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Cognitive Decline in Presymptomatic Alzheimer Disease

Cognitive Decline in Presymptomatic Alzheimer Disease Fundamental questions remain in the search for the cause and treatment of Alzheimer disease (AD). As yet, it is not fully known what mechanisms trigger the sequence of neurologic changes that lead to neuronal death and dementia.1,2 An often-cited model proposes that APP in the brain is abnormally cleaved into smaller particles that produce a toxic β-amyloid peptide, which clump into extracellular plaques. The toxic effects of Aβ induce hyperphosphorylation of the microtubule-associated protein tau, causing neurofibrillary tangles, cell death, and subsequent dementia.3 Measures of these biomarkers can be obtained from cerebrospinal fluid and with neuroimaging. This model has been modified to allow a more complex temporal ordering of some biomarkers.4 More important, this model suggests that the disease begins decades before the onset of clinical symptoms. The most common risk factor is age. To date, no effective treatment has been found.5 Treatment that will delay or slow progression of AD likely will depend on early detection. Episodic memory impairment is the earliest marker of dementia in most cases. Longitudinal studies6,7 of participants at risk for AD by virtue of old age have found that a slow decline in memory precedes a period of accelerated memory decline, leading to dementia. Some studies8,9 have found that cognitive measures are at least as sensitive to disease onset as neuropathologic biomarkers. A promising line of research is the study of individuals with one of the rare genetic mutations that causes autosomal dominant Alzheimer disease (ADAD). This form of the disease contrasts with most sporadic, late-life cases in which no single-gene mutation is responsible. Most cases of ADAD are the result of a single PSEN1 (GenBank NM_000021) mutation, and others are caused by mutations of PSEN2 (GenBank NG_007381) or APP. Carriers can be identified at an early age presumably before the disease begins. Longitudinal studies of ADAD offer a unique opportunity to measure progression in biomarker abnormalities from the earliest changes to the full clinical expression of the disease. The importance of longitudinal analysis was demonstrated by the finding that concentrations of biomarkers can decrease, rather than continue to increase or stay the same, as ADAD progresses.10 The study by Aguirre-Acevedo et al11 in this issue of JAMA Neurology explores when cognitive decline is measurable and what cognitive functions are the earliest to change. They present data of a kindred of PSEN1 E280A carriers with ADAD followed up longitudinally for 20 years who at study entry were 18 years and older. A total of 493 carriers met the study inclusion criteria, and 256 carriers were examined twice or more with the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) test battery12 at 2-year intervals with a median follow-up of 5 years. Most (386 [78.3%]) were cognitively normal, whereas 51 (10.3%) had symptoms of mild impairment (Clinical Dementia Rating, 0.5). Word list memory had the earliest change, occurring a mean of 12 years before the clinical diagnosis of mild cognitive impairment and 17 years before a dementia diagnosis. Cognitive declines occurring later were observed in verbal fluency, naming, and constructional praxis, whereas the CERAD total score had the greatest decrease after onset of cognitive decline. The study’s longitudinal data revealed that those with a higher educational level were approximately 3 years older at onset, but they had a steeper cognitive decline after onset, which is consistent with reports of individuals with sporadic, late-onset AD. Other factors associated with steeper cognitive decline were a history of diabetes mellitus, hypertension, or tobacco and alcohol use. The particular tests that studies report as most sensitive for detecting cognitive decline depend on the range of tests included in the assessment. In a cross-sectional study13 from the global Dominantly Inherited Alzheimer Network, cognitively intact mutation carriers performed worse than the noncarriers on delayed memory and semantic categorization tests. A previous study reported cognitive findings from a small sample of asymptomatic carriers.14 The combination of tests most sensitive to differentiating carriers from noncarriers at baseline was memory for words and drawings and Mini-Mental State Examination orientation to time and total score. The tests most sensitive to longitudinal cognitive decline during 5 years of follow-up were memory for 3 phrases, oral arithmetic problem solving, and visuospatial memory, construction, and reasoning. Overall, these studies are consistent with cognitive findings from sporadic AD studies that indicate that impaired episodic verbal memory is one of the most robust findings, although lesser impairment in other cognitive domains often is found. Although the expression of AD is similar in ADAD and the more common late-onset form of disease, some differences