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Neurobiol Aging. 2016 May;41:200.e13-200.e20. doi: 10.1016/j.neurobiolaging.2016.02.024. Epub 2016 Mar 3.

Assessment of the genetic variance of late-onset Alzheimer's disease.

Collaborators (186)

Adams PM, Albert MS, Albin RL, Apostolova LG, Arnold SE, Asthana S, Atwood CS, Baldwin CT, Barber RC, Barmada MM, Barnes LL, Barral S, Beach TG, Becker JT, Beecham GW, Beekly D, Bennett DA, Bigio EH, Bird TD, Blacker D, Boeve BF, Bowen JD, Boxer A, Burke JR, Burns JM, Buxbaum JD, Cairns NJ, Cantwell LB, Cao C, Carlson CS, Carlsson CM, Carney RM, Carrasquillo MM, Carroll SL, Chui HC, Clark DG, Corneveaux J, Crane PK, Cribbs DH, Crocco EA, Cruchaga C, De Jager PL, DeCarli C, Demirci FY, Dick M, Dickson DW, Doody RS, Duara R, Ertekin-Taner N, Evans DA, Faber KM, Fairchild TJ, Fallon KB, Fardo DW, Farlow MR, Ferris S, Foroud TM, Frosch MP, Galasko DR, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Goate AM, Graff-Radford NR, Green RC, Growdon JH, Hakonarson H, Hamilton RL, Hamilton-Nelson KL, Hardy J, Harrell LE, Honig LS, Huebinger RM, Huentelman MJ, Hulette CM, Hyman BT, Jarvik GP, Jicha GA, Jin LW, Jun G, Kamboh MI, Karydas A, Katz MJ, Kauwe JSK, Kaye JA, Kim R, Kowall NW, Kramer JH, Kukull WA, Kunkle BW, LaFerla FM, Lah JJ, Larson EB, Leverenz JB, Levey AI, Li G, Lieberman AP, Lin CF, Lipton RB, Lopez OL, Lunetta KL, Lyketsos CG, Mack WJ, Marson DC, Martin ER, Martiniuk F, Mash DC, Masliah E, McCormick WC, McCurry SM, McDavid AN, McKee AC, Mesulam M, Miller BL, Miller CA, Miller JW, Montine TJ, Morris JC, Mukherjee S, Murrell JR, Myers AJ, Naj AC, O'Bryant S, Olichney JM, Pankratz VS, Parisi JE, Partch A, Paulson HL, Perry W, Peskind E, Petersen RC, Pierce A, Poon WW, Potter H, Quinn JF, Raj A, Raskind M, Reiman EM, Reisberg B, Reisch JS, Reitz C, Ringman JM, Roberson ED, Rogaeva E, Rosen HJ, Rosenberg RN, Royall DR, Sager MA, Sano M, Saykin AJ, Schneider JA, Schneider LS, Seeley WW, Smith AG, Sonnen JA, Spina S, St George-Hyslop P, Stern RA, Swerdlow RH, Tanzi RE, Thornton-Wells TA, Trojanowski JQ, Troncoso JC, Tsuang DW, Valladares O, Van Deerlin VM, Van Eldik LJ, Vardarajan BN, Vinters HV, Vonsattel JP, Wang LS, Weintraub S, Welsh-Bohmer KA, Wendland JR, Wilhelmsen KC, Williamson J, Wingo TS, Winslow AR, Wishnek S, Woltjer RL, Wright CB, Wu CK, Younkin SG, Yu CE, Yu L.

Author information

1
Department of Biology, Brigham Young University, Provo, UT, USA.
2
Department of Medicine, University of Washington, Seattle, WA, USA.
3
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.
4
Department of Neurology and the Taub Institute on Alzheimer's Disease and the Aging Brain, Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA.
5
Department of Biostatistics, Boston University, Boston, MA, USA; Department of Epidemiology, Boston University, Boston, MA, USA; Department of Medicine (Genetics Program), Boston University, Boston, MA, USA; Department of Neurology, Boston University, Boston, MA, USA; Department of Ophthalmology, Boston University, Boston, MA, USA.
6
Dr. John T. Macdonald Foundation Department of Human Genetics, and The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.
7
Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
8
Department of Biology, Brigham Young University, Provo, UT, USA. Electronic address: kauwe@byu.edu.

Abstract

Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

KEYWORDS:

Alzheimer's disease; Genetic variance; Genetics

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