Discovery and refinement of loci associated with lipid levels

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 P<0.05 with baseline lipid traits. Trait-specific genetic risk scores were robustly associated (3×10^-4>P>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; P_interaction=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.

Associations of genetic variants for adult lipid levels with lipid levels in children. The Generation R Study

Lipid concentrations are heritable traits. Recently, the number of known genetic loci associated with lipid levels in adults increased from 95 to 157. The effects of these 157 loci have not been tested in children. Considering that lipid levels track from childhood to adulthood, we studied to determine whether these variants already affected lipid concentrations in a large group of 2,645 children with a median age of 6.0 years (95% range 5.7-7.3 years) from the population-based Generation R Study. Twenty-eight SNPs associated with TGs, 39 SNPs associated with total cholesterol (TC), 28 SNPs associated with LDL cholesterol (LDL-C), and 56 SNPs associated with HDL cholesterol (HDL-C) were analyzed individually and combined into genetic risk scores (GRSs). All risk scores were associated with their specific outcomes. The differences in mean absolute lipid and lipoprotein values between the 10% of children with the highest lipid or lipoprotein GRS versus the 10% with the lowest score were 0.28, 0.25, 0.32, and 0.30 mmol/l for TGs, TC, LDL-C, and HDL-C, respectively. In conclusion, we show for the first time that GRSs based on 157 SNPs associated with adult lipid concentrations are associated with lipid levels in children. The genetic background of these phenotypes at least partly overlaps between children and adults.

Genetic variants in CETP increase risk of intracerebral hemorrhage

Objective

In observational epidemiologic studies, higher plasma high‐density lipoprotein cholesterol (HDL‐C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL‐C; as such, medicines that inhibit CETP and raise HDL‐C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL‐C also increase risk for ICH.

Methods

We performed 2 candidate‐gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL‐C as well as ICH risk.

Results

Twelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10⁻⁴) with no heterogeneity across studies (I² = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL‐C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10⁻⁶).

Interpretation

Genetic variants in CETP associated with increased HDL‐C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL‐raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730–740

Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study

Lipid traits (total, low-density and high-density lipoprotein cholesterol, and triglycerides) are risk factors for cardiovascular disease. DNA methylation is not only an inherited but also modifiable epigenetic mark that has been related to cardiovascular risk factors. Our aim was to identify loci showing differential DNA methylation related to serum lipid levels. Blood DNA methylation was assessed using the Illumina Human Methylation 450 BeadChip. A two-stage epigenome-wide association study was performed, with a discovery sample in the REGICOR study (n = 645) and validation in the Framingham Offspring Study (n = 2,542). Fourteen CpG sites located in nine genes (SREBF1, SREBF2, PHOSPHO1, SYNGAP1, ABCG1, CPT1A, MYLIP, TXNIP and SLC7A11) and 2 intergenic regions showed differential methylation in association with lipid traits. Six of these genes and 1 intergenic region were new discoveries showing differential methylation related to total cholesterol (SREBF2), HDL-cholesterol (PHOSPHO1, SYNGAP1 and an intergenic region in chromosome 2) and triglycerides (MYLIP, TXNIP and SLC7A11). These CpGs explained 0.7%, 9.5% and 18.9% of the variability of total cholesterol, HDL cholesterol and triglycerides in the Framingham Offspring Study, respectively. The expression of the genes SREBF2 and SREBF1 was inversely associated with methylation of their corresponding CpGs (P-value = 0.0042 and 0.0045, respectively) in participants of the GOLDN study (n = 98). In turn, SREBF1 expression was directly associated with HDL cholesterol (P-value = 0.0429). Genetic variants in SREBF1, PHOSPHO1, ABCG1 and CPT1A were also associated with lipid profile. Further research is warranted to functionally validate these new loci and assess the causality of new and established associations between these differentially methylated loci and lipid metabolism.

Rheumatoid Arthritis and Coronary Artery Disease: Genetic Analyses Do Not Support a Causal Relation

OBJECTIVE

Inflammatory diseases, specifically rheumatoid arthritis (RA), are assumed to increase the risk of coronary artery disease (CAD). More recently, multiple single-nucleotide polymorphisms (SNP) associated with RA risk were identified. If causal mechanisms affecting risks of RA and CAD are overlapping, risk alleles for RA might also increase the risk of CAD.

METHODS

Sixty-one SNP associating with RA in genome-wide significant analyses were tested for association with CAD in CARDIoGRAM (Coronary ARtery DIsease Genome wide Replication and Meta-analysis), a metaanalysis including genome-wide association data (22,233 CAD cases, 64,762 controls). In parallel, a set of SNP being associated with low-density lipoprotein cholesterol (LDL-C) was tested as a positive control.

RESULTS

Twenty-nine RA-associated SNP displayed a directionality-consistent association with CAD (OR range 1.002-1.073), whereas 32 RA-associated SNP were not associated with CAD (OR range 0.96-0.99 per RA risk-increasing allele). The proportion (48%) of directionality-consistent associated SNP equaled the proportion expected by chance (50%, p = 0.09). Of only 5 RA-associated SNP showing p values for CAD < 0.05, 4 loci (C5orf30, IL-6R, PTPN22, and RAD51B) showed directionality-consistent effects on CAD, and 1 (rs10774624, locus SH2B3) reached study-wide significance (p = 7.29E-06). By contrast, and as a proof of concept, 46 (74%) out of 62 LDL-C-associated SNP displayed a directionality-consistent association with CAD, a proportion that was significantly different from 50% (p = 5.9E-05).

CONCLUSION

We found no evidence that RA-associated SNP as a group are associated with CAD. Even though we were not able to study potential effects of all genetic variants individually, shared nongenetic factors may more plausibly explain the observed coincidence of the 2 conditions.

Explicating heterogeneity of complex traits has strong potential for improving GWAS efficiency

Common strategy of genome-wide association studies (GWAS) relying on large samples faces difficulties, which raise concerns that GWAS have exhausted their potential, particularly for complex traits. Here, we examine the efficiency of the traditional sample-size-centered strategy in GWAS of these traits, and its potential for improvement. The paper focuses on the results of the four largest GWAS meta-analyses of body mass index (BMI) and lipids. We show that just increasing sample size may not make p-values of genetic effects in large (N > 100,000) samples smaller but can make them larger. The efficiency of these GWAS, defined as ratio of the log-transformed p-value to the sample size, in larger samples was larger than in smaller samples for a small fraction of loci. These results emphasize the important role of heterogeneity in genetic associations with complex traits such as BMI and lipids. They highlight the substantial potential for improving GWAS by explicating this role (affecting 11–79% of loci in the selected GWAS), especially the effects of biodemographic processes, which are heavily underexplored in current GWAS and which are important sources of heterogeneity in the various study populations. Further progress in this direction is crucial for efficient use of genetic discoveries in health care.

