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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546546PMC
http://dx.doi.org/10.1002/ana.24466DOI Listing

Publication Analysis

Top Keywords

rare coding
12
coding variants
12
caribbean hispanic
12
coding mutations
8
alzheimer disease
8
genome-wide association
8
association studies
8
targeted sequencing
8
abca7 bin1
8
caucasian load
8

Similar Publications

Background: Our previous study has identified an association of a single nucleotide polymorphism (SNP) in the miR-423 gene with recurrent spontaneous abortion (RSA). The presence of additional RSA-linked SNPs in the miR-423 gene remains unclear.

Methods: We evaluated polymorphisms in the coding region of miR-423 in Han Chinese women with unexplained RSA (URSA).

View Article and Find Full Text PDF

Elucidating the genetic contributions to Parkinson's disease (PD) etiology across diverse ancestries is a critical priority for the development of targeted therapies in a global context. We conducted the largest sequencing characterization of potentially disease-causing, protein-altering and splicing mutations in 710 cases and 11,827 controls from genetically predicted African or African admixed ancestries. We explored copy number variants (CNVs) and runs of homozygosity (ROHs) in prioritized early onset and familial cases.

View Article and Find Full Text PDF

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder, but its genetic architecture remains incompletely characterized. Rare coding variants, which can profoundly impact gene function, represent an underexplored dimension of ADHD risk. In this study, we analyzed large-scale DNA sequencing datasets from ancestrally diverse cohorts and observed significant enrichment of rare protein-truncating and deleterious missense variants in highly evolutionarily constrained genes.

View Article and Find Full Text PDF

Sudden cardiac death (SCD) is a major health concern, which can be the sign of a latent mitochondrial disease. However, mitochondrial DNA (mtDNA) contribution is largely unexplored in SCD at population level. Recently, mtDNA variants have been associated with congenital cardiopathy and higher risk of ischemic heart disease, suggesting them as potential risk factors also in SCD.

View Article and Find Full Text PDF

Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records.

Int J Med Inform

January 2025

Rheumatology and Allergy Clinical Epidemiology Research Center and Division of Rheumatology, Allergy, and Immunology, and Mongan Institute, Department of Medicine, Massachusetts General Hospital Boston MA USA. Electronic address:

Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!