Background: Identifying biomarkers to enrich prognostication and risk predictions in individuals at high risk of developing psychosis will enable stratified early intervention efforts. Brain-derived neurotrophic factor has been widely studied in schizophrenia and in first-episode psychosis with promising results. The aim of this study was to examine the levels of serum brain-derived neurotrophic factor between healthy controls and individuals with ultra-high risk of psychosis. Methods: A sample of 106 healthy controls and 105 ultra-high risk of psychosis individuals from the Longitudinal Youth at Risk Study was included in this study. Ultra-high risk of psychosis status was determined using the Comprehensive Assessment of At-Risk Mental State at recruitment. Calgary Depression Scale for Schizophrenia was used to assess the severity of depression. All participants were followed up for 2 years, and ultra-high risk of psychosis remitters were defined by ultra-high risk of psychosis individuals who no longer fulfilled Comprehensive Assessment of At-Risk Mental State criteria at the end of the study period. Levels of brain-derived neurotrophic factor were measured in the serum by enzyme-linked immunosorbent assay method. Results: The ultra-high risk of psychosis group had significantly higher baseline levels of serum brain-derived neurotrophic factor compared with the control group (3.7 vs 3.3 ng/mL, P = .018). However, baseline levels of serum brain-derived neurotrophic factor did not predict the development of psychosis (OR = 0.64, CI = 0.40–1.02) or remission (OR= 0.83, CI = 0.60–1.15) from ultra- high risk of psychosis status. Conclusion: Findings from our study did not support a role for serum brain-derived neurotrophic factor in predicting outcomes in ultra-high risk of psychosis individuals. However, the finding of higher levels of serum brain-derived neurotrophic factor in ultra-high risk of psychosis individuals deserves further study. Keywords. brain-derived neurotrophic factor, ultra-high risk of psychosis, peripheral markers Introduction The ultra-high risk state for psychosis (UHR) was conceived to be and clinically operationalized criteria, conversion rates across akin to a prodromal phase for psychosis but identified prospec- studies have declined considerably (Yung et al., 2008 Ruhrmann ; tively (Yung et al., 2005). Over the years, using well-researched et al., 2010; Simon and Umbricht, 2010). It is now clear that while Received: November 22, 2017; Revised: March 11, 2018; Accepted: March 23, 2018 © The Author(s) 2018. Published by Oxford University Press on behalf of CINP. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, 1 provided the original work is properly cited. For commercial re-use, please contact email@example.com Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy036/4953164 by Ed 'DeepDyve' Gillespie user on 08 June 2018 2 | International Journal of Neuropsychopharmacology, 2018 Significance Statement Levels of serum brain-derived neurotrophic factor (BDNF) were significantly higher in participants identified to be at ultra-high risk of psychosis (UHR) than in healthy controls. This difference may be due to usage of antidepressants. In addition, baseline level of serum BDNF did not predict conversion to psychosis or remission status in the UHR group. Findings from our study did not support a role for serum BDNF in predicting outcomes in UHR individuals. However, the finding of higher levels of serum BDNF in UHR individuals deserves further study. a significant proportion develops psychosis, the majority do not. community agencies including educational institutes and social While studies have identified a list of predictors to aid clinicians services, or were self-referred. Participants were excluded if they in stratifying the UHR sample by different risk probabilities to had a past or current history of psychosis or mental retardation, guide clinical decision making in early intervention strategies, were currently using illicit substances, were taking mood stabi- none of the predictors have included biological measurements lizers, had previous antipsychotic exposure of >5 mg/d halop- (Fusar-Poli et al., 2013). eridol for 3 weeks (or equivalent) or were on an antipsychotic at Brain-derived neurotrophic factor (BDNF) has been widely the point of recruitment, or had medical causes associated with studied for association with development, regeneration, sur - their attenuated psychotic