Inferring disease risk genes from sequencing data in multiplex pedigrees through sharing of rare variants.

TitleInferring disease risk genes from sequencing data in multiplex pedigrees through sharing of rare variants.
Publication TypeJournal Article
Year of Publication2018
AuthorsBureau, A, Begum, F, Taub, MA, Hetmanski, JB, Parker, MM, Albacha-Hejazi, H, Scott, AF, Murray, JC, Marazita, ML, Bailey-Wilson, JE, Beaty, TH, Ruczinski, I
JournalGenet Epidemiol
Date Published2018 Sep 24
ISSN1098-2272
Abstract

We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g., within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affected is required. Here, we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, a partial sharing test based on RV sharing probabilities for subsets of affected relatives and a haplotype-based RV definition. RVS also has the desirable feature of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared with alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared with the pedigree Variant Annotation, Analysis, and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.

DOI10.1002/gepi.22155
Alternate JournalGenet. Epidemiol.
PubMed ID30246882
Grant ListU01 DE020073 / / National Institutes of Health /
R37 DE008559 / DE / NIDCR NIH HHS / United States
U01-DE-018993 / / National Institutes of Health /
R37-DE-08559 / / National Institutes of Health /
U01 DE018993 / DE / NIDCR NIH HHS / United States
U01-DE024425 / / National Institutes of Health /
R03 DE021437 / DE / NIDCR NIH HHS / United States
R01 DE014581 / DE / NIDCR NIH HHS / United States
R01-DE-009886 / / National Institutes of Health /
R01-DE-016148 / / National Institutes of Health /
R01-DE-014581 / / National Institutes of Health /
X01HG006177 / / Center for Inherited Disease Research /
R03-DE-02579 / / National Institutes of Health /
U01 DE020073 / DE / NIDCR NIH HHS / United States
HHSN268200782096C / / NIH to Johns Hopkins University /
P50-DE-016215 / / National Institutes of Health /
P50 DE016215 / DE / NIDCR NIH HHS / United States
Collaborative Research Team 8 / / Canadian Statistical Sciences Institute /