Lipid effects of switching from prescription EPA+DHA (omega-3-acid ethyl esters) to prescription EPA only (icosapent ethyl) in dyslipidemic patients

OBJECTIVES

Residual cardiovascular risk and persistently elevated triglycerides (TGs) may remain despite statin therapy in patients with dyslipidemia. Prescription omega-3 fatty acid formulations containing docosahexaenoic acid (DHA) and/or eicosapentaenoic acid (EPA) have been shown to reduce TGs and may potentially lower residual cardiovascular risk. However, DHA may raise low-density lipoprotein cholesterol (LDL-C) and compromise treatment goals. Icosapent ethyl (Vascepa®), a high-purity prescription EPA formulation, has been shown to lower TGs and other lipid parameters without raising LDL-C. There are no prospective, randomized, controlled trials of the effects of switching patients from omega-3-acid ethyl esters (Lovaza®), a prescription formulation containing EPA+DHA, to icosapent ethyl.

METHODS

This retrospective chart review included records of high-risk patients aged ≥18 years receiving stable statin therapy for dyslipidemia who had been switched from prescription omega-3-acid ethyl esters 4 g/day to prescription icosapent ethyl 4 g/day and had available laboratory lipid profiles after receiving each for ≥2 months. Lipid assessments were conducted by local laboratories. Patient records were excluded if there were changes in medication or health condition that could affect lipid parameters.

RESULTS

The records of 8 patients (6 women and 2 men; 54-83 years) met eligibility criteria. Following the switch to icosapent ethyl, LDL-C changes ranged from +3.2% to -69.1% (reduced in 7 patients), total cholesterol was reduced in all patients (-3.5% to -44.3%), and TG changes ranged from +32.4% to -59.0% (reduced in 6 patients). Decreases or no changes in non-high-density lipoprotein cholesterol were observed; changes in high-density lipoprotein cholesterol varied. No adverse events related to either product were reported.

CONCLUSION

In this real-world retrospective analysis, switching high-risk statin-treated patients from omega-3-acid ethyl esters to icosapent ethyl resulted in favorable lipid changes. The analysis was limited by the small patient numbers, but lipid results were consistent with randomized controlled trials and previous case series.

Higher chylomicron remnants and LDL particle numbers associate with CD36 SNPs and DNA methylation sites that reduce CD36

Cluster of differentiation 36 (CD36) variants influence fasting lipids and risk of metabolic syndrome, but their impact on postprandial lipids, an independent risk factor for cardiovascular disease, is unclear. We determined the effects of SNPs within a ∼410 kb region encompassing CD36 and its proximal and distal promoters on chylomicron (CM) remnants and LDL particles at fasting and at 3.5 and 6 h following a high-fat meal (Genetics of Lipid Lowering Drugs and Diet Network study, n = 1,117). Five promoter variants associated with CMs, four with delayed TG clearance and five with LDL particle number. To assess mechanisms underlying the associations, we queried expression quantitative trait loci, DNA methylation, and ChIP-seq datasets for adipose and heart tissues that function in postprandial lipid clearance. Several SNPs that associated with higher serum lipids correlated with lower adipose and heart CD36 mRNA and aligned to active motifs for PPARγ, a major CD36 regulator. The SNPs also associated with DNA methylation sites that related to reduced CD36 mRNA and higher serum lipids, but mixed-model analyses indicated that the SNPs and methylation independently influence CD36 mRNA. The findings support contributions of CD36 SNPs that reduce adipose and heart CD36 RNA expression to inter-individual variability of postprandial lipid metabolism and document changes in CD36 DNA methylation that influence both CD36 expression and lipids.

Association of KCTD10, MVK, and MMAB polymorphisms with dyslipidemia and coronary heart disease in Han Chinese population

Background

Several genome-wide association studies have discovered novel loci at chromosome 12q24, which includes mevalonate kinase (MVK), methylmalonic aciduria (cobalamin deficiency) cbIB type (MMAB), and potassium channel tetramerization domain-containing 10 (KCTD10), all of which influence HDL-cholesterol concentrations. However, there are few reports on the associations between these polymorphisms and HDL-C concentrations in Chinese population. This study aimed to evaluate the associations between functional polymorphisms in three genes (MVK, MMAB and KCTD10) and HDL-C concentrations, as well as coronary heart disease (CHD) susceptibility in Chinese individuals.

Methods

We systematically selected and genotyped 18 potentially functional polymorphisms in MVK, MMAB and KCTD10 by using the TaqMan OpenArray Genotyping System in a Chinese population including 399 dyslipidemia cases, 697 CHD cases and 465 controls. Multivariate logistic regression analyses were performed to estimate the relationship between the genotypes and dyslipidemia, CHD risk with adjustment of relevant confounders.

Results

Among six polymorphisms showing significant associations with dyslipidemia, the minor alleles of rs11066782 in KCTD10, rs11613718 in KCTD10 and rs11067233 in MMAB were significantly associated with a decreased risk of CHD (additive model: OR = 0.71, 95 % CI = 0.53–0.97, P = 0.029 for rs11066782; OR = 0.73, 95 % CI = 0.54–0.99, P = 0.044 for rs11613718 and OR = 0.57, 95 % CI = 0.40–0.80, P = 0.001 for rs11067233). Further combined analysis showed that individuals carrying “3-4” favorable alleles presented a 62 % (OR = 0.38, 95 % CI = 0.21–0.66) decreased risk of CHD compared with those carrying “0–2” favorable alleles.

Conclusions

These findings suggest that rs11066782 in KCTD10, rs11613718 in KCTD10 and rs11067233 in MMAB may contribute to the susceptibility of CHD by altering plasma HDL-C levels in Han Chinese.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-016-0348-7) contains supplementary material, which is available to authorized users.

Association Between Low-Density Lipoprotein Cholesterol-Lowering Genetic Variants and Risk of Type 2 Diabetes: A Meta-analysis

Importance

Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes.

Objective

To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes.

Design, Setting, and Participants

The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016.

Exposures

Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR.

Main Outcomes and Measures

Odds ratios (ORs) for type 2 diabetes and coronary artery disease.