symptoms. Data collected at baseline vival, and maintenance of neurons in the brain (Huang and and 24-month/final study visit was used for this study. Lee, 2006; Nurjono et al., 2012). Meta-analyses drew attention to Ethics approval for this study was provided by the National the role of BDNF in mental disorders such as mood disorders, Healthcare Group’s Domain Specific Review Board. After com- Alzheimer’s disease, and psychosis, suggesting BDNF as a can- plete description of the study to the participants, written didate biomarker for diagnostic and prognostic purposes for informed consent was obtained. Participants who provided a disease outcomes and other comorbidities. (Brunoni et al., 2008; blood sample were included in the present study. Green et al., 2011; Ji et al., 2015). Although BDNF was thought to influence the predisposition in schizophrenia development, Assessments there is a lack of longitudinal perspective in the evaluation of The Comprehensive Assessment of At-Risk Mental State (CAARMS) prognostic utility of BDNF in psychosis (Nurjono et al., 2012). is a semistructured interview used to evaluate if an individual Levels of BDNF are influenced by obesity, smoking, aging, meets the UHR criteria (Yung et al., 2005). The positive symptom gender, and medications (Golden et al., 2010; B. H. Lee and Kim, subscale was used, which assesses 4 symptom domains: Unusual 2010; Zhang et al., 2010; Bus et al., 2011; Toll and Mané, 2015), all Thought Content (UTC), Non-bizarre Ideas (NBI), Perceptual of which have some association with mental disorders. BDNF’s Abnormalities (PA), and Disorganized Speech (DS). Each symptom role in metabolism and food regulation through modulation was rated for the maximum intensity, frequency and duration, of hypothalamus has been implicated in the development of pattern, and related distress over the last 1 year. obesity (Lebrun et al., 2006; Araya et al., 2008; Lee et al., 2016). UHR positive individuals fall into one or more of the following Smoking, which is prevalent in schizophrenia and ultra-high groups: vulnerability group (at risk of psychosis due to the combi- risk groups, has also been associated with an elevation in serum nation of a trait risk factor and a significant deterioration in men- BDNF level due to the effects of chronic nicotine exposure on tal state and/or function), attenuated psychotic symptoms group the hippocampus (Kenny et al., 2000; Lee et al., 2013, 2016). (at risk of psychosis due to subthreshold psychotic syndrome), Depression was reported to be the most frequent diagnosis in and brief limited intermittent psychotic symptoms group (at risk UHR (Lim et al., 2015), and antidepressant treatments stimulate of psychosis due to a recent history of frank psychotic symp- neurogenesis, synaptogenesis, and neuronal maturation and toms that resolved spontaneously within a week). The CAARMS increase BDNF activity, thus increasing serum BDNF levels in interview was repeated at every time point. CAARMS total score depressed patients (Lee and Kim, 2010). These factors further refers to the sum of multiples of intensity and frequency of confound the relationship between BDNF and mental disorders. CAARMS subscales—UTC, NBI, PA, and DS (Morrison et al., 2012). However, in a meta-analysis of 17 studies by Green et al (2011), Remission status was determined through a change in CAARMS only 1 study included obesity and smoking as confounders in status from positive at baseline to not meeting UHR criteria at the comparison of serum BDNF levels between schizophrenia 24 months or the final study visit, whichever is the latest. and healthy controls (Green et al., 2011). The Structured Clinical Interview for DSM IV Axis I Disorders The present study aims to evaluate the serum BDNF levels in was used to assess for the presence of any psychiatric disor - a group of UHR individuals from the Longitudinal Youth at Risk ders. This interview was performed at recruitment and again at Study (LYRIKS) (Lee et al., 2013; Lim et al., 2015) and to exam- the end of the follow-up period or when a participant developed ine the association between conversion and remission status at psychosis. 