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Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease
Alzheimer’s disease (AD) progresses through a lengthy asymptomatic period during which pathological changes accumulate prior to development of clinical symptoms. As disease-modifying treatments are developed, tools to stratify risk of clinical disease will be required to guide their use. In this stu...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002814/ https://www.ncbi.nlm.nih.gov/pubmed/36909654 http://dx.doi.org/10.21203/rs.3.rs-2577025/v1 |
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author | Tandon, Raghav Zhao, Liping Watson, Caroline M. Elmor, Morgan Heilman, Craig Sanders, Katherine Hales, Chadwick M. Yang, Huiying Loring, David W. Goldstein, Felicia C. Hanfelt, John J. Duong, Duc M. Johnson, Erik C.B. Wingo, Aliza P. Wingo, Thomas S. Roberts, Blaine R. Seyfried, Nicholas T. Levey, Allan I. Mitchell, Cassie S. Lah, James J. |
author_facet | Tandon, Raghav Zhao, Liping Watson, Caroline M. Elmor, Morgan Heilman, Craig Sanders, Katherine Hales, Chadwick M. Yang, Huiying Loring, David W. Goldstein, Felicia C. Hanfelt, John J. Duong, Duc M. Johnson, Erik C.B. Wingo, Aliza P. Wingo, Thomas S. Roberts, Blaine R. Seyfried, Nicholas T. Levey, Allan I. Mitchell, Cassie S. Lah, James J. |
author_sort | Tandon, Raghav |
collection | PubMed |
description | Alzheimer’s disease (AD) progresses through a lengthy asymptomatic period during which pathological changes accumulate prior to development of clinical symptoms. As disease-modifying treatments are developed, tools to stratify risk of clinical disease will be required to guide their use. In this study, we examine the relationship of AD biomarkers in healthy middle-aged individuals to health history, family history, and neuropsychological measures and identify cerebrospinal fluid (CSF) biomarkers to stratify risk of progression from asymptomatic to symptomatic AD. CSF from cognitively normal (CN) individuals (N=1149) in the Emory Healthy Brain Study were assayed for Aβ(42), total Tau (tTau), and phospho181-Tau (pTau), and a subset of 134 cognitively normal, but biomarker-positive, individuals were identified with asymptomatic AD (AsymAD) based on a locally-determined cutoff value for ratio of tTau to Aβ(42). These AsymAD cases were matched for demographic features with 134 biomarker-negative controls (CN/BM-) and compared for differences in medical comorbidities and family history. Dyslipidemia emerged as a distinguishing feature between AsymAD and CN/BM-groups with significant association with personal and family history of dyslipidemia. A weaker relationship was seen with diabetes, but there was no association with hypertension. Examination of the full cohort by median regression revealed a significant relationship of CSF Aβ(42) (but not tTau or pTau) with dyslipidemia and diabetes. On neuropsychological tests, CSF Aβ(42) was not correlated with performance on any measures, but tTau and pTau were strongly correlated with visuospatial perception and visual episodic memory. In addition to traditional CSF AD biomarkers, a panel of AD biomarker peptides derived from integrating brain and CSF proteomes were evaluated using machine learning strategies to identify a set of 8 peptides that accurately classified CN/BM- and symptomatic AD CSF samples with AUC of 0.982. Using these 8 peptides in a low dimensional t-distributed Stochastic Neighbor Embedding analysis and k-Nearest Neighbor (k=5) algorithm, AsymAD cases were stratified into “Control-like” and “AD-like” subgroups based on their proximity to CN/BM- or AD CSF profiles. Independent analysis of these cases using a Joint Mutual Information algorithm selected a set of 5 peptides with 81% accuracy in stratifying cases into AD-like and Control-like subgroups. Performance of both sets of peptides was evaluated and validated in an independent data set from the Alzheimer’s Disease Neuroimaging Initiative. Based on our findings, we conclude that there is an important role of lipid metabolism in asymptomatic stages of AD. Visuospatial perception and visual episodic memory may be more sensitive than language-based abilities to earliest stages of cognitive decline in AD. Finally, candidate CSF peptides show promise as next generation biomarkers for predicting progression from asymptomatic to symptomatic stages of AD. |
format | Online Article Text |
