Discovery and refinement of loci associated with lipid levels

Genetic loci associated with ideal cardiovascular health: A meta-analysis of genome-wide association studies

BACKGROUND

Multiple genetic loci are associated with clinical cardiovascular (CV) disease and individual CV risk factors. Individuals with ideal levels of all major CV risk factors have very low risk for CV disease morbidity or mortality. Ideal levels of risk factors can be attained by lifestyle modifications; however, little is known about gene variants associated with ideal CV health. Our objective was to carry out a genome-wide association study on the trait.

METHODS AND RESULTS

We examined 2 dichotomous phenotypes of ideal CV health-clinical (untreated cholesterol <200 mg/dL, untreated blood pressure <120/<80, not diabetic) and clinical+behavioral (clinical plus: not a current smoker, body mass index <25 kg/m(2))-among white participants aged 50±5 years. We performed a meta-analysis of 4 genome-wide association studies (total n=11,708) from the MESA, CARDIA, ARIC, and Framingham Heart Study cohorts. We identified a single-nucleotide polymorphism (rs445925) in the APOC1/APOE region that was associated with clinical ideal CV health at genome-wide level of significance (P<2.0 × 10(-9)). The significance of this region was validated using exome chip genotyping. The association with ideal CV health was attenuated after adjusting for low-density lipoprotein cholesterol.

CONCLUSION

A common single-nucleotide polymorphism in the APOC1/APOE region, previously found to be associated with protective levels of cholesterol and lower CV risk, may be associated with ideal health. In future replication studies, larger sample sizes may be needed to detect loci with more modest effects on ideal CV health. In addition to the important impact of lifestyle modifications, we have identified evidence for gene variation that plays a role in ideal CV health.

Detecting novel genes for low-density lipoprotein cholesterol in European population using bioinformatics analysis

AIM

The aim of this study was to identify related genes for low-density lipoprotein cholesterol and evaluate the functional relevance to provide evidences for prioritizing these genes.

MATERIALS & METHODS

We performed a gene-based association study in about 188,578 individuals. Furthermore, we performed bioinformatics analyses to support the identified genes.

RESULTS

A total of 292 genes were found to be significant after Bonferroni correction (p < 2.3 × 10^-6). Among these genes, 59 seemed to be associated with coronary artery disease (CAD).

CONCLUSION

The evidence obtained from the analyses of this study signified the importance of many genes, for example, LDLR, ABCG5, ABCG8, APOB, HNF1A, PTPN11, APOA5 and MCM6, which were also associated with CAD. The findings might provide more insights into the genetic basis of lipid metabolism and CAD.

Genome-Wide Studies of Type 2 Diabetes and Lipid Traits in Hispanics

Although disproportionately affected by increasing rates of type 2 diabetes and dyslipidemias, Hispanic populations are underrepresented in efforts to understand genetic susceptibility to these disorders. Where research has been undertaken, these populations have provided substantial insight into identification of novel risk-associated genes and have aided in the ability to fine map previously described risk loci. Genome-wide analyses in Hispanic and trans-ethnic populations have resulted in identification of more than 40 replicated or novel genes with significant effects for type 2 diabetes or lipid traits. Initial investigations into rare variant effects have identified new risk-associated variants private to Hispanic populations, and preliminary results suggest metagenomic approaches in Hispanic populations, such as characterizing the gut microbiome, will enable the development of new predictive tools and therapeutic targets for type 2 diabetes. Future genome-wide studies in expanded cohorts of Hispanics are likely to result in new insights into the genetic etiology of metabolic health.

Profiling and Validation of the Circular RNA Repertoire in Adult Murine Hearts

For several decades, cardiovascular disease has been the leading cause of death throughout all countries. There is a strong genetic component to many disease subtypes (e.g., cardiomyopathy) and we are just beginning to understand the relevant genetic factors. Several studies have related RNA splicing to cardiovascular disease and circular RNAs (circRNAs) are an emerging player. circRNAs, which originate through back-splicing events from primary transcripts, are resistant to exonucleases and typically not polyadenylated. Initial functional studies show clear phenotypic outcomes for selected circRNAs. We provide, for the first time, a comprehensive catalogue of RNase R-resistant circRNA species for the adult murine heart. This work combines state-of-the-art circle sequencing with our novel DCC software to explore the circRNA landscape of heart tissue. Overall, we identified 575 circRNA species that pass a beta-binomial test for enrichment (false discovery rate of 1%) in the exonuclease-treated sequencing sample. Several circRNAs can be directly attributed to host genes that have been previously described as associated with cardiovascular disease. Further studies of these candidate circRNAs may reveal disease-relevant properties or functions of specific circRNAs.

Enrichment of SNPs in Functional Categories Reveals Genes Affecting Complex Traits

Genome-wide association studies (GWAS) have indicated potential to identify heritability of common complex phenotypes, but traditional approaches have limited ability to detect hiding signals because single SNP has weak effect size accounting for only a small fraction of overall phenotypic variations. To improve the power of GWAS, methods have been developed to identify truly associated genes by jointly testing effects of all SNPs. However, equally considering all SNPs within a gene might dilute strong signals of SNPs in real functional categories. Here, we observed a consistent pattern on enrichment of significant SNPs in eight functional categories across six phenotypes, with the highest enrichment in coding and both UTR regions while the lowest enrichment in the intron. Based on the pattern of SNP enrichment in functional categories, we developed a new approach for detecting gene associations on traits (DGAT) by selecting the most significant functional category and then using SNPs within it to assess gene associations. The method was found to be robust in type I error rate on simulated data, and to have mostly higher power in detecting associated genes for three different diseases than other methods. Further analysis indicated ability of the DGAT to detect novel genes. The DGAT is available by http://sparks-lab.org/server/DGAT.

Effect of SORT1, APOB and APOE polymorphisms on LDL-C and coronary heart disease in Pakistani subjects and their comparison with Northwick Park Heart Study II

Background

Many SNPs have been identified in genes regulating LDL-C metabolism, but whether their influence is similar in subjects from different ethnicities is unclear. Effect of 4 such SNPs on LDL-C and coronary heart disease (CHD) was examined in Pakistani subjects and was compared with middle aged UK men from Northwick Park Heart Study II (NPHSII).

Methods

One thousand nine hundred sixty-five (1770 non CHD, 195 CHD) UK and 623 (219 non CHD, 404 CHD) Pakistani subjects were enrolled in the study. The SNPs SORT1 rs646776, APOB rs1042031 and APOE rs429358, rs7412 were genotyped by TaqMan/KASPar technique and their gene score was calculated. LDL-C was calculated by Friedewald equation, results were analyzed using SPSS.

Results

Allele frequencies were significantly different (p = <0.05) between UK and Pakistani subjects. However, the SNPs were associated with LDL-C in both groups. In UK non CHD, UK CHD, Pakistani non CHD and Pakistani CHD respectively, for rs646776, per risk allele increase in LDL-C(mmol/l) was 0.18(0.04), 0.06(0.11), 0.15(0.04) and 0.27(0.06) respectively. For rs1042031, per risk allele increase in LDL-C in four groups was 0.11(0.04), 0.04(0.14), 0.15(0.06) and 0.25(0.09) respectively. For APOE genotypes, compared to Ɛ3, each Ɛ2 decreased LDL-C by 0.11(0.06), 0.07(0.15), 0.20(0.08) and 0.38(0.09), while each Ɛ4 increased LDL-C by 0.43(0.06), 0.39(0.21), 0.19(0.11) and 0.39(0.14) respectively. Overall gene score explained a considerable proportion of sample variance in four groups (3.8 %, 1.26 % 13.7 % and 12.3 %). Gene score in both non-CHD groups was significantly lower than CHD subjects.

