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Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease

For Alzheimer’s disease–a leading cause of dementia and global morbidity–improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer’s dis...

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Autores principales: Paranjpe, Manish D., Chaffin, Mark, Zahid, Sohail, Ritchie, Scott, Rotter, Jerome I., Rich, Stephen S., Gerszten, Robert, Guo, Xiuqing, Heckbert, Susan, Tracy, Russ, Danesh, John, Lander, Eric S., Inouye, Michael, Kathiresan, Sekar, Butterworth, Adam S., Khera, Amit V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436054/
https://www.ncbi.nlm.nih.gov/pubmed/36048760
http://dx.doi.org/10.1371/journal.pgen.1010294
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author Paranjpe, Manish D.
Chaffin, Mark
Zahid, Sohail
Ritchie, Scott
Rotter, Jerome I.
Rich, Stephen S.
Gerszten, Robert
Guo, Xiuqing
Heckbert, Susan
Tracy, Russ
Danesh, John
Lander, Eric S.
Inouye, Michael
Kathiresan, Sekar
Butterworth, Adam S.
Khera, Amit V.
author_facet Paranjpe, Manish D.
Chaffin, Mark
Zahid, Sohail
Ritchie, Scott
Rotter, Jerome I.
Rich, Stephen S.
Gerszten, Robert
Guo, Xiuqing
Heckbert, Susan
Tracy, Russ
Danesh, John
Lander, Eric S.
Inouye, Michael
Kathiresan, Sekar
Butterworth, Adam S.
Khera, Amit V.
author_sort Paranjpe, Manish D.
collection PubMed
description For Alzheimer’s disease–a leading cause of dementia and global morbidity–improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer’s disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer’s disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer’s disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer’s disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer’s disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.
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spelling pubmed-94360542022-09-02 Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease Paranjpe, Manish D. Chaffin, Mark Zahid, Sohail Ritchie, Scott Rotter, Jerome I. Rich, Stephen S. Gerszten, Robert Guo, Xiuqing Heckbert, Susan Tracy, Russ Danesh, John Lander, Eric S. Inouye, Michael Kathiresan, Sekar Butterworth, Adam S. Khera, Amit V. PLoS Genet Research Article For Alzheimer’s disease–a leading cause of dementia and global morbidity–improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer’s disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer’s disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer’s disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer’s disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer’s disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution. Public Library of Science 2022-09-01 /pmc/articles/PMC9436054/ /pubmed/36048760 http://dx.doi.org/10.1371/journal.pgen.1010294 Text en © 2022 Paranjpe et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Paranjpe, Manish D.
Chaffin, Mark
Zahid, Sohail
Ritchie, Scott
Rotter, Jerome I.
Rich, Stephen S.
Gerszten, Robert
Guo, Xiuqing
Heckbert, Susan
Tracy, Russ
Danesh, John
Lander, Eric S.
Inouye, Michael
Kathiresan, Sekar
Butterworth, Adam S.
Khera, Amit V.
Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title_full Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title_fullStr Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title_full_unstemmed Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title_short Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease
title_sort neurocognitive trajectory and proteomic signature of inherited risk for alzheimer’s disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436054/
https://www.ncbi.nlm.nih.gov/pubmed/36048760
http://dx.doi.org/10.1371/journal.pgen.1010294
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