Results

Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95% CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95% CI, 1.70-3.43]; P < .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95% CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0% for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles.

Conclusions and Relevance

In this meta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other genes was associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication. We identified 30 new blood pressure- or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.

Genetic Correlation Analysis Suggests Association between Increased Self-Reported Sleep Duration in Adults and Schizophrenia and Type 2 Diabetes

STUDY OBJECTIVES

We sought to examine how much of the heritability of self-report sleep duration is tagged by common genetic variation in populations of European ancestry and to test if the common variants contributing to sleep duration are also associated with other diseases and traits.

METHODS

We utilized linkage disequilibrium (LD)-score regression to estimate the heritability tagged by common single nucleotide polymorphisms (SNPs) in the CHARGE consortium genome-wide association study (GWAS) of self-report sleep duration. We also used bivariate LD-score regression to investigate the genetic correlation of sleep duration with other publicly available GWAS datasets.

RESULTS

We show that 6% (SE = 1%) of the variance in self-report sleep duration in the CHARGE study is tagged by common SNPs in European populations. Furthermore, we find evidence of a positive genetic correlation (rG) between sleep duration and type 2 diabetes (rG = 0.26, P = 0.02), and between sleep duration and schizophrenia (rG = 0.19, P = 0.01).

CONCLUSIONS

Our results show that increased sample sizes will identify more common variants for self-report sleep duration; however, the heritability tagged is small when compared to other traits and diseases. These results also suggest that those who carry variants that increase risk to type 2 diabetes and schizophrenia are more likely to report longer sleep duration.

Epigenetics of Lipid Phenotypes

Dyslipidemia is a well-established risk factor for cardiovascular disease, the main cause of death worldwide. Blood lipid profiles are patterned by both genetic and environmental factors. In recent years, epigenetics has emerged as a paradigm that unifies these influences. In this review, we have summarized the latest evidence implicating epigenetic mechanisms-DNA methylation, histone modification, and regulation by RNAs-in lipid homeostasis. Key findings have emerged in a number of novel epigenetic loci located in biologically plausible genes (e.g. CPT1A, ABCG1, SREBF1, and others), as well as microRNA-33a/b. Evidence from animal and cell culture models suggests a complex interplay between different classes of epigenetic processes in the lipid-related genomic regions. While epigenetic findings hold the potential to explain the interindividual variability in lipid profiles as well as the underlying mechanisms, they have yet to be translated into effective therapies for dyslipidemia.

Notch, lipids, and endothelial cells

PURPOSE OF REVIEW

Notch signaling is an evolutionary conserved pathway critical for cardiovascular development and angiogenesis. More recently, the contribution of Notch signaling to the homeostasis of the adult vasculature has emerged as an important novel paradigm, but much remains to be understood.

RECENT FINDINGS

Recent findings shed light on the impact of Notch in vascular and immune responses to microenvironmental signals as well as on the onset of atherosclerosis. In the past year, studies in human and mice explored the role of Notch in the maintenance of a nonactivated endothelium. Novel pieces of evidence suggest that this pathway is sensitive to environmental factors, including inflammatory mediators and diet-derived by-products.

SUMMARY

An emerging theme is the ability of Notch to respond to changes in the microenvironment, including glucose and lipid metabolites. In turn, alterations in Notch enable an important link between metabolism and transcriptional changes, thus this receptor appears to function as a metabolic sensor with direct implications to gene expression.

Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes

AIMS/HYPOTHESIS

Identification of novel biomarkers for type 2 diabetes and their genetic determinants could lead to improved understanding of causal pathways and improve risk prediction.

METHODS

In this study, we used data from non-targeted metabolomics performed using liquid chromatography coupled with tandem mass spectrometry in three Swedish cohorts (Uppsala Longitudinal Study of Adult Men [ULSAM], n = 1138; Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS], n = 970; TwinGene, n = 1630). Metabolites associated with impaired fasting glucose (IFG) and/or prevalent type 2 diabetes were assessed for associations with incident type 2 diabetes in the three cohorts followed by replication attempts in the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort (n = 855). Assessment of the association of metabolite-regulating genetic variants with type 2 diabetes was done using data from a meta-analysis of genome-wide association studies.

RESULTS

Out of 5961 investigated metabolic features, 1120 were associated with prevalent type 2 diabetes and IFG and 70 were annotated to metabolites and replicated in the three cohorts. Fifteen metabolites were associated with incident type 2 diabetes in the four cohorts combined (358 events) following adjustment for age, sex, BMI, waist circumference and fasting glucose. Novel findings included associations of higher values of the bile acid deoxycholic acid and monoacylglyceride 18:2 and lower concentrations of cortisol with type 2 diabetes risk. However, adding metabolites to an existing risk score improved model fit only marginally. A genetic variant within the CYP7A1 locus, encoding the rate-limiting enzyme in bile acid synthesis, was found to be associated with lower concentrations of deoxycholic acid, higher concentrations of LDL-cholesterol and lower type 2 diabetes risk. Variants in or near SGPP1, GCKR and FADS1/2 were associated with diabetes-associated phospholipids and type 2 diabetes.

CONCLUSIONS/INTERPRETATION

We found evidence that the metabolism of bile acids and phospholipids shares some common genetic origin with type 2 diabetes.

ACCESS TO RESEARCH MATERIALS

Metabolomics data have been deposited in the Metabolights database, with accession numbers MTBLS93 (TwinGene), MTBLS124 (ULSAM) and MTBLS90 (PIVUS).

Lipidomic analyses in epidemiology

Clinical lipid measurements have been the mainstay of risk assessment for chronic disease since the Framingham study commenced over 60 years ago. Thousands of subsequent epidemiological studies have provided much insight into the relationship between plasma lipid profiles, health and disease. However, the human lipidome consists of thousands of individual lipid species, and current lipidomic technology presents us with an unprecedented opportunity to measure lipid phenotypes, representing genomic, metabolic, diet and lifestyle-related exposures, in large epidemiological studies. The number of epidemiological studies using lipidomic profiling is increasing and has the potential to provide improved biological and clinical insight into human disease. In this review, we discuss current lipidomic technologies, epidemiological studies using these technologies and the statistical approaches used in the analysis of the resulting data. We highlight the potential of integrating genomic and lipidomic datasets and discuss the future opportunities and challenges in this emerging field.

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Is High-Density Lipoprotein Cholesterol Causally Related to Kidney Function? Evidence From Genetic Epidemiological Studies

Supplemental Digital Content is available in the text.