24-month follow-up with serum BDNF level at recruitment. UHR positive participants were further assessed, at recruit- ment and 6-monthly intervals, on the Calgary Depression Scale for Schizophrenia (CDSS). Methods Study Settings and Subjects Measurement of Serum BDNF Levels LYRIKS was a prospective, observational study conducted in Venous blood was collected into a serum separating tube from Singapore on youths aged 14 to 29 to assess risk factors for study participants and allowed to coagulate at room tempera- psychosis. Details of the study have been previously reported ture for approximately 30 minutes. Serum was collected after (Lee et al., 2013; Mitter et al., 2014; Lim et al., 2015). In brief, centrifugation for 10 minutes at 4°C using a clinical centrifuge participants were recruited from psychiatric clinics, various (Hettich). BDNF was then measured using commercially available Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy036/4953164 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Yin Yee et al. | 3 ELISA (Millipore) with the range of sensitivity from 7.8 to 500 pg/ Table 1. Study Participants’ Demographics at Baseline mL and intra-assay variations of <20%. Briefly, the serum sam- Control UHR ples were diluted 1:2 in sample diluent provided by the kit and (n = 106) (n = 105) ran in duplicates. The samples were subsequently incubated in 1:1000 biotinylated mouse anti–human BDNF monoclonal anti- n (%) n (%) P Value body overnight at 4°C before they were incubated in 1:1000 bioti- nylated mouse anti-BDNF monoclonal antibody for 2 hours and Ethnicity .754 1:1000 streptavidin–horseradish peroxidase conjugate solution Chinese 72 (68.6) 75 (71.4) Malay 20 (19.0) 20 (19.0) for 1 hour at room temperature. TMB/E substrate was then added Indian 12 (11.4) 8 (7.6) to each sample for 15 minutes, and the reaction was stopped Others 1 (1.0) 2 (1.9) with the addition of stop solution provided as part of the kit. Gender .251 Immediately after the reactions were stopped, the plate was read Male 63 (60.0) 71 (67.6) at 450 nm absorbance. Samples with readings outside the range Female 42 (40.0) 34 (32.4) of sensitivity were excluded from subsequent analyses. Smoking status .052 No 86 (81.9) 74 (70.5) Data Analysis Yes 19 (18.1) 31 (29.5) Psychiatric comorbidities Data was analyzed on SPSS Statistics version 23 (IBM Co.). Bipolar disorder 2 (1.9) Descriptive statistics were tabulated for control and UHR posi- Depressive disorders 1 (0.9) 39 (37) tive groups. Statistical significance was set at P < .05. Categorical Anxiety disorders 1 (0.9) 41 (39) variables were examined using chi-squared test. Continuous Substance use disorders 2 (1.9) variables were analyzed via Mann-Whitney U test and data were Adjustment disorders 6 (5.7) reported as mean and SD. Kruskal-Wallis H was used to compare b Antidepressants usage serum BDNF levels among control, UHR on antidepressants, and No 105 (100.0) 59 (56.2) UHR not on antidepressants at baseline. A multivariate linear Yes 0 (0.0) 46 (43.8) regression model was employed to examine the associations Mean (SD) Mean (SD) between CAARMS scores, CDSS scores, and serum BDNF levels Age 22.0 (3.8) 21.8 (3.6) .13 of UHR positive individuals. Logistic regression analysis was BMI 22.3 (3.6) 22.5 (4.9) .546 used to study the relationship between remission, conversion CAARMS total 1.0 (2.6) 24.1 (15.1) <.005 status, and serum BDNF level at baseline. Age, gender, body CDSS — 5.8 (5.0) mass index (BMI), smoking status, and use of antidepressants Serum BDNF (ng/mL) 3.3 (1.5) 3.7 (1.4) 0.018 at baseline were included in the regression models as they have Abbreviations: BMI, body mass index; CAARMS ,Comprehensive Assessment been shown to influence serum BDNF levels (Green et al., 2011; of At-Risk Mental State; CDSS Calg , ary Depression Scale for Schizophrenia; Björkholm and Monteggia, 2016; Lee et al., 2016). BDNF, brain derived neurotrophic factor. Chi-squared test for categorical variables, Mann-Whitney U test for continuous variables. Results Antidepressants used in current study were amitriptyline, clomi- pramine, venlafaxine, dothiepin, mirtazapine, fluvoxamine, fluox- Participant Demographics etine, sertraline, paroxetine, and escitalopram. A total of 106 healthy controls and 105 individuals with UHR CAARMS = (I F ) + (I F ) + (I F ) + (I F ). UTC* UTC NBI* NBI PA* PA DS* DS were included in the present study. A detailed description of the demographics can be found in Table 1. There were no differences (n = 59). Mann-Whitney U test was performed to compare serum in ethnicity, gender, age, BMI, and smoking status between the 2 BDNF levels at baseline between groups. UHR not on antidepres- groups. Approximately 44% of UHR individuals were on antide- sants had a significantly higher baseline