Estimating the total number of susceptibility variants underlying complex diseases from genome-wide association studies

Recently genome-wide association studies (GWAS) have identified numerous susceptibility variants for complex diseases. In this study we proposed several approaches to estimate the total number of variants underlying these diseases. We assume that the variance explained by genetic markers (Vg) follow an exponential distribution, which is justified by previous studies on theories of adaptation. Our aim is to fit the observed distribution of Vg from GWAS to its theoretical distribution. The number of variants is obtained by the heritability divided by the estimated mean of the exponential distribution. In practice, due to limited sample sizes, there is insufficient power to detect variants with small effects. Therefore the power was taken into account in fitting. Besides considering the most significant variants, we also tried to relax the significance threshold, allowing more markers to be fitted. The effects of false positive variants were removed by considering the local false discovery rates. In addition, we developed an alternative approach by directly fitting the z-statistics from GWAS to its theoretical distribution. In all cases, the "winner's curse" effect was corrected analytically. Confidence intervals were also derived. Simulations were performed to compare and verify the performance of different estimators (which incorporates various means of winner's curse correction) and the coverage of the proposed analytic confidence intervals. Our methodology only requires summary statistics and is able to handle both binary and continuous traits. Finally we applied the methods to a few real disease examples (lipid traits, type 2 diabetes and Crohn's disease) and estimated that hundreds to nearly a thousand variants underlie these traits.     

Common variants for atrial fibrillation: results from genome-wide association studies

Atrial fibrillation (AF) affects more than 5 million people worldwide; however, none of the anti-arrhythmic drugs available now are entirely optimal in terms of efficacy and safety. A better understanding of the molecular mechanism of AF will facilitate the process of finding new strategies to prevent AF. As the non-familial AF is the major form of AF, identifying common variants for AF in these populations by genome-wide association studies will definitely accelerate this process. This review summarizes the recently identified common AF variants on 4q25, 16q22, and 1q21 and discusses their implications for the clinic.     

Copy number variants in pharmacogenetic genes

Variation in drug efficacy and toxicity remains an important clinical concern. Presently, single nucleotide polymorphisms (SNPs) only explain a portion of this problem, even in situations where the pharmacological trait is clearly heritable. The Human CNV Project identified copy number variations (CNVs) across approximately 12% of the human genome, and these CNVs were considered causes of diseases. Although the contribution of CNVs to the pathogenesis of many common diseases is questionable, CNVs play a clear role in drug-related genes by altering drug metabolizing and drug response. In this review, we provide a comprehensive evaluation of the clinical relevance of CNVs to drug efficacy, toxicity, and disease prevalence in world populations, and discuss the implication of using CNVs as a diagnostic tool in clinical intervention.     

CONAN: copy number variation analysis software for genome-wide association studies

Background  

Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.     

On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants

Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). The impact of this method, especially for heterogeneous human populations, is to reduce the false-positive rate, inflate other spuriously small p values, and have little impact on the p values associated with true positive loci. Thus, it highlights true positives by downplaying false positives. We perform a GWA by matching Americans with type 1 diabetes (T1D) to controls from Germany. Despite the complex study design, these analyses identify numerous loci known to confer risk for T1D.     

Copy number variants in patients with severe oligozoospermia and Sertoli-cell-only syndrome

A genetic origin is estimated in 30% of infertile men with the common phenotypes of oligo- or azoospermia, but the pathogenesis of spermatogenic failure remains frequently obscure. To determine the involvement of Copy Number Variants (CNVs) in the origin of male infertility, patients with idiopathic severe oligozoospermia (N = 89), Sertoli-cell-only syndrome (SCOS, N = 37)) and controls with normozoospermia (N = 100) were analysed by array-CGH using the 244A/400K array sets (Agilent Technologies). The mean number of CNVs and the amount of DNA gain/loss were comparable between all groups. Ten recurring CNVs were only found in patients with severe oligozoospermia, three only in SCOS and one CNV in both groups with spermatogenic failure but not in normozoospermic men. Sex-chromosomal, mostly private CNVs were significantly overrepresented in patients with SCOS. CNVs found several times in all groups were analysed in a case-control design and four additional candidate genes and two regions without known genes were associated with SCOS (P<1×10⁻³). In conclusion, by applying array-CGH to study male infertility for the first time, we provide a number of candidate genes possibly causing or being risk factors for the men''s spermatogenic failure. The recurring, patient-specific and private, sex-chromosomal CNVs as well as those associated with SCOS are candidates for further, larger case-control and re-sequencing studies.     

Copy number variants in a highly inbred Iberian porcine strain

We carried out a comprehensive genomic analysis of porcine copy number variants (CNVs) based on whole‐genome SNP genotyping data and provided new measures of genomic diversity (number, length and distribution of CNV events) for a highly inbred strain (the Guadyerbas strain). This strain represents one of the most ancient surviving populations of the Iberian breed, and it is currently in serious danger of extinction. CNV detection was conducted on the complete Guadyerbas population, adjusted for genomic waves, and used strict quality criteria, pedigree information and the latest porcine genome annotation. The analysis led to the detection of 65 CNV regions (CNVRs). These regions cover 0.33% of the autosomal genome of this particular strain. Twenty‐nine of these CNVRs were identified here for the first time. The relatively low number of detected CNVRs is in line with the low variability and high inbreeding estimated previously for this Iberian strain using pedigree, microsatellite or SNP data. A comparison across different porcine studies has revealed that more than half of these regions overlap with previously identified CNVRs or multicopy regions. Also, a preliminary analysis of CNV detection using whole‐genome sequence data for four Guadyerbas pigs showed overlapping for 16 of the CNVRs, supporting their reliability. Some of the identified CNVRs contain relevant functional genes (e.g., the SCD and USP15 genes), which are worth being further investigated because of their importance in determining the quality of Iberian pig products. The CNVR data generated could be useful for improving the porcine genome annotation.     

Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest

We study the number of causal variants and associated regions identified by top SNPs in rankings given by the popular 1 df chi-squared statistic, support vector machine (SVM) and the random forest (RF) on simulated and real data. If we apply the SVM and RF to the top 2r chi-square-ranked SNPs, where r is the number of SNPs with P-values within the Bonferroni correction, we find that both improve the ranks of causal variants and associated regions and achieve higher power on simulated data. These improvements, however, as well as stability of the SVM and RF rankings, progressively decrease as the cutoff increases to 5r and 10r. As applications we compare the ranks of previously replicated SNPs in real data, associated regions in type 1 diabetes, as provided by the Type 1 Diabetes Consortium, and disease risk prediction accuracies as given by top ranked SNPs by the three methods. Software and webserver are available at http://svmsnps.njit.edu.     

Analysing biological pathways in genome-wide association studies

Genome-wide association (GWA) studies have typically focused on the analysis of single markers, which often lacks the power to uncover the relatively small effect sizes conferred by most genetic variants. Recently, pathway-based approaches have been developed, which use prior biological knowledge on gene function to facilitate more powerful analysis of GWA study data sets. These approaches typically examine whether a group of related genes in the same functional pathway are jointly associated with a trait of interest. Here we review the development of pathway-based approaches for GWA studies, discuss their practical use and caveats, and suggest that pathway-based approaches may also be useful for future GWA studies with sequencing data.     

Genomic variants associated with the number and diameter of muscle fibers in pigs as revealed by a genome-wide association study

Muscle fiber characteristics comprise a set of complex traits that influence the mea quality and lean meat production of livestock. However, the genetic and biological mechanisms regulating muscle fiber characteristics are largely unknown in pigs. Based on a genome-wide association study (GWAS) performed on 421 Large White × Min pig F2 individuals presenting well-characterized phenotypes, this work aimed to detect genome variations and candidate genes for five muscle fiber characteristics: percentage of type I fibers (FIB1P), percentage of type IIA fibers (FIB2AP), percentage of type IIB fibers (FIB2BP), diameter of muscle fibers (DIAMF) and number of muscle fibers per unit area (NUMMF). The GWAS used the Illumina Porcine SNP60K genotypic data, which were analyzed by a mixed model. Seven and 10 single nucleotide polymorphisms (SNPs) were significantly associated with DIAMF and NUMMF, respectively (P < 1.10E-06); no SNP was significantly associated with FIB1P, FIB2AP or FIB2B. For DIAMF, the significant SNPs on chromosome 4 were located in the previously reported quantitative trait loci (QTL) interval. Because the significant SNPs on chromosome 6 were not mapped in the previously reported QTL interval, a putative novel QTL was suggested for this locus. None of the previously reported QTL intervals on chromosomes 6 and 14 harbored significant SNPs for NUMMF; thus, new potential QTLs on these two chromosomes are suggested in the present work. The most significant SNPs associated with DIAMF (ALGA0025682) and NUMMF (MARC0046984) explained 12.02% and 11.59% of the phenotypic variation of these traits, respectively. In addition, both SNPs were validated as associated with DIAMF and NUMMF in Beijing Black pigs (P < 0.01). Some candidate genes or non-coding RNAs, such as solute carrier family 44 member 5 and miR-124a-1 for DIAMF, and coiled-coil serine rich protein 2 for NUMMF, were identified based on their close location to the significant SNPs. This study revealed some genome-wide association variants for muscle fiber characteristics, and it provides valuable information to discover the genetic mechanisms controlling these traits in pigs.     

Density of common complex ocular traits in the aging eye: analysis of secondary traits in genome-wide association studies

Genetic association studies are identifying genetic risks for common complex ocular traits such as age-related macular degeneration (AMD). The subjects used for discovery of these loci have been largely from clinic-based, case-control studies. Typically, only the primary phenotype (e.g., AMD) being studied is systematically documented and other complex traits (e.g., affecting the eye) are largely ignored. The purpose of this study was to characterize these other or secondary complex ocular traits present in the cases and controls of clinic-based studies being used for genetic study of AMD. The records of 100 consecutive new patients (of any diagnosis) age 60 or older for which all traits affecting the eye had been recorded systematically were reviewed. The average patient had 3.5 distinct diagnoses. A subset of 10 complex traits was selected for further study because they were common and could be reliably diagnosed. The density of these 10 complex ocular traits increased by 0.017 log-traits/year (P = 0.03), ranging from a predicted 2.74 at age 60 to 4.45 at age 90. Trait-trait association was observed only between AMD and primary vitreomacular traction (P = 0.0009). Only 1% of subjects age 60 or older had no common complex traits affecting the eye. Extrapolations suggested that a study of 2000 similar subjects would have sufficient power to detect genetic association with an odds ratio of 2.0 or less for 4 of these 10 traits. In conclusion, the high prevalence of complex traits affecting the aging eye and the inherent biases in referral patterns leads to the potential for confounding by undocumented secondary traits within case-control studies. In addition to the primary trait, other common ocular phenotypes should be systematically documented in genetic association studies so that adjustments for potential trait-trait associations and other bias can be made and genetic risk variants identified in secondary analyses.     

Auditory neuroscience: filling in the gaps

Our sensory systems fill in information obscured by other, competing signals to maintain a stable representation of the world. A correlate of the continuity illusion, in which sounds are perceived to continue despite being interrupted by other sounds, has now been found in the auditory cortex.