Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Genetic variants in LPL, OASL and TOMM40/APOE-C1-C2-C4 genes are associated with multiple cardiovascular-related traits.

BACKGROUND: Genome-wide association studies (GWAS) have become a major strategy for genetic dissection of human complex diseases. Analysing multiple phenotypes jointly may improve both our ability to detect genetic variants with multiple effects and our understanding of their common features. Allelic associations for multiple biochemical traits (serum alanine aminotransferase, aspartate aminotransferase, butrylycholinesterase (BCHE), C-reactive protein (CRP), ferritin, gamma glutamyltransferase (GGT), glucose, high-density lipoprotein cholesterol (HDL), insulin, low-density lipoprotein cholesterol (LDL), triglycerides and uric acid), and body-mass index, were examined. METHODS: We aimed to identify common genetic variants affecting more than one of these traits using genome-wide association analysis in 2548 adolescents and 9145 adults from 4986 Australian twin families. Multivariate and univariate associations were performed. RESULTS: Multivariate analyses identified eight loci, and univariate association analyses confirmed two loci influencing more than one trait at p < 5 × 10-8. These are located on chromosome 8 (LPL gene affecting HDL and triglycerides) and chromosome 19 (TOMM40/APOE-C1-C2-C4 gene cluster affecting LDL and CRP). A locus on chromosome 12 (OASL gene) showed effects on GGT, LDL and CRP. The loci on chromosomes 12 and 19 unexpectedly affected LDL cholesterol and CRP in opposite directions. CONCLUSIONS: We identified three possible loci that may affect multiple traits and validated 17 previously-reported loci. Our study demonstrated the usefulness of examining multiple phenotypes jointly and highlights an anomalous effect on CRP, which is increasingly recognised as a marker of cardiovascular risk as well as of inflammation.

Candidate gene association study in type 2 diabetes indicates a role for genes involved in beta-cell function as well as insulin action.

Type 2 diabetes is an increasingly common, serious metabolic disorder with a substantial inherited component. It is characterised by defects in both insulin secretion and action. Progress in identification of specific genetic variants predisposing to the disease has been limited. To complement ongoing positional cloning efforts, we have undertaken a large-scale candidate gene association study. We examined 152 SNPs in 71 candidate genes for association with diabetes status and related phenotypes in 2,134 Caucasians in a case-control study and an independent quantitative trait (QT) cohort in the United Kingdom. Polymorphisms in five of 15 genes (33%) encoding molecules known to primarily influence pancreatic beta-cell function-ABCC8 (sulphonylurea receptor), KCNJ11 (KIR6.2), SLC2A2 (GLUT2), HNF4A (HNF4alpha), and INS (insulin)-significantly altered disease risk, and in three genes, the risk allele, haplotype, or both had a biologically consistent effect on a relevant physiological trait in the QT study. We examined 35 genes predicted to have their major influence on insulin action, and three (9%)-INSR, PIK3R1, and SOS1-showed significant associations with diabetes. These results confirm the genetic complexity of Type 2 diabetes and provide evidence that common variants in genes influencing pancreatic beta-cell function may make a significant contribution to the inherited component of this disease. This study additionally demonstrates that the systematic examination of panels of biological candidate genes in large, well-characterised populations can be an effective complement to positional cloning approaches. The absence of large single-gene effects and the detection of multiple small effects accentuate the need for the study of larger populations in order to reliably identify the size of effect we now expect for complex diseases.

A longitudinal genetic study of plasma lipids in adolescent twins.

Plasma lipids such as high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol and triglyceride levels contribute to variation in the risk of cardiovascular disease. The early stages of atherosclerosis in childhood have also been associated with changes in triglycerides, LDL and HDL. Heritability estimates for lipids and lipoproteins for adolescents are in the range .71 to .82, but little is known about changes of genetic and environmental influences over time in adolescence. We have investigated the contribution of genetic and environmental influences to variation in lipids in adolescent twins and their nontwin siblings using longitudinal twin and family data. Plasma HDL and LDL cholesterol, total cholesterol and triglycerides data from 965 twin pairs at 12, 14 and 16 years of age and their siblings have been analyzed. Longitudinal genetic models that included effects of age, sex and their interaction were fitted to assess whether the same or different genes influence each trait at different ages. Results suggested that more than one genetic factor influences HDL, LDL, total cholesterol and triglycerides over time at ages 12, 14 and 16 years. There was no evidence of shared environmental effects except for HDL and little evidence of long-term nonshared environmental effects was found. Our study suggested that there are developmental changes in the genes affecting plasma lipid concentrations across adolescence.

A longitudinal genetic study of uric acid and liver enzymes in adolescent twins.

