Person:

Mora, Samia

Objective: Variation in the fat mass and obesity-associated (FTO) gene is associated with obesity. The extent to which separate and combined effects of physical activity and caloric intake modify this association remains unclear. Research Design and Methods: FTO polymorphism rs8050136 was measured, and physical activity, caloric intake, and anthropometrics were self-reported in 21,675 apparently healthy Caucasian women. Results: The effect of the risk allele (A) on BMI was larger among inactive or higher intake women, with additive effects of inactivity and high intake on the associated genetic risk. Specifically, each A allele was associated with mean BMI difference of +0.73 (SE 0.08) kg/m(^2) among inactive women ((\leq)median, 8.8 MET-hours/week), compared with +0.31 (0.06) kg/m(^2), P < 0.0001, among active women (>8.8 MET-hours/week). Similarly, each A allele was associated with mean BMI difference of +0.65 (0.07) among high intake women (>median, 1,679 kcals/day), compared with +0.38 (0.07) kg/m(^2), P = 0.005, among low intake women ((\leq)1,679 kcals/day). Among inactive/high intake women, each A allele was associated with mean BMI difference of +0.97 (0.11) kg/m(^2) vs. +0.22 (0.08) kg/m(^2) among inactive/low intake women, P < 0.0001. Among inactive/high intake women, each A allele carried increased risk of obesity (odds ratio 1.39, 95% CI 1.27–1.52) and diabetes (odds ratio 1.36, 95% CI 1.07–1.73). Conclusions: In this study, lifestyle factors modified the genetic risk of FTO on obesity phenotypes, particularly among women who were both inactive and had high intake. Healthier lifestyle patterns blunted but did not completely eliminate the associated genetic risk.

Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

We conducted a genome-wide association analysis of 7 subfractions of low density lipoproteins (LDLs) and 3 subfractions of intermediate density lipoproteins (IDLs) measured by gradient gel electrophoresis, and their response to statin treatment, in 1868 individuals of European ancestry from the Pharmacogenomics and Risk of Cardiovascular Disease study. Our analyses identified four previously-implicated loci (SORT1, APOE, LPA, and CETP) as containing variants that are very strongly associated with lipoprotein subfractions (log10Bayes Factor > 15). Subsequent conditional analyses suggest that three of these (APOE, LPA and CETP) likely harbor multiple independently associated SNPs. Further, while different variants typically showed different characteristic patterns of association with combinations of subfractions, the two SNPs in CETP show strikingly similar patterns - both in our original data and in a replication cohort - consistent with a common underlying molecular mechanism. Notably, the CETP variants are very strongly associated with LDL subfractions, despite showing no association with total LDLs in our study, illustrating the potential value of the more detailed phenotypic measurements. In contrast with these strong subfraction associations, genetic association analysis of subfraction response to statins showed much weaker signals (none exceeding log10Bayes Factor of 6). However, two SNPs (in APOE and LPA) previously-reported to be associated with LDL statin response do show some modest evidence for association in our data, and the subfraction response proles at the LPA SNP are consistent with the LPA association, with response likely being due primarily to resistance of Lp(a) particles to statin therapy. An additional important feature of our analysis is that, unlike most previous analyses of multiple related phenotypes, we analyzed the subfractions jointly, rather than one at a time. Comparisons of our multivariate analyses with standard univariate analyses demonstrate that multivariate analyses can substantially increase power to detect associations. Software implementing our multivariate analysis methods is available at http://stephenslab.uchicago.edu/software.html.

Background: Levels of LDL (low‐density lipoprotein) cholesterol in the population are declining, and increasing attention is being focused on residual lipid‐related pathways of atherosclerotic cardiovascular disease risk beyond LDL cholesterol. Among individuals with low (<130 mg/dL) LDL cholesterol, we undertook detailed profiling of circulating atherogenic lipoproteins in relation to incident cardiovascular disease in 2 populations. Methods and Results: We performed proton nuclear magnetic resonance spectroscopy to quantify concentrations of LDL and VLDL (very low‐density lipoprotein) particle subclasses in 11 984 JUPITER trial participants (NCT00239681). Adjusted Cox models examined cardiovascular disease risk associated with lipoprotein measures according to treatment allocation. Risk (adjusted hazard ratio [95%CI] per SD increment) among placebo‐allocated participants was associated with total LDL particles (1.19 [1.02, 1.38]) and total VLDL particles (1.21 [1.04, 1.41]), as well as apolipoprotein B, non–high‐density lipoprotein cholesterol, and triglycerides, but not LDL‐c. Rosuvastatin reduced LDL measures but had variable effects on triglyceride and VLDL measures. On‐statin levels of the smallest VLDL particle subclass were associated with a 68% per‐SD (adjusted hazard ratio 1.68 [1.28, 2.22]) increase in residual risk—this risk was related to VLDL cholesterol and not triglyceride or larger VLDL particles. There was evidence that residual risk prediction during statin therapy could be significantly improved through the inclusion of key VLDL measures (Harrell C‐index 0.780 versus 0.712; P<0.0001). In an independent, prospective cohort of 4721 individuals referred for cardiac catheterization (CATHGEN), similar patterns of lipoprotein‐related risk were observed. Conclusions: Atherogenic lipoprotein particle concentrations were associated with cardiovascular disease risk when LDL cholesterol was low. VLDL lipoproteins, particularly the smallest remnant subclass, may represent unused targets for risk prediction and potential therapeutic intervention for reducing residual risk. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681.

Background: It is uncertain whether pharmacological reductions in very‐low‐density lipoproteins (VLDLs), and their component triglyceride and cholesterol could reduce residual risk of atherosclerotic cardiovascular disease (ASCVD) events among individuals in whom low‐density lipoprotein cholesterol (LDL‐C) has been adequately lowered. We examined whether individuals with greater on‐statin reductions in VLDL‐related measures—beyond reductions in LDL‐C—were at further reduced risk of ASCVD. Methods and Results: In 9423 participants in the JUPITER (Justification for the Use of Statins in Prevention) trial (NCT00239681), at baseline and on statin we measured standard lipids, 400‐MHz proton nuclear magnetic resonance spectroscopy‐measured VLDL particle subclasses (small, medium, and large VLDL lipoprotein particle concentration), and total VLDL cholesterol mass. Compared with individuals allocated to placebo, we examined risk of incident ASCVD (N=211) among statin‐allocated participants who achieved minimal (<median) or greater (≥median) marker reductions using adjusted Cox models. On‐statin changes in VLDL‐related markers were only modestly correlated (Spearman r≤0.29) with change in LDL‐C. On‐statin median LDL‐C was 54 mg/dL and triglyceride was 101 mg/dL. Dose‐response reductions in ASCVD risk were observed for greater reductions in LDL‐C, VLDL cholesterol mass, and small VLDL lipoprotein particle concentration; the latter 2 remained significant after incremental adjustment for change in LDL‐C (P≤0.006). Conversely, there was no further risk reduction with greater reductions in triglycerides or large/medium VLDL lipoprotein particle concentration. Conclusions: Pharmacological reduction in small, cholesterol‐enriched, triglyceride‐depleted VLDL was associated with reduction in ASCVD risk. Chemically measured triglycerides may not sufficiently capture risk related to VLDL pathways. These findings also support broader profiling of lipid and lipoprotein changes in response to statins as prognostic markers of individual benefit, supporting more precision‐medicine, individualized approaches to cardiovascular risk reduction. Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT00239681.