed using the t statistic. The significance of t statistics was determined by controlling the false-discovery rate using the entire gray matter as the search region (ie, exploratory approach). This yielded a t threshold = 3.5 at P < .05. The relationship between gray matter concentration and BDI-II scores in the concussed groups was examined using multiple regression analyses with age and PCS as confounding factors. Statistical analysis Analysis of variance was carried out on the demographic data. Analysis of covariance was used to compare performance on the working memory and control tasks, using age and PCS scores as covariates. Bonferroni correction was used for post hoc analysis. Finally, multiple regression analyses with BDI-II scores as the main predictor and age and PCS scores as confounding factors were carried out to examine the relationship between severity of symptoms of depression and fMRI BOLD signal change in each voxel of interest. Results Analysis of variance indicated significant group differences in PCS (F3,55 = 27.19; P < .01) and age (F3,55 = 6.18; P < .01). Post hoc tests showed that the control group had significantly fewer PCS than the mild (P < .01) and moderate (P < .01) depression symptom groups. There was no difference in PCS between the control and no depression symptom groups (P > .05). Post hoc tests also indicated that subjects in the control group were significantly younger than those in the mild (P < .01) and moderate (P < .01) depression symptom groups but not significantly different from the no depression symptom group (P > .05). Furthermore, no significant age difference was found between the concussed groups, and the concussed groups did not differ in terms of number of previous concussions (F2,39 = 2.70; P > .05) and time since injury (F2,39 = 0.15; P > .05). Because of the possible confounding effects of age and PCS, these factors were included in subsequent statistical analyses as covariates. Behavioral Analyses of covariance with age and PCS as covariates were performed on the accuracy (percentage correct) and speed (response speed in milliseconds) data from the working memory and control tasks collected during the fMRI session. There were no significant group differences in response accuracy (working memory, F3,55 = 1.08; P > .05; control task, F3,55 = 0.19; P > .05) and speed (working memory, F3,55 = 0.80; P > .05; control task, F3,55 = 0.37; P > .05) (Table 2). But as shown in Table 2, there was a trend for less accurate and slower performance in those athletes with concussion with symptoms of depression. Functional mri Whole-brain analysis was carried out to generate overall activation patterns for each group and the results are presented in Figure 1. The noninjured control group as well as the athletes with concussion who did not report symptoms of depression (BDI-II score < 10) exhibited the expected bilateral increase in fMRI signal in the dorsolateral prefrontal cortex (DLPC), dorsal anterior cingulate cortex (dACC), insular cortex, striatum, and thalamus, consistent with our previous findings.11 Athletes with concussion with mild depression symptoms showed attenuated task-related activity in these regions, with significant BOLD changes detected only in the insular cortex (bilaterally), dACC, and left striatum. The moderate depression symptom group showed even more decreased activity in those regions, the only significant activation peak being in the dACC. In addition, examination of the negative peaks from whole-brain analysis (Figure 1B) revealed that the control and no depression symptom concussed groups showed similar deactivation patterns in the rostral anterior cingulate cortex (rACC), posterior cingulate cortex, medial orbitofrontal cortex (mOFC), and parahippocampal gyrus (bilateral). In contrast, the mild depression symptom group showed less deactivation in these areas, and this attenuation was even more pronounced in those athletes with moderate depression symptoms. To examine further the relationship between brain activations and the severity of depression symptoms, voxelwise regression analyses were performed on the entire fMRI time series using scores on the BDI-II as a predictor, with age and PCS as covariates. This allowed identification of the cerebral regions where changes in BOLD signals were modulated by the scores on the BDI-II. After removing the effect of age and PCS, the magnitude of fMRI BOLD signals in the rACC, mOFC, posterior cingulate, and left and right parahippocampal gyri was found to be positively correlated with BDI-II scores. Furthermore, both the right and left DLPC, left insula, and left striatum were found to be negatively correlated with the severity of depression symptoms as assessed with the BDI-II (Figure 2). As expected, athletes with a higher rating on the PCS Scale usually scored higher on the BDI-II (Figure 3A). This, however, was not always the case; a subgroup of athletes with concussion (n = 6) had significant PCS complaints but normal scores on the BDI-II. As shown in Figure 3B, C, and D, this group of athletes showed reduced task-related cerebral activations in the right DLPC compared with the controls, as seen in those with symptoms of depression. However, there was a crucial difference in the rACC and the mOFC between the 2 groups with high PCS scores with and without depression symptoms. In these cerebral areas, athletes with high PCS but normal BDI-II scores showed similar negative BOLD signal changes as the control group. In contrast, these negative BOLD responses were significantly attenuated in those athletes with high PCS scores and symptoms of depression. This difference can be illustrated further by contrasting the BOLD responses of this group with those reporting mild depression symptoms. Both groups had similar PCS scores (25 vs 27) and showed reduced activations in the right DLPC when compared with the control subjects. However, only those with symptoms of depression had significantly fewer task-related BOLD decreases in the rACC and the mOFC, and they showed greater signal reduction in the right DLPC compared with the no depression symptom but high PCS score group. Structural mri and voxel-based morphometry The MRIs were evaluated by a clinical neuroradiologist and were all found to be normal. Group comparisons of gray matter concentration are shown in Figure 4. Differences in gray