Objective—

A recent observational study with almost 2 million men reported an association between low high-density lipoprotein (HDL) cholesterol and worse kidney function. The causality of this association would be strongly supported if genetic variants associated with HDL cholesterol were also associated with kidney function.

Approach and Results—

We used 68 genetic variants (single-nucleotide polymorphisms [SNPs]) associated with HDL cholesterol in genome-wide association studies including >188 000 subjects and tested their association with estimated glomerular filtration rate (eGFR) using summary statistics from another genome-wide association studies meta-analysis of kidney function including ≤133 413 subjects. Fourteen of the 68 SNPs (21%) had a P value <0.05 compared with the 5% expected by chance (Binomial test P=5.8×10⁻⁶). After Bonferroni correction, 6 SNPs were still significantly associated with eGFR. The genetic variants with the strongest associations with HDL cholesterol concentrations were not the same as those with the strongest association with kidney function and vice versa. An evaluation of pleiotropy indicated that the effects of the HDL-associated SNPs on eGFR were not mediated by HDL cholesterol. In addition, we performed a Mendelian randomization analysis. This analysis revealed a positive but nonsignificant causal effect of HDL cholesterol–increasing variants on eGFR.

Conclusions—

In summary, our findings indicate that HDL cholesterol does not causally influence eGFR and propose pleiotropic effects on eGFR for some HDL cholesterol–associated SNPs. This may cause the observed association by mechanisms other than the mere HDL cholesterol concentration.

Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance

Background

Genome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Here we perform the first proof of concept viral GWAS examining drug resistance (DR), a phenotype with well understood genetics.

Method

We performed a GWAS of DR in a sample of 343 HIV subtype C patients failing 1^st line antiretroviral treatment in rural KwaZulu-Natal, South Africa. The majority and minority variants within each sequence were called using PILON, and GWAS was performed within PLINK. HIV WGS from patients failing on different antiretroviral treatments were compared to sequences derived from individuals naïve to the respective treatment.

Results

GWAS methodology was validated by identifying five associations on a genetic level that led to amino acid changes known to cause DR. Further, we highlighted the ability of GWAS to identify epistatic effects, identifying two replicable variants within amino acid 68 of the reverse transcriptase protein previously described as potential fitness compensatory mutations. A possible additional DR variant within amino acid 91 of the matrix region of the Gag protein was associated with tenofovir failure, highlighting GWAS’s ability to identify variants outside classical candidate genes. Our results also suggest a polygenic component to DR.

Conclusions

These results validate the applicability of GWAS to HIV WGS data even in relative small samples, and emphasise how high throughput sequencing can provide novel and clinically relevant insights. Further they suggested that for viruses like HIV, population structure was only minor concern compared to that seen in bacteria or parasite GWAS. Given the small genome length and reduced burden for multiple testing, this makes HIV an ideal candidate for GWAS.

Improved methods for multi-trait fine mapping of pleiotropic risk loci

MOTIVATION

Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation.

RESULTS

In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data.

AVAILABILITY AND IMPLEMENTATION

The fastPAINTOR framework is implemented in the PAINTOR v3.0 package which is publicly available to the research community http://bogdan.bioinformatics.ucla.edu/software/paintor CONTACT: gkichaev@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Rooted in risk: genetic predisposition for low-density lipoprotein cholesterol level associates with diminished low-density lipoprotein cholesterol response to statin treatment

AIMS

To utilize previously reported lead SNPs for low-density lipoprotein cholesterol (LDL-c) levels to find additional loci of importance to statin response, and examine whether genetic predisposition to LDL-c levels associates with differential statin response.

METHODS

We investigated effects on statin response of 59 LDL-c SNPs, by combining summary level statistics from the Global Lipids Genetics and Genomic Investigation of Statin Therapy consortia.

RESULTS

Lead SNPs for APOE, SORT1 and NPC1L1 were associated with a decreased LDL-c response to statin treatment, as was overall genetic predisposition for increased LDL-c levels as quantified with 59 SNPs, with a 5.4% smaller statin response per standard deviation increase in genetically raised LDL-c levels.

CONCLUSION

Genetic predisposition for increased LDL-c level may decrease efficacy of statin therapy.

Analysis with the exome array identifies multiple new independent variants in lipid loci

It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.

An APOC3 3'UTR variant associated with plasma triglycerides levels and coronary heart disease by creating a functional miR-4271 binding site

Apolipoprotein C-III (APOC3) is a key regulator of plasma triglycerides levels. Increasing evidence has shown that loss-of-function mutations in APOC3 is associated with reduction in plasma triglycerides levels and will confer a benefit in patients at high risk for cardiovascular disease. However, these favorable mutations were extremely distribution discrepant among different ethnics. In this study, the APOC3 gene was resequenced and we identified a common variant which located in the microRNA-binding site in APOC3 and would affect its expression and the risk of coronary heart disease (CHD). The molecular mechanism was explored. We found that the T allele of rs4225 suppressed APOC3 translation by facilitating miR-4271 binding, but not the G allele. Subjects carrying the GG genotype had higher plasma APOC3 levels (p for trend = 0.03) than those with the TT genotype. Furthermore, the T allele was significantly associated with decreased triglyceride levels [Beta (SE): -0.024 (0.020), P = 0.03]. Finally, the case-control study suggested that the TT genotype resulted in a significant reduction in overall CHD risk [OR, 0.89 (95% confidence interval, 0.77-0.98), P = 0.009]. In conclusion, our results provide evidence that the rs4225 in the 3'-UTR of APOC3 might contribute to the risk of CHD by interfering with miR-4271 binding.

Bias due to participant overlap in two-sample Mendelian randomization

Mendelian randomization analyses are often performed using summarized data. The causal estimate from a one‐sample analysis (in which data are taken from a single data source) with weak instrumental variables is biased in the direction of the observational association between the risk factor and outcome, whereas the estimate from a two‐sample analysis (in which data on the risk factor and outcome are taken from non‐overlapping datasets) is less biased and any bias is in the direction of the null. When using genetic consortia that have partially overlapping sets of participants, the direction and extent of bias are uncertain. In this paper, we perform simulation studies to investigate the magnitude of bias and Type 1 error rate inflation arising from sample overlap. We consider both a continuous outcome and a case‐control setting with a binary outcome. For a continuous outcome, bias due to sample overlap is a linear function of the proportion of overlap between the samples. So, in the case of a null causal effect, if the relative bias of the one‐sample instrumental variable estimate is 10% (corresponding to an F parameter of 10), then the relative bias with 50% sample overlap is 5%, and with 30% sample overlap is 3%. In a case‐control setting, if risk factor measurements are only included for the control participants, unbiased estimates are obtained even in a one‐sample setting. However, if risk factor data on both control and case participants are used, then bias is similar with a binary outcome as with a continuous outcome. Consortia releasing publicly available data on the associations of genetic variants with continuous risk factors should provide estimates that exclude case participants from case‐control samples.