exist. Patients with ADAD have faster cognitive decline and more prominent attention deficits and nonmemory symptoms.13 The study by Aguirre-Acevedo et al11 has several limitations. A small percentage of participants with a classification of dementia were included. Participants had low educational levels, and there was no information about the participants’ use of symptom-modifying medicines. The word list memory test used has ceiling effects for middle-aged adults with average or better educational levels. No longitudinal biomarker data were included in these analyses. An estimated 40 million people live with dementia worldwide. In the United States alone, as many as 5.1 million people 65 years and older have AD. It is critical to find an effective treatment of AD because of the devastating personal, family, and societal cost of this illness. This quest faces major challenges. The large overlap of abnormalities in the brains of older people with dementia and those who are cognitively intact precludes the usefulness of biomarkers at higher ages.15 In addition, memory decline, although mild, occurs for most people with advanced age. Therefore, examining large populations of elderly people is inefficient because many will not develop dementia. For those who do, it is difficult to detect the onset of initial symptoms. Achieving this goal will depend on more and better cost-effective means of early detection of this disease. Identifying the earliest and most reliable cognitive decline increases the sensitivity of early diagnosis and provides a valuable, cost-effective tool for tracking effectiveness of treatment. Back to top Article Information Corresponding Author: Diane B. Howieson, PhD, ABPP-CN, Department of Neurology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97201 (howiesod@ohsu.edu). Conflict of Interest Disclosures: None reported. Published Online: February 22, 2016. doi:10.1001/jamaneurol.2015.4993. References 1. Braak H, Del Tredici K. The preclinical phase of the pathological process underlying sporadic Alzheimer’s disease. Brain. 2015;138(pt 10):2814-2833.PubMedGoogle ScholarCrossref 2. Drachman DA. The amyloid hypothesis, time to move on: amyloid is the downstream result, not cause, of Alzheimer’s disease. Alzheimers Dement. 2014;10(3):372-380.PubMedGoogle ScholarCrossref 3. Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9(1):119-128.PubMedGoogle ScholarCrossref 4. Jack CR Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207-216.PubMedGoogle ScholarCrossref 5. Salloway S, Sperling R, Fox NC, et al; Bapineuzumab 301 and 302 Clinical Trial Investigators. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med. 2014;370(4):322-333.PubMedGoogle ScholarCrossref 6. Hall CB, Lipton RB, Sliwinski M, Stewart WF. A change point model for estimating the onset of cognitive decline in preclinical Alzheimer’s disease. Stat Med. 2000;19(11-12):1555-1566.PubMedGoogle ScholarCrossref 7. Li C, Dowling NM, Chappell R. Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer’s disease. Biometrics. 2015;71(3):625-635.PubMedGoogle ScholarCrossref 8. Gomar JJ, Conejero-Goldberg C, Davies P, Goldberg TE; Alzheimer’s Disease Neuroimaging Initiative. Extension and refinement of the predictive value of different classes of markers in ADNI: four-year follow-up data. Alzheimers Dement. 2014;10(6):704-712.PubMedGoogle ScholarCrossref 9. Jedynak BM, Liu B, Lang A, Gel Y, Prince JL; Alzheimer’s Disease Neuroimaging Initiative. A computational method for computing an Alzheimer’s disease progression score; experiments and validation with the ADNI data set. Neurobiol Aging. 2015;36(suppl 1):S178-S184.PubMedGoogle ScholarCrossref 10. Fagan AM, Xiong C, Jasielec MS, et al; Dominantly Inherited Alzheimer Network. Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer’s disease. Sci Transl Med. 2014;6(226):226ra30.PubMedGoogle ScholarCrossref 11. Aguirre-Acevedo DC, Lopera F, Henao E, et al. Cognitive decline in a Colombian kindred with autosomal dominant Alzheimer disease: a retrospective cohort study [published online February 22, 2016]. JAMA Neurol. doi:10.1001/jamaneurol.2015.4851.Google Scholar 12. Morris JC, Heyman A, Mohs RC, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), part I: clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39(9):1159-1165.PubMedGoogle ScholarCrossref 13. Storandt M, Balota DA, Aschenbrenner AJ, Morris JC. Clinical and psychological characteristics of the initial cohort of the Dominantly Inherited Alzheimer Network (DIAN). Neuropsychology. 2014;28(1):19-29.PubMedGoogle ScholarCrossref 14. Ardila A, Lopera F, Rosselli M, et al. Neuropsychological profile of a large kindred with familial Alzheimer’s disease caused by the E280A single presenilin-1 mutation. Arch Clin Neuropsychol. 2000;15(6):515-528.PubMedGoogle ScholarCrossref 15. Richard E, Schmand B, Eikelenboom P, Westendorp RG, Van Gool WA. The Alzheimer myth and biomarker research in dementia. J Alzheimers Dis. 2012;31(suppl 3):S203-S209.PubMedGoogle Scholar http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Neurology American Medical Association