matter concentration were noted between the control and mild depression symptom group in the rACC, left DLPC, left insula, and left parahippocampal gyrus. The moderate depression symptom group also showed less gray matter density in these areas in addition to reduced gray matter concentration in the right DLPC and right insula. Finally, differences in gray matter density were found between the control and no depression symptom athletes with concussion in the left and right insula. Multiple regression analysis controlling for age and PCS revealed a significant effect of BDI-II scores on gray matter density in the rACC (Figure 5). Specifically, an increase in the severity of depression symptoms was associated with further reduction of gray matter in this area. Comment Depressed mood is frequently reported by individuals who have sustained a cerebral concussion,17,18 but little is known about the neural substrate of this alteration in mood state. Herein, we report differences in neural activity in athletes with concussion and symptoms of depression, athletes with concussion without symptoms of depression, and normal control subjects. Functional MRI results showed that those athletes with concussion and mild symptoms of depression had fewer task-related BOLD signal increases in the prefrontal region and striatum, and this reduced activation was even more pronounced in those with moderate symptoms of depression. Similar findings have been reported by McAllister and colleagues19-21 in a series of fMRI studies using n-back tasks. In these studies, patients with mild head injury showed less task-related brain activity than the control group when comparing 1-back vs 0-back conditions. Interestingly, patients with head injury showed a greater increase in brain activation when working memory demand increased (ie, 2-back vs 1-back) relative to the control subjects. In the present study, working memory tasks that required active monitoring and manipulation of information activated the DLPC, striatum, and thalamus in healthy subjects. These areas are known to be involved in the performance of such tasks. Dopaminergic input into the striatum and frontal cortex plays a major regulatory role in neural activity in these areas and there is considerable evidence pointing to the role of the dopaminergic system in depression. These include reports of reduction of the dopamine level in patients with depression22,23 and the antidepressant effects of selective dopaminergic agents such amineptine24,25 and pramipexole dihydrochloride.26,27 Thus, our finding may indicate an abnormal dopaminergic function within this cortico-striato-thalamic system in athletes with concussion with symptoms of depression. This possibility is supported by studies that demonstrate antidepressant effects of repetitive transcranial magnetic stimulation in the DLPC,28 presumably by inducing dopamine release in the striatum.29 We also found that athletes with concussion with symptoms of depression had different neural responses in the parahippocampal gyrus, mOFC, rACC, and posterior cingulate cortex. In these regions, athletes with depression symptoms showed less reduction in activity relative to the control group. This attenuation was positively correlated with the severity of symptoms of depression expressed by these athletes. Functional imaging studies with healthy subjects have frequently shown a decrease in activities in these brain regions when performing working memory and other cognitive tasks that require attention.30-32 Furthermore, reduction of neural activity in these areas appears to be inversely correlated with activity in the DLPC,33,34 with the degree of reduction increasing with the demands of the task.31,35 Thus, it is necessary to consider the role of task difficulty in the activity reported herein. Paus et al36 reviewed 107 blood-flow activation studies and concluded that increased activity in the anterior cingulate is likely to occur in the more difficult tasks. It can therefore be argued that the increased BOLD signal in athletes with depression symptoms may simply reflect greater cognitive demand. This is unlikely, however, because the athletes with symptoms of depression did not show a statistically significant difference in performance. Thus, task difficulty may be excluded as a factor responsible for the level of activity in the anterior cingulate region. A more plausible explanation why athletes with symptoms of depression showed less reduction in activity relative to the control group during the performance of the working memory task (ie, the normal response in healthy subjects) is that in these athletes activity in the rACC and mOFC may have been increased relative to the normal subjects. Elevated neural activities in these regions have been associated with experimentally induced anxiety and sadness in normal subjects and in patients with major depressive disorder (MDD).37-39 Positron emission tomographic studies on major depression have also reported increased metabolism in the rACC,40,41 reversible with antidepressant medication.40 In a study using fMRI, Rose et al42 reported that patients with MDD had relatively higher fMRI signals in the mOFC and rACC when performing an n-back working memory task than normal control subjects. Although none of the athletes with symptoms of depression reported herein were clinically diagnosed with MDD, our results are strikingly similar to existing functional neuroimaging findings in major depression and are consistent with a limbic-frontal model of depression.43,44 They suggest that symptoms of depression following head trauma may share the same underlying neural mechanism as MDD. The presence of abnormal neural activity in athletes with concussion with symptoms of depression demonstrated by our fMRI data is in keeping with the results of our voxel-based morphometric study. We found that athletes with concussion with depression symptoms showed reduced gray matter density in brain regions necessary to carry out the working memory task. The concussed groups in the present study consisted of athletes who sustained a cerebral concussion on average 5 to 7 months previously and who continued to experience a variable degree of PCS. Other voxel-based morphometric studies have shown both gray and white matter losses in head trauma populations,45,46 and our findings lend further support to