Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Genetic susceptibility, dietary cholesterol intake, and plasma cholesterol levels in a Chinese population

Accompanied with nutrition transition, non-HDL-C levels of individuals in Asian countries has increased rapidly, which has caused the global epicenter of nonoptimal cholesterol to shift from Western countries to Asian countries. Thus, it is critical to underline major genetic and dietary determinants. In the current study of 2,330 Chinese individuals, genetic risk scores (GRSs) were calculated for total cholesterol (TC; GRS_TC, 57 SNPs), LDL-C (GRS_LDL-C, 45 SNPs), and HDL-C (GRS_HDL-C, 65 SNPs) based on SNPs from the Global Lipid Genetics Consortium study. Cholesterol intake was estimated by a 74-item food-frequency questionnaire. Associations of dietary cholesterol intake with plasma TC and LDL-C strengthened across quartiles of the GRS_TC (effect sizes: -0.29, 0.34, 2.45, and 6.47; P _interaction = 0.002) and GRS_LDL-C (effect sizes: -1.35, 0.17, 5.45, and 6.07; P _interaction = 0.001), respectively. Similar interactions with non-HDL-C were observed between dietary cholesterol and GRS_TC (P _interaction = 0.001) and GRS_LDL-C (P _interaction = 0.004). The adverse effects of GRS_TC on TC (effect sizes across dietary cholesterol quartiles: 0.51, 0.82, 1.21, and 1.31; P _interaction = 0.023) and GRS_LDL-C on LDL-C (effect sizes across dietary cholesterol quartiles: 0.66, 0.52, 1.12, and 1.56; P _interaction = 0.020) were more profound in those having higher cholesterol intake compared with those with lower intake. Our findings suggest significant interactions between genetic susceptibility and dietary cholesterol intake on plasma cholesterol profiles in a Chinese population.

The APOA5-rs662799 Polymorphism Is a Determinant of Dyslipidemia in Vietnamese Primary School Children

Apolipoprotein A-V encoded by apolipoprotein 5 (APOA5) gene plays an important role in lipid metabolism, especially in the regulation of plasma triglycerol levels. The study aimed to evaluate the association of the APOA5-rs662799 polymorphism with dyslipidemia in Vietnamese children and the potential modification of obesity-related traits (body mass index, waist circumference, hip circumference, and waist-to-hip ratio) on this association. A case-control study was conducted with a total of 154 dyslipidemia cases and 389 controls at the age of 6 to 10 recruited at 31 primary schools in Hanoi city of Vietnam. Genotype for APOA5-rs662799 polymorphism was determined by the restriction fragment length polymorphism analysis. The association of APOA5-rs662799 polymorphism with dyslipidemia adjusting for age, sex, residence, and obesity-related traits was analyzed by binary logistic regression analysis. The results showed that in comparison with T/T and T/C carriers, the C/C carriers had a higher concentration of serum TAG in cases (p =0.049). Carriers of the C allele (C/C + T/C) had higher risk for developing dyslipidemia and hypertriglyceridemia than subjects with T/T genotype (odds ratio, OR = 1.7, p =0.0062 and OR = 1.6, p = 0.026, respectively). The association remained significant after adjusting for age, gender, residence, and obesity status (OR = 1.75, p = 0.006 and OR = 1.53, p = 0.049, respectively) or other obesity-related traits. The study suggested that the APOA5-rs662799 polymorphism may be a determinant of dyslipidemia and hypertriglyceridemia in Vietnamese children, independent of obesity-related traits.

Characterization and in silico analyses of the BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers

Pathogenic variants in the coding regions of the BRCA1/2 lead dysfunctional or nonfunctional BRCA proteins however the contribution of non-coding BRCA1/2 variants to BRCA-related disease risk has not been fully elucidated. Thus, we characterized the functional impact of both coding and non-coding BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers. The data were produced by resequencing the exons and exon-intron junctions of the BRCA1/2 in 125 individuals and were comprehensively analyzed by using bioinformatics tools and databases. A total of 96 variants (59 coding and 37 non-coding) including 7 novel variants were identified and analyzed for their functional importance. We identified 11 missense variants that potentially affect protein function; 22 variants were likely to alter different types of posttranslational modifications. Also, multiple non-coding BRCA1/2 variants were found to reside in the critical regulatory regions that have the potential to act as eQTLs and affect alternative splicing. The results of our study shed light on the possible contributions of not only coding variants but also non-coding BRCA1/2 variants in BRCRA-related cancers. Further investigation is required to fully understand their potential associations with phenotypes which may ultimately lead their utilization on cancer management as a biomarker.

CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information

MOTIVATION

Genome-wide association studies (GWASs) have been successful in identifying many genetic variants associated with complex traits. However, the mechanistic links between these variants and complex traits remain elusive. A scientific hypothesis is that genetic variants influence complex traits at the organismal level via affecting cellular traits, such as regulating gene expression and altering protein abundance. Although earlier works have already presented some scientific insights about this hypothesis and their findings are very promising, statistical methods that effectively harness multilayered data (e.g. genetic variants, cellular traits and organismal traits) on a large scale for functional and mechanistic exploration are highly demanding.