id | pubmed-10002814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-100028142023-03-11 Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease Tandon, Raghav Zhao, Liping Watson, Caroline M. Elmor, Morgan Heilman, Craig Sanders, Katherine Hales, Chadwick M. Yang, Huiying Loring, David W. Goldstein, Felicia C. Hanfelt, John J. Duong, Duc M. Johnson, Erik C.B. Wingo, Aliza P. Wingo, Thomas S. Roberts, Blaine R. Seyfried, Nicholas T. Levey, Allan I. Mitchell, Cassie S. Lah, James J. Res Sq Article Alzheimer’s disease (AD) progresses through a lengthy asymptomatic period during which pathological changes accumulate prior to development of clinical symptoms. As disease-modifying treatments are developed, tools to stratify risk of clinical disease will be required to guide their use. In this study, we examine the relationship of AD biomarkers in healthy middle-aged individuals to health history, family history, and neuropsychological measures and identify cerebrospinal fluid (CSF) biomarkers to stratify risk of progression from asymptomatic to symptomatic AD. CSF from cognitively normal (CN) individuals (N=1149) in the Emory Healthy Brain Study were assayed for Aβ(42), total Tau (tTau), and phospho181-Tau (pTau), and a subset of 134 cognitively normal, but biomarker-positive, individuals were identified with asymptomatic AD (AsymAD) based on a locally-determined cutoff value for ratio of tTau to Aβ(42). These AsymAD cases were matched for demographic features with 134 biomarker-negative controls (CN/BM-) and compared for differences in medical comorbidities and family history. Dyslipidemia emerged as a distinguishing feature between AsymAD and CN/BM-groups with significant association with personal and family history of dyslipidemia. A weaker relationship was seen with diabetes, but there was no association with hypertension. Examination of the full cohort by median regression revealed a significant relationship of CSF Aβ(42) (but not tTau or pTau) with dyslipidemia and diabetes. On neuropsychological tests, CSF Aβ(42) was not correlated with performance on any measures, but tTau and pTau were strongly correlated with visuospatial perception and visual episodic memory. In addition to traditional CSF AD biomarkers, a panel of AD biomarker peptides derived from integrating brain and CSF proteomes were evaluated using machine learning strategies to identify a set of 8 peptides that accurately classified CN/BM- and symptomatic AD CSF samples with AUC of 0.982. Using these 8 peptides in a low dimensional t-distributed Stochastic Neighbor Embedding analysis and k-Nearest Neighbor (k=5) algorithm, AsymAD cases were stratified into “Control-like” and “AD-like” subgroups based on their proximity to CN/BM- or AD CSF profiles. Independent analysis of these cases using a Joint Mutual Information algorithm selected a set of 5 peptides with 81% accuracy in stratifying cases into AD-like and Control-like subgroups. Performance of both sets of peptides was evaluated and validated in an independent data set from the Alzheimer’s Disease Neuroimaging Initiative. Based on our findings, we conclude that there is an important role of lipid metabolism in asymptomatic stages of AD. Visuospatial perception and visual episodic memory may be more sensitive than language-based abilities to earliest stages of cognitive decline in AD. Finally, candidate CSF peptides show promise as next generation biomarkers for predicting progression from asymptomatic to symptomatic stages of AD. American Journal Experts 2023-02-28 /pmc/articles/PMC10002814/ /pubmed/36909654 http://dx.doi.org/10.21203/rs.3.rs-2577025/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Tandon, Raghav Zhao, Liping Watson, Caroline M. Elmor, Morgan Heilman, Craig Sanders, Katherine Hales, Chadwick M. Yang, Huiying Loring, David W. Goldstein, Felicia C. Hanfelt, John J. Duong, Duc M. Johnson, Erik C.B. Wingo, Aliza P. Wingo, Thomas S. Roberts, Blaine R. Seyfried, Nicholas T. Levey, Allan I. Mitchell, Cassie S. Lah, James J. Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title | Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title_full | Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title_fullStr | Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title_full_unstemmed | Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title_short | Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer’s Disease |
title_sort | predictors of cognitive decline in healthy middle-aged individuals with asymptomatic alzheimer’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002814/ https://www.ncbi.nlm.nih.gov/pubmed/36909654 http://dx.doi.org/10.21203/rs.3.rs-2577025/v1 |
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