serum BDNF level than pressants at the time of recruitment. healthy controls (3.7 ± 1.4 vs 3.3 ± 1.5 ng/mL, U = 2473, P = .026). There were no differences in ethnicity, gender, smoking sta- There was no significant difference in baseline serum BDNF tus, age, and BMI among healthy controls, remitters, nonremit- levels between healthy controls and UHR on antidepressants, ters, and converters at baseline. While healthy controls (0.9 ± 2.8) at 3.3 ± 1.5 ng/mL and 3.6 ± 1.5 ng/mL, respectively (U = 2046.5, had a significantly lowest baseline CAARMS total score (P < .05), P = .116). A similar observation was made for the difference there was no difference among the remitters (24.8 ± 17.0), non- between UHR on antidepressants and UHR not on antidepres- remitters (22.9 ± 13.8), and converters (25.6± 12.5) CAARMS total sants (U = 1322, P = .821) (Figure 1). score. There was also no difference in baseline CDSS scores Follow-up data were available for 71 controls and 71 UHR among remitters (5.5 ± 4.9), nonremitters (5.8 ± 5.3), and convert- individuals. Of the 71 UHR individuals with follow-up data, 35 ers (6.3 ± 5.0) (P = .879). There was a significant number of remit- were remitters, 26 were nonremitters, and 10 were converters. ters (37%), nonremitters (33%), and converters (45%) who were We did not observe a significant difference in serum BDNF levels on antidepressants since baseline (P < .005). between both time points (see Table 2). Serum BDNF Level at Baseline and 24-Month Associations between Baseline Serum BDNF Level Follow-Up and Psychopathology Indices, Conversion, and The UHR group was observed to have a significantly higher Remission Status serum BDNF level than healthy controls at baseline (U = 4519.5, There was no significant association between baseline lev- P = .018). To investigate the effects of antidepressants on serum els of serum BDNF with baseline CAARMS and CDSS scores BDNF in the current dataset, UHR group was further divided into (see Table 3). Baseline levels of serum BDNF were also not 2 groups—on antidepressants (n = 46) and not on antidepressants Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy036/4953164 by Ed 'DeepDyve' Gillespie user on 08 June 2018 4 | International Journal of Neuropsychopharmacology, 2018 Figure 1. Baseline serum brain-derived neurotropic factor (BDNF) levels between groups. Table 2. Serum BDNF Levels at Baseline and 24-Month Follow-Up Table 3. Associations between Serum BDNF and Psychopathology at Baseline Serum BDNF (ng/mL) Adjusted for Gender, Age, Baseline 24-month follow-up P value BMI, Smoking, and Use of Unadjusted Antidepressants Healthy control n = 76 3.3 (1.5) n = 71 3.0 (1.0) .254 Remitter n = 41 3.7 (1.3) n = 35 3.4 (0.7) .147 β 95% CI P value β 95% CI P value Nonremitter n = 27 3.6 (1.5) n = 26 3.7 (1.5) .949 CAARMS 0.10 -1.03–3.10 .323 0.10 -1.00–3.11 .308 Converter n = 11 2.9 (1.8) n = 10 3.4 (1.3) .241 CDSS 0.12 -0.27–1.08 .239 0.12 -0.28–1.08 .248 Wilcoxon signed ranks test. However, we did not observe the effect of antidepressant on associated with conversion (OR= 0.64, CI = 0.40–1.02) or serum BDNF levels in our dataset. This could be due to varying remission (OR = 0.83, CI = 0.60–1.15) in the UHR group (see duration and dosage of psychotropic medications of the UHR Tables 4 and 5). group. There has been a continuous effort to identify predic- tors of psychosis over the past decade. The North American Prodrome Longitudinal Study reported 5 clinical predictors Discussion in their participants with high risk of psychosis: genetic risk with functional decline, high unusual thought content Levels of serum BDNF have been commonly reported to be lower in patients with mental disorders, suggesting the utility scores, high suspicion or paranoia scores, low social func- tioning, and history of substance abuse (Seidman et al., 2010). of BDNF as a biomarker in mood disorders, schizophrenia, and Alzheimer’s disorder (Brunoni et al., 2008Gr ; een et al., 2011; Ji Similar to the North American Prodrome Longitudinal Study, the Personal Assessment and Crisis Evaluation Study identi- et al., 2015). However, there is no longitudinal study of the appli- cation of BDNF as a biomarker. To our knowledge, this study is fied high unusual thought content scores, low functioning, and genetic risk with functional decline to be predictors of the first to report the levels of serum BDNF in individuals with UHR. The present study found a higher baseline serum BDNF psychosis in