RESULTS

In this study, we propose a collaborative mixed model (CoMM) to investigate the mechanistic role of associated variants in complex traits. The key idea is built upon the emerging scientific evidence that genetic effects at the cellular level are much stronger than those at the organismal level. Briefly, CoMM combines two models: the first model relating gene expression with genotype and the second model relating phenotype with predicted gene expression using the first model. The two models are fitted jointly in CoMM, such that the uncertainty in predicting gene expression has been fully accounted. To demonstrate the advantages of CoMM over existing methods, we conducted extensive simulation studies, and also applied CoMM to analyze 25 traits in NFBC1966 and Genetic Epidemiology Research on Aging (GERA) studies by integrating transcriptome information from the Genetic European in Health and Disease (GEUVADIS) Project. The results indicate that by leveraging regulatory information, CoMM can effectively improve the power of prioritizing risk variants. Regarding the computational efficiency, CoMM can complete the analysis of NFBC1966 dataset and GERA datasets in 2 and 18 min, respectively.

AVAILABILITY AND IMPLEMENTATION

The developed R package is available at https://github.com/gordonliu810822/CoMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A fast and powerful eQTL weighted method to detect genes associated with complex trait using GWAS summary data

Although genomewide association studies (GWASs) have identified many genetic variants underlying complex traits, a large fraction of heritability still remains unexplained. Integrative analysis that incorporates additional information, such as expression quantitativetrait locus (eQTL) data into sequencing studies (denoted as transcriptomewide association study [TWAS]), can aid the discovery of trait-associated genetic variants. However, general TWAS methods only incorporate one eQTL-derived weight (e.g., cis-effect), and thus can suffer a substantial loss of power when the single estimated cis-effect is not predictive for the effect size of a genetic variant or when there are estimation errors in the estimated cis-effect, or if the data are not consistent with the model assumption. In this study, we propose an omnibus test (OT) which utilizes a Cauchy association test to integrate association evidence demonstrated by three different traditional tests (burden test, quadratic test, and adaptive test) using GWAS summary data with multiple eQTL-derived weights. The p value of the proposed test can be calculated analytically, and thus it is fast and efficient. We applied our proposed test to two schizophrenia (SCZ) GWAS summary data sets and two lipids trait (HDL) GWAS summary data sets. Compared with the three traditional tests, our proposed OT can identify more trait-associated genes.

A gene-diet interaction-based score predicts response to dietary fat in the Women's Health Initiative

BACKGROUND

Although diet response prediction for cardiometabolic risk factors (CRFs) has been demonstrated using single genetic variants and main-effect genetic risk scores, little investigation has gone into the development of genome-wide diet response scores.

OBJECTIVE

We sought to leverage the multistudy setup of the Women's Health Initiative cohort to generate and test genetic scores for the response of 6 CRFs (BMI, systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and fasting glucose) to dietary fat.

METHODS

A genome-wide interaction study was undertaken for each CRF in women (n ∼ 9000) not participating in the dietary modification (DM) trial, which focused on the reduction of dietary fat. Genetic scores based on these analyses were developed using a pruning-and-thresholding approach and tested for the prediction of 1-y CRF changes as well as long-term chronic disease development in DM trial participants (n ∼ 5000).

RESULTS

Only 1 of these genetic scores, for LDL cholesterol, predicted changes in the associated CRF. This 1760-variant score explained 3.7% (95% CI: 0.09, 11.9) of the variance in 1-y LDL cholesterol changes in the intervention arm but was unassociated with changes in the control arm. In contrast, a main-effect genetic risk score for LDL cholesterol was not useful for predicting dietary fat response. Further investigation of this score with respect to downstream disease outcomes revealed suggestive differential associations across DM trial arms, especially with respect to coronary heart disease and stroke subtypes.

CONCLUSIONS

These results lay the foundation for the combination of many genome-wide gene-diet interactions for diet response prediction while highlighting the need for further research and larger samples in order to achieve robust biomarkers for use in personalized nutrition.

Legacy Data Confound Genomics Studies

Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

Carotid Intima-Media Thickness: Novel Loci, Sex-Specific Effects, and Genetic Correlations With Obesity and Glucometabolic Traits in UK Biobank

OBJECTIVE

Atherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultrasound measurement of the carotid intima-media thickness (cIMT) can be used to measure vascular remodeling, which is indicative of atherosclerosis. Genome-wide association studies have identified many genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here, we conducted genome-wide association analyses in UKB (UK Biobank; N=22 179), the largest single study with consistent cIMT measurements. Approach and Results: We used BOLT-LMM software to run linear regression of cIMT in UKB, adjusted for age, sex, and genotyping chip. In white British participants, we identified 5 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a locus on chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body mass index and glucometabolic traits were also observed. Two loci influenced risk of ischemic heart disease.

