Gregory R. Warnes

Bio: Gregory R. Warnes is an academic researcher from Pfizer. The author has contributed to research in topics: Gene & Markov chain Monte Carlo. The author has an hindex of 9, co-authored 11 publications receiving 2996 citations. Previous affiliations of Gregory R. Warnes include University of Rochester.

Genome-wide scan identifies variation in MLXIPL associated with plasma triglycerides.

Abstract: We tested over 267,000 SNPs in 1,005 Northern Europeans and 248,000 in 1,006 Indian Asians for association with triglycerides and HDL cholesterol, with replication in 10,536 subjects. We found association of a nonsynonymous SNP (rs3812316, G771C, Gln241His) in MLXIPL with plasma triglyceride levels (combined P = 1.4 x 10(-10)). MLXIPL coordinates transcriptional regulation of enzymes that channel glycolytic end-products into lipogenesis and energy storage, making MLXIPL a plausible 'thrifty gene'.

Differentiation of DNA reactive and non-reactive genotoxic mechanisms using gene expression profile analysis.

Abstract: Genotoxic stress triggers a variety of biological responses including the transcriptional activation of genes regulating DNA repair, cell survival and cell death. Here, we investigated whether gene expression profiles can differentiate between DNA reactive and DNA non-reactive mechanisms of genotoxicity. We analyzed gene expression profiles and micronucleus levels in L5178Y cells treated with cisplatin and sodium chloride. The assessment of cisplatin genotoxicity (up to six-fold increase in the number of micronuclei) and gene expression profile (increased expression of genotoxic stress-associated genes) was in agreement with cisplatin mode of action as a DNA adduct-forming agent. The gene expression profile analysis of cisplatin-treated cells identified a number of genes with robust up regulation of mRNA expression including genes associated with DNA damage (i.e. members of GADD45 family), early response (i.e. cFOS), and heat shock protein (i.e. HSP40 homologue). The gene expression changes correlated well with DNA damage as measured by DNA–protein crosslinks and platinum–DNA binding. To differentiate the genotoxic stress-associated expression profile of cisplatin from a general toxic stress, we have compared the gene expression profile of cisplatin-treated cells to cells treated with sodium chloride, which causes osmotic shock and cell lysis. Although the sodium chloride treatment caused a two-fold induction of micronuclei, the gene expression profile at equitoxic concentrations was remarkably distinct from the profile observed with cisplatin. The profile of sodium chloride featured a complete lack of expression changes in genes associated with DNA damage and repair. In summary, the gene expression profiles clearly distinguished between DNA reactive and non-reactive genotoxic mechanisms of cisplatin and sodium chloride. Our results suggest the potential utility of gene expression profile analysis for elucidating mechanism of action of genotoxic agents.

JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling

Abstract: JAGS is a program for Bayesian Graphical modelling which aims for compatibility with Classic BUGS. The program could eventually be developed as an R package. This article explains the motivations for this program, briefly describes the architecture and then discusses some ideas for a vectorized form of the BUGS language.

Biological, clinical and population relevance of 95 loci for blood lipids

Abstract: Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Genome-wide association studies for complex traits: consensus, uncertainty and challenges

Abstract: The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk

Abstract: Blood pressure is a heritable trait(1) influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (>= 140 mm Hg systolic blood pressure or >= 90 mm Hg diastolic blood pressure)(2). Even small increments in blood pressure are associated with an increased risk of cardiovascular events(3). This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

Large-scale association analysis identifies new risk loci for coronary artery disease

Abstract: Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.