Genetic Determinants of Dyslipidemia

Dyslipidemia is a chronic deviation from normal blood lipid levels that can lead to atherosclerosis and other cardiovascular diseases; dyslipidemia and its sequelae are caused by the complex interplay of genetic and environmental factors. Although circulating concentrations of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (LDL-C) have a strong genetic underpinning, not much is known about the genetic factors that affect long-term deteriorations in lipid concentrations. Through the work described in this thesis I sought to identify novel genetic loci associated with long-term lipid level changes and identify gene × environment interactions influencing blood lipid and lipoprotein concentrations.In Papers I and II, large European prospective cohort studies with long-term follow-up were analyzed. The Gene–Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk (GLACIER) Study (N=3,495) was analyzed in the discovery phase of these studies. The MDC, PIVUS, ULSAM and MRC Ely studies (Nmax=8,263) were utilized as replication cohorts. In Paper III, Scandinavian adults from the GLACIER, MDC, Inter99 and Health 2006 Studies were meta-analyzed (Nmax=18,190). In Paper IV, analyses were conducted in the Diabetes Prevention Program (DPP) (N=2,993) multi-ethnic randomized clinical trial. Participants from the GLACIER Study and DPP, the two discovery studies intensively used in this thesis, were genotyped with the Illumina CardioMetaboChip array.In Paper I, TC- and TG-specific genetic risk scores (GRSs) were robustly associated with TC- and TG level changes, respectively. Three genomic loci, APOE, TRIB1 and APOA1 were associated with either TC- or TG changes and were replicated in subsequent analyses. In Paper II, in addition to the findings of Paper I, seven further loci were associated with TC- or TG changes. Of these, variants at CAPN3, HPR and SIX5 showed suggestive evidence for association with coronary artery disease. In Paper III, a robust sex-heterogeneous interaction between the TG-related GRS and body mass index was observed for circulating blood TG levels. In Paper IV, an interaction between the large HDL particle-associated GRS and the lifestyle intervention for large HDL particle concentrations was observed.In conclusion, this thesis work shows genetic associations for long-term lipid changes and demonstrates examples of gene × environment interactions that influence blood lipid concentrations

Smoking Status, Snus Use, and Variation at the CHRNA5-CHRNA3-CHRNB4 Locus in Relation to Obesity: The GLACIER Study

A genetic variant within the CHRNA5-CHRNA3-CHRNB4 region (rs1051730), previously associated with smoking quantity, was recently shown to interact with smoking on obesity predisposition. We attempted to replicate this finding in the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk (GLACIER) Study, a prospective cohort study of adults from northern Sweden (n = 16,426). We also investigated whether a similar interaction is apparent between rs1051730 and snus, a type of moist oral tobacco, to determine whether this interaction is driven by factors that cigarettes and snus have in common, such as nicotine. Main effects of smoking, snus, and the rs1051730 variant and pairwise interaction terms (smoking x rs1051730 and snus x rs1051730) were tested in relation to body mass index (BMI; calculated as weight (kg)/height (m)(2)) through the use of multivariate linear models adjusted for age and sex. Smoking status and BMI were inversely related (beta = -0.46 kg/m(2), standard error (SE) = 0.08; P 0.05); the T allele was associated with lower BMI in the overall cohort (beta = -0.10 kg/m(2), SE = 0.05; P = 0.03) and with smoking quantity in those in whom this was measured (n = 5,304) (beta = 0.08, SE = 0.01; P < 0.0001). Neither smoking status (P-interaction = 0.29) nor snus use (P-interaction = 0.89) modified the association between the rs1051730 variant and BMI

Genetic Determinants of Long-Term Changes in Blood Lipid Concentrations: 10-Year Follow-Up of the GLACIER Study