CONCLUSIONS

These findings replicate previously reported associations, highlight novel biology, and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

Biological Role of Unsaturated Fatty Acid Desaturases in Health and Disease

Polyunsaturated fatty acids (PUFAs) are considered one of the most important components of cells that influence normal development and function of many organisms, both eukaryotes and prokaryotes. Unsaturated fatty acid desaturases play a crucial role in the synthesis of PUFAs, inserting additional unsaturated bonds into the acyl chain. The level of expression and activity of different types of desaturases determines profiles of PUFAs. It is well recognized that qualitative and quantitative changes in the PUFA profile, resulting from alterations in the expression and activity of fatty acid desaturases, are associated with many pathological conditions. Understanding of underlying mechanisms of fatty acid desaturase activity and their functional modification will facilitate the development of novel therapeutic strategies in diseases associated with qualitative and quantitative disorders of PUFA.

Identifying small-effect genetic associations overlooked by the conventional fixed-effect model in a large-scale meta-analysis of coronary artery disease

MOTIVATION

Common small-effect genetic variants that contribute to human complex traits and disease are typically identified using traditional fixed-effect (FE) meta-analysis methods. However, the power to detect genetic associations under FE models deteriorates with increasing heterogeneity, so that some small-effect heterogeneous loci might go undetected. A modified random-effects meta-analysis approach (RE2) was previously developed that is more powerful than traditional fixed and random-effects methods at detecting small-effect heterogeneous genetic associations, the method was updated (RE2C) to identify small-effect heterogeneous variants overlooked by traditional fixed-effect meta-analysis. Here, we re-appraise a large-scale meta-analysis of coronary disease with RE2C to search for small-effect genetic signals potentially masked by heterogeneity in a FE meta-analysis.

RESULTS

Our application of RE2C suggests a high sensitivity but low specificity of this approach for discovering small-effect heterogeneous genetic associations. We recommend that reports of small-effect heterogeneous loci discovered with RE2C are accompanied by forest plots and standardized predicted random-effects statistics to reveal the distribution of genetic effect estimates across component studies of meta-analyses, highlighting overly influential outlier studies with the potential to inflate genetic signals.

AVAILABILITY AND IMPLEMENTATION

Scripts to calculate standardized predicted random-effects statistics and generate forest plots are available in the getspres R package entitled from https://magosil86.github.io/getspres/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-Expression Profiling Analysis

Dyslipidemia is a major risk factor for cardiovascular disease. Although many genetic factors have been unveiled, a large fraction of the phenotypic variance still needs further investigation. Chromosome 1 (Chr 1) harbors multiple gene loci that regulate blood lipid levels, and identifying functional genes in these loci has proved challenging. We constructed a mouse population, Chr 1 substitution lines (C1SLs), where only Chr 1 differs from the recipient strain C57BL/6J (B6), while the remaining chromosomes are unchanged. Therefore, any phenotypic variance between C1SLs and B6 can be attributed to the differences in Chr 1. In this study, we assayed plasma lipid and glucose levels in 13 C1SLs and their recipient strain B6. Through weighted gene co-expression network analysis of liver transcriptome and “guilty-by-association” study, eight associated modules of plasma lipid and glucose were identified. Further joint analysis of human genome wide association studies revealed 48 candidate genes. In addition, 38 genes located on Chr 1 were also uncovered, and 13 of which have been functionally validated in mouse models. These results suggest that C1SLs are ideal mouse models to identify functional genes on Chr 1 associated with complex traits, like dyslipidemia, by using gene co-expression network analysis.

Genome-wide association study of metabolic syndrome in Korean populations

Metabolic syndrome (MetS) which is caused by obesity and insulin resistance, is well known for its predictive capability for the risk of type 2 diabetes mellitus and cardiovascular disease. The development of MetS is associated with multiple genetic factors, environmental factors and lifestyle. We performed a genome-wide association study to identify single-nucleotide polymorphism (SNP) related to MetS in large Korean population based samples of 1,362 subjects with MetS and 6,061 controls using the Axiom^® Korean Biobank Array 1.0. We replicated the data in another sample including 502 subjects with MetS and 1,751 controls. After adjusting for age and sex, rs662799 located in the APOA5 gene were significantly associated with MetS. 15 SNPs in GCKR, C2orf16, APOA5, ZPR1, and BUD13 were associated with high triglyceride (TG). 14 SNPs in APOA5, ALDH1A2, LIPC, HERPUD1, and CETP, and 2 SNPs in MTNR1B were associated with low high density lipoprotein cholesterol (HDL-C) and high fasting blood glucose respectively. Among these SNPs, 6 TG SNPs: rs1260326, rs1260333, rs1919127, rs964184, rs2075295 and rs1558861 and 11 HDL-C SNPs: rs4775041, rs10468017, rs1800588, rs72786786, rs173539, rs247616, rs247617, rs3764261, rs4783961, rs708272, and rs7499892 were first discovered in Koreans. Additional research is needed to confirm these 17 novel SNPs in Korean population.

Progressive effects of single-nucleotide polymorphisms on 16 phenotypic traits based on longitudinal data

Background

There are many research studies have estimated the heritability of phenotypic traits, but few have considered longitudinal changes in several phenotypic traits together.

Objective

To evaluate the progressive effect of single nucleotide polymorphisms (SNPs) on prominent health-related phenotypic traits by determining SNP-based heritability (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h_{snp}^{2}$$\end{document}hsnp2) using longitudinal data.

