Comparison of genomic DNA sequences from human and mouse revealed a new apolipoprotein (APO) gene ( APOAV ) located proximal to the well-characterized APOAI/CIII/AIV gene cluster on human 11q23. Mice expressing a human APOAV transgene showed a decrease in plasma triglyceride concentrations to one-third of those in control mice; conversely, knockout mice lacking Apoav had four times as much plasma triglycerides as controls. In humans, single nucleotide polymorphisms (SNPs) across the APOAV locus were found to be significantly associated with plasma triglyceride levels in two independent studies. These findings indicate that APOAV is an important determinant of plasma triglyceride levels, a major risk factor for coronary artery disease.

The recently identified apolipoprotein A5 gene (APOA5) has been shown to play an important role in determining plasma triglyceride concentrations in humans and mice. We previously identified an APOA5 haplotype (designated APOA5*2) that is present in approximately 16% of Caucasians and is associated with increased plasma triglyceride concentrations. In this report we describe another APOA5 haplotype (APOA5*3) containing the rare allele of the single nucleotide polymorphism c.56C>G that changes serine to tryptophan at codon 19 and is independently associated with high plasma triglyceride levels in three different populations. In a sample of 264 Caucasian men and women with plasma triglyceride concentrations above the 90th percentile or below the 10th percentile, the APOA5*3 haplotype was more than three-fold more common in the group with high plasma triglyceride levels. In a second independently ascertained sample of Caucasian men and women (n=419) who were studied while consuming their self-selected diets as well as after high-carbohydrate diets and high-fat diets, the APOA5*3 haplotype was associated with increased plasma triglyceride levels on all three dietary regimens. In a third population comprising 2660 randomly selected individuals, the APOA5*3 haplotype was found in 12% of Caucasians, 14% of African-Americans and 28% of Hispanics and was associated with increased plasma triglyceride levels in both men and women in each ethnic group. These findings establish that the APOA5 locus contributes significantly to inter-individual variation in plasma triglyceride levels in humans. Together, the APOA5*2 and APOA5*3 haplotypes are found in 25-50% of African-Americans, Hispanics and Caucasians and support the contribution of common human variation to quantitative phenotypes in the general population.

Since triglycerides (TG) are a major independent risk factor for coronary heart disease, understanding their genetic and environmental determinants is of major importance. Mouse models indicate an inverse relationship between levels of the newly identified apolipoprotein AV (APOAV) and TG concentrations. We have examined the relative influence of human APOA5 variants on plasma lipids, compared to the impact of variation in APOC3 and APOA4 which lie in the same cluster. Single nucleotide polymorphisms (SNPs) in APOA5 (S19W, -1131T>C) and APOA4 (T347S, Q360H) and an APOA4/A5 intergenic T>C SNP were examined in a large study of healthy middle-aged men (n=2808). APOA5 19WW and -1131CC men had 52% and 40% higher TG (P<0.003) compared to common allele homozygotes, respectively, effects which were independent and additive. APOA4 347SS men had 23% lower TG compared to TT men (P<0.002). Haplotype analysis was carried out to identify TG-raising alleles and included, in addition, four previously genotyped APOC3 SNPs (-2845T>G, -482C>T, 1100C>T, and 3238C>G). The major TG-raising alleles were defined by APOA5 W19 and APOC3 -482T. This suggests that the TG-lowering effect of APOA4 S347 might merely reflect the strong negative linkage disequilibrium with the common alleles of these variants. Thus variation in APOA5 is associated with differences in TGs in healthy men, independent of those previously reported for APOC3, while association between APOA4 and TG reflects linkage disequilibrium with these sites. The molecular mechanisms for these effects remain to be determined.

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Polycystic ovary syndrome (PCOS) is a common, highly heritable complex disorder of unknown aetiology characterized by hyperandrogenism, chronic anovulation and defects in glucose homeostasis. Increased luteinizing hormone relative to follicle-stimulating hormone secretion, insulin resistance and developmental exposure to androgens are hypothesized to play a causal role in PCOS. Here we map common genetic susceptibility loci in European ancestry women for the National Institutes of Health PCOS phenotype, which confers the highest risk for metabolic morbidities, as well as reproductive hormone levels. Three loci reach genome-wide significance in the case–control meta-analysis, two novel loci mapping to chr 8p32.1 and chr 11p14.1, and a chr 9q22.32 locus previously found in Chinese PCOS. The same chr 11p14.1 SNP, rs11031006, in the region of the follicle-stimulating hormone B polypeptide (FSHB) gene strongly associates with PCOS diagnosis and luteinizing hormone levels. These findings implicate neuroendocrine changes in disease pathogenesis.