The C1431T polymorphism of peroxisome proliferator activated receptor γ (PPARγ) is associated with low risk of diabetes in a Pakistani cohort

BACKGROUND

Diabetes is a socioeconomic burden in Pakistan. International diabetes federation reported 6.9 million cases of diabetes and 87,548 deaths due to diabetes in Pakistan in 2014. Peroxisome proliferators-activated receptors are transcription factors, regulating several physiological processes.

AIM

The aim of the current study was to determine the prevalence of silent variant C1431T in exon 6 of PPAR-y and analyze its effect on various anthropometric and biochemical parameters in a Pakistani cohort.

METHODS

We collected 926 samples, 500 healthy controls (fasting blood sugar <99 mg/dL, random blood sugar <126 mg/dL) and 426 cases with diabetes (fasting blood sugar >99 mg/dL, random blood sugar >126 mg/dL). The genotyping was done by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) and serum biochemical parameters were determined by commercially available kits.

RESULTS

The genotyping results by RLFP showed allelic frequency C = 61.2 % and T = 38.8 % in controls while C = 74.5 % and T = 25.5 % in cases (OR 0.536, CI 0.439-0.655, p = 8.2 × 10(-10)) and genotypic frequency CC = 38.8 %, CT = 44.7 %, TT = 16.5 % in controls. While CC = 53.6 %, CT = 41.4 %, TT = 5.1 % in cases (OR 0.544, CI 0.408-0.726, p = 2.3 × 10(-10)). The rare T allele appeared to be a protective allele i.e., the presence of rare allele lowered the risk of diabetes in the studied cohort. The biochemical and anthropometric parameters were analyzed for any significant association with the SNP showing that C1431T variant has an association with BMI, weight, fasting glucose and LDLC. However, no significant association was found with age, gender, height, HDLC, TC, triglycerides and leptin.

CONCLUSION

In conclusion, the presence of minor allele lowers the risk of diabetes and the effect may involve modulating certain serum parameters.

APOA5 genetic and epigenetic variability jointly regulate circulating triacylglycerol levels

Apolipoprotein A5 gene (APOA5) variability explains part of the individual's predisposition to hypertriacylglycerolaemia (HTG). Such predisposition has an inherited component (polymorphisms) and an acquired component regulated by the environment (epigenetic modifications). We hypothesize that the integrated analysis of both components will improve our capacity to estimate APOA5 contribution to HTG. We followed a recruit-by-genotype strategy to study a population composed of 44 individuals with high cardiovascular disease risk selected as being carriers of at least one APOA5 SNP (-1131T>C and/or, S19W and/or 724C>G) compared against 34 individuals wild-type (WT) for these SNPs. DNA methylation patterns of three APOA5 regions [promoter, exon 2 and CpG island (CGI) in exon 3] were evaluated using pyrosequencing technology. Carriers of APOA5 SNPs had an average of 57.5% higher circulating triacylglycerol (TG) levels (P=0.039). APOA5 promoter and exon 3 were hypermethylated whereas exon 2 was hypomethylated. Exon 3 methylation positively correlated with TG concentration (r=0.359, P=0.003) and with a lipoprotein profile associated with atherogenic dyslipidaemia. The highest TG concentrations were found in carriers of at least one SNP and with a methylation percentage in exon 3 ≥82% (P=0.009). In conclusion, CGI methylation in exon 3 of APOA5 acts, in combination with -1131T>C, S19W and 724C>G polymorphisms, in the individual's predisposition to high circulating TG levels. This serves as an example that combined analysis of SNPs and methylation applied to a larger set of genes would improve our understanding of predisposition to HTG.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration

BACKGROUND

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development.

RESULTS

To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics.

RESEARCH

idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use.

CONCLUSIONS

Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes

IMPORTANCE

Low-density lipoprotein cholesterol (LDL-C) is causally related to coronary artery disease (CAD), but the relevance of high-density lipoprotein cholesterol (HDL-C) and triglycerides (TGs) is uncertain. Lowering of LDL-C levels by statin therapy modestly increases the risk of type 2 diabetes, but it is unknown whether this effect is specific to statins.

OBJECTIVE

To investigate the associations of 3 routinely measured lipid fractions with CAD and diabetes through mendelian randomization (MR) using conventional MR and making use of newer approaches, such as multivariate MR and MR-Egger, that address the pleiotropy of genetic instruments where relevant.

DESIGN, SETTING, AND PARTICIPANTS

Published data from genome-wide association studies were used to construct genetic instruments and then applied to investigate associations between lipid fractions and the risk of CAD and diabetes using MR approaches that took into account pleiotropy of genetic instruments. The study was conducted from March 12 to December 31, 2015.

MAIN OUTCOMES AND MEASURES

Coronary artery disease and diabetes.

RESULTS

Genetic instruments composed of 130 single-nucleotide polymorphisms (SNPs) were used for LDL-C (explaining 7.9% of its variance), 140 SNPs for HDL-C (6.6% of variance), and 140 SNPs for TGs (5.9% of variance). A 1-SD genetically instrumented elevation in LDL-C levels (equivalent to 38 mg/dL) and TG levels (equivalent to 89 mg/dL) was associated with higher CAD risk; odds ratios (ORs) were 1.68 (95% CI, 1.51-1.87) for LDL-C and 1.28 (95% CI, 1.13-1.45) for TGs. The corresponding OR for HDL-C (equivalent to a 16-mg/dL increase) was 0.95 (95% CI, 0.85-1.06). All 3 lipid traits were associated with a lower risk of type 2 diabetes. The ORs were 0.79 (95% CI, 0.71-0.88) for LDL-C and 0.83 (95% CI, 0.76-0.90) for HDL-C per 1-SD elevation. For TG, the MR estimates for diabetes were inconsistent, with MR-Egger giving an OR of 0.83 (95%CI, 0.72-0.95) per 1-SD elevation.