Methods

Sixteen phenotypic traits associated with major health indices were observed biennially for 6843 individuals with 10-year follow-up in a Korean community-based cohort. Average SNP heritability and longitudinal changes in the total period were estimated using a two-stage model. Average and periodic differences for each subject were considered responses to estimate SNP heritability. Furthermore, a genome-wide association study (GWAS) was performed for significant SNPs.

Results

Each SNP heritability for the phenotypic mean of all sixteen traits through 6 periods (baseline and five follow-ups) were significant. Gradually, the forced vital capacity in one second (FEV1) reflected the only significant SNP heritability among longitudinal changes at a false discovery rate (FDR)-adjusted 0.05 significance level (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h_{snp}^{2} = 0.171$$\end{document}hsnp2=0.171, FDR = 0.0012). On estimating chromosomal heritability, chromosome 2 displayed the highest heritability upon periodic changes in FEV1. SNPs including rs2272402 and rs7209788 displayed a genome-wide significant association with longitudinal changes in FEV1 (P = 1.22 × 10⁻⁸ for rs2272402 and P = 3.36 × 10⁻⁷ for rs7209788). De novo variants including rs4922117 (near LPL, P = 2.13 × 10⁻¹⁵) of log-transformed high-density lipoprotein (HDL) ratios and rs2335418 (near HMGCR, P = 3.2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document}× 10⁻⁹) of low-density lipoprotein were detected on GWAS.

Conclusion

Significant genetic effects on longitudinal changes in FEV1 among the middle-aged general population and chromosome 2 account for most of the genetic variance.

Electronic supplementary material

The online version of this article (10.1007/s13258-019-00902-x) contains supplementary material, which is available to authorized users.

STEPS: an efficient prospective likelihood approach to genetic association analyses of secondary traits in extreme phenotype sequencing

It has been well acknowledged that methods for secondary trait (ST) association analyses under a case-control design (ST$_{\text{CC}}$) should carefully consider the sampling process to avoid biased risk estimates. A similar situation also exists in the extreme phenotype sequencing (EPS) designs, which is to select subjects with extreme values of continuous primary phenotype for sequencing. EPS designs are commonly used in modern epidemiological and clinical studies such as the well-known National Heart, Lung, and Blood Institute Exome Sequencing Project. Although naïve generalized regression or ST$_{\text{CC}}$ method could be applied, their validity is questionable due to difference in statistical designs. Herein, we propose a general prospective likelihood framework to perform association testing for binary and continuous STs under EPS designs (STEPS), which can also incorporate covariates and interaction terms. We provide a computationally efficient and robust algorithm to obtain the maximum likelihood estimates. We also present two empirical mathematical formulas for power/sample size calculations to facilitate planning of binary/continuous STs association analyses under EPS designs. Extensive simulations and application to a genome-wide association study of benign ethnic neutropenia under an EPS design demonstrate the superiority of STEPS over all its alternatives above.

The interaction between ABCA1 polymorphism and physical activity on the HDL-cholesterol levels in a Japanese population

Few studies have investigated the interactions between HDL-C-related SNPs identified by genome-wide association (GWA) study and physical activity (PA) on HDL-C. First, we conducted a sex-stratified GWA study in a discovery sample (2,231 men and 2,431 women) and replication sample (2,599 men and 3,109 women) to identify SNPs influencing log-transformed HDL-C in Japanese participants in the baseline survey of the Japan Multi-Institutional Collaborative Cohort Study. We also replicated previously reported HDL-C-related SNPs in a combined (discovery plus replication) sample (4,830 men and 5,540 women). We then analyzed the interactions of the HDL-C-related SNPs with PA on HDL-C. The sex-stratified GWA analyses identified 11 and 10 HDL-C-related SNPs in men and women as targets for an interaction analysis. Among these, only one interaction of ABCA1 rs1883025 with PA was statistically significant in men, after Bonferroni correction [P-interaction = 0.001 (α = 0.05/21 = 0.002)]. The per-major-allele (C allele) increase in log-transformed HDL-C was lost in men with low PA (β = 0.008) compared with those with medium (β = 0.032) or high PA (β = 0.034). These findings suggest that the benefit of carrying a C allele of ABCA1 rs1883025 on enhancing HDL-C may be attenuated in inactive men.

Integrative Network Analysis of Multi-Omics Data in the Link between Plasma Carotenoid Concentrations and Lipid Profile

INTRODUCTION

Carotenoids, which are a reliable biomarker of fruit and vegetable consumption, are positively associated with the lipid profile. Circulating carotenoid concentrations may interact with several omics profiles including genome, transcriptome, and epigenome. Few studies have used multi-omics approaches, and they rarely include environmental factors, such as diet.

OBJECTIVE

The objective of this observational study was to examine the potential role of multi-omics data in the interconnection between diet, represented by total carotenoids, and lipid profile using weighted gene correlation network analysis (WGCNA).

METHODS

Blood leukocyte DNA methylation levels of 472,245 CpG sites and whole blood gene expression levels of 18,160 transcripts were tested for associations with total carotenoid concentrations using regressions in 48 healthy subjects. WGCNA was used to identify co-omics modules and hub genes related to the lipid profile.

