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Gene-based segregation method for identifying rare variants in family-based sequencing studies.

ABSTRACT: Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of Mendelian transmission. This test takes into account different degrees of relatedness in families, the number of functional rare variants in the gene, and their minor allele frequencies in the corresponding population. In addition, a weighted version of this test allows incorporating additional subject phenotypes to improve statistical power. We show via simulations that the GESE and weighted GESE tests maintain appropriate type I error rate, and have greater power than several commonly used region-based methods. We apply our method to whole-exome sequencing data from 49 extended pedigrees with severe, early-onset chronic obstructive pulmonary disease (COPD) in the Boston Early-Onset COPD study (BEOCOPD) and identify several promising candidate genes. Our proposed methods show great potential for identifying rare coding variants of large effect and high penetrance for family-based sequencing data. The proposed tests are implemented in an R package that is available on CRAN (https://cran.r-project.org/web/packages/GESE/).

SUBMITTER: Qiao D

PROVIDER: S-EPMC5397337 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Gene-based segregation method for identifying rare variants in family-based sequencing studies.

Qiao Dandi D Lange Christoph C Laird Nan M NM Won Sungho S Hersh Craig P CP Morrow Jarrett J Hobbs Brian D BD Lutz Sharon M SM Ruczinski Ingo I Beaty Terri H TH Silverman Edwin K EK Cho Michael H MH

Genetic epidemiology 20170213 4

Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of ...[more]

PMID: 28191685

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Project description:IntroductionMigraine has long been known as a common complex disease caused by genetic and environmental factors. The pathophysiology and the specific genetic susceptibility are poorly understood. Common variants only explain a small part of the heritability of migraine. It is thought that rare genetic variants with bigger effect size may be involved in the disease. Since migraine has a tendency to cluster in families, a family approach might be the way to find these variants. This is also indicated by identification of migraine-associated loci in classical linkage-analyses in migraine families. A single migraine study using a candidate-gene approach was performed in 2010 identifying a rare mutation in the TRESK potassium channel segregating in a large family with migraine with aura, but this finding has later become questioned. The technologies of next-generation sequencing (NGS) now provides an affordable tool to investigate the genetic variation in the entire exome or genome. The family-based study design using NGS is described in this paper. We also review family studies using NGS that have been successful in finding rare variants in other common complex diseases in order to argue the promising application of a family approach to migraine.MethodPubMed was searched to find studies that looked for rare genetic variants in common complex diseases through a family-based design using NGS, excluding studies looking for de-novo mutations, or using a candidate-gene approach and studies on cancer. All issues from Nature Genetics and PLOS genetics 2014, 2015 and 2016 (UTAI June) were screened for relevant papers. Reference lists from included and other relevant papers were also searched. For the description of the family-based study design using NGS an in-house protocol was used.ResultsThirty-two successful studies, which covered 16 different common complex diseases, were included in this paper. We also found a single migraine study. Twenty-three studies found one or a few family specific variants (less than five), while other studies found several possible variants. Not all of them were genome wide significant. Four studies performed follow-up analyses in unrelated cases and controls and calculated odds ratios that supported an association between detected variants and risk of disease. Studies of 11 diseases identified rare variants that segregated fully or to a large degree with the disease in the pedigrees.ConclusionIt is possible to find rare high risk variants for common complex diseases through a family-based approach. One study using a family approach and NGS to find rare variants in migraine has already been published but with strong limitations. More studies are under way.

Dataset Information

Gene-based segregation method for identifying rare variants in family-based sequencing studies.

Publications

Gene-based segregation method for identifying rare variants in family-based sequencing studies.

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