their cohort (Thompson et al., 2011). Participants with high risk of psychosis in the Basel Early Detection of level in the UHR group. However, baseline levels of BDNF were not associated with severity of symptoms—both psychotic and Psychosis Clinic study, high suspiciousness, high anhedo- nia, or asociality scores contributed to high transition risk depressive symptoms. There was also no association between baseline serum BDNF level and conversion or remission status (Riecher-Rössler et al., 2009). Clinical markers, family history of psychosis, neurocognitive, electrophysiological measures, at 24-month follow-up visit. Contrary to a recent systemic review on drug naïve, first- environmental factors, lifestyles, and conducting multicenter studies were suggested to aid in improving the prediction of episode psychosis patients, the present study observed a higher baseline serum BDNF level in UHR individuals (Toll psychosis (Fusar-Poli et al., 2013). While the abovementioned studies identified predictors through psychopathology indi- and Mané, 2015). As suggested by previous studies, this dif- ference in serum BDNF level may be due to usage of anti- ces, the present study is the first attempt to explore the util- ity of serum BDNF levels in the prediction of conversion and depressants, as almost one-half of UHR individuals were on antidepressants (Fusar-Poli et al., 2014Lim et ; al., 2015). remission in UHR individuals. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy036/4953164 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Yin Yee et al. | 5 Table 4. Prediction of Conversion Status at 24-Month Follow-Up Using Serum BDNF at Baseline Adjusted for Gender, Age, BMI, Smoking, and Use Unadjusted of Antidepressants Odds Ratio 95% CI P value Odds Ratio 95% CI P value Serum BDNF 0.63 0.40–1.00 .051 0.64 0.40–1.02 .060 Table 5. Prediction of Remission Status at 24-Month Follow-Up Using Serum BDNF at Baseline Adjusted for Gender, Age, BMI, Smoking, and Use Unadjusted of Antidepressants Odds Ratio 95% CI P value Odds Ratio 95% CI P value Serum BDNF 0.84 0.62–1.14 .266 0.83 0.60–1.15 .183 The present study has some limitations. Psychotropic medi- BDNF levels: implications for the role of neuroplasticity in cations have been studied to influence serum BDNF levels depression. Int J Neuropsychopharmacol 11:1169–1180. (Björkholm and Monteggia, 2016). In this observational study, we Bus BA, Molendijk ML, Penninx BJ, Buitelaar JK, Kenis G, Prickaerts were unable to adjust or control for participants’ prior use of J, Elzinga BM, Voshaar RC (2011) Determinants of serum brain- psychotropic medications. Serum BDNF may not provide a direct derived neurotrophic factor. Psychoneuroendocrinology index of BDNF level in the central nervous system and may not 36:228–239. represent the degree of synaptic plasticity or neuronal mainten- Fusar-Poli P, Nelson B, Valmaggia L, Yung AR, McGuire PK (2014) ance. The small sample size for converters might limit the stat- Comorbid depressive and anxiety disorders in 509 individu- istical power to detect a difference. Genotypic information on als with an at-risk mental state: impact on psychopathology val66met BDNF polymorphism was unavailable and might have and transition to psychosis. Schizophr Bull 40:120–131. affected expression of serum BDNF levels (Toll and Mané, 2015). Fusar-Poli P, et al (2013) The psychosis high-risk state: a compre- The present study is the first to explore serum BDNF levels hensive state-of-the-art review. JAMA Psychiatry 70:107–120. in an UHR group and if it adds additional prognostic accuracy Golden E, Emiliano A, Maudsley S, Windham BG, Carlson OD, in predicting clinical outcomes. While we found, rather unex- Egan JM, Driscoll I, Ferrucci L, Martin B, Mattson MP (2010) pectedly, higher levels of serum BDNF in individuals with UHR, Circulating brain-derived neurotrophic factor and indices of this difference might have been caused by antidepressant use. metabolic and cardiovascular health: data from the Baltimore Our study did not support the use of serum BDNF levels in UHR longitudinal study of aging. Plos One 5:e10099. individuals to predict development of psychosis or remission Green MJ, Matheson SL, Shepherd A, Weickert CS, Carr VJ (2011) from the UHR state. 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International Journal of Neuropsychopharmacology – Oxford University Press
Published: Mar 23, 2018
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