the existence of an organic basis to persistent PCS.47 As shown in Figure 4 and Figure 5, gray matter loss was also noted in the no depression symptom, concussed group in the insular cortex bilaterally. However, only those athletes with concussion with symptoms of depression displayed further gray matter reduction in the medial frontal and temporal regions, and the reduced gray matter volume in the rACC was negatively correlated with the severity of depression symptoms. These findings are consistent with the roles of these cerebral areas in affective disorders; they are also in accordance with findings of hypometabolism in the left DLPC in patients with depression48,49 and with the antidepressant effects of repetitive transcranial magnetic stimulation applied to this cortical region.50-52 Studies that examined outcomes following traumatic brain injury have reported a prevalence of depression a few years after the injury.53-55 The question arises as to whether the symptoms of depression represent an emotional reaction to the trauma and to the ongoing PCS or whether there is an underlying pathological nature. Levin et al56 found that patients with mild brain injury with documented lesions on computed tomographic scan were at greater risk for major depressive episodes 3 months postinjury. Recently, Jorge et al17 reported that depression following head trauma was equally frequent among mild, moderate, and severe cases 1 year postinjury. In addition to poorer functional outcome, patients with head injury with depression also showed, as we did, significantly reduced gray matter volumes in the left prefrontal cortex. The athletes with concussion in the present study were young individuals without a medical history of mood disorder. It is therefore not likely that our concussed sample had a preexisting reduction in gray matter density that led to their vulnerability to develop depressive disorder following concussion. In addition, we also found reduced gray matter concentration in the concussed but no depression symptom group. Thus, the structural changes reported herein were likely due to concussion, and the symptoms of depression were probably the result of a pathological state in the medial prefrontal region caused by the trauma. These results, together with findings from previous studies, point to an underlying pathological nature to the symptoms of depression following brain trauma. Our data also indicate that the presence of PCS with depression symptoms is associated with a greater reduction in cerebral activity in the DLPC than with PCS alone and are consistent with reports of greater disability and poorer outcome in patients with head trauma with depression.57 Some potential limitations of the present study merit consideration. First, our study focused primarily on complex concussions (ie, with persistent PCS) in young male athletes. This sampling limits the generalizability of our findings to the athlete with concussion and head injury populations at large. For instance, studies have repeatedly found sex differences in depression; hence, our finding may not apply to a female population. Furthermore, the athletes with concussion in our study represent the “complex” concussion subtype defined by the new concussion classification introduced by the International Conference on Concussion in Sports.3 Thus, our finding may not be applicable to the “simple” concussion subtype in which symptoms disappear within days and symptoms of depression experienced during this limited period are likely to be related to exogenous factors (eg, reaction to trauma, missing play) rather than endogenous factors (eg, brain lesion, altered physiology). Also, our results may not be representative of more severe forms of head injury in which lesions are usually visible by conventional morphological imaging such as computed tomography and MRI, and the pathological changes following such injury may differ from those described herein. Finally, we did not test a control group with symptoms of depression and no concussion. Because we found that athletes with concussion with symptoms of depression showed BOLD response patterns consistent with functional neuroimaging findings in clinical depression, we suggest that they may share the same underlying pathological nature in the medial prefrontal region. This conclusion would be strengthened if we can demonstrate the same activation pattern between athletes with concussion with depression symptoms and athletes without concussion with depression. Investigations on the long-term consequences of head injury have pointed to a link between a history of brain injury and an increase in the likelihood of developing major depression later in life.58,59 Given that depression is associated with significant functional deficits, early identification of the nature of depression symptoms following head trauma (psychological vs pathological) has important implications for early intervention and successful outcome. Correspondence: Alain Ptito, PhD, Neuropsychology/Cognitive Neuroscience Unit, Montreal Neurological Institute, 3801 University St, Montreal, QC H3A 2B4, Canada ([email protected]). Submitted for Publication: April 10, 2007; final revision received July 5, 2007; accepted August 23, 2007. Author Contributions: Drs Ptito and Johnston had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis and the final decision to submit for publication. Financial Disclosure: None reported. Funding/Support: This study was supported by Canadian Institutes of Health Research operating grant MOP-64271. Dr Chen is supported by a Fonds de la Recherche en Santé du Québec doctoral award. Role of the Sponsor: The funding agency was not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or in the preparation, review, and submission of the manuscript. Additional Contributions: Mary Mooney, PhD, Lynn Bookalam, MSc, and James Hieminga, BMus, helped recruit the subjects and coordinate testing. Thomas Paus, MD, PhD, provided comments and suggestions. References 1. Holm LCassidy JDCarroll LJBorg J Summary of the WHO Collaborating Centre for Neurotrauma Task Force on Mild Traumatic Brain Injury. J Rehabil Med 2005;37 (3) 137- 141PubMedGoogle Scholar 2. Johnston KMBloom GARamsay JKissick JMontgomery DFoley DChen JPtito A Current concepts in concussion rehabilitation. 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