Cognitive Decline in Presymptomatic Alzheimer Disease

JAMA Neurology , Volume 73 (4) – Apr 1, 2016

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American Medical Association
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Copyright © 2016 American Medical Association. All Rights Reserved.
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2168-6149
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10.1001/jamaneurol.2015.4993
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Abstract

Fundamental questions remain in the search for the cause and treatment of Alzheimer disease (AD). As yet, it is not fully known what mechanisms trigger the sequence of neurologic changes that lead to neuronal death and dementia.1,2 An often-cited model proposes that APP in the brain is abnormally cleaved into smaller particles that produce a toxic β-amyloid peptide, which clump into extracellular plaques. The toxic effects of Aβ induce hyperphosphorylation of the microtubule-associated protein tau, causing neurofibrillary tangles, cell death, and subsequent dementia.3 Measures of these biomarkers can be obtained from cerebrospinal fluid and with neuroimaging. This model has been modified to allow a more complex temporal ordering of some biomarkers.4 More important, this model suggests that the disease begins decades before the onset of clinical symptoms. The most common risk factor is age. To date, no effective treatment has been found.5 Treatment that will delay or slow progression of AD likely will depend on early detection. Episodic memory impairment is the earliest marker of dementia in most cases. Longitudinal studies6,7 of participants at risk for AD by virtue of old age have found that a slow decline in memory precedes a period of accelerated memory decline, leading to dementia. Some studies8,9 have found that cognitive measures are at least as sensitive to disease onset as neuropathologic biomarkers. A promising line of research is the study of individuals with one of the rare genetic mutations that causes autosomal dominant Alzheimer disease (ADAD). This form of the disease contrasts with most sporadic, late-life cases in which no single-gene mutation is responsible. Most cases of ADAD are the result of a single PSEN1 (GenBank NM_000021) mutation, and others are caused by mutations of PSEN2 (GenBank NG_007381) or APP. Carriers can be identified at an early age presumably before the disease begins. Longitudinal studies of ADAD offer a unique opportunity to measure progression in biomarker abnormalities from the earliest changes to the full clinical expression of the disease. The importance of longitudinal analysis was demonstrated by the finding that concentrations of biomarkers can decrease, rather than continue to increase or stay the same, as ADAD progresses.10 The study by Aguirre-Acevedo et al11 in this issue of JAMA Neurology explores when cognitive decline is measurable and what cognitive functions are the earliest to change. They present data of a kindred of PSEN1 E280A carriers with ADAD followed up longitudinally for 20 years who at study entry were 18 years and older. A total of 493 carriers met the study inclusion criteria, and 256 carriers were examined twice or more with the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) test battery12 at 2-year intervals with a median follow-up of 5 years. Most (386 [78.3%]) were cognitively normal, whereas 51 (10.3%) had symptoms of mild impairment (Clinical Dementia Rating, 0.5). Word list memory had the earliest change, occurring a mean of 12 years before the clinical diagnosis of mild cognitive impairment and 17 years before a dementia diagnosis. Cognitive declines occurring later were observed in verbal fluency, naming, and constructional praxis, whereas the CERAD total score had the greatest decrease after onset of cognitive decline. The study’s longitudinal data revealed that those with a higher educational level were approximately 3 years older at onset, but they had a steeper cognitive decline after onset, which is consistent with reports of individuals with sporadic, late-onset AD. Other factors associated with steeper cognitive decline were a history of diabetes mellitus, hypertension, or tobacco and alcohol use. The particular tests that studies report as most sensitive for detecting cognitive decline depend on the range of tests included in the assessment. In a cross-sectional study13 from the global Dominantly Inherited Alzheimer Network, cognitively intact mutation carriers performed worse than the noncarriers on delayed memory and semantic categorization tests. A previous study reported cognitive findings from a small sample of asymptomatic carriers.14 The combination of tests most sensitive to differentiating carriers from noncarriers at baseline was memory for words and drawings and Mini-Mental State Examination orientation to time and total score. The tests most sensitive to longitudinal cognitive decline during 5 years of follow-up were memory for 3 phrases, oral arithmetic problem solving, and visuospatial memory, construction, and reasoning. Overall, these studies are consistent with cognitive findings from sporadic AD studies that indicate that impaired episodic verbal memory is one of the most robust findings, although lesser impairment in other cognitive domains often is found. Although the expression of AD is similar in