For example, given that EL inversely affects HDL-C levels, variants that decrease EL should cause increased HDL-C and should occur at a higher frequency in high HDL-C individuals, andvice versa

For example, given that EL inversely affects HDL-C levels, variants that decrease EL should cause increased HDL-C and should occur at a higher frequency in high HDL-C individuals, andvice versa. levels of theLIPGgene product endothelial lipase (EL), consistent with its part in HDL-C catabolism. Additionally, we found that a common nonfunctional coding BCR-ABL-IN-1 variant associated BCR-ABL-IN-1 with HDL-C (rs2000813) is in linkage disequilibrium having a 5 UTR variant (rs34474737) that decreasesLIPGpromoter activity. We attribute the gene regulatory part of rs34474737 to the observed association of the coding BCR-ABL-IN-1 variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci. == Author Summary == Genetic association studies possess recognized genomic areas that impact quantifiable traits such as lipid levels. When a gene and a trait are found to be associated with one another, the gene is usually further studied to determine its part in influencing the trait. One approach is to sequence the gene in individuals in the extremes of the trait’s distribution with the hope of finding rare mutations that directly contribute to the trait. Until now studies using this approach have focused on genetic variance in the protein coding sequence of these genes and have been mainly successful in identifying functionally important mutations. However, additional studies have found an abundance of noncoding variance in the genome that may also contribute to the heritability of these traits. Here we seek to determine the contribution of such noncoding mutations to high density lipoprotein cholesterol (HDL-C) levels in humans using the HDL-C candidate geneLIPGas an example. Via a sequencing study in individuals with high and low HDL-C levels, we demonstrate that both rare and common noncoding mutations are influential contributors to the allelic spectrum of such traits and should become further characterized after initial association with the trait. == Intro == Numerous studies have connected low levels of high density lipoprotein cholesterol (HDL-C) with an increased risk of developing coronary heart disease (CHD)[1],[2],[3],[4],[5],[6],[7]. HDL-C levels are approximately 50% heritable[8]. Genome-wide association studies (GWAS) for lipid characteristics have recognized many genes previously associated with HDL metabolism and numerous novel loci[9],[10],[11],[12],[13],[14]. However, the identification of the causal variants in these loci offers proven hard. Resequencing studies have not recognized common coding variants that clarify BCR-ABL-IN-1 the associations. Such results may suggest that causal coding variants are rarer than anticipated[15]or lie in the gene regulatory areas. Furthermore, many of the variants recognized BCR-ABL-IN-1 by GWAS are embedded in gene deserts. Although a portion of these connected variants may tag less-common variants with strong phenotypic effects, some noncoding variants are likely to be causal themselves[16]. However, combining the variance explained by all the common variants recognized to date leaves missing heritability[17]that may be explained, at least in part, by rare variants. Several HDL-C candidate genes, including those with known physiological relevance to HDL-C metabolism, have been characterized though targeted gene-resequencing methods[18]. Through these studies, the exons of HDL-C candidate genes (ABCAI,APOAI,LCAT)[19]and additional mechanistically implicated genes (ANGPTL4,LIPG)[20],[21]have been sequenced in individuals in the extremes of the HDL-C phenotypic distribution. Rare coding loss-of-function variants were shown to segregate with the phenotype in a manner consistent with the known physiological part of the gene product in increasing or reducing HDL-C levels. Causality of the recognized variants was shown via a combination ofin vitrofunctional studies and computational methods. Because the event of each rare variant was too low to test its association in our sequencing cohorts, individual variants in each phenotypic intense were grouped with each other (collapsed), and the total number of rare variants in the sequenced region was compared between cohorts. This method of rare variant association analysis, known as the Rabbit Polyclonal to KAL1 cohort allelic sums test (Solid)[22],[23], has been instrumental in showing that rare loss-of-function variants modulate HDL-C levels in humans. However, few studies to date have utilized this approach to study rare regulatory variants, which do not constantly segregate with the phenotypic extremes of continuous characteristics as stringently as deleterious.