Biochemical traits such as plasma alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma glutamyltransferase (GGT) and uric acid are associated with obesity, and with risk of cardiovascular disease, metabolic syndrome and diabetes. Each is subject to genetic influences, but little is known about changes in genetic and environmental influences on these traits over time. We investigated the contribution of genetic and environmental influences to variation in these biochemical traits in adolescent twins and their nontwin siblings from 965 twin families. Twins were studied at ages 12, 14 and 16 years. Multivariate genetic models that included effects of age and sex were fitted to determine whether the same or different genetic or environmental factors influence each trait at different ages. Results showed that the genetic factors influencing AST, ALT, GGT and uric acid change over time during adolescence, and that the magnitude of these effects differs between males and females. The nonshared environment effects were generally time specific. There are developmental changes in genes affecting these traits during adolescence.

Heritability of left ventricular mass in a large cohort of twins.

INTRODUCTION: Left ventricular hypertrophy is recognized as one of the most important independent predictors of adverse cardiovascular outcome. The aetiology of LVH includes a number of well-recognized causes but there is considerable interest in the genetics of cardiac muscle hypertrophy. We used a large prospective twin database in order to establish the heritability of left ventricular mass (LVM). METHODS: Normotensive twins were prospectively recruited. Demographic data were collected. The LVM was determined using the Penn formulae derived from data collected from echocardiography. RESULTS: A total of 376 Caucasian twin pairs (182 monozygotic and 194 dizygotic) aged 25-79 years were recruited. All subjects were normotensive with no significant differences in blood pressure (mean blood pressure: monozygotic twins, 132/83 mmHg; dizygotic twins, 131/82 mmHg) or body mass index between the monozygotic and dizygotic twins. The mean LVM for monozygotic twins was 140.9 g, compared with 140.2 g for dizygotic twins. Heritability estimates suggest that the genetic variance of LVM is 0.59 (95% confidence interval, 0.5-0.67). No common shared environmental effects were identified under this model. CONCLUSION: Our data from the largest set of twin pairs studied to date show that LVM has a sizeable genetic basis that is probably polygenic. This result has important implications for the understanding of normal and abnormal cardiac morphology at the molecular level.

Genetic and environmental influences on lipids, lipoproteins, and apolipoproteins: effects of menopause.

OBJECTIVE: Levels of lipids and (apo)lipoproteins are known to increase after menopause, but it is unknown whether the genetic and environmental variability alters or whether lipids and (apo)lipoproteins are influenced by different genes before and after menopause. METHODS AND RESULTS: We studied 453 monozygotic and 1280 dizygotic pairs of female white twins recruited from the St. Thomas' UK Adult Twin Registry and measured total cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL), triglycerides, lipoprotein(a) [Lp(a)], apolipoprotein A1 (apoA1), and apolipoprotein B (apoB). Variance components software was used to estimate genetic and environmental influences on serum lipid levels in premenopausal and postmenopausal women. Total variance was higher for triglycerides, HDL, and apoB after menopause. Postmenopausal women showed larger genetic variance for most lipids, apart from apoB and Lp(a). In premenopausal females, total cholesterol, LDL, HDL, apoA1, and apoB all showed an influence of the shared environment (22% to 34%), which, after menopause, decreased in HDL and completely disappeared in total cholesterol, LDL, and apoA1. Only for Lp(a), with a high heritability of 87%, did the same model fit premenopausal and postmenopausal women. Generally, there was no indication that different genes influence lipids before and after menopause. CONCLUSIONS: These findings imply that genetic studies of lipids can pool results from premenopausal and postmenopausal women and that family-based interventions, such as changes in diet, are more likely to succeed in younger women, in whom the environmental influences are greater.

PGC-1alpha genotype modifies the association of volitional energy expenditure with [OV0312]O2max.

UNLABELLED: Sedentary lifestyles are increasingly common and result in low cardiorespiratory fitness ([OV0312]O2max), a well-established predictor of early mortality and coronary heart disease (CHD). Adaptation in [OV0312]O2max after exercise training varies considerably between people. Because there are hereditary components to fitness, it is likely that genetic factors explain some of this variability. PPARGC1 (PGC-1alpha) coactivates genes involved in energy transduction and mitochondrial biogenesis. Transgenic mouse data demonstrate that overexpression of PGC-1alpha mRNA increases endurance capacity by transformation of nonoxidative to oxidative skeletal muscle tissue. Other murine studies demonstrate that exercise increases PGC-1alpha mRNA expression. PURPOSE: To explore whether a candidate polymorphism in the PGC-1alpha gene modifies the association between physical activity energy expenditure (PAEE) and predicted [OV0312]O2max ([OV0312]O2max.pred). METHOD: We examined whether the Gly482Ser polymorphism of PGC-1alpha modified the relationship between objectively measured PAEE and [OV0312]O2max.pred in a population-based sample of 599 healthy middle-aged people. PAEE was assessed using individual calibration with 4 d of heart rate monitoring. [OV0312]O2max.pred was measured during a submaximal exercise stress test on a bicycle ergometer. RESULTS: Homozygosity at the Ser482 allele was found in 12.7% of the cohort, whereas 38.9% and 48.4% carried the Gly482Gly and Gly482Ser genotypes, respectively. The association between PAEE and [OV0312]O2max.pred (mL x kg(-1) x min(-1)) was strongest in people homozygous for the Ser482 allele (beta = 12.03; P < 0.00001) compared with carriers of the Gly allele (beta = 5.61; P < 0.00001). In a recessive model for the Ser482 allele, the interaction between PAEE and genotype on [OV0312]O2max.pred (L x min(-1)) was highly significant (P = 0.009). CONCLUSION: Our results indicate that Ser482 homozygotes may be most capable of improving cardiorespiratory fitness when physically active, and that Gly482Ser may explain some of the between-person variance previously reported in cardiorespiratory adaptation after exercise training.