Conclusions

The SNPs show a dose response association with LDL-C levels and risk of CHD in both populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-016-0253-0) contains supplementary material, which is available to authorized users.

Targeted exonic sequencing of GWAS loci in the high extremes of the plasma lipids distribution

OBJECTIVE

Genome-wide association studies (GWAS) for plasma lipid levels have mapped numerous genomic loci, with each region often containing many protein-coding genes. Targeted re-sequencing of exons is a strategy to pinpoint causal variants and genes.

METHODS

We performed solution-based hybrid selection of 9008 exons at 939 genes within 95 GWAS loci for plasma lipid levels and sequenced using next-generation sequencing technology individuals with extremely high as well as low to normal levels of low-density lipoprotein cholesterol (LDL-C, n = 311; mean low = 71 mg/dl versus high = 241 mg/dl), triglycerides (TG, n = 308; mean low = 75 mg/dl versus high = 1938 mg/dl), and high-density lipoprotein cholesterol (HDL-C, n = 684; mean low = 32 mg/dl versus high = 102 mg/dl). We identified 15,002 missense, nonsense, or splice site variants with a frequency <5%. We tested whether coding sequence variants, individually or aggregated within a gene, were associated with plasma lipid levels. To replicate findings, we performed sequencing in independent participants (n = 6424).

RESULTS

Across discovery and replication sequencing, we found 6 variants with significant associations with plasma lipids. Of these, one was a novel association: p.Ser147Asn variant in APOA4 (14.3% frequency, TG OR = 0.49, P = 7.1 × 10(-4)) with TG. In gene-level association analyses where rare variants within each gene are collapsed, APOC3 (P = 2.1 × 10(-5)) and LDLR (P = 5.0 × 10(-12)) were associated with plasma lipids.

CONCLUSIONS

After sequencing genes from 95 GWAS loci in participants with extremely high plasma lipid levels, we identified one new coding variant associated with TG. These results provide insight regarding design of similar sequencing studies with respect to sample size, follow-up, and analysis methodology.

Frequency of rare mutations and common genetic variations in severe hypertriglyceridemia in the general population of Spain

Background

Hypertriglyceridemia (HTG) is a common complex metabolic trait that results of the accumulation of relatively common genetic variants in combination with other modifier genes and environmental factors resulting in increased plasma triglyceride (TG) levels. The majority of severe primary hypertriglyceridemias is diagnosed in adulthood and their molecular bases have not been fully defined yet. The prevalence of HTG is highly variable among populations, possibly caused by differences in environmental factors and genetic background. However, the prevalence of very high TG and the frequency of rare mutations causing HTG in a whole non-selected population have not been previously studied.

Methods

The total of 23,310 subjects over 18 years from a primary care-district in a middle-class area of Zaragoza (Spain) with TG >500 mg/dL were selected to establish HTG prevalence. Those affected of primary HTG were considered for further genetic analisys. The promoters, coding regions and exon-intron boundaries of LPL, LMF1, APOC2, APOA5, APOE and GPIHBP1 genes were sequenced. The frequency of rare variants identified was studied in 90 controls.

Results

One hundred ninety-four subjects (1.04 %) had HTG and 90 subjects (46.4 %) met the inclusion criteria for primary HTG. In this subgroup, nine patients (12.3 %) were carriers of 7 rare variants in LPL, LMF1, APOA5, GPIHBP1 or APOE genes. Three of these mutations are described for the first time in this work. The presence of a rare pathogenic mutation did not confer a differential phenotype or a higher family history of HTG.

Conclusion

The prevalence of rare mutations in candidate genes in subjects with primary HTG is low. The low frequency of rare mutations, the absence of a more severe phenotype or the dominant transmission of the HTG would not suggest the use of genetic analysis in the clinical practice in this population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-016-0251-2) contains supplementary material, which is available to authorized users.

Cardiovascular Risk Factors and Ischemic Heart Disease: Is the Confluence of Risk Factors Greater Than the Parts? A Genetic Approach

BACKGROUND

Cardiovascular risk factors tend to aggregate. The biological and predictive value of this aggregation is questioned and genetics could shed light on this debate. Our aims were to reappraise the impact of risk factor confluence on ischemic heart disease (IHD) risk by testing whether genetic risk scores (GRSs) associated with these factors interact on an additive or multiplicative scale, and to determine whether these interactions provide additional value for predicting IHD risk.

METHODS AND RESULTS

We selected genetic variants associated with blood pressure, body mass index, waist circumference, triglycerides, type-2 diabetes mellitus, high-density lipoprotein and low-density lipoprotein cholesterol, and IHD to create GRSs for each factor. We tested and meta-analyzed the impact of additive (synergy index) and multiplicative (βinteraction) interactions between each GRS pair in 1 case-control (n=6042) and 4 cohort studies (n=17 794) and evaluated the predictive value of these interactions. We observed 2 multiplicative interactions: GRSLDL·GRSTriglycerides (βinteraction=-0.096; SE=0.028) and nonpleiotropic GRSIHD·GRSLDL (βinteraction=0.091; SE=0.028). Inclusion of these interaction terms did not improve predictive capacity.

CONCLUSIONS

The confluence of low-density lipoprotein cholesterol and triglycerides genetic risk load has an additive effect on IHD risk. The interaction between low-density lipoprotein cholesterol and IHD genetic load is more than multiplicative, supporting the hazardous impact on atherosclerosis progression of the combination of inflammation and increased lipid levels. The capacity of risk factor confluence to improve IHD risk prediction is questionable. Further studies in larger samples are warranted to confirm and expand our results.

A Class of Diacylglycerol Acyltransferase 1 Inhibitors Identified by a Combination of Phenotypic High-throughput Screening, Genomics, and Genetics

Excess lipid storage is an epidemic problem in human populations. Thus, the identification of small molecules to treat or prevent lipid storage-related metabolic complications is of great interest. Here we screened > 320.000 compounds for their ability to prevent a cellular lipid accumulation phenotype. We used fly cells because the multifarious tools available for this organism should facilitate unraveling the mechanism-of-action of active small molecules. Of the several hundred lipid storage inhibitors identified in the primary screen we concentrated on three structurally diverse and potent compound classes active in cells of multiple species (including human) and negligible cytotoxicity. Together with Drosophila in vivo epistasis experiments, RNA-Seq expression profiles suggested that the target of one of the small molecules was diacylglycerol acyltransferase 1 (DGAT1), a key enzyme in the production of triacylglycerols and prominent human drug target. We confirmed this prediction by biochemical and enzymatic activity tests.

•

We identified > 600 potent small molecule inhibitors of cellular lipid storage deposition.

•

RNA-Seq expression profiling discriminated the activity of three lead scaffolds and guided subsequent functional studies.

•

We discovered a class of DGAT1 inhibitors, which is active in fly and mammalian cell lines as well as whole flies.

