Manifestations of Alzheimer’s disease genetic risk in the blood are evident in a multiomic analysis in healthy adults aged 18 to 90
Authors: Heath Laura , Earls John C. , Magis Andrew T. , Kornilov Sergey A. , Lovejoy Jennifer C. , Funk Cory C. , Rappaport Noa , Logsdon Benjamin A. , Mangravite Lara M. , Kunkle Brian W. , Martin Eden R. , Naj Adam C. , Ertekin-Taner Nilüfer , Golde Todd E. , Hood Leroy , Price Nathan D. ,   Alzheimer’s Disease Genetics Consortium, Abner Erin , Adams Perrie M. , Albert Marilyn S. , Albin Roger L. , Allen Mariet , Amlie-Wolf Alexandre , Apostolova Liana G. , Arnold Steven E. , Asthana Sanjay , Atwood Craig S. , Baldwin Clinton T. , Barber Robert C. , Barnes Lisa L. , Barral Sandra , Beach Thomas G. , Becker James T. , Beecham Gary W. , Beekly Duane , Bennett David , Bigio Eileen H. , Bird Thomas D. , Blacker Deborah , Boeve Bradley F. , Bowen James D. , Boxer Adam , Burke James R. , Burns Jeffrey M. , Bush Will , Butkiewicz Mariusz , Buxbaum Joseph D. , Cairns Nigel J. , Cantwell Laura B. , Cao Chuanhai , Carlson Chris S. , Carlsson Cynthia M. , Carney Regina M. , Chui Helena C. , Crane Paul K. , Cribbs David H. , Crocco Elizabeth A. , Cuccaro Michael L. , De Jager Philip L. , DeCarli Charles , Dick Malcolm , Dickson Dennis W. , Dombroski Beth A. , Doody Rachelle S. , Duara Ranjan , Ertekin-Taner Nilufer , Evans Denis A. , Faber Kelley M. , Fairchild Thomas J. , Fallon Kenneth B. , Fardo David W. , Farlow Martin R. , Farrer Lindsay A. , Ferris Steven , Foroud Tatiana M. , Frosch Matthew P. , Galasko Douglas R. , Gearing Marla , Geschwind Daniel H. , Ghetti Bernardino , Gilbert John R. , Goate Alison M. , Green Robert C. , Growdon John H. , Haines Jonathan , Hakonarson Hakon , Hamilton Ronald L. , Hamilton-Nelson Kara L. , Harrell Lindy E. , Honig Lawrence S. , Huebinger Ryan M. , Huentelman Matthew J. , Hulette Christine M. , Hyman Bradley T. , Jarvik Gail P. , Jin Lee-Way , Jun Gyungah R. , Kamboh M. Ilyas , Karydas Anna , Katz Mindy J. , Kaye Jeffrey A. , Keene C. Dirk , Kim Ronald , Kowall Neil W. , Kramer Joel H. , Kukull Walter A. , Kunkle Brian W. , Kuzma Amanda B. , LaFerla Frank M. , Lah James J. , Larson Eric B. , Leverenz James B. , Levey Allan I. , Lieberman Andrew P. , Lipton Richard B. , Lunetta Kathryn L. , Lyketsos Constantine G. , Malamon John , Marson Daniel C. , Martin Eden R. , Martiniuk Frank , Mash Deborah C. , Masliah Eliezer , Mayeux Richard , McCormick Wayne C. , McCurry Susan M. , McDavid Andrew N. , McKee Ann C. , Mesulam Marsel , Miller Bruce L. , Miller Carol A. , Miller Joshua W. , Montine Thomas J. , Morris John C. , Mukherjee Shubhabrata , Myers Amanda J. , Naj Adam C. , O’Bryant Sid , Olichney John M. , Parisi Joseph E. , Paulson Henry L. , Pericak-Vance Margaret A. , Perry William R. , Peskind Elaine , Petersen Ronald C. , Pierce Aimee , Poon Wayne W. , Potter Huntington , Qu Liming , Quinn Joseph F. , Raj Ashok , Raskind Murray , Reiman Eric M. , Reisberg Barry , Reisch Joan S. , Reitz Christiane , Ringman John M. , Roberson Erik D. , Rogaeva Ekaterina , Rosen Howard J. , Rosenberg Roger N. , Royall Donald R. , Sager Mark A. , Sano Mary , Saykin Andrew J. , Schellenberg Gerard D. , Schneider Julie A. , Schneider Lon S. , Seeley William W. , Slifer Susan , Smith Amanda G. , Song Yeunjoo , Sonnen Joshua A. , Spina Salvatore , George-Hyslop Peter St , Stern Robert A. , Swerdlow Russell H. , Tang Mitchell , Tanzi Rudolph E. , Trojanowski John Q. , Troncoso Juan C. , Tsuang Debby W. , Valladares Otto , Van Deerlin Vivianna M. , Van Eldik Linda J. , Vance Jeffery , Vardarajan Badri N. , Vinters Harry V. , Vonsattel Jean Paul , Wang Li-San , Weintraub Sandra , Welsh-Bohmer Kathleen A. , Whitehead Patrice , Wilhelmsen Kirk C. , Williamson Jennifer , Wingo Thomas S. , Woltjer Randall L. , Wright Clinton B. , Wu Chuang-Kuo , Younkin Steven G. , Yu Chang-En , Yu Lei , Zhao Yi 
Published: April 2022

AbstractGenetics 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 phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants and an AD-specific polygenic risk score (PGRS), adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed. We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. We did not observe associations between the PGRS and any analyte. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case–control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.