RESULTS

Among genes associated with total carotenoid concentrations, a total of 236 genes were identified at both DNA methylation and gene expression levels. Using WGCNA, six modules, consisting of groups of highly correlated genes represented by colors, were identified and linked to the lipid profile. Probes clustered in the turquoise and green modules correlated with plasma lipid concentrations. A total of 28 hub genes were identified.

CONCLUSIONS

Genome-wide DNA methylation and gene expression levels were both associated with plasma total carotenoid concentrations. Several hub genes, mostly involved in lipid metabolism and inflammatory response with several genetic variants associated with plasma lipid concentrations, came out of the integrative analysis. This provides a comprehensive understanding of the interactive molecular system between carotenoids, omics, and plasma lipid profile.

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

Sleep duration is associated with an adverse lipid profile. Here, the authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time.

A genome-wide search for gene-by-obesity interaction loci of dyslipidemia in Koreans shows diverse genetic risk alleles

Dyslipidemia is a well-established risk factor for CVD. Studies suggest that similar fat accumulation in a given population might result in different levels of dyslipidemia risk among individuals; for example, despite similar or leaner body composition compared with Caucasians, Asians of Korean descent experience a higher prevalence of dyslipidemia. These variations imply a possible role of gene-obesity interactions on lipid profiles. Genome-wide association studies have identified more than 500 loci regulating plasma lipids, but the interaction structure between genes and obesity traits remains unclear. We hypothesized that some loci modify the effects of obesity on dyslipidemia risk and analyzed extensive gene-environment interactions (G×Es) at genome-wide levels to search for replicated gene-obesity interactive SNPs. In four Korean cohorts (n = 18,025), we identified and replicated 20 gene-obesity interactions, including novel variants (SCN1A and SLC12A8) and known lipid-associated variants (APOA5, BUD13, ZNF259, and HMGCR). When we estimated the additional heritability of dyslipidemia by considering G×Es, the gain was substantial for triglycerides (TGs) but mild for LDL cholesterol (LDL-C) and total cholesterol (Total-C); the interaction explained up to 18.7% of TG, 2.4% of LDL-C, and 1.9% of Total-C heritability associated with waist-hip ratio. Our findings suggest that some individuals are prone to develop abnormal lipid profiles, particularly with regard to TGs, even with slight increases in obesity indices; ethnic diversities in the risk alleles might partly explain the differential dyslipidemia risk between populations. Research about these interacting variables may facilitate knowledge-based approaches to personalize health guidelines according to individual genetic profiles.

Contributions of Interactions Between Lifestyle and Genetics on Coronary Artery Disease Risk

PURPOSE OF THE REVIEW

To summarize current knowledge on interactions between genetic variants and lifestyle factors (G×L) associated with the development of coronary artery disease (CAD) and prioritize future research.

RECENT FINDINGS

Genetic risk and combined lifestyle factors and behaviors have a log-additive effect on the risk of developing CAD. First, we describe genetic and lifestyle factors associated with CAD and then focus on G×L interactions. The majority of G×L interaction studies are small-scale candidate gene studies that lack replication and therefore provide spurious results. Only a few studies, of which most use genetic risk scores or genome-wide approaches to test interactions, are robust in number and analysis strategy. These studies provide evidence for the existence of G×L interactions in the development of CAD. Further G×L interactions studies are important as they contribute to our understanding of disease pathophysiology and possibly provide insights for improving interventions or personalized recommendations.

ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response

Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report a genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyze ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. We identify a previously-unreported genome-wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP p = 2.831 × 10⁻⁹). Knockdown or genomic knockout of the zebrafish ortholog results in reduction in pancreatic β-cell number which we demonstrate to be due to increased apoptosis in islets. siRNA transfection of murine Zranb3 in MIN6 β-cells results in impaired insulin secretion in response to high glucose, implicating Zranb3 in β-cell functional response to high glucose conditions. We also show transferability in our study of 32 established T2D loci. Our findings advance understanding of the genetics of T2D in non-European ancestry populations.

Type 2 diabetes (T2D) is prevalent in populations worldwide, however, mostly studied in European and mixed-ancestry populations. Here, the authors perform a genome-wide association study for T2D in over 5,000 sub-Saharan Africans and identify a locus, ZRANB3, that is specific for this population.

Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver

Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory elements of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the effects of genetic variation on histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 74 GWAS loci that have been associated with at least one complex phenotype. Our results reveal a repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.

Identification of female-specific genetic variants for metabolic syndrome and its component traits to improve the prediction of metabolic syndrome in females

Background

Metabolic syndrome (MetS), defined as a cluster of metabolic risk factors including dyslipidemia, insulin-resistance, and elevated blood pressure, has been known as partly heritable. MetS effects the lives of many people worldwide, yet females have been reported to be more vulnerable to this cluster of risks.

Methods

To elucidate genetic variants underlying MetS specifically in females, we performed a genome-wide association study (GWAS) for MetS as well as its component traits in a total of 9932 Korean female subjects (including 2276 MetS cases and 1692 controls). To facilitate the prediction of MetS in females, we calculated a genetic risk score (GRS) combining 14 SNPs detected in our GWA analyses specific for MetS.

