1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

HapMap imputed genome-wide association studies (GWAS) have revealed > 50 loci at which common variants with minor allele frequency > 5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 x 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until wholegenome sequencing becomes feasible in large samples

Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men for six ectopic fat traits in European, African, Hispanic, and Chinese ancestry populations, with and without sex stratification. In total, 7 new loci were identified in association with ectopic fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; PATXN1 and UBE2E2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting a physiological role for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes impact adipocyte biology and how their perturbations contribute to systemic metabolic disease

a mixed-method approach

Background Sedentary behaviours (SB) can be characterized by low energy expenditure in a reclining position (e.g., sitting) often associated with work and transport. Prolonged SB is associated with increased risk for chronic conditions, and due to technological advances, the working population is in office settings with high occupational exposure to SB. This study aims to assess SB among office workers, as well as barriers and strategies towards reducing SB in the work setting. Methods Using a mixed-methods approach guided by the socio-ecological framework, non-academic office workers from a professional school in a large public university were recruited. Of 180 eligible office workers, 40 enrolled and completed all assessments. Self- reported and objectively measured SB and activity levels were captured. Focus group discussion (FGD) were conducted to further understand perceptions, barriers, and strategies to reducing workplace SB. Environmental factors were systematically evaluated by trained research staff using an adapted version of the Checklist for Health Promotion Environments at Worksites (CHEW). Thematic analysis of FGD was conducted and descriptive analysis of quantitative data was performed. Results The sample was mostly Chinese (n = 33, 80 %) with a total of 24 (60 %) female participants. Most participants worked five days a week for about 9.5(0.5) hrs/day. Accelerometer data show that participants spend the majority of their days in sedentary activities both on workdays (76.9 %) and non-workdays (69.5 %). Self-report data confirm these findings with median sitting time of 420(180) minutes at work. From qualitative analyses, major barriers to reducing SB emerged, including the following themes: workplace social and cultural norms, personal factors, job scope, and physical building/office infrastructure. CHEW results confirm a lack of support from the physical infrastructure and information environment to reducing SB. Conclusions There is high SB among office workers in this sample. We identified multiple levels of influence for prolonged occupational SB, with a particular emphasis on workplace norms and infrastructure as important barriers to reducing SB and increasing PA. A larger, representative sample of the Singaporean population is needed to confirm our findings but it seems that any intervention aimed at reducing SB in the workplace should target individual, environmental, and organizational levels

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain \u3e99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies

Objective: To examine the interactions between genetic predisposition and consumption of fried food in relation to body mass index (BMI) and obesity. Design: Prospective cohort study. Setting: Health professionals in the United States. Participants: 9623 women from the Nurses’ Health Study, 6379 men from the Health Professionals Follow-up Study, and a replication cohort of 21 421 women from the Women’s Genome Health Study. Main outcome measure Repeated measurement of BMI over follow-up. Results: There was an interaction between fried food consumption and a genetic risk score based on 32 BMI-associated variants on BMI in both the Nurses’ Health Study and Health Professionals Follow-up Study (P≤0.001 for interaction). Among participants in the highest third of the genetic risk score, the differences in BMI between individuals who consumed fried foods four or more times a week and those who consumed fried foods less than once a week amounted to 1.0 (SE 0.2) in women and 0.7 (SE 0.2) in men, whereas the corresponding differences were 0.5 (SE 0.2) and 0.4 (SE 0.2) in the lowest third of the genetic risk score. The gene-diet interaction was replicated in the Women’s Genome Health Study (P<0.001 for interaction). Viewed differently, the genetic association with adiposity was strengthened with higher consumption of fried foods. In the combined three cohorts, the differences in BMI per 10 risk alleles were 1.1 (SE 0.2), 1.6 (SE 0.3), and 2.2 (SE 0.6) for fried food consumption less than once, one to three times, and four or more times a week (P<0.001 for interaction); and the odds ratios (95% confidence intervals) for obesity per 10 risk alleles were 1.61 (1.40 to 1.87), 2.12 (1.73 to 2.59), and 2.72 (2.12 to 3.48) across the three categories of consumption (P=0.002 for interaction). In addition, the variants in or near genes highly expressed or known to act in the central nervous system showed significant interactions with fried food consumption, with the FTO (fat mass and obesity associated) variant showing the strongest result (P<0.001 for interaction). Conclusion: Our findings suggest that consumption of fried food could interact with genetic background in relation to obesity, highlighting the particular importance of reducing fried food consumption in individuals genetically predisposed to obesity

Atherogenic Lipoprotein Determinants of Cardiovascular Disease and Residual Risk Among Individuals With Low Low‐Density Lipoprotein Cholesterol

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

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

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF &lt;5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study.

Epigenetic changes may contribute substantially to risks of diseases of aging. Previous studies reported seven methylation variable positions (MVPs) robustly associated with incident type 2 diabetes mellitus (T2DM). However, their causal roles in T2DM are unclear. In an incident T2DM case-cohort study nested within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort, we used whole blood DNA collected at baseline, up to 11 years before T2DM onset, to investigate the role of methylation in the etiology of T2DM. We identified 15 novel MVPs with robust associations with incident T2DM and robustly confirmed three MVPs identified previously (near to TXNIP, ABCG1, and SREBF1). All 18 MVPs showed directionally consistent associations with incident and prevalent T2DM in independent studies. Further conditional analyses suggested that the identified epigenetic signals appear related to T2DM via glucose and obesity-related pathways acting before the collection of baseline samples. We integrated genome-wide genetic data to identify methylation-associated quantitative trait loci robustly associated with 16 of the 18 MVPs and found one MVP, cg00574958 at CPT1A, with a possible direct causal role in T2DM. None of the implicated genes were previously highlighted by genetic association studies, suggesting that DNA methylation studies may reveal novel biological mechanisms involved in tissue responses to glycemia