CONCLUSIONS AND RELEVANCE

Routinely measured lipid fractions exhibit contrasting associations with the risk of CAD and diabetes. Increased LDL-C, HDL-C, and possibly TG levels are associated with a lower risk of diabetes. This information will be relevant to the design of clinical trials of lipid-modifying agents, which should carefully monitor participants for dysglycemia and the incidence of diabetes.

Adiposity-Dependent Regulatory Effects on Multi-tissue Transcriptomes

Obesity is a global epidemic that is causally associated with a range of diseases, including type 2 diabetes and cardiovascular disease, at the population-level. However, there is marked heterogeneity in obesity-related outcomes among individuals. This might reflect genotype-dependent responses to adiposity. Given that adiposity, measured by BMI, is associated with widespread changes in gene expression and regulatory variants mediate the majority of known complex trait loci, we sought to identify gene-by-BMI (G × BMI) interactions on the regulation of gene expression in a multi-tissue RNA-sequencing (RNA-seq) dataset from the TwinsUK cohort (n = 856). At a false discovery rate of 5%, we identified 16 cis G × BMI interactions (top cis interaction: CHURC1, rs7143432, p = 2.0 × 10(-12)) and one variant regulating 53 genes in trans (top trans interaction: ZNF423, rs3851570, p = 8.2 × 10(-13)), all in adipose tissue. The interactions were adipose-specific and enriched for variants overlapping adipocyte enhancers, and regulated genes were enriched for metabolic and inflammatory processes. We replicated a subset of the interactions in an independent adipose RNA-seq dataset (deCODE genetics, n = 754). We also confirmed the interactions with an alternate measure of obesity, dual-energy X-ray absorptiometry (DXA)-derived visceral-fat-volume measurements, in a subset of TwinsUK individuals (n = 682). The identified G × BMI regulatory effects demonstrate the dynamic nature of gene regulation and reveal a functional mechanism underlying the heterogeneous response to obesity. Additionally, we have provided a web browser allowing interactive exploration of the dataset, including of association between expression, BMI, and G × BMI regulatory effects in four tissues.

Tribbles-1: a novel regulator of hepatic lipid metabolism in humans

The protein tribbles-1, encoded by the gene TRIB1, is increasingly recognized as a major regulator of multiple cellular and physiological processes in humans. Recent human genetic studies, as well as molecular biological approaches, have implicated this intriguing protein in the aetiology of multiple human diseases, including myeloid leukaemia, Crohn's disease, non-alcoholic fatty liver disease (NAFLD), dyslipidaemia and coronary artery disease (CAD). Genome-wide association studies (GWAS) have repeatedly identified variants at the genomic TRIB1 locus as being significantly associated with multiple plasma lipid traits and cardiovascular disease (CVD) in humans. The involvement of TRIB1 in hepatic lipid metabolism has been validated through viral-mediated hepatic overexpression of the gene in mice; increasing levels of TRIB1 decreased plasma lipids in a dose-dependent manner. Additional studies have implicated TRIB1 in the regulation of hepatic lipogenesis and NAFLD. The exact mechanisms of TRIB1 regulation of both plasma lipids and hepatic lipogenesis remain undetermined, although multiple signalling pathways and transcription factors have been implicated in tribbles-1 function. Recent reports have been aimed at developing TRIB1-based lipid therapeutics. In summary, tribbles-1 is an important modulator of human energy metabolism and metabolic syndromes and worthy of future studies aimed at investigating its potential as a therapeutic target.

A genome-wide association study meta-analysis of clinical fracture in 10,012 African American women

Background

Osteoporosis is a major public health problem associated with excess disability and mortality. It is estimated that 50–70% of the variation in osteoporotic fracture risk is attributable to genetic factors. The purpose of this hypothesis-generating study was to identify possible genetic determinants of fracture among African American (AA) women in a GWAS meta-analysis.

Methods

Data on clinical fractures (all fractures except fingers, toes, face, skull or sternum) were analyzed among AA female participants in the Women's Health Initiative (WHI) (N = 8155), Cardiovascular Health Study (CHS) (N = 504), BioVU (N = 704), Health ABC (N = 651), and the Johnston County Osteoarthritis Project (JoCoOA) (N = 291). Affymetrix (WHI) and Illumina (Health ABC, JoCoOA, BioVU, CHS) GWAS panels were used for genotyping, and a 1:1 ratio of YRI:CEU HapMap haplotypes was used as an imputation reference panel. We used Cox proportional hazard models or logistic regression to evaluate the association of ~ 2.5 million SNPs with fracture risk, adjusting for ancestry, age, and geographic region where applicable. We conducted a fixed-effects, inverse variance-weighted meta-analysis. Genome-wide significance was set at P < 5 × 10^− 8.

Results

One SNP, rs12775980 in an intron of SVIL on chromosome 10p11.2, reached genome-wide significance (P = 4.0 × 10^− 8). Although this SNP has a low minor allele frequency (0.03), there was no evidence for heterogeneity of effects across the studies (I² = 0). This locus was not reported in any previous osteoporosis-related GWA studies. We also interrogated previously reported GWA-significant loci associated with fracture or bone mineral density in our data. One locus (SMOC1) generalized, but overall there was not substantial evidence of generalization. Possible reasons for the lack of generalization are discussed.

Conclusion

This GWAS meta-analysis of fractures in African American women identified a potentially novel locus in the supervillin gene, which encodes a platelet-associated factor and was previously associated with platelet thrombus formation in African Americans. If validated in other populations of African descent, these findings suggest potential new mechanisms involved in fracture that may be particularly important among African Americans.

•

This was a hypothesis-generating GWAS for fracture in African Americans.

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One potentially novel locus (SVIL) was identified at GWA-significant levels.

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SVIL has been associated with platelet thrombus formation in African-Americans.

Leveraging human genetics to guide drug target discovery

Identifying appropriate molecular targets is a critical step in drug development. Despite many advantages, the traditional tools of observational epidemiology and cellular or animal models of disease can be misleading in identifying causal pathways likely to lead to successful therapeutics. Here, we review some favorable aspects of human genetics studies that have the potential to accelerate drug target discovery. These include using genetic studies to identify pathways relevant to human disease, leveraging human genetics to discern causal relationships between biomarkers and disease, and studying genetic variation in humans to predict the potential efficacy and safety of inhibitory compounds aimed at molecular targets. We present some examples taken from studies of plasma lipids and coronary artery disease to highlight how human genetics can accelerate therapeutics development.