Results

GWA analyses identified 14 moderate signals (P_meta < 5X10^− 5) specific to females for MetS. In addition, two genome-wide significant female-specific associations (P_meta < 5X10^− 8) were detected for rs455489 in DSCAM for fasting plasma glucose (FPG) and for rs7115583 in SIK3 for high-density lipoprotein cholesterol (HDLC). Logistic regression analyses (adjusted for area and age) between the GRS and MetS in females indicated that the GRS was associated with increased prevalence of MetS in females (P = 5.28 × 10^− 14), but not in males (P = 3.27 × 10^− 1). Furthermore, in the MetS prediction models using GRS, the area under the curve (AUC) of the receiver operating characteristics (ROC) curve was higher in females (AUC = 0.85) than in males (AUC = 0.57).

Conclusion

This study highlights new female-specific genetic variants associated with MetS and its component traits and suggests that the GRS of MetS variants is a likely useful predictor of MetS in females.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0830-y) contains supplementary material, which is available to authorized users.

Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

Exome chip-driven association study of lipidemia in >14,000 Koreans and evaluation of genetic effect on identified variants between different ethnic groups

Lipid levels in blood are widely used to diagnose and monitor chronic diseases. It is essential to identify the genetic traits involved in lipid metabolism for understanding chronic diseases. However, the influence of genetic traits varies depending on race, sex, age, and ethnicity. Therefore, research focusing on populations of individual countries is required, and the results can be used as a basis for comparison of results of other studies at the cross-racial and cross-country levels. In the present study, we selected lipid-related variants and evaluated their effects on lipid-related diseases in more than 14,000 subjects of three cohorts using the Illumina Human Exome Beadchip. A genome-wide association study was conducted using EPACTs after adjusting for age, sex, and recruitment area. A genome-wide significance cutoff was defined as p < 5E-08 in all the three cohorts. Sixteen variants represented the lipid traits and were classified as vulnerable to borderline hypertriglyceridemia, hyper-LDL-cholesterolemia, or hypo-HDL-cholesterolemia. Moreover, we compared the genetic effects of the 16 variants between ethnic groups and identified the missense variants in apolipoprotein A-V, cholesterol ester transfer protein, and apolipoprotein E as Asian-specific. Our study provides candidate genes as markers for chronic diseases through the evaluation of genetic effects.

Weighted gene co-expression network analysis to explain the relationship between plasma total carotenoids and lipid profile

Background

Variability in circulating carotenoids may be attributable to several factors including, among others, genetic variants and lipid profile. However, relatively few studies have considered the impact of gene expression in the inter-individual variability in circulating carotenoids. Most studies considered expression of genes individually and ignored their high degree of interconnection. Weighted gene co-expression network analysis (WGCNA) is a systems biology method used for finding gene clusters with highly correlated expression levels and for relating them to phenotypic traits. The objective of the present observational study is to examine the relationship between plasma total carotenoid concentrations and lipid profile using WGCNA.

Results

Whole blood expression levels of 533 probes were associated with plasma total carotenoids. Among the four WGCNA distinct modules identified, turquoise, blue, and brown modules correlated with plasma high-density lipoprotein cholesterol (HDL-C) and total cholesterol. Probes showing a strong association with HDL-C and total cholesterol were also the most important elements of the brown and blue modules. A total of four and 29 hub genes associated with total carotenoids were potentially related to HDL-C and total cholesterol, respectively.

Conclusions

Expression levels of 533 probes were associated with plasma total carotenoid concentrations. Using WGCNA, four modules and several hub genes related to lipid and carotenoid metabolism were identified. This integrative analysis provides evidence for the potential role of gene co-expression in the relationship between carotenoids and lipid concentrations. Further studies and validation of the hub genes are needed.

Electronic supplementary material

The online version of this article (10.1186/s12263-019-0639-5) contains supplementary material, which is available to authorized users.

Allele-specific enhancers mediate associations between LCAT and ABCA1 polymorphisms and HDL metabolism

For most complex traits, the majority of SNPs identified through genome-wide association studies (GWAS) reside within noncoding regions that have no known function. However, these regions are enriched for the regulatory enhancers specific to the cells relevant to the specific trait. Indeed, many of the GWAS loci that have been functionally characterized lie within enhancers that regulate expression levels of key genes. In order to identify polymorphisms with potential allele-specific regulatory effects, we developed a bioinformatics pipeline that harnesses epigenetic signatures as well as transcription factor (TF) binding motifs to identify putative enhancers containing a SNP with potential allele-specific TF binding in linkage disequilibrium (LD) with a GWAS-identified SNP. We applied the approach to GWAS findings for blood lipids, revealing 7 putative enhancers harboring associated SNPs, 3 of which lie within the introns of LCAT and ABCA1, genes that play crucial roles in cholesterol biogenesis and lipoprotein metabolism. All 3 enhancers demonstrated allele-specific in vitro regulatory activity in liver-derived cell lines. We demonstrated that these putative enhancers are in close physical proximity to the promoters of their respective genes, in situ, likely through chromatin looping. In addition, the associated alleles altered the likelihood of transcription activator STAT3 binding. Our results demonstrate that through our approach, the LD blocks that contain GWAS signals, often hundreds of kilobases in size with multiple SNPs serving as statistical proxies to the true functional site, can provide an experimentally testable hypothesis for the underlying regulatory mechanism linking genetic variants to complex traits.