Obesity and other lipid storage associated diseases are a growing health threat of human populations. In an undirected phenotypic screen, we identified pharmacologically active small molecules that reduce or enhance lipid storage. Our work focuses on three lead structures that prevent lipid storage in diverse cellular systems including cells from a diabetes patient. In order to elucidate the compound mechanisms-of-action and cellular targets, we used a combination of RNA-Seq transcriptional profiling and diverse functional assays. Our results strongly suggest that one of our lead structures represents a class of inhibitors targeting the key lipogenic enzyme diacylglycerol acyltransferase 1.

Minireview: Genome Editing of Human Pluripotent Stem Cells for Modeling Metabolic Disease

The pathophysiology of metabolic diseases such as coronary artery disease, diabetes, and obesity is complex and multifactorial. Developing new strategies to prevent or treat these diseases requires in vitro models with which researchers can extensively study the molecular mechanisms that lead to disease. Human pluripotent stem cells and their differentiated derivatives have the potential to provide an unlimited source of disease-relevant cell types and, when combined with recent advances in genome editing, make the goal of generating functional metabolic disease models, for the first time, consistently attainable. However, this approach still has certain limitations including lack of robust differentiation methods and potential off-target effects. This review describes the current progress in human pluripotent stem cell-based metabolic disease research using genome-editing technology.

Variation in SLC19A3 and Protection From Microvascular Damage in Type 1 Diabetes

The risk of long-term diabetes complications is not fully explained by diabetes duration or long-term glycemic exposure, suggesting the involvement of genetic factors. Because thiamine regulates intracellular glucose metabolism and corrects for multiple damaging effects of high glucose, we hypothesized that variants in specific thiamine transporters are associated with risk of severe retinopathy and/or severe nephropathy because they modify an individual's ability to achieve sufficiently high intracellular thiamine levels. We tested 134 single nucleotide polymorphisms (SNPs) in two thiamine transporters (SLC19A2/3) and their transcription factors (SP1/2) for an association with severe retinopathy or nephropathy or their combination in the FinnDiane cohort. Subsequently, the results were examined for replication in the DCCT/EDIC and Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) cohorts. We found two SNPs in strong linkage disequilibrium in the SLC19A3 locus associated with a reduced rate of severe retinopathy and the combined phenotype of severe retinopathy and end-stage renal disease. The association for the combined phenotype reached genome-wide significance in a meta-analysis that included the WESDR cohort. These findings suggest that genetic variations in SLC19A3 play an important role in the pathogenesis of severe diabetic retinopathy and nephropathy and may explain why some individuals with type 1 diabetes are less prone than others to develop microvascular complications.

Mendelian randomization to assess causal effects of blood lipids on coronary heart disease: lessons from the past and applications to the future

PURPOSE OF REVIEW

Mendelian randomization is a technique for judging the causal impact of a risk factor on an outcome from observational data using genetic variants. Although evidence from Mendelian randomization for the effects of major lipids and lipoproteins on coronary heart disease (CHD) risk has been around for a relatively long time, new data resources and new methodological approaches have given fresh insight into these relationships. The lessons from these analyses are likely to be highly relevant when it comes to lipidomics and the analyses of lipid subspecies whose biology is less well understood.

RECENT FINDINGS

Although analyses of low-density lipoprotein cholesterol and lipoprotein(a) are unambiguous as there are genetic variants that associate exclusively with these risk factors and have well understood biology, analyses for triglycerides, and high-density lipoprotein cholesterol (HDL-c) are less clear. For example, a subset of genetic variants having specific associations with HDL-c are not associated with CHD risk, but an allele score including all variants associated with HDL-c does associate with CHD risk. Recently developed methods, such as multivariable Mendelian randomization, Mendelian randomization-Egger, and a weighted median method, suggest that the relationship between HDL-c and CHD risk is null, thus confirming experimental evidence.

SUMMARY

Robust methods for Mendelian randomization have important utility for understanding the causal relationships between major lipids and CHD risk, and are likely to play an important role in judging the causal relevance of lipid subspecies and other metabolites measured on high-dimensional phenotyping platforms.

Genetic insights into statin-associated diabetes risk

PURPOSE OF REVIEW

Meta-analyses of major statin trials have suggested that statin therapy modestly increases the risk of developing diabetes. However, the quality of the data on which these findings are based is not without weaknesses and it has also been unclear whether this effect, if true, is an on-target or off-target effect of statins.

RECENT FINDINGS

In a major Mendelian randomization study of variants in the HMGCR gene, which encodes the protein through which statins exert their effect, two polymorphisms associated with lower LDL-cholesterol were also associated with higher weight, higher waist circumference, higher glucose and higher diabetes risk. These findings correspond with findings from the statin trials. In addition, new observational studies using a genetic risk score for LDL-cholesterol suggest that other pathways linked to LDL-cholesterol metabolism may also affect diabetes risk.

SUMMARY

Genetic studies indicate that the observed effect of statins on diabetes risk in trials is highly likely to be a true on-target effect. Although other recent studies have suggested that genetically determined lower LDL-cholesterol may be linked to diabetes risk, further data from both genetic studies and clinical trials of other LDL-cholesterol lowering agents are needed to confirm or refute this.

What can we learn about lipoprotein metabolism and coronary heart disease from studying rare variants?

PURPOSE OF REVIEW

Rare variant association studies (RVAS) target the class of genetic variation with frequencies less than 1%. Recently, investigators have used exome sequencing in RVAS to identify rare alleles responsible for Mendelian diseases but have experienced greater difficulty discovering such alleles for complex diseases. In this review, we describe what we have learned about lipoprotein metabolism and coronary heart disease through the conduct of RVAS.

RECENT FINDINGS

Rare protein-altering genetic variation can provide important insights that are not as easily attainable from common variant association studies. First, RVAS can facilitate gene discovery by identifying novel rare protein-altering variants in specific genes that are associated with disease. Second, rare variant associations can provide supportive evidence for putative drug targets for novel therapies. Finally, rare variants can uncover new pathways and reveal new biologic mechanisms.

SUMMARY

The field of human genetics has already made tremendous progress in understanding lipoprotein metabolism and the causes of coronary heart disease in the context of rare variants. As next generation sequencing becomes more cost-effective, RVAS with larger sample sizes will be conducted. This will lead to more novel rare variant discoveries and the translation of genomic data into biological knowledge and clinical insights for cardiovascular disease.

Combined hyperlipidemia: familial but not (usually) monogenic

PURPOSE OF REVIEW

Combined hyperlipidemia (CHL) is a complex phenotype that is commonly encountered clinically and is often associated with the expression of early heart disease. The affixed adjective 'familial' gives the impression that the trait is monogenic, like familial hypercholesterolemia. But despite significant efforts, genetic studies have yielded little evidence of single gene determinants of CHL.

RECENT FINDINGS

Sophisticated linkage studies suggest that individual lipid components of the CHL phenotype - such as elevated LDL and triglyceride - each have several determinants that segregate independently in families. Furthermore, DNA sequencing shows that rare large-effect variants in genes such as LDL receptor (LDLR) and lipoprotein lipase are found in some CHL patients, explaining the elevated LDL cholesterol and triglyceride components, respectively. In addition, multiple common small-effect lipid-altering variants accumulate in an individual's genome, raising the LDL cholesterol and/or triglyceride components by multiple mechanisms. Finally, secondary factors, such as poor diet, obesity,fatty liver or diabetes further modulate the expression of the biochemically defined CHL phenotype.

SUMMARY

Given the current state of genetic understanding, CHL may be best conceptualized as a syndrome with common clinical presentation but multigenic causes, similar to other common conditions such as type 2 diabetes.

Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia?

