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dc.contributor.authorParanjpe, Manish D
dc.contributor.authorChaffin, Mark
dc.contributor.authorZahid, Sohail
dc.contributor.authorRitchie, Scott
dc.contributor.authorRotter, Jerome I
dc.contributor.authorRich, Stephen S
dc.contributor.authorGerszten, Robert
dc.contributor.authorGuo, Xiuqing
dc.contributor.authorHeckbert, Susan
dc.contributor.authorTracy, Russ
dc.contributor.authorDanesh, John
dc.contributor.authorLander, Eric S
dc.contributor.authorInouye, Michael
dc.contributor.authorKathiresan, Sekar
dc.contributor.authorButterworth, Adam S
dc.contributor.authorKhera, Amit V
dc.date.accessioned2022-12-13T16:12:06Z
dc.date.available2022-12-13T16:12:06Z
dc.date.issued2022-09
dc.identifier.urihttps://hdl.handle.net/1721.1/146853
dc.description.abstract<jats:p>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 &lt; 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.</jats:p>en_US
dc.language.isoen
dc.publisherPublic Library of Science (PLoS)en_US
dc.relation.isversionof10.1371/journal.pgen.1010294en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.titleNeurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s diseaseen_US
dc.typeArticleen_US
dc.identifier.citationParanjpe, Manish D, Chaffin, Mark, Zahid, Sohail, Ritchie, Scott, Rotter, Jerome I et al. 2022. "Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer’s disease." PLOS Genetics, 18 (9).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.relation.journalPLOS Geneticsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-12-13T15:59:08Z
dspace.orderedauthorsParanjpe, MD; Chaffin, M; Zahid, S; Ritchie, S; Rotter, JI; Rich, SS; Gerszten, R; Guo, X; Heckbert, S; Tracy, R; Danesh, J; Lander, ES; Inouye, M; Kathiresan, S; Butterworth, AS; Khera, AVen_US
dspace.date.submission2022-12-13T15:59:10Z
mit.journal.volume18en_US
mit.journal.issue9en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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