LncRNA ENST00000602558.1 regulates ABCG1 expression and cholesterol efflux from vascular smooth muscle cells through a p65-dependent pathway

BACKGROUND AND AIMS

Long non-coding RNAs (lncRNAs) have proven to be involved in the progression of atherosclerosis and dyslipidemia. In addition, vascular smooth muscle cells (VSMCs) phenotype switching, including VSMCs-derived foam cells formation, plays a key role in the pathogenesis of atherosclerosis. LncRNA ENST00000602558.1, one of the differentially expressed lncRNAs between coronary artery disease (CAD) patients and healthy controls identified by our previous study, was located to TG and HDL susceptibility loci, but its role and underlying mechanism in the pathogenesis of atherosclerosis remain unclear. The present study aims to explore the role and underlying mechanism of ENST00000602558.1 in the regulation of cholesterol efflux from VSMCs.

METHODS

ABCG1 mRNA and protein expression in VSMCs was detected using qRT-PCR and Western blot, respectively. ABCG1-mediated cholesterol efflux to HDL from VSMCs was measured by means of NBD-cholesterol fluorescence intensity. The binding of ENST00000602558.1 to p65 and p65 to ABCG1 promoter region was detected by RNA immunoprecipitation (RIP) assay and chromatin immunoprecipitation (ChIP) assay, respectively.

RESULTS

Overexpression of ENST00000602558.1 downregulated ABCG1 mRNA and protein expression, while knockdown of ENST00000602558.1 upregulated ABCG1 mRNA and protein expression. Consistently, ENST00000602558.1 overexpression decreased ABCG1-mediated cholesterol efflux to HDL from VSMCs by 30.38% (p < 0.001), and knockdown of ENST00000602558.1 increased ABCG1-mediated cholesterol efflux to HDL from VSMCs by 30.41% (p = 0.001). In addition to cholesterol efflux, overexpression of ENST00000602558.1 increased lipid accumulation and TC/TG levels, while knockdown of ENST00000602558.1 decreased lipid accumulation and TC/TG levels in VSMCs. Furthermore, we confirmed that ENST00000602558.1 regulated ABCG1 expression and ABCG1-mediated cholesterol efflux from VSMCs through binding to p65.

CONCLUSIONS

In conclusion, ENST00000602558.1 played an important role in mediating cholesterol efflux to HDL from VSMCs by regulating ABCG1 expression through binding to p65.

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

Enhancer deletion and allelic effects define a regulatory molecular mechanism at the VLDLR cholesterol GWAS locus

Total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) are heritable risk factors for cardiovascular disease, yet the molecular mechanisms underlying the majority of blood lipid-associated genome-wide association studies signals remain elusive. One association signal is located in intron 3 of VLDLR; rs3780181-A is a risk allele associated (P ≤ 2 × 10-9) with increased TC and LDL-C. We investigated variants, genes and mechanisms underlying this association signal. We used a functional genetic approach to show that the intronic region spanning rs3780181 exhibited 1.6-7.6-fold enhancer activity in human HepG2 hepatocyte, THP-1 monocyte and Simpson-Golabi-Behmel Syndrome (SGBS) preadipocyte cells and that the rs3780181-A risk allele showed significantly less enhancer activity compared with the G allele, consistent with the direction of an expression quantitative trait locus in liver. In addition, rs3780181 alleles showed differential binding to multiple nuclear proteins, including stronger IRF2 binding to the rs3780181 G allele. We used a CRISPR-cas9 approach to delete 475 and 663 bp of the putative enhancer element in HEK293T kidney cells; compared to expression of mock-edited cell lines, the homozygous enhancer deletion cell lines showed 1.2-fold significantly (P < 0.04) decreased expression of VLDLR, as well as 1.5-fold decreased expression of SMARCA2, located 388 kb away. Together, these results identify an enhancer of VLDLR expression and suggest that altered binding of one or more factors bound to rs3780181 alleles decreases enhancer activity and reduces at least VLDLR expression, leading to increased TC and LDL-C.

Metabolome-based signature of disease pathology in MS

BACKGROUND

Diagnostic delays are common for multiple sclerosis (MS) since diagnosis typically depends on the presentation of nonspecific clinical symptoms together with radiologically-determined central nervous system (CNS) lesions. It is important to reduce diagnostic delays as earlier initiation of disease modifying therapies mitigates long-term disability. Developing a metabolomic blood-based MS biomarker is attractive, but prior efforts have largely focused on specific subsets of metabolite classes or analytical platforms. Thus, there are opportunities to interrogate metabolite profiles using more expansive and comprehensive approaches for developing MS biomarkers and for advancing our understanding of MS pathogenesis.