Background—

Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability.

Methods and Results—

We tested whether established triglyceride-associated loci modify the relationship of body mass index (BMI) and triglyceride concentrations in 2 Swedish cohorts (the Gene–Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIER Study; N=4312] and the Malmö Diet and Cancer Study [N=5352]). The genetic loci were amalgamated into a weighted genetic risk score (WGRS TG ) by summing the triglyceride-elevating alleles (weighted by their established marginal effects) for all loci. Both BMI and the WGRS TG were strongly associated with triglyceride concentrations in GLACIER, with each additional BMI unit (kg/m 2 ) associated with 2.8% ( P =8.4×10 –84 ) higher triglyceride concentration and each additional WGRS TG unit with 2% ( P =7.6×10 –48 ) higher triglyceride concentration. Each unit of the WGRS TG was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants ( P interaction =0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRS TG ×BMI interaction effect ( P interaction =6.0×10 –4 ), which was strengthened by including data from the Danish cohorts ( P interaction =6.5×10 –7 ). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRS TG ×BMI×sex) was observed ( P interaction =0.03), where the WGRS TG ×BMI interaction was only statistically significant in females. Using protein–protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci.

Conclusions—

Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females.

Genome-wide significant results identified for plasma apolipoprotein H levels in middle-aged and older adults

Apolipoprotein H (ApoH) is a multi-functional plasma glycoprotein that has been associated with negative health outcomes. ApoH levels have high heritability. We undertook a genome-wide association study of ApoH levels using the largest sample to date and replicated the results in an independent cohort (total N = 1,255). In the discovery phase, a meta-analysis of two cohorts, the Sydney Memory and Ageing Study (Sydney MAS) and the Older Australian Twins Study (OATS) (n = 942) revealed genome-wide significant results in or near the APOH gene on chromosome 17 (top SNP, rs7211380, p = 1 × 10⁻¹¹). The results were replicated in an independent cohort, the Hunter Community Study (p < 0.002) (n = 313). Conditional and joint analysis (COJO) confirmed the association of the chromosomal 17 region with ApoH levels. The set of independent SNPs identified by COJO explained 23% of the variance. The relationships between the top SNPs and cardiovascular/lipid/cognition measures and diabetes were assessed in Sydney MAS, with suggestive results observed for diabetes and cognitive performance. However, replication of these results in the smaller OATS cohort was not found. This work provides impetus for future research to better understand the contribution of genetics to ApoH levels and its possible impacts on health.

Plasma Levels of Risk-Variant APOL1 Do Not Associate with Renal Disease in a Population-Based Cohort

Two common missense variants in APOL1 (G1 and G2) have been definitively linked to CKD in black Americans. However, not all individuals with the renal-risk genotype develop CKD, and little is known about how APOL1 variants drive disease. Given the association of APOL1 with HDL particles, which are cleared by the kidney, differences in the level or quality of mutant APOL1‑HDL particles could be causal for disease and might serve as a useful risk stratification marker. We measured plasma levels of G0 (low risk), G1, and G2 APOL1 in 3450 individuals in the Dallas Heart Study using a liquid chromatography-MS method that enabled quantitation of the different variants. Additionally, we characterized native APOL1‑HDL from donors with no or two APOL1 risk alleles by size-exclusion chromatography and analysis of immunopurified APOL1‑HDL particles. Finally, we identified genetic loci associated with plasma APOL1 levels and tested for APOL1-dependent association with renal function. Although we replicated the previous association between APOL1 variant status and renal function in nondiabetic individuals, levels of circulating APOL1 did not associate with microalbuminuria or GFR. Furthermore, the size or known components of APOL1‑HDL did not consistently differ in subjects with the renal-risk genotype. Genetic association studies implicated variants in loci harboring haptoglobin-related protein (HPR), APOL1, and ubiquitin D (UBD) in the regulation of plasma APOL1 levels, but these variants did not associate with renal function. Collectively, these data demonstrate that the risk of renal disease associated with APOL1 is probably not related to circulating levels of the mutant protein.

Association of Lipid-Related Genetic Variants with the Incidence of Atrial Fibrillation: The AFGen Consortium

BACKGROUND

Several studies have shown associations between blood lipid levels and the risk of atrial fibrillation (AF). To test the potential effect of blood lipids with AF risk, we assessed whether previously developed lipid gene scores, used as instrumental variables, are associated with the incidence of AF in 7 large cohorts.

METHODS

We analyzed 64,901 individuals of European ancestry without previous AF at baseline and with lipid gene scores. Lipid-specific gene scores, based on loci significantly associated with lipid levels, were calculated. Additionally, non-pleiotropic gene scores for high-density lipoprotein cholesterol (HDLc) and low-density lipoprotein cholesterol (LDLc) were calculated using SNPs that were only associated with the specific lipid fraction. Cox models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of AF per 1-standard deviation (SD) increase of each lipid gene score.

RESULTS

During a mean follow-up of 12.0 years, 5434 (8.4%) incident AF cases were identified. After meta-analysis, the HDLc, LDLc, total cholesterol, and triglyceride gene scores were not associated with incidence of AF. Multivariable-adjusted HR (95% CI) were 1.01 (0.98-1.03); 0.98 (0.96-1.01); 0.98 (0.95-1.02); 0.99 (0.97-1.02), respectively. Similarly, non-pleiotropic HDLc and LDLc gene scores showed no association with incident AF: HR (95% CI) = 1.00 (0.97-1.03); 1.01 (0.99-1.04).

CONCLUSIONS

In this large cohort study of individuals of European ancestry, gene scores for lipid fractions were not associated with incident AF.

miRNA regulation of LDL-cholesterol metabolism

In the past decade, microRNAs (miRNAs) have emerged as key regulators of circulating levels of lipoproteins. Specifically, recent work has uncovered the role of miRNAs in controlling the levels of atherogenic low-density lipoprotein LDL (LDL)-cholesterol by post-transcriptionally regulating genes involved in very low-density lipoprotein (VLDL) secretion, cholesterol biosynthesis, and hepatic LDL receptor (LDLR) expression. Interestingly, several of these miRNAs are located in genomic loci associated with abnormal levels of circulating lipids in humans. These findings reinforce the interest of targeting this subset of non-coding RNAs as potential therapeutic avenues for regulating plasma cholesterol and triglyceride (TAG) levels. In this review, we will discuss how these new miRNAs represent potential pre-disposition factors for cardiovascular disease (CVD), and putative therapeutic targets in patients with cardiometabolic disorders. This article is part of a Special Issue entitled: MicroRNAs and lipid/energy metabolism and related diseases edited by Carlos Fernández-Hernando and Yajaira Suárez.

New Therapeutic Approaches to the Treatment of Dyslipidemia

Dyslipidemia is a risk factor for atherosclerotic cardiovascular disease (ASCVD). Abundant data indicate that low-density lipoproteins (LDL) are causal for ASCVD; a new class of LDL-lowering medicines, the PCSK9 inhibitors, will address much unmet medical need. Human genetics suggest that triglyceride-rich lipoproteins (TRL) are pro-atherogenic and have pointed to a number of protein regulators of lipoprotein lipase activity that are candidates for therapeutic targeting. Finally, high-density lipoprotein (HDL) cholesterol does not appear to be causally associated with protection from ASCVD, reinforced by the failure of three CETP inhibitors in CV outcome trials, but HDL function remains of interest.

