Learning the optimal scale for GWAS through hierarchical SNP aggregation

Motivation: Genome-Wide Association Studies (GWAS) seek to identify causal genomic variants associated with rare human diseases. The classical statistical approach for detecting these variants is based on univariate hypothesis testing, with healthy individuals being tested against affected individuals at each locus. Given that an individual's genotype is characterized by up to one million SNPs, this approach lacks precision, since it may yield a large number of false positives that can lead to erroneous conclusions about genetic associations with the disease. One way to improve the detection of true genetic associations is to reduce the number of hypotheses to be tested by grouping SNPs. Results: We propose a dimension-reduction approach which can be applied in the context of GWAS by making use of the haplotype structure of the human genome. We compare our method with standard univariate and multivariate approaches on both synthetic and real GWAS data, and we show that reducing the dimension of the predictor matrix by aggregating SNPs gives a greater precision in the detection of associations between the phenotype and genomic regions

Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates.

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To identify roles of rare and common variants on BP, we conducted genetic analyses in 26 Colombia and Costa Rica pedigrees ascertained for bipolar disorder 1 (BP1), the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 838 individuals and high-coverage whole-genome sequencing of 449 individuals. We compared polygenic risk scores (PRS), estimated using the latest BP1 genome-wide association study (GWAS) summary statistics, between BP1 individuals and related controls. We also evaluated whether BP1 individuals had a higher burden of rare deleterious single-nucleotide variants (SNVs) and rare copy number variants (CNVs) in a set of genes related to BP1. We found that compared with unaffected relatives, BP1 individuals had higher PRS estimated from BP1 GWAS statistics (P = 0.001 ~ 0.007) and displayed modest increase in burdens of rare deleterious SNVs (P = 0.047) and rare CNVs (P = 0.002 ~ 0.033) in genes related to BP1. We did not observe rare variants segregating in the pedigrees. These results suggest that small-to-moderate effect rare and common variants are more likely to contribute to BP1 risk in these extended pedigrees than a few large-effect rare variants

Accurate Liability Estimation Improves Power in Ascertained Case Control Studies

Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in non-randomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (Liability Estimator As a Phenotype, https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and demonstrate that this can lead to a substantial power increase

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

Association of the IL-10 gene family locus on chromosome 1 with juvenile idiopathic arthritis (JIA)

The cytokine IL-10 and its family members have been implicated in autoimmune diseases and we have previously reported that genetic variants in IL-10 were associated with a rare group of diseases called juvenile idiopathic arthritis (JIA). The aim of this study was to fine map genetic variants within the IL-10 cytokine family cluster on chromosome 1 using linkage disequilibrium (LD)-tagging single nucleotide polymorphisms (tSNPs) approach with imputation and conditional analysis to test for disease associations

Multi-level evidence of an allelic hierarchy of USH2A variants in hearing, auditory processing and speech/language outcomes.

Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems