Detection of rare disease variants in extended pedigrees using RVS

RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations

A large proportion of genetic variations involved in complex diseases are rare and located within noncoding regions, making the interpretation of underlying biological mechanisms a daunting task. Although technical and methodological progress has been made to annotate the genome, current disease-rare-variant association tests incorporating such annotations suffer from two major limitations. First, they are generally restricted to case-control designs of unrelated individuals, which often require tens or hundreds of thousands of individuals to achieve sufficient power. Second, they were not evaluated with region-based annotations needed to interpret the causal regulatory mechanisms. In this work, we propose RetroFun-RVS, a new retrospective family-based score test, incorporating functional annotations. A critical feature of the proposed method is to aggregate genotypes to compare against rare variant-sharing expectations among affected family members. Through extensive simulations, we have demonstrated that RetroFun-RVS integrating networks based on 3D genome contacts as functional annotations reach greater power over the region-wide test, other strategies to include subregions and competing methods. Also, the proposed framework shows robustness to non-informative annotations, maintaining its power when causal variants are spread across regions. Asymptotic p-values are susceptible to Type I error inflation when the number of families with rare variants is small, and a bootstrap procedure is recommended in these instances. Application of RetroFun-RVS is illustrated on whole genome sequence in the Eastern Quebec Schizophrenia and Bipolar Disorder Kindred Study with networks constructed from 3D contacts and epigenetic data on neurons. In summary, the integration of functional annotations corresponding to regions or networks with transcriptional impacts in rare variant tests appears promising to highlight regulatory mechanisms involved in complex diseases.

Elevated common variant genetic risk for tourette syndrome in a densely-affected pedigree

Tourette syndrome (TS) is a highly heritable neuropsychiatric disorder with complex patterns of genetic inheritance. Recent genetic findings in TS have highlighted both numerous common variants with small effects and a few rare variants with moderate or large effects. Here we searched for genetic causes of TS in a large, densely-affected British pedigree using a systematic genomic approach. This pedigree spans six generations and includes 122 members, 85 of whom were individually interviewed, and 53 of whom were diagnosed as "cases" (consisting of 28 with definite or probable TS, 20 with chronic multiple tics [CMT], and five with obsessive-compulsive behaviors [OCB]). A total of 66 DNA samples were available (25 TS, 15 CMT, 4 OCB cases, and 22 unaffecteds) and all were genotyped using a dense single nucleotide polymorphism (SNP) array to identify shared segments, copy number variants (CNVs), and to calculate genetic risk scores. Eight cases were also whole genome sequenced to test whether any rare variants were shared identical by descent. While we did not identify any notable CNVs, single nucleotide variants, indels or repeat expansions of near-Mendelian effect, the most distinctive feature of this family proved to be an unusually high load of common risk alleles for TS. We found that cases within this family carried a higher load of TS common variant risk similar to that previously found in unrelated TS cases. Thus far, the strongest evidence from genetic data for contribution to TS risk in this family comes from multiple common risk variants rather than one or a few variants of strong effect.

Rare germline variants in individuals diagnosed with schizophrenia within multiplex families

An extensive catalog of common and rare genetic variants contributes to overall risk for schizophrenia and related disorders. As a complement to population genetics efforts, here we present whole genome sequences of multiple affected probands within individual families to search for possible high penetrance driver variants. From a total of 15 families diagnostically evaluated by a single research psychiatrist, we performed whole genome sequencing of a total of 61 affected individuals, called SNPs, indels, and copy number variants, and compared to reference genomes. In fourteen out of fifteen families, the schizophrenia polygenic risk score for each proband was within the control range defined by the Thousand Genomes cohort. In six families, each affected member carried a very rare or private, predicted-damaging, variant in at least one gene. Among these genes, variants in LRP1 and TENM2 suggest these are candidate disease-related genes when taken into context with existing population genetic studies and biological information. Results add to the number of pedigree sequences reported, suggest pathways for the investigation of biological mechanisms, and are consistent with the overall accumulating evidence that very rare damaging variants contribute to the heritability of schizophrenia.

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

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.