A common variant association study reveals novel susceptibility loci for low HDL-cholesterol levels in ethnic Arabs

The genetic susceptibility to acquiring low high density lipoprotein-cholesterol (LHDLC) levels is not completely elucidated yet. In this study, we performed a common variant association study for harboring this trait in ethnic Arabs. We employed the Affymetrix high-density Axiom Genome-Wide ASI Array (Asian population) providing a coverage of 598,000 single nucleotide variations (SNPs) to genotype 5495 individuals in a two-phase study involving discovery and validation sets of experiments. The rs1800775 [1.31 (1.22-1.42); p = 3.41E-12] in the CETP gene and rs359027 [1.26 (1.16-1.36); p = 2.55E-08] in the LMCD1 gene were significantly associated with LHDLC levels. Furthermore, rs3104435 [1.26 (1.15-1.38); p = 1.19E-06] at the MATN1 locus, rs9835344 [1.16 (1.08-1.26); p = 8.75E-06] in the CNTN6 gene, rs1559997 [1.3 (1.14-1.47); p = 9.48E-06] in the SDS gene and rs1670273 [1.2 (1.1-1.31); p = 4.81E-06] in the DMN/SYNM gene exhibited suggestive association with the disorder. Seven other variants including rs1147169 in the PLCL1 gene, rs10248618 in the DNAH11, rs476155 in the GLIS3, rs7024300 in the ABCA1, intergenic rs10836699, rs11603691 in P2RX3 and rs750134 in CORO1C gene exhibited borderline protective properties. Validation and joint meta-analysis resulted in rs1800775, rs3104435 and rs359027 retaining their predisposing properties, while rs10836699 and rs11603691 showed protective properties. Our data show several predisposing variants across the genome for LHDLC levels in ethnic Arabs.

Epigenetic and genetic variations at the TNNT1 gene locus are associated with HDL-C levels and coronary artery disease

AIM

To assess whether epigenetic and genetic variations at the TNNT1 gene locus are associated with high-density lipoprotein cholesterol (HDL-C) and coronary artery disease (CAD). Patients, materials & methods: TNNT1 DNA methylation and c.-20G>A polymorphism were genotyped in subjects with and without familial hypercholesterolemia (FH).

RESULTS

Lower TNNT1 DNA methylation levels were independently associated with lower HDL-C levels and with the TNNT1 c.-20G>A polymorphism. In FH men, carriers of the TNNT1 c.-20G>A polymorphism had lower HDL-C levels and an increased risk of CAD compared with noncarriers. In non-FH men, a higher TNNT1 DNA methylation level was associated with CAD.

CONCLUSION

These results suggest that TNNT1 genetic and epigenetic variations are associated with HDL-C levels and CAD.

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

Mapping perturbed molecular circuits that underlie complex diseases remains a great challenge. We developed a comprehensive resource of 394 cell type- and tissue-specific gene regulatory networks for human, each specifying the genome-wide connectivity among transcription factors, enhancers, promoters and genes. Integration with 37 genome-wide association studies (GWASs) showed that disease-associated genetic variants--including variants that do not reach genome-wide significance--often perturb regulatory modules that are highly specific to disease-relevant cell types or tissues. Our resource opens the door to systematic analysis of regulatory programs across hundreds of human cell types and tissues (http://regulatorycircuits.org).

Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk

Therapeutic interventions that lower LDL-cholesterol effectively reduce the risk of coronary artery disease (CAD). However, statins, the most widely prescribed LDL-cholesterol lowering drugs, increase diabetes risk. We used genome-wide association study (GWAS) data in the public domain to investigate the relationship of LDL-C and diabetes and identify loci encoding potential drug targets for LDL-cholesterol modification without causing dysglycemia. We obtained summary-level GWAS data for LDL-C from GLGC, glycemic traits from MAGIC, diabetes from DIAGRAM and CAD from CARDIoGRAMplusC4D consortia. Mendelian randomization analyses identified a one standard deviation (SD) increase in LDL-C caused an increased risk of CAD (odds ratio [OR] 1.63 (95 % confidence interval [CI] 1.55, 1.71), which was not influenced by removing SNPs associated with diabetes. LDL-C/CAD-associated SNPs showed consistent effect directions (binomial P = 6.85 × 10⁻⁵). Conversely, a 1-SD increase in LDL-C was causally protective of diabetes (OR 0.86; 95 % CI 0.81, 0.91), however LDL-cholesterol/diabetes-associated SNPs did not show consistent effect directions (binomial P = 0.15). HMGCR, our positive control, associated with LDL-C, CAD and a glycemic composite (derived from GWAS meta-analysis of four glycemic traits and diabetes). In contrast, PCSK9, APOB, LPA, CETP, PLG, NPC1L1 and ALDH2 were identified as “druggable” loci that alter LDL-C and risk of CAD without displaying associations with dysglycemia. In conclusion, LDL-C increases the risk of CAD and the relationship is independent of any association of LDL-C with diabetes. Loci that encode targets of emerging LDL-C lowering drugs do not associate with dysglycemia, and this provides provisional evidence that new LDL-C lowering drugs (such as PCSK9 inhibitors) may not influence risk of diabetes.

Assessment of established HDL-C loci for association with HDL-C levels and type 2 diabetes in Pima Indians

AIMS/HYPOTHESIS

Epidemiological studies in Pima Indians identified elevated levels of HDL-cholesterol (HDL-C) as a protective factor against type 2 diabetes risk in women. We assessed whether HDL-C-associated single-nucleotide polymorphisms (SNPs) also associate with type 2 diabetes in female Pima Indians.

METHODS

Twenty-one SNPs in established HDL-C loci were initially analysed in 2,675 full-heritage Pima Indians. SNPs shown to associate with HDL-C (12 SNPs) were assessed for association with type 2 diabetes in 7,710 Pima Indians (55.6% female sex). The CETP locus provided the strongest evidence for association with HDL-C and was further interrogated by analysing tag SNPs.

RESULTS

Twelve of the 21 SNPs analysed had a significant association with HDL-C in Pima Indians; five SNPs representing four loci (CETP, DOCK6, PPP1R3B and ABCA1) reached genome-wide significance. Three SNPs, at CETP, KLF14 and HNF4A, associated with type 2 diabetes only in female participants with the HDL-C-lowering allele increasing diabetes risk (p values: 3.2 × 10(-4) to 7.7 × 10(-5)); the association remained significant even after adjustment for HDL-C. Additional analysis across CETP identified rs6499863 as having the strongest association with type 2 diabetes in female participants (p = 5.0 × 10(-6)) and this association remained independent of the HDL-C association.

CONCLUSIONS/INTERPRETATION

SNPs at the CETP, HNF4A and KLF14 locus are associated with HDL-C levels and type 2 diabetes (in female participants). However, since HNF4A and KLF14 are established loci for type 2 diabetes, it is unlikely that HDL-C solely mediates these associations.