Pleiotropic Analysis of Lung Cancer and Blood Triglycerides

Epidemiologically related traits may share genetic risk factors, and pleiotropic analysis could identify individual loci associated with these traits. Because of their shared epidemiological associations, we conducted pleiotropic analysis of genome-wide association studies of lung cancer (12 160 lung cancer case patients and 16 838 control subjects) and cardiovascular disease risk factors (blood lipids from 188 577 subjects, type 2 diabetes from 148 821 subjects, body mass index from 123 865 subjects, and smoking phenotypes from 74 053 subjects). We found that 6p22.1 (rs6904596, ZNF184) was associated with both lung cancer (P = 5.50x10(-6)) and blood triglycerides (P = 1.39x10(-5)). We replicated the association in 6097 lung cancer case patients and 204 657 control subjects (P = 2.40 × 10(-4)) and in 71 113 subjects with triglycerides data (P = .01). rs6904596 reached genome-wide significance in lung cancer meta-analysis (odds ratio = 1.15, 95% confidence interval = 1.10 to 1.21 ,: Pcombined = 5.20x10(-9)). The large sample size provided by the lipid GWAS data and the shared genetic risk factors between the two traits contributed to the uncovering of a hitherto unidentified genetic locus for lung cancer.

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids

AIMS

An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants.

METHODS

Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform.

RESULTS

The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects.

CONCLUSIONS

Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.

Interaction Between Peroxisome Proliferator Activated Receptor δ and Epithelial Membrane Protein 2 Polymorphisms Influences HDL-C Levels in the Chinese Population

Peroxisome proliferator activated receptors (PPARs) are transcription factors involved in the regulation of key metabolic pathways. Numerous in vivo and in vitro studies have established their important roles in lipid metabolism. A few SNPs in PPAR genes have been reported to be associated with lipid levels. In this study, we aimed to investigate the interactive effects between single nucleotide polymorphisms (SNPs) in three PPAR isoforms α/δ/γ and other genetic variants across the genome on plasma high-density lipoprotein-cholesterol (HDL-C) levels. Study subjects (N = 2003) were genotyped using Illumina HumanOmniZhongHua-8 Beadchip. Fifty-three tag SNPs ± 100 kb of PPAR α, δ, and γ (r(2) < 0.2) were selected. The effect of interactions between PPAR SNPs and those across the genome on HDL-C was tested using linear regression models. One statistically significant interaction influencing HDL-C was detected between PPARδ SNP rs2267668 and epithelial membrane protein 2 (EMP2) downstream SNP rs7191411 (N = 1993, β = 0.74, adjusted P = 0.022). This interaction was successfully replicated in the meta-analysis of two additional Chinese cohorts (N = 3948, P = 0.01). The present study showed a novel SNP × SNP interaction between rs2267668 in PPARδ and rs7191411 in EMP2 that has significant impact on circulating HDL-C levels in the Singaporean Chinese population.

Coding-sequence variants are associated with blood lipid levels in 14,473 Chinese

Previously identified common variants explain only a small fraction of the trait heritability and at most loci the identities of the underlying causal genes and their functional variants still remain unknown. To identify the low-frequency and rare coding variants that influence lipid levels, we conducted a meta-analysis of exome-wide association studies in 14,473 Chinese subjects, followed by a joint analysis with 1000 genomes imputed data from 6,534 samples. We replicated 24 previously reported lipid loci with exome-wide significance (P < 3.3 × 10 ^{-  7}), including fourteen coding variants at ten confirmed lipid loci (P range from 1.44 × 10 ^{-  7} to 1.64 × 10 ^{-  45}). Of these, six coding variants showed population-specific associations and were independent of previously identified associations in European populations, including four low-frequency (PCSK9 p.Arg93Cys, HMGCR p.Tyr311Ser, APOA5 p.Gly185Cys and CETP p.Asp399Gly) and two common (APOB p.Arg532Trp and APOA4 p.Ser147Asn) variants. Furthermore, we detected three new lead non-coding variants at LPA, LIPC and LDLR in Chinese. The independent variants at PCSK9, HMGCR, LPA, APOA5 and LDLR were also associated with increased risk of coronary artery disease in the expected direction. In gene-based tests, the burden of rare or low frequency variants in PCSK9, HMGCR and CEPT exhibited strong associations with blood lipid levels (P < 2.8 × 10 ^{-  6}). Our findings identify additional population-specific possible causal variants. Our data demonstrate that the inter-ethnic differences in allele frequencies of coding variants may lead to different association signals across ethnic groups, highlighting the importance of including diverse populations to uncover genetic variation associated with lipid levels.

Gene set analysis for interpreting genetic studies

Interpretation of genome-wide association study (GWAS) results is lacking behind the discovery of new genetic associations. Consequently, there is an urgent need for data-driven methods for interpreting genetic association studies. Gene set analysis (GSA) can identify aetiologic pathways and functional annotations and may hence point towards novel biological insights. However, despite the growing availability of GSA tools, the sizeable amount of variants identified for a vast number of complex traits, and many irrefutably trait-associated gene sets, the gap between discovery and interpretation remains. More efficient interpretation requires more complete and consistent gene set representations of biological pathways, phenotypes and functional annotations. In this review, I examine different types of gene sets, discuss how inconsistencies in gene set definitions impact GSA, describe how GSA has helped to elucidate biology and outline potential future directions.

Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex traits and diseases. However, elucidating the causal genes underlying GWAS hits remains challenging. We applied the summary data-based Mendelian randomization (SMR) method to 28 GWAS summary datasets to identify genes whose expression levels were associated with traits and diseases due to pleiotropy or causality (the expression level of a gene and the trait are affected by the same causal variant at a locus). We identified 71 genes, of which 17 are novel associations (no GWAS hit within 1 Mb distance of the genes). We integrated all the results in an online database ( http://www.cnsgenomics/shiny/SMRdb/ ), providing important resources to prioritize genes for further follow-up, for example in functional studies.

Non-alcoholic fatty liver disease and risk of cardiovascular disease

Non-alcoholic fatty liver disease (NAFLD) has become the leading cause of chronic liver diseases worldwide, causing considerable liver-related mortality and morbidity. During the past decade, it has also become increasingly evident that NAFLD is a multisystem disease that affects many extra-hepatic organ systems, including the heart and the vascular system. In this updated clinical review, we discuss the rapidly expanding body of clinical and epidemiological evidence that supports a strong association of NAFLD with cardiovascular diseases (CVDs) and other functional and structural myocardial abnormalities. We also discuss some recently published data that correlate NAFLD due to specific genetic polymorphisms with the risk of CVDs. Finally, we briefly examine the assessment tools for estimating the global CVD risk in patients with NAFLD as well as the conventional and the more innovative pharmacological approaches for the treatment of CVD risk in this group of patients.

