BACKGROUND Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case... Show moreBACKGROUND Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case-cohort study within the prospective Cardiovascular Registry Maastricht (CAREMA) cohort, we tested if genetic risk scores (GRS) based on GWAS-identified SNPs are associated with and predictive for future CHD. METHODS AND RESULTS Incident cases (n=742), that is, participants who developed CHD during a median follow-up of 12.1 years (range, 0.0-16.9 years), were compared with a randomly selected subcohort of 2221 participants selected from the total cohort (n=21 148). We genotyped 179 SNPs previously associated with CHD or CHD RF in GWAS as published up to May 2, 2011. The allele-count GRS, composed of all SNPs, the 153 RF SNPs, or the 29 CHD SNPs were not associated with CHD independent of CHD RF. The weighted 29 CHD SNP GRS, with weights obtained from GWAS for every SNP, were associated with CHD independent of CHD RF (hazard ratio, 1.12 per weighted risk allele; 95% confidence interval, 1.04-1.21) and improved risk reclassification with 2.8% (P=0.031). As an exploratory approach to achieve weighting, we performed least absolute shrinkage and selection operator (LASSO) regression analysis on all SNPs and the CHD SNPs. The CHD LASSO GRS performed equal to the weighted CHD GRS, whereas the Overall LASSO GRS performed slightly better than the weighted CHD GRS. CONCLUSIONS A GRS composed of CHD SNPs improves risk prediction when adjusted for the effect sizes of the SNPs. Alternatively LASSO regression analysis may be used to achieve weighting; however, validation in independent populations is required. Show less
Stienstra, R.; Joosten, L.A.B.; Koenen, T.; Tits, B. van; Diepen, J.A. van; Berg, S.A.A. van den; ... ; Netea, M.G. 2010
Obesity-induced inflammation originating from expanding adipose tissue interferes with insulin sensitivity. Important metabolic effects have been recently attributed to IL-1 beta and IL-18, two... Show moreObesity-induced inflammation originating from expanding adipose tissue interferes with insulin sensitivity. Important metabolic effects have been recently attributed to IL-1 beta and IL-18, two members of the IL-1 family of cytokines. Processing of IL-1 beta and IL-18 requires cleavage by caspase-1, a cysteine protease regulated by a protein complex called the inflammasome. We demonstrate that the inflammasome/caspase-1 governs adipocyte differentiation and insulin sensitivity. Caspase-1 is upregulated during adipocyte differentiation and directs adipocytes toward a more insulin-resistant phenotype. Treatment of differentiating adipocytes with recombinant IL-1 beta and IL-18, or blocking their effects by inhibitors, reveals that the effects of caspase-1 on adipocyte differentiation are largely conveyed by IL-1 beta. Caspase-1 and IL-1 beta activity in adipose tissue is increased both in diet-induced and genetically induced obese animal models. Conversely, mice deficient in caspase-1 are more insulin sensitive as compared to wild-type animals. In addition, differentiation of preadipocytes isolated from caspase-1(-/-) or NLRP3(-/-) mice resulted in more metabolically active fat cells. In vivo, treatment of obese mice with a caspase-1 inhibitor significantly increases their insulin sensitivity. Indirect calorimetry analysis revealed higher fat oxidation rates in caspase-1(-/-) animals. In conclusion, the inflammasome is an important regulator of adipocyte function and insulin sensitivity, and caspase-1 inhibition may represent a novel therapeutic target in clinical conditions associated with obesity and insulin resistance. Show less
Lichtenstein, L.; Mattijssen, F.; Wit, N.J. de; Georgiadi, A.; Hooiveld, G.J.; Meer, R. van der; ... ; Kersten, S. 2010
Dietary saturated fat is linked to numerous chronic diseases, including cardiovascular disease. Here we study the role of the lipoprotein lipase inhibitor AngptI4 in the response to dietary... Show moreDietary saturated fat is linked to numerous chronic diseases, including cardiovascular disease. Here we study the role of the lipoprotein lipase inhibitor AngptI4 in the response to dietary saturated fat. Strikingly, in mice lacking AngptI4, saturated fat induces a severe and lethal phenotype characterized by fibrinopurulent peritonitis, ascites, intestinal fibrosis, and cachexia. These abnormalities are preceded by a massive acute phase response induced by saturated but not unsaturated fat or medium-chain fat, originating in mesenteric lymph nodes (MLNs). MLNs undergo dramatic expansion and contain numerous lipid-laden macrophages. In peritoneal macrophages incubated with chyle, AngptI4 dramatically reduced foam cell formation, inflammatory gene expression, and chyle-induced activation of ER stress. Induction of macrophage AngptI4 by fatty acids is part of a mechanism that serves to reduce postprandial lipid uptake from chyle into MLN-resident macrophages by inhibiting triglyceride hydrolysis, thereby preventing macrophage activation and foam cell formation and protecting against progressive, uncontrolled saturated fat-induced inflammation. Show less
Background: Plasma total cholesterol (TC) levels are highly genetically determined. Although ample evidence of genetic determination of separate lipoprotein cholesterol levels has been reported,... Show moreBackground: Plasma total cholesterol (TC) levels are highly genetically determined. Although ample evidence of genetic determination of separate lipoprotein cholesterol levels has been reported, using TC level directly as a phenotype in a relatively large broad-gene based association study has not been reported to date. Methods and results: We genotyped 361 single nucleotide polymorphisms (SNPs) across 243 genes based on pathways potentially relevant to cholesterol metabolism in 3575 subjects that were examined thrice over 11 years. Twenty-three SNPs were associated with TC levels after adjustment for multiple testing. We used 12 of them (rs7412 and rs429358 in APOE, rs646776 in CELSR2, rs1367117 in APOB, rs6756629 in ABCG5, rs662799 in APOA5, rs688 in LDLR, rs10889353 in DOCK7, rs2304130 in NCAN, rs3846662 in HMGCR, rs2275543 in ABCA1, rs7275 in SMARCA4) that were confirmed in previous candidate association or genome-wide-association studies to define a gene risk score (GRS). Average TC levels increased from 5.23 +/- 0.82 mmol/L for those with 11 or less cholesterol raising alleles to 6.03 +/- 1.11 mmol/L for those with 18 or more (P for trend <0.0001). The association with TC levels was slightly stronger when the weighted GRS that weighted the magnitude of allelic effects was used. Conclusion: A panel of common genetic variants in the genes pivotal in cholesterol metabolism could possibly help identify those people who are at risk of high cholesterol levels. (C) 2010 Elsevier Ireland Ltd. All rights reserved. Show less
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have... Show moreMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. Show less