Significant impact of miRNA-target gene networks on genetics of human complex traits

The impact of microRNA (miRNA) on the genetics of human complex traits, especially in the context of miRNA-target gene networks, has not been fully assessed. Here, we developed a novel analytical method, MIGWAS, to comprehensively evaluate enrichment of genome-wide association study (GWAS) signals in miRNA–target gene networks. We applied the method to the GWAS results of the 18 human complex traits from >1.75 million subjects, and identified significant enrichment in rheumatoid arthritis (RA), kidney function, and adult height (P < 0.05/18 = 0.0028, most significant enrichment in RA with P = 1.7 × 10⁻⁴). Interestingly, these results were consistent with current literature-based knowledge of the traits on miRNA obtained through the NCBI PubMed database search (adjusted P = 0.024). Our method provided a list of miRNA and target gene pairs with excess genetic association signals, part of which included drug target genes. We identified a miRNA (miR-4728-5p) that downregulates PADI2, a novel RA risk gene considered as a promising therapeutic target (rs761426, adjusted P = 2.3 × 10⁻⁹). Our study indicated the significant impact of miRNA–target gene networks on the genetics of human complex traits, and provided resources which should contribute to drug discovery and nucleic acid medicine.

Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants

Variation in human lifespan is 20 to 30% heritable in twins but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data, excluding early deaths). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. In GWAS, a nicotine receptor locus(CHRNA3, previously associated with increased smoking and lung cancer) was associated with fathers' survival. Less common variants requiring further confirmation were also identified. Offspring of longer lived parents had more protective alleles for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate analyses, variants in the TOMM40/APOE locus were associated with longevity, but FOXO variants were not. Associations between extreme longevity (mother >=98 years, fathers >=95 years, n=1,339) and disease alleles were similar, with an additional association with HDL cholesterol (p=5.7x10-3). These results support a multiple protective factors model influencing lifespan and longevity (top 1% survival) in humans, with prominent roles for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable.

Integrated analyses of gene expression and genetic association studies in a founder population

Genome-wide association studies (GWASs) have become a standard tool for dissecting genetic contributions to disease risk. However, these studies typically require extraordinarily large sample sizes to be adequately powered. Strategies that incorporate functional information alongside genetic associations have proved successful in increasing GWAS power. Following this paradigm, we present the results of 20 different genetic association studies for quantitative traits related to complex diseases, conducted in the Hutterites of South Dakota. To boost the power of these association studies, we collected RNA-sequencing data from lymphoblastoid cell lines for 431 Hutterite individuals. We then used Sherlock, a tool that integrates GWAS and expression quantitative trait locus (eQTL) data, to identify weak GWAS signals that are also supported by eQTL data. Using this approach, we found novel associations with quantitative phenotypes related to cardiovascular disease, including carotid intima-media thickness, left atrial volume index, monocyte count and serum YKL-40 levels.

The effect of genetic variation in PCSK9 on the LDL-cholesterol response to statin therapy

Statins (HMG-CoA reductase inhibitors) lower low-density lipoprotein cholesterol (LDL-C) and prevent cardiovascular disease. However, there is wide individual variation in LDL-C response. Drugs targeting proprotein convertase subtilin/kexin type 9 (PCSK9) lower LDL-C and will be used with statins. PCSK9 mediates the degradation of LDL receptors (LDLRs). Therefore, a greater LDL-C response to statins would be expected in individuals with PCSK9 loss-of-function (LOF) variants because LDLR degradation is reduced. To examine this hypothesis, the effect of 11 PCSK9 functional variants on statin response was determined in 669 African Americans. One LOF variant, rs11591147 (p.R46L) was significantly associated with LDL-C response to statin (P=0.002). In the three carriers, there was a 55.6% greater LDL-C reduction compared with non-carriers. Another functional variant, rs28362261 (p.N425S), was marginally associated with statin response (P=0.0064).The effect of rs11591147 was present in individuals of European ancestry (N=2388, P=0.054). The therapeutic effect of statins may be modified by genetic variation in PCSK9.

Mapping and Congenic Dissection of Genetic Loci Contributing to Hyperglycemia and Dyslipidemia in Mice

Background

Patients with dyslipidemia have an increased risk of developing type 2 diabetes, and diabetic patients often have dyslipidemia. Potential genetic connections of fasting plasma glucose with plasma lipid profile were evaluated using hyperlipidemic mice.

Methods

225 male F₂ mice were generated from BALB/cJ (BALB) and SM/J(SM) Apoe-deficient (Apoe^−/−) mice and fed a Western diet for 5 weeks. Fasting plasma glucose and lipid levels of F₂ mice were measured before and after 5 weeks of Western diet and quantitative trait locus (QTL) analysis was performed using data collected from these two time points. 144 SNP(single nucleotide polymorphism) markers across the entire genome were typed.

Results

One major QTL (logarithm of odds ratio (LOD): 6.46) peaked at 12.7 cM on chromosome 9,Bglu16, and 3 suggestive QTLs on chromosomes 15, 18 and X were identified for fasting glucose, and over 10 loci identified for lipid traits. Bglu16 was adjacent to a major QTL, Hdlq17, for high-density lipoprotein (HDL) cholesterol (LOD: 6.31, peak: 19.1 cM). A congenic strain with a donor chromosomal region harboring Bglu16 and Hdlq17 on the Apoe^−/− background showed elevations in plasma glucose and HDL levels. Fasting glucose levels were significantly correlated with non-HDL cholesterol and triglyceride levels, especially on the Western diet, but only marginally correlated with HDL levels in F₂ mice.

Conclusions

We have demonstrated a correlative relationship between fasting glucose and plasma lipids in a segregating F₂ population under hyperlipidemic conditions, and this correlation is partially due to genetic linkage between the two disorders.

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci

BACKGROUND

Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs.

METHODS

We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT), to identify protein-coding gene association with 14 cardiometabolic (CMD) related traits across 6 publicly available genome wide association (GWA) meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1.

RESULTS

We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes.

CONCLUSIONS

We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and adds significant value with respect to its potential for identifying multiple novel and clinically relevant trait associations.

Integrative approaches for large-scale transcriptome-wide association studies

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼ 3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

Interaction of Insulin Resistance and Related Genetic Variants With Triglyceride-Associated Genetic Variants

BACKGROUND

Several studies suggest that some triglyceride-associated single-nucleotide polymorphisms (SNPs) have pleiotropic and opposite effects on glycemic traits. This potentially implicates them in pathways such as de novo lipogenesis, which is presumably upregulated in the context of insulin resistance. We therefore tested whether the association of triglyceride-associated SNPs with triglyceride levels differs according to one's level of insulin resistance.

METHODS AND RESULTS

In 3 cohort studies (combined n=12 487), we tested the interaction of established triglyceride-associated SNPs (individually and collectively) with several traits related to insulin resistance, on triglyceride levels. We also tested the interaction of triglyceride SNPs with fasting insulin-associated SNPs, individually and collectively, on triglyceride levels. We find significant interactions of a weighted genetic risk score for triglycerides with insulin resistance on triglyceride levels (Pinteraction=2.73×10(-11) and Pinteraction=2.48×10(-11) for fasting insulin and homeostasis model assessment of insulin resistance, respectively). The association of the triglyceride genetic risk score with triglyceride levels is >60% stronger among those in the highest tertile of homeostasis model assessment of insulin resistance compared with those in the lowest tertile. Individual SNPs contributing to this trend include those in/near GCKR, CILP2, and IRS1, whereas PIGV-NROB2 and LRPAP1 display an opposite trend of interaction. In the pooled data set, we also identify a SNP-by-SNP interaction involving a triglyceride-associated SNP, rs4722551 near MIR148A, with a fasting insulin-associated SNP, rs4865796 in ARL15 (Pinteraction=4.1×10(-5)).

CONCLUSIONS

Our findings may thus provide genetic evidence for the upregulation of triglyceride levels in insulin-resistant individuals, in addition to identifying specific genetic loci and a SNP-by-SNP interaction implicated in this process.