Recent genome-wide meta-analyses identified 157 loci associated with cross-sectional lipid traits. Here we tested whether these loci associate (singly and in trait-specific genetic risk scores [GRS]) with longitudinal changes in total cholesterol (TC) and triglyceride (TG) levels in a population-based prospective cohort from Northern Sweden (the GLACIER Study). We sought replication in a southern Swedish cohort (the MDC Study; N = 2,943). GLACIER Study participants (N = 6,064) were genotyped with the MetaboChip array. Up to 3,495 participants had 10-yr follow-up data available in the GLACIER Study. The TC- and TG-specific GRSs were strongly associated with change in lipid levels (β = 0.02 mmol/l per effect allele per decade follow-up, P = 2.0×10−11 for TC; β = 0.02 mmol/l per effect allele per decade follow-up, P = 5.0×10−5 for TG). In individual SNP analysis, one TC locus, apolipoprotein E (APOE) rs4420638 (β = 0.12 mmol/l per effect allele per decade follow-up, P = 2.0×10−5), and two TG loci, tribbles pseudokinase 1 (TRIB1) rs2954029 (β = 0.09 mmol/l per effect allele per decade follow-up, P = 5.1×10−4) and apolipoprotein A-I (APOA1) rs6589564 (β = 0.31 mmol/l per effect allele per decade follow-up, P = 1.4×10−8), remained significantly associated with longitudinal changes for the respective traits after correction for multiple testing. An additional 12 loci were nominally associated with TC or TG changes. In replication analyses, the APOE rs4420638, TRIB1 rs2954029, and APOA1 rs6589564 associations were confirmed (P≤0.001). In summary, trait-specific GRSs are robustly associated with 10-yr changes in lipid levels and three individual SNPs were strongly associated with 10-yr changes in lipid levels

Housing environment and mental health of Europeans during the COVID-19 pandemic: a cross-country comparison

Many studies have investigated the impact of the COVID-19 pandemic on mental health. Throughout the pandemic, time spent at home increased to a great extent due to restrictive measures. Here we set out to investigate the relationship between housing conditions and the mental health of populations across European countries. We analyzed survey data collected during spring 2020 from 69,136 individuals from four cohorts from Denmark, France, and the UK. The investigated housing conditions included household density, composition, and crowding, access to outdoor facilities, dwelling type, and urbanicity. The outcomes were loneliness, anxiety, and life satisfaction. Logistic regression models were used, and results were pooled using random-effects meta-analysis. In the meta-analysis, living alone was associated with higher levels of loneliness (OR = 3.08, 95% CI 1.87–5.07), and lower life satisfaction (OR = 1.27, 95% CI 1.05–0.55), compared to living with others. Not having access to an outdoor space and household crowding were suggestively associated with worse outcomes. Living in crowded households, living alone, or lacking access to outdoor facilities may be particularly important in contributing to poor mental health during a lockdown. Addressing the observed fundamental issues related to housing conditions within society will likely have positive effects in reducing social inequalities, as well as improving preparedness for future pandemics

Comprehensive Analysis of Established Dyslipidemia-Associated Loci in the Diabetes Prevention Program

Background-We assessed whether 234 established dyslipidemia-associated loci modify the effects of metformin treatment and lifestyle intervention (versus placebo control) on lipid and lipid subfraction levels in the Diabetes Prevention Program randomized controlled trial. Methods and Results-We tested gene treatment interactions in relation to baseline-adjusted follow-up blood lipid concentrations (high-density lipoprotein [HDL] and low-density lipoprotein-cholesterol, total cholesterol, and triglycerides) and lipoprotein subfraction particle concentrations and size in 2993 participants with pre-diabetes. Of the previously reported single-nucleotide polymorphism associations, 32.5% replicated at PP>1.1×10-16) with their respective baseline traits for all but 2 traits. Lifestyle modified the effect of the genetic risk score for large HDL particle numbers, such that each risk allele of the genetic risk scores was associated with lower concentrations of large HDL particles at follow-up in the lifestyle arm (β=-0.11 μmol/L per genetic risk scores risk allele; 95% confidence interval,-0.188 to-0.033; P=5×10-3; Pinteraction=1×10-3 for lifestyle versus placebo), but not in the metformin or placebo arms (P>0.05). In the lifestyle arm, participants with high genetic risk had more favorable or similar trait levels at 1-year compared with participants at lower genetic risk at baseline for 17 of the 20 traits. Conclusions-Improvements in large HDL particle concentrations conferred by lifestyle may be diminished by genetic factors. Lifestyle intervention, however, was successful in offsetting unfavorable genetic loading for most lipid traits. Clinical Trial Registration-URL: https://www.clinicaltrials.gov. Unique Identifier: NCT00004992

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179