Implications of thermogenic adipose tissues for metabolic health

Excess and ectopic fat accumulation in obesity is a major risk factor for developing hyperlipidemia, type 2 diabetes and cardiovascular disease. The activation of brown and/or beige adipocytes is a promising target for the treatment of metabolic disorders as the combustion of excess energy by these thermogenic adipocytes may help losing weight and improving plasma parameters including triglyceride, cholesterol and glucose levels. The regulation of heat production by thermogenic adipose tissues is based on a complex crosstalk between the autonomous nervous system, intracellular and secreted factors. This multifaceted alignment regulates thermogenic demands to environmental circumstances in dependence on available energy resources. This review summarizes the current knowledge how thermogenic tissues can be targeted to combat the burden of diseases with a special focus on lipid metabolism and diseases related to lipoprotein metabolism.

Progress in the care of common inherited atherogenic disorders of apolipoprotein B metabolism

Familial hypercholesterolaemia, familial combined hyperlipidaemia (FCH) and elevated lipoprotein(a) are common, inherited disorders of apolipoprotein B metabolism that markedly accelerate the onset of atherosclerotic cardiovascular disease (ASCVD). These disorders are frequently encountered in clinical lipidology and need to be accurately identified and treated in both index patients and their family members, to prevent the development of premature ASCVD. The optimal screening strategies depend on the patterns of heritability for each condition. Established therapies are widely used along with lifestyle interventions to regulate levels of circulating lipoproteins. New therapeutic strategies are becoming available, and could supplement traditional approaches in the most severe cases, but their long-term cost-effectiveness and safety have yet to be confirmed. We review contemporary developments in the understanding, detection and care of these highly atherogenic disorders of apolipoprotein B metabolism.

Serum gamma-glutamyl transferase and risk of type 2 diabetes in the general Korean population: a Mendelian randomization study

Elevated gamma-glutamyl transferase (GGT) levels are associated with higher risk of type 2 diabetes in observational studies, but the underlying causal relationship is still unclear. Here, we tested a hypothesis that GGT levels have a causal effect on type 2 diabetes risk using Mendelian randomization. Data were collected from 7640 participants in a South Korean population. In a single instrumental variable (IV) analysis using two stage least squares regression with the rs4820599 in the GGT1 gene region as an instrument, one unit of GGT levels (IU/L) was associated with 11% higher risk of type 2 diabetes (odds ratio (OR) = 1.11, 95% confidence interval (CI): 1.04 to 1.19). In a multiple IV analysis using seven genetic variants that have previously been demonstrated to be associated with GGT at a genome-wide level of significance, the corresponding estimate suggested a 2.6% increase in risk (OR = 1.026, 95% CI: 1.001 to 1.052). In a two-sample Mendelian randomization analysis using genetic associations with type 2 diabetes taken from a trans-ethnic GWAS study of 110 452 independent samples, the single IV analysis confirmed an association between the rs4820599 and type 2 diabetes risk (P-value = 0.04); however, the estimate from the multiple IV analysis was compatible with the null (OR = 1.007, 95% CI: 0.993 to 1.022) with considerable heterogeneity between the causal effects estimated using different genetic variants. Overall, there is weak genetic evidence that GGT levels may have a causal role in the development of type 2 diabetes.

Common variants upstream of KDR encoding VEGFR2 and in TTC39B associate with endometriosis

We conducted a genome-wide association scan (GWAS) of endometriosis using 25.5 million sequence variants detected through whole-genome sequencing (WGS) of 8,453 Icelanders and imputed into 1,840 cases and 129,016 control women, followed by testing of associated variants in Danish samples. Here we report the discovery of a new endometriosis susceptibility locus on 4q12 (rs17773813[G], OR=1.28; P=3.8 × 10⁻¹¹), upstream of KDR encoding vascular endothelial growth factor receptor 2 (VEGFR2). The variant correlates with disease severity (P=0.0046) when moderate/severe endometriosis cases are tested against minimal/mild cases. We further report association of rs519664[T] in TTC39B on 9p22 with endometriosis (P=4.8 × 10⁻¹⁰; OR=1.29). The involvement of KDR in endometriosis risk highlights the importance of the VEGF pathway in the pathogenesis of the disease.

Endometriosis is a common gynaecological disease but the underlying pathogenesis is poorly understood, however there is a strong familial component. Here the authors conduct a genome wide association study and identify a novel susceptibility locus that correlates with disease severity.

Mendelian Randomization Studies Do Not Support a Role for Vitamin D in Coronary Artery Disease

BACKGROUND

Observational studies support a possible association between decreased vitamin D levels and risk of coronary artery disease (CAD); however, it remains unclear whether this relationship is causal. We aimed to evaluate whether genetically lowered vitamin D levels influence the risk of CAD using a Mendelian randomization approach.

METHODS AND RESULTS

In this 2-stage Mendelian randomization study, we first identified single-nucleotide polymorphisms associated with 25-hydroxyvitamin D (25OHD) levels in the SUNLIGHT consortium (n=33 996), then tested them for possible violation of Mendelian randomization assumptions. A count of risk alleles was tested for association with 25OHD levels in a separate cohort (n=2347). Alleles were weighted by their relative effect on 25OHD and tested for their combined effect on CAD in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) study (22 233 cases/64 762 controls). Four single-nucleotide polymorphisms were identified to be associated with 25OHD levels, all in or near genes implicated in 25OHD synthesis, transport or metabolism. A count of these risk alleles was strongly associated with 25OHD (n=2347, F-test statistic=49.7, P=2×10(-12)). None of the single-nucleotide polymorphisms associated with 25OHD levels were associated with CAD (all P values >0.6). The Mendelian randomization odds ratio (OR) for CAD was 0.99 (95% confidence interval, 0.84-1.17; P=0.93; I(2)=0) per SD decrease in log-transformed 25OHD levels. These results persisted after sensitivity analyses for population stratification and pleiotropy.

CONCLUSIONS

Genetically lowered 25OHD levels were not associated with increased risk of CAD in a large, well-powered study, suggesting that previous associations between circulating 25OHD levels and CAD are possibly confounded or due to reverse causation.