Causal Role of Alcohol Consumption in an Improved Lipid Profile: The Atherosclerosis Risk in Communities (ARIC) Study

INTRODUCTION

Health benefits of low-to-moderate alcohol consumption may operate through an improved lipid profile. A Mendelian randomization (MR) approach was used to examine whether alcohol consumption causally affects lipid levels.

METHODS

This analysis involved 10,893 European Americans (EA) from the Atherosclerosis Risk in Communities (ARIC) study. Common and rare variants in alcohol dehydrogenase and acetaldehyde dehydrogenase genes were evaluated for MR assumptions. Five variants, residing in the ADH1B, ADH1C, and ADH4 genes, were selected as genetic instruments and were combined into an unweighted genetic score. Triglycerides (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-c) and its subfractions (HDL2-c and HDL3-c), low-density lipoprotein cholesterol (LDL-c), small dense LDL-c (sdLDL-c), apolipoprotein B (apoB), and lipoprotein (a) (Lp(a)) levels were analyzed.

RESULTS

Alcohol consumption significantly increased HDL2-c and reduced TG, total cholesterol, LDL-c, sdLDL-c, and apoB levels. For each of these lipids a non-linear trend was observed. Compared to the first quartile of alcohol consumption, the third quartile had a 12.3% lower level of TG (p < 0.001), a 7.71 mg/dL lower level of total cholesterol (p = 0.007), a 10.3% higher level of HDL2-c (p = 0.007), a 6.87 mg/dL lower level of LDL-c (p = 0.012), a 7.4% lower level of sdLDL-c (p = 0.037), and a 3.5% lower level of apoB (p = 0.058, poverall = 0.022).

CONCLUSIONS

This study supports the causal role of regular low-to-moderate alcohol consumption in increasing HDL2-c, reducing TG, total cholesterol, and LDL-c, and provides evidence for the novel finding that low-to-moderate consumption of alcohol reduces apoB and sdLDL-c levels among EA. However, given the nonlinearity of the effect of alcohol consumption, even within the range of low-to-moderate drinking, increased consumption does not always result in a larger benefit.

Protein kinase STK25 controls lipid partitioning in hepatocytes and correlates with liver fat content in humans

AIMS/HYPOTHESIS

Type 2 diabetes is closely associated with pathological lipid accumulation in the liver, which is suggested to actively contribute to the development of insulin resistance. We recently identified serine/threonine protein kinase 25 (STK25) as a regulator of liver steatosis, whole-body glucose tolerance and insulin sensitivity in a mouse model system. The aim of this study was to assess the role of STK25 in the control of lipid metabolism in human liver.

METHODS

Intracellular fat deposition, lipid metabolism and insulin sensitivity were studied in immortalised human hepatocytes (IHHs) and HepG2 hepatocellular carcinoma cells in which STK25 was overexpressed or knocked down by small interfering RNA. The association between STK25 mRNA expression in human liver biopsies and hepatic fat content was analysed.

RESULTS

Overexpression of STK25 in IHH and HepG2 cells enhanced lipid deposition by suppressing β-oxidation and triacylglycerol (TAG) secretion, while increasing lipid synthesis. Conversely, knockdown of STK25 attenuated lipid accumulation by stimulating β-oxidation and TAG secretion, while inhibiting lipid synthesis. Furthermore, TAG hydrolase activity was repressed in hepatocytes overexpressing STK25 and reciprocally increased in cells with STK25 knockdown. Insulin sensitivity was reduced in STK25-overexpressing cells and enhanced in STK25-deficient hepatocytes. We also found a statistically significant positive correlation between STK25 mRNA expression in human liver biopsies and hepatic fat content.

CONCLUSIONS/INTERPRETATION

Our data suggest that STK25 regulates lipid partitioning in human liver cells by controlling TAG synthesis as well as lipolytic activity and thereby NEFA release from lipid droplets for β-oxidation and TAG secretion. Our findings highlight STK25 as a potential drug target for the prevention and treatment of type 2 diabetes.

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.

Evaluation of pleiotropic effects among common genetic loci identified for cardio-metabolic traits in a Korean population

Background

The genetic contribution to complex diseases or traits, including cardio-metabolic traits, has been elucidated recently by large-scale genome-wide association studies. These genome-wide association studies have indicated that most pleiotropic loci contain genes associated with lipids. Clinically, lipid related abnormalities are strongly associated with other diseases such as type 2 diabetes, coronary artery disease and hypertension. The aim of this study was to evaluate the shared genetic background of lipids and other cardio-metabolic traits.

Methods

We conducted meta-analyses of the association between 157 published lipid-associated loci and 10 cardio-metabolic traits in 14,028 Korean individuals genotyped using the Exome chip (Illumina HumanExome BeadChip). We also examined whether the pleiotropic effects of such loci constituted independent (i.e., biological) pleiotropy or mediated pleiotropy in these metabolic pathways.

Results

Eighteen lipid-associated loci were significantly associated with one of six cardio-metabolic traits after correction for multiple testing (P < 3.70 × 10⁻⁴). Region 12q24.12 had pleiotropic effects on fasting plasma glucose, blood pressure and obesity-related traits (body mass index and waist-hip ratio) independent of its effects on the lipid profile. Lipid risk scores, calculated according to whether or not subjects carried the risk allele for lipid traits, were significantly associated with fasting plasma glucose, blood pressure and obesity-related traits.

Conclusions

The 12q24.12 region showed ethnic-specific genetic pleiotropy among cardio-metabolic traits in this study. Our findings may help to account for molecular mechanisms based on shared genetic background underlying not only dyslipidemia, but also cardiovascular disease and type 2 diabetes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-016-0337-1) contains supplementary material, which is available to authorized users.

Low Levels of HDL in Fragile X Syndrome Patients

Fragile X syndrome (FXS) is the most common form of familial mental retardation and one of the leading known causes of autism. The mutation responsible for FXS is a large expansion of the CGG repeats in the promoter region of the FMR1 gene resulting in the transcriptional silencing of the gene in the pathophysiology of Fragile X syndrome was hypothesized. 23 male patients affected by Fragile X syndrome (full mutation in the FMR1 gene) and 24 controls were included in the study. The serum levels of HDL-C were lower in FXS patients (p < 0.001). The serum levels triacylglycerols were higher in FXS patients (p = 0.007) Further study involving larger samples are necessary to confirm the results and define the health implications for abnormal lipid levels in FXS patients.

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.

Clinical applications of molecular genetic discoveries

Genome-wide association studies of complex traits have mapped >15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as next-generation sequencing to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high-throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single-gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population and in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: "The good physician treats the disease; the great physician treats the patient who has the disease." The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease.

Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study

BACKGROUND

The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading genetic approach to the identification of novel biological pathways underlying diseases in humans. Until recently, GWAS in ischaemic stroke have been limited by small sample sizes and have yielded few loci associated with ischaemic stroke. We did a large-scale GWAS to identify additional susceptibility genes for stroke and its subtypes.