Genome-wide association analyses identify 18 new loci associated with serum urate concentrations.

Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.

Evidence of differential allelic effects between adolescents and adults for plasma high-density lipoprotein.

A recent meta-analysis of genome-wide association (GWA) studies identified 95 loci that influence lipid traits in the adult population and found that collectively these explained about 25-30% of heritability for each trait. Little is known about how these loci affect lipid levels in early life, but there is evidence that genetic effects on HDL- and LDL-cholesterol (HDL-C, LDL-C) and triglycerides vary with age. We studied Australian adults (N = 10,151) and adolescents (N = 2,363) who participated in twin and family studies and for whom we have lipid phenotypes and genotype information for 91 of the 95 genetic variants. Heterogeneity tests between effect sizes in adult and adolescent cohorts showed an excess of heterogeneity for HDL-C (p(Het)<0.05 at 5 out of 37 loci), but no more than expected by chance for LDL-C (1 out of 14 loci), or trigycerides (0 out 24). There were 2 (out of 5) with opposite direction of effect in adolescents compared to adults for HDL-C, but none for LDL-C. The biggest difference in effect size was for LDL-C at rs6511720 near LDLR, adolescents (0.021 ± 0.033 mmol/L) and adults (0.157 ± 0.023 mmol/L), p(Het) = 0.013; followed by ZNF664 (p(Het) = 0.018) and PABPC4 (p(Het) = 0.034) for HDL-C. Our findings suggest that some of the previously identified variants associate differently with lipid traits in adolescents compared to adults, either because of developmental changes or because of greater interactions with environmental differences in adults.

Common variants in TMPRSS6 are associated with iron status and erythrocyte volume.

We report a genome-wide association study to iron status. We identify an association of SNPs in TPMRSS6 to serum iron (rs855791, combined P = 1.5 x 10(-20)), transferrin saturation (combined P = 2.2 x 10(-23)) and erythrocyte mean cell volume (MCV, combined P = 1.1 x 10(-10)). We also find suggestive evidence of association with blood hemoglobin levels (combined P = 5.3 x 10(-7)). These findings demonstrate the involvement of TMPRSS6 in control of iron homeostasis and in normal erythropoiesis.

Association between physical activity and blood pressure is modified by variants in the G-protein coupled receptor 10.

Hypertension is strongly related to cardiovascular disease and all-cause mortality. Exercise reduces blood pressure but the response varies between individuals. The mechanisms by which physical activity energy expenditure (PAEE) modifies blood pressure are not fully defined but include modulation of sympathetic tone. Novel polymorphisms in the G-protein coupled receptor (GPR10) have been linked with high blood pressure. GPR10 may mediate the relationship between PAEE and blood pressure via central nervous mechanisms. We examined whether two GPR10 polymorphisms (G-62A and C914T) modify the association between PAEE and blood pressure in the MRC Ely study (N=687). When stratified by the C914T genotype, there were between-group differences for body mass index (BMI) (P=0.05), diastolic blood pressure (DBP) (P=0.006), and systolic blood pressure (SBP) (P=0.005). No differences were found between G-62A genotypes. The previously reported inverse relationship between PAEE and blood pressure was not observed in minor allele carriers for either polymorphism (A62 carriers: DBP beta-1.11, P=0.52; SBP beta-1.66, P=0.52. T914 carriers: SBP beta=3.27; P=0.60) but was in common allele homozygotes (G62G: DBP beta-6.18 P=0.00001; SBP beta-8.54 P=0.0001. C914C: SBP beta-7.07; P=0.00001). This corresponded to a significant interaction between PAEE and GPR10 polymorphisms on DBP (G-62A: P=0.006) and SBP (G-62A: P=0.008. C914T: P=0.068). Significant interactions were observed between haplotype (derived from G-62A and C914T), PAEE, and blood pressure (DBP: P=0.08; SBP: P=0.023). The effect of physical activity on blood pressure is highly variable at population level. Knowledge of GPR10 genotype may define those who are least likely to benefit from physical activity. These findings may have relevance in the targeted treatment of hypertensive disease.