ADAD and the more common late-onset form of disease, some differences exist. Patients with ADAD have faster cognitive decline and more prominent attention deficits and nonmemory symptoms.13 The study by Aguirre-Acevedo et al11 has several limitations. A small percentage of participants with a classification of dementia were included. Participants had low educational levels, and there was no information about the participants’ use of symptom-modifying medicines. The word list memory test used has ceiling effects for middle-aged adults with average or better educational levels. No longitudinal biomarker data were included in these analyses. An estimated 40 million people live with dementia worldwide. In the United States alone, as many as 5.1 million people 65 years and older have AD. It is critical to find an effective treatment of AD because of the devastating personal, family, and societal cost of this illness. This quest faces major challenges. The large overlap of abnormalities in the brains of older people with dementia and those who are cognitively intact precludes the usefulness of biomarkers at higher ages.15 In addition, memory decline, although mild, occurs for most people with advanced age. Therefore, examining large populations of elderly people is inefficient because many will not develop dementia. For those who do, it is difficult to detect the onset of initial symptoms. Achieving this goal will depend on more and better cost-effective means of early detection of this disease. Identifying the earliest and most reliable cognitive decline increases the sensitivity of early diagnosis and provides a valuable, cost-effective tool for tracking effectiveness of treatment. Back to top Article Information Corresponding Author: Diane B. Howieson, PhD, ABPP-CN, Department of Neurology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97201 (howiesod@ohsu.edu). Conflict of Interest Disclosures: None reported. Published Online: February 22, 2016. doi:10.1001/jamaneurol.2015.4993. References 1. Braak H, Del Tredici K. The preclinical phase of the pathological process underlying sporadic Alzheimer’s disease. Brain. 2015;138(pt 10):2814-2833.PubMedGoogle ScholarCrossref 2. Drachman DA. The amyloid hypothesis, time to move on: amyloid is the downstream result, not cause, of Alzheimer’s disease. Alzheimers Dement. 2014;10(3):372-380.PubMedGoogle ScholarCrossref 3. Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9(1):119-128.PubMedGoogle ScholarCrossref 4. Jack CR Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207-216.PubMedGoogle ScholarCrossref 5. Salloway S, Sperling R, Fox NC, et al; Bapineuzumab 301 and 302 Clinical Trial Investigators. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med. 2014;370(4):322-333.PubMedGoogle ScholarCrossref 6. Hall CB, Lipton RB, Sliwinski M, Stewart WF. A change point model for estimating the onset of cognitive decline in preclinical Alzheimer’s disease. Stat Med. 2000;19(11-12):1555-1566.PubMedGoogle ScholarCrossref 7. Li C, Dowling NM, Chappell R. Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer’s disease. Biometrics. 2015;71(3):625-635.PubMedGoogle ScholarCrossref 8. Gomar JJ, Conejero-Goldberg C, Davies P, Goldberg TE; Alzheimer’s Disease Neuroimaging Initiative. Extension and refinement of the predictive value of different classes of markers in ADNI: four-year follow-up data. Alzheimers Dement. 2014;10(6):704-712.PubMedGoogle ScholarCrossref 9. Jedynak BM, Liu B, Lang A, Gel Y, Prince JL; Alzheimer’s Disease Neuroimaging Initiative. A computational method for computing an Alzheimer’s disease progression score; experiments and validation with the ADNI data set. Neurobiol Aging. 2015;36(suppl 1):S178-S184.PubMedGoogle ScholarCrossref 10. Fagan AM, Xiong C, Jasielec MS, et al; Dominantly Inherited Alzheimer Network. Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer’s disease. Sci Transl Med. 2014;6(226):226ra30.PubMedGoogle ScholarCrossref 11. Aguirre-Acevedo DC, Lopera F, Henao E, et al. Cognitive decline in a Colombian kindred with autosomal dominant Alzheimer disease: a retrospective cohort study [published online February 22, 2016]. JAMA Neurol. doi:10.1001/jamaneurol.2015.4851.Google Scholar 12. Morris JC, Heyman A, Mohs RC, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), part I: clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39(9):1159-1165.PubMedGoogle ScholarCrossref 13. Storandt M, Balota DA, Aschenbrenner AJ, Morris JC. Clinical and psychological characteristics of the initial cohort of the Dominantly Inherited Alzheimer Network (DIAN). Neuropsychology. 2014;28(1):19-29.PubMedGoogle ScholarCrossref 14. Ardila A, Lopera F, Rosselli M, et al. Neuropsychological profile of a large kindred with familial Alzheimer’s disease caused by the E280A single presenilin-1 mutation. Arch Clin Neuropsychol. 2000;15(6):515-528.PubMedGoogle ScholarCrossref 15. Richard E, Schmand B, Eikelenboom P, Westendorp RG, Van Gool WA. The Alzheimer myth and biomarker research in dementia. J Alzheimers Dis. 2012;31(suppl 3):S203-S209.PubMedGoogle Scholar

Journal

JAMA NeurologyAmerican Medical Association

Published: Apr 1, 2016

Keywords: alzheimer's disease,mutation,dementia,amyloid beta-protein precursor,disease progression,cognitive impairment,autosomal dominant inheritance,episodic memory,age-related cognitive decline,psen1 gene,psen2 gene

References