METHODS

To identify genetic loci associated with ischaemic stroke, we did a two-stage GWAS. In the first stage, we included 16 851 cases with state-of-the-art phenotyping data and 32 473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtypes of ischaemic stroke were recorded by centrally trained and certified investigators who used the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identifying samples that were genotyped on nearly identical arrays and were of similar genetic ancestral background. We cleaned and imputed data by use of dense imputation reference panels generated from whole-genome sequence data. We did genome-wide testing to identify stroke-associated loci within each stratum for each available phenotype, and we combined summary-level results using inverse variance-weighted fixed-effects meta-analysis. In the second stage, we did in-silico lookups of 1372 single nucleotide polymorphisms identified from the first stage GWAS in 20 941 cases and 364 736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification system, in accordance with local standards. Results from the two stages were then jointly analysed in a final meta-analysis.

FINDINGS

We identified a novel locus (G allele at rs12122341) at 1p13.2 near TSPAN2 that was associated with large artery atherosclerosis-related stroke (first stage odds ratio [OR] 1·21, 95% CI 1·13-1·30, p=4·50 × 10^-8; joint OR 1·19, 1·12-1·26, p=1·30 × 10^-9). Our results also supported robust associations with ischaemic stroke for four other loci that have been reported in previous studies, including PITX2 (first stage OR 1·39, 1·29-1·49, p=3·26 × 10^-19; joint OR 1·37, 1·30-1·45, p=2·79 × 10^-32) and ZFHX3 (first stage OR 1·19, 1·11-1·27, p=2·93 × 10^-7; joint OR 1·17, 1·11-1·23, p=2·29 × 10^-10) for cardioembolic stroke, and HDAC9 (first stage OR 1·29, 1·18-1·42, p=3·50 × 10^-8; joint OR 1·24, 1·15-1·33, p=4·52 × 10^-9) for large artery atherosclerosis stroke. The 12q24 locus near ALDH2, which has previously been associated with all ischaemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke (first stage OR 1·20, 1·12-1·28, p=6·82 × 10^-8; joint OR 1·17, 1·11-1·23, p=2·92 × 10^-9). Other loci associated with stroke in previous studies, including NINJ2, were not confirmed.

INTERPRETATION

Our results suggest that all ischaemic stroke-related loci previously implicated by GWAS are subtype specific. We identified a novel gene associated with large artery atherosclerosis stroke susceptibility. Follow-up studies will be necessary to establish whether the locus near TSPAN2 can be a target for a novel therapeutic approach to stroke prevention. In view of the subtype-specificity of the associations detected, the rich phenotyping data available in the Stroke Genetics Network (SiGN) are likely to be crucial for further genetic discoveries related to ischaemic stroke.

FUNDING

US National Institute of Neurological Disorders and Stroke, National Institutes of Health.

Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease

Metabolites derived from dietary choline and L-carnitine, such as trimethylamine N-oxide and betaine, have recently been identified as novel risk factors for atherosclerosis in mice and humans. We sought to identify genetic factors associated with plasma betaine levels and determine their effect on risk of coronary artery disease (CAD). A two-stage genome-wide association study (GWAS) identified two significantly associated loci on chromosomes 2q34 and 5q14.1. The lead variant on 2q24 (rs715) localizes to carbamoyl-phosphate synthase 1 (CPS1), which encodes a mitochondrial enzyme that catalyses the first committed reaction and rate-limiting step in the urea cycle. Rs715 is also significantly associated with decreased levels of urea cycle metabolites and increased plasma glycine levels. Notably, rs715 yield a strikingly significant and protective association with decreased risk of CAD in only women. These results suggest that glycine metabolism and/or the urea cycle represent potentially novel sex-specific mechanisms for the development of atherosclerosis.

Dietary choline metabolites, such as trimethylamine N-oxide and betaine, have been associated with coronary artery disease (CAD). Here, Hartiala et al. identify two genetic loci for betaine levels on chromosomes 2q34 and 5q14.1 and find that the 2q34 locus was also associated with other pathway intermediates, and decreased risk of CAD in women.

Pancreatic Cancer Genetics

Although relatively rare, pancreatic tumors are highly lethal [1]. In the United States, an estimated 48,960 individuals will be diagnosed with pancreatic cancer and 40,560 will die from this disease in 2015 [1]. Globally, 337,872 new pancreatic cancer cases and 330,391 deaths were estimated in 2012 [2]. In contrast to most other cancers, mortality rates for pancreatic cancer are not improving; in the US, it is predicted to become the second leading cause of cancer related deaths by 2030 [3, 4]. The vast majority of tumors arise in the exocrine pancreas, with pancreatic ductal adenocarcinoma (PDAC) accounting for approximately 95% of tumors. Tumors arising in the endocrine pancreas (pancreatic neuroendocrine tumors) represent less than 5% of all pancreatic tumors [5]. Smoking, type 2 diabetes mellitus (T2D), obesity and pancreatitis are the most consistent epidemiological risk factors for pancreatic cancer [5]. Family history is also a risk factor for developing pancreatic cancer with odds ratios (OR) ranging from 1.7-2.3 for first-degree relatives in most studies, indicating that shared genetic factors may play a role in the etiology of this disease [6-9]. This review summarizes the current knowledge of germline pancreatic cancer risk variants with a special emphasis on common susceptibility alleles identified through Genome Wide Association Studies (GWAS).

Looking beyond GWAS: allele-specific transcription factor binding drives the association of GALNT2 to HDL-C plasma levels

BACKGROUND

Plasma levels of high-density lipoprotein cholesterol (HDL-C) have been associated to cardiovascular disease. The high heritability of HDL-C plasma levels has been an incentive for several genome wide association studies (GWASs) which identified, among others, variants in the first intron of the GALNT2 gene strongly associated to HDL-C levels. However, the lead GWAS SNP associated to HDL-C levels in this genomic region, rs4846914, is located outside of transcription factor (TF) binding sites defined by chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) experiments in the ENCODE project and is therefore unlikely to be functional. In this study we apply a bioinformatics approach which rely on the premise that ChIP-seq reads can identify allele specific binding of a TF at cell specific regulatory elements harboring allele specific SNPs (AS-SNPs). EMSA and luciferase assays were used to validate the allele specific binding and to test the enhancer activity of the regulatory element harboring the AS-SNP rs4846913 as well as the neighboring rs2144300 which are in high LD with rs4846914.

FINDINGS

Using luciferase assays we found that rs4846913 and the neighboring rs2144300 displayed allele specific enhancer activity. We propose that an inhibitor binds preferentially to the rs4846913-C allele with an inhibitory boost from the synergistic binding of other TFs at the neighboring SNP rs2144300. These events influence the transcription level of GALNT2.

CONCLUSIONS

The results suggest that rs4846913 and rs2144300 drive the association to HDL-C plasma levels through an inhibitory regulation of GALNT2 rather than the reported lead GWAS SNP rs4846914.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.

Genome-wide association studies (GWAS) typically generate lists of trait- or disease-associated SNPs. Yet, such output sheds little light on the underlying molecular mechanisms and tools are needed to extract biological insight from the results at the SNP level. Pathway analysis tools integrate signals from multiple SNPs at various positions in the genome in order to map associated genomic regions to well-established pathways, i.e., sets of genes known to act in concert. The nature of GWAS association results requires specifically tailored methods for this task. Here, we present Pascal (Pathway scoring algorithm), a tool that allows gene and pathway-level analysis of GWAS association results without the need to access the original genotypic data. Pascal was designed to be fast, accurate and to have high power to detect relevant pathways. We extensively tested our approach on a large collection of real GWAS association results and saw better discovery of confirmed pathways than with other popular methods. We believe that these results together with the ease-of-use of our publicly available software will allow Pascal to become a useful addition to the toolbox of the GWAS community.