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[O2–08–04]: NOVEL GENETIC VARIANTS ASSOCIATED WITH FAMILIAL LATE‐ONSET ALZHEIMER DISEASE IN THE ALZHEIMER's DISEASE SEQUENCING PROJECT
Author(s) -
Zhang Xiaoling,
Ma Yiyi,
Lancour Dan,
Farrell John,
Chung Jaeyoon,
Mayeux Richard,
Haines Jonathan L.,
Schellenberg Gerard D.,
PericakVance Margaret A.,
Lunetta Kathryn L.,
Farrer Lindsay A.
Publication year - 2017
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2017.07.189
Subject(s) - bonferroni correction , exome sequencing , genetics , disease , allele , single nucleotide polymorphism , early onset alzheimer's disease , gene , biology , medicine , alzheimer's disease , genotype , mutation , statistics , mathematics
Background:The Alzheimer’s Disease Sequencing Project (ADSP) is an initiative to identify rare genetic variation influencing Late Onset Alzheimer’s Disease (LOAD) risk. As part of the ADSP, we performed whole-genome sequencing (WGS) in 67 Caribbean Hispanic (CH) and 44 non-Hispanic white (NHW) extended families multiply affected by LOAD, followed by extensive quality control, variant filtering, and gene-based association tests.Methods: WGS datawere generated for 351 subjects from 67 CH families and 197 subjects from 44 NHW families, including both AD and cognitively intact relatives. Alignment was performed using the Burrows-Wheeler algorithm, followed by genotype calling using a consensus calling pipeline that used both GATK genotype calls and ATLAS genotype calls. Variants were annotated for allele frequency and predicted functional impact, categorized into damaging (e.g., loss of function, high CADD scores, etc) and likely damaging (e.g., non-synonymous, moderate CADD, etc). We performed gene-based association testing, accounting for family structure using the FSKAT software. Association was performed using rare variants (MAF<0.01) and two models (damaging set only; damaging and likely damaging), with CH and NHW sets analyzed separately. Results:Examination of the 30 known LOAD genes (largely identified by GWAS-based meta-analyses) confirmed the role of rare functional variation in a number of genes, including CR1 (p 1⁄40.040 in NHW, p1⁄40.049 in CH; damaging variants only) and SLC24A4 (p1⁄40.002 in NHW, p1⁄40.040 in CH). Other candidate genes showed nominal association in one but not both datasets (AKAP9, FERMT2, GRN, HLA-DRB5, MEF2C in NHW dataset; BIN1, PTK2B in CH). Additional genes showed strong association in the CH dataset, with nominal association in the NHW. These include ATG2A (p1⁄40.0003 in CH, p1⁄40.02 in NHW), a gene involved in both autophagy and lipid droplet formation, and CD69 (p1⁄40.00054 in CH, p1⁄40.02 in NHW), a gene involved in cell proliferation.Conclusions:These results suggest rare, functional variation may influence LOAD risk in multiplex families, even among genes identified through common variation. We also show association with novel genes, ATG2A and CD69, with support from both CH and NHW families. Variants are currently being validated using other technologies, and follow-up and replication analyses are ongoing.