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Ann Neurol. 2015 Sep;78(3):487-98. doi: 10.1002/ana.24466. Epub 2015 Jul 28.

Rare coding mutations identified by sequencing of Alzheimer disease genome-wide association studies loci.

Author information

1
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY.
2
Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY.
3
Departments of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY.
4
Systems Biology, Columbia University, New York, NY.
5
Tanz Centre for Research in Neurodegenerative Diseases and Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
6
Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.
7
Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY.
8
School of Medicine, Mother and Teacher Pontifical Catholic University, Santiago, Dominican Republic.
9
Department of Medicine, Geriatrics Program, School of Medicine, University of Puerto Rico, San Juan, Puerto Rico.
10
Cambridge Institute for Medical Research, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
11
Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY.

Abstract

OBJECTIVE:

To detect rare coding variants underlying loci detected by genome-wide association studies (GWAS) of late onset Alzheimer disease (LOAD).

METHODS:

We conducted targeted sequencing of ABCA7, BIN1, CD2AP, CLU, CR1, EPHA1, MS4A4A/MS4A6A, and PICALM in 3 independent LOAD cohorts: 176 patients from 124 Caribbean Hispanics families, 120 patients and 33 unaffected individuals from the 129 National Institute on Aging LOAD Family Study; and 263 unrelated Canadian individuals of European ancestry (210 sporadic patients and 53 controls). Rare coding variants found in at least 2 data sets were genotyped in independent groups of ancestry-matched controls. Additionally, the Exome Aggregation Consortium was used as a reference data set for population-based allele frequencies.

RESULTS:

Overall we detected a statistically significant 3.1-fold enrichment of the nonsynonymous mutations in the Caucasian LOAD cases compared with controls (p = 0.002) and no difference in synonymous variants. A stop-gain mutation in ABCA7 (E1679X) and missense mutation in CD2AP (K633R) were highly significant in Caucasian LOAD cases, and mutations in EPHA1 (P460L) and BIN1 (K358R) were significant in Caribbean Hispanic families with LOAD. The EPHA1 variant segregated completely in an extended Caribbean Hispanic family and was also nominally significant in the Caucasians. Additionally, BIN1 (K358R) segregated in 2 of the 6 Caribbean Hispanic families where the mutations were discovered.

INTERPRETATION:

Targeted sequencing of confirmed GWAS loci revealed an excess burden of deleterious coding mutations in LOAD, with the greatest burden observed in ABCA7 and BIN1. Identifying coding variants in LOAD will facilitate the creation of tractable models for investigation of disease-related mechanisms and potential therapies.

PMID:
26101835
PMCID:
PMC4546546
DOI:
10.1002/ana.24466
[Indexed for MEDLINE]
Free PMC Article

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