Analysis of Whole Exome Sequencing with Cardiometabolic Traits Using Family-Based Linkage and Association in the IRAS Family Study

PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data

With the advances of next-generation sequencing technology, the field of disease research has been revolutionized. However, pinpointing the disease-causing variants from millions of revealed variants is still a tough task. Here, we have reviewed the existing linkage analysis tools and presented PedMiner, a web-based application designed to narrow down candidate variants from family based whole-exome sequencing (WES) data through linkage analysis. PedMiner integrates linkage analysis, variant annotation and prioritization in one automated pipeline. It provides graphical visualization of the linked regions along with comprehensive annotation of variants and genes within these linked regions. This efficient and comprehensive application will be helpful for the scientific community working on Mendelian inherited disorders using family based WES data.

Relevance of Multi-Omics Studies in Cardiovascular Diseases

Cardiovascular diseases are the leading cause of death around the world. Despite the larger number of genes and loci identified, the precise mechanisms by which these genes influence risk of cardiovascular disease is not well understood. Recent advances in the development and optimization of high-throughput technologies for the generation of “omics data” have provided a deeper understanding of the processes and dynamic interactions involved in human diseases. However, the integrative analysis of “omics” data is not straightforward and represents several logistic and computational challenges. In spite of these difficulties, several studies have successfully applied integrative genomics approaches for the investigation of novel mechanisms and plasma biomarkers involved in cardiovascular diseases. In this review, we summarized recent studies aimed to understand the molecular framework of these diseases using multi-omics data from mice and humans. We discuss examples of omics studies for cardiovascular diseases focused on the integration of genomics, epigenomics, transcriptomics, and proteomics. This review also describes current gaps in the study of complex diseases using systems genetics approaches as well as potential limitations and future directions of this emerging field.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Exome Sequencing Identifies Genetic Variants Associated with Circulating Lipid Levels in Mexican Americans: The Insulin Resistance Atherosclerosis Family Study (IRASFS)

Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h² = 0.50), high-density lipoprotein (HDL, h² = 0.57), total cholesterol (TC, h² = 0.53), and triglyceride (TG, h² = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, P_TG = 3.67 × 10^-10, LOD_TG = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r² = 1.0) rs189547099 (P_TG = 6.31 × 10^-08, LOD_TG = 3.13, MAF = 0.50%) and chr4:157997598 (P_TG = 6.31 × 10^-08, LOD_TG = 3.13, MAF = 0.50%) reached exome-wide significance (P < 9.11 × 10^-08). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD > 3 with the strongest signal at rs1141070 (LOD_LDL = 4.30, P_LDL = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P < 5.00 × 10^-05, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, P_LDL = 4.44 × 10^-17, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels.

Identification of novel genetic loci GAL3ST4 and CHGB involved in susceptibility to leprosy

Leprosy has long been thought to have a strong genetic component, and so far, only positional cloning and genomewide association studies have been used to study the genetic susceptibility to leprosy,while whole exome sequencing (WES) approach has not yet been applied. In this study, we used WES approach on four leprosy patients and four healthy control relatives from two leprosy families. We found three new susceptible loci of leprosy, one in GAL3ST4 and two in CHGB. We went on to validate the findings of WES using 151 leprosy cases and 226 healthy controls by Sanger sequencing. Stratified by gender, GAL3ST4 was found to be the susceptible gene only for the female population, and CHGB48 and CHGB23 were susceptibile to leprosy for the male population, respectively). Moreover, the gene expression levels of the three susceptible loci were measured by real-time PCR after the stimulation by M. leprae antigens in the PBMC (peripheral blood mononuclear cells) of 69 healthy people. The results showed that the female subjects with high frequent genotype in GAL3ST4 had a fivefold elevated expression. We suggest the polymorphisms in GAL3ST4 in different population are associated with increased risk of leprosy.