{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Heath L"],"funding":["NIA NIH HHS","NCRR NIH HHS","Howard Hughes Medical Institute","NIMH NIH HHS","Medical Research Council","NIMHD NIH HHS","NHGRI NIH HHS","NCI NIH HHS","NINDS NIH HHS","Wellcome Trust","National Institute on Aging"],"pagination":["6117"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9005657"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["12(1)"],"pubmed_abstract":["Genetics play an important role in late-onset Alzheimer's Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a "],"journal":["Scientific reports"],"pubmed_title":["Manifestations of Alzheimer's disease genetic risk in the blood are evident in a multiomic analysis in healthy adults aged 18 to 90."],"pmcid":["PMC9005657"],"funding_grant_id":["UL1 RR029893","R01 AG013616","U24 AG026395","P50 AG005146","R01 AG009956","R01 AG019085","P50 AG005142","U01 AG046139","R37 AG015473","P30 AG066518","P30 AG066444","P30 AG019610","R01 AG022018","R01 AG048927","R01 AG027944","R01 AG062634","KL2 RR024151","R01 AG022374","R01 AG030146","P50 AG008702","P30 AG010124","P30 AG012300","P30 AG062422","P30 AG010161","R01 AG017173","U01 HG006375","R01 AG037212","R01 AG042437","RC2 AG036502","U01 AG032984","U24 AG041689","U19 AG023122","R01 AG028786","P01 AG003991","R01 AG015819","P30 AG028383","P30 AG013846","U01 AG010483","P30 AG008017","P30 AG010133","P50 AG033514","P01 AG019724","P50 AG005681","R01 AG031581","R01 AG012101","P30 AG072980","R01 CA129769","U01 AG006781","P50 AG008671","R01 AG032990","U24 AG021886","P01 AG002219","P30 AG072975","P30 AG072976","P30 AG072977","R01 AG026916","R01 AG041797","P30 AG072972","P50 AG023501","P30 AG008051","R01 MH080295","P30 AG010129","RC2 AG036650","P30 AG072979","P50 AG016582","P30 AG013854","P50 AG005138","R01 AG009029","U01 HG004610","P50 AG005134","P30 AG028377","P50 AG005136","U01 AG016976","R01 NS059873","P50 AG005131","RF1 AG051504","P50 AG005133","R01 AG035137","R01 AG020688","RC2 AG036528","P50 AG016574","R01 AG033193","R01-AG062634-01","P20 MD000546","R01 AG061796","U01 AG024904","P01 AG026276","U01 HG008657","R01 AG025259","R01 AG017917","P50 AG016573","P50 AG016570"],"pubmed_authors":["Peskind E","O'Bryant S","Lunetta KL","Cuccaro ML","Carney RM","Rosen HJ","McKee AC","Pierce A","Bowen JD","DeCarli C","Jin LW","Larson EB","Magis AT","Rogaeva E","Heath L","Rosenberg RN","Stern RA","Duara R","Martiniuk F","Kramer JH","Younkin SG","Sano M","Schneider JA","Wu CK","Boxer A","Kornilov SA","Lah JJ","Galasko DR","Seeley WW","Potter H","Yu L","Van Deerlin VM","Cao C","Smith AG","Perry WR","Zhao Y","Katz MJ","Reisch JS","Tsuang DW","Lovejoy JC","Tanzi RE","Jarvik GP","Boeve BF","Asthana S","Growdon JH","Weintraub S","Albert MS","Cantwell LB","Barber RC","Burns JM","Kunkle BW","Malamon J","Mesulam M","Beach TG","Woltjer RL","Keene CD","Huentelman MJ","Apostolova LG","Kowall NW","Trojanowski JQ","Reitz C","Swerdlow RH","Kukull WA","Evans DA","Crocco EA","Vance J","Rappaport N","Reisberg B","Green RC","Ringman JM","LaFerla FM","Reiman EM","Crane PK","Wang LS","Becker JT","Carlsson CM","Petersen RC","Abner E","Beecham GW","Hakonarson H","Lyketsos CG","Cribbs DH","Fardo DW","Barral S","Van Eldik LJ","Fallon KB","Miller BL","Bigio EH","Kaye JA","Vonsattel JP","Paulson HL","Funk CC","Buxbaum JD","McCurry SM","Miller CA","Honig LS","Baldwin CT","Goate AM","Yu CE","De Jager PL","Saykin AJ","Faber KM","Bennett D","Whitehead P","Harrell LE","Quinn JF","Lipton RB","Welsh-Bohmer KA","Chui HC","Hyman BT","Gilbert JR","Huebinger RM","Lieberman AP","Martin ER","Sager MA","Schellenberg GD","Spina S","Pericak-Vance MA","Valladares O","Blacker D","Karydas A","Masliah E","Vardarajan BN","Royall DR","Jun GR","Ghetti B","Hulette CM","Burke JR","Wilhelmsen KC","Adams PM","Atwood CS","Hamilton-Nelson KL","Mukherjee S","Cairns NJ","Hood L","Dick M","Naj AC","Roberson ED","Tang M","Qu L","Earls JC","Foroud TM","Sonnen JA","Beekly D","Kuzma AB","Marson DC","Kim R","Kamboh MI","Arnold SE","Allen M","Hamilton RL","Bush W","Albin RL","Dickson DW","Fairchild TJ","Farlow MR","Vinters HV","Olichney JM","Myers AJ","George-Hyslop PS","Butkiewicz M","Dombroski BA","Farrer LA","McCormick WC","Wright CB","Poon WW","Haines J","Logsdon BA","Mash DC","Ertekin-Taner N","Price ND","Barnes LL","McDavid AN","Miller JW","Golde TE","Doody RS","Gearing M","Parisi JE","Troncoso JC","Mangravite LM","Ferris S","Leverenz JB","Alzheimer’s Disease Genetics Consortium","Frosch MP","Geschwind DH","Williamson J","Amlie-Wolf A","Song Y","Mayeux R","Schneider LS","Levey AI","Slifer S","Bird TD","Raj A","Morris JC","Carlson CS","Wingo TS","Montine TJ","Raskind M"],"additional_accession":[]},"is_claimable":false,"name":"Manifestations of Alzheimer's disease genetic risk in the blood are evident in a multiomic analysis in healthy adults aged 18 to 90.","description":"Genetics play an important role in late-onset Alzheimer's Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Apr","modification":"2026-05-30T15:07:31.816Z","creation":"2024-11-14T20:22:55.811Z"},"accession":"S-EPMC9005657","cross_references":{"pubmed":["35413975"],"doi":["10.1038/s41598-022-09825-2"]}}