METHODS

To identify putative blood-based MS biomarkers, we comprehensively interrogated the metabolite profiles in 12 non-Hispanic white, non-smoking, male MS cases who were drug naïve for 3 months prior to biospecimen collection and 13 non-Hispanic white, non-smoking male controls who were frequency matched to cases by age and body mass index. We performed untargeted two-dimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS) and targeted lipidomic and amino acid analysis on serum. 325 metabolites met quality control and supervised machine learning was used to identify metabolites most informative for MS status. The discrimination potential of these select metabolites were assessed using receiver operator characteristic curves based on logistic models; top candidate metabolites were defined as having area under the curves (AUC) >80%. The associations between whole-genome expression data and the top candidate metabolites were examined, followed by pathway enrichment analyses. Similar associations were examined for 175 putative MS risk variants and the top candidate metabolites.

RESULTS

12 metabolites were determined to be informative for MS status, of which 6 had AUCs >80%: pyroglutamate, laurate, acylcarnitine C14:1, N-methylmaleimide, and 2 phosphatidylcholines (PC ae 40:5, PC ae 42:5). These metabolites participate in glutathione metabolism, fatty acid metabolism/oxidation, cellular membrane composition, and transient receptor potential channel signaling. Pathway analyses based on the gene expression association for each metabolite suggested enrichment for pathways associated with apoptosis and mitochondrial dysfunction. Interestingly, the predominant MS genetic risk allele HLA-DRB1×15:01 was associated with one of the 6 top metabolites.

CONCLUSION

Our analysis represents the most comprehensive description of metabolic changes associated with MS in serum, to date, with the inclusion of genomic and genetic information. We identified atypical metabolic processes that differed between MS patients and controls, which may enable the development of biological targets for diagnosis and treatment.

The Korea Biobank Array: Design and Identification of Coding Variants Associated with Blood Biochemical Traits

We introduce the design and implementation of a new array, the Korea Biobank Array (referred to as KoreanChip), optimized for the Korean population and demonstrate findings from GWAS of blood biochemical traits. KoreanChip comprised >833,000 markers including >247,000 rare-frequency or functional variants estimated from >2,500 sequencing data in Koreans. Of the 833 K markers, 208 K functional markers were directly genotyped. Particularly, >89 K markers were presented in East Asians. KoreanChip achieved higher imputation performance owing to the excellent genomic coverage of 95.38% for common and 73.65% for low-frequency variants. From GWAS (Genome-wide association study) using 6,949 individuals, 28 associations were successfully recapitulated. Moreover, 9 missense variants were newly identified, of which we identified new associations between a common population-specific missense variant, rs671 (p.Glu457Lys) of ALDH2, and two traits including aspartate aminotransferase (P = 5.20 × 10⁻¹³) and alanine aminotransferase (P = 4.98 × 10⁻⁸). Furthermore, two novel missense variants of GPT with rare frequency in East Asians but extreme rarity in other populations were associated with alanine aminotransferase (rs200088103; p.Arg133Trp, P = 2.02 × 10⁻⁹ and rs748547625; p.Arg143Cys, P = 1.41 × 10⁻⁶). These variants were successfully replicated in 6,000 individuals (P = 5.30 × 10⁻⁸ and P = 1.24 × 10⁻⁶). GWAS results suggest the promising utility of KoreanChip with a substantial number of damaging variants to identify new population-specific disease-associated rare/functional variants.

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

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

Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

A Perception on Genome-Wide Genetic Analysis of Metabolic Traits in Arab Populations

Despite dedicated nation-wide efforts to raise awareness against the harmful effects of fast-food consumption and sedentary lifestyle, the Arab population continues to struggle with an increased risk for metabolic disorders. Unlike the European population, the Arab population lacks well-established genetic risk determinants for metabolic disorders, and the transferability of established risk loci to this population has not been satisfactorily demonstrated. The most recent findings have identified over 240 genetic risk loci (with ~400 independent association signals) for type 2 diabetes, but thus far only 25 risk loci (ADAMTS9, ALX4, BCL11A, CDKAL1, CDKN2A/B, COL8A1, DUSP9, FTO, GCK, GNPDA2, HMG20A, HNF1A, HNF1B, HNF4A, IGF2BP2, JAZF1, KCNJ11, KCNQ1, MC4R, PPARγ, SLC30A8, TCF7L2, TFAP2B, TP53INP1, and WFS1) have been replicated in Arab populations. To our knowledge, large-scale population- or family-based association studies are non-existent in this region. Recently, we conducted genome-wide association studies on Arab individuals from Kuwait to delineate the genetic determinants for quantitative traits associated with anthropometry, lipid profile, insulin resistance, and blood pressure levels. Although these studies led to the identification of novel recessive variants, they failed to reproduce the established loci. However, they provided insights into the genetic architecture of the population, the applicability of genetic models based on recessive mode of inheritance, the presence of genetic signatures of inbreeding due to the practice of consanguinity, and the pleiotropic effects of rare disorders on complex metabolic disorders. This perspective presents analysis strategies and study designs for identifying genetic risk variants associated with diabetes and related traits in Arab populations.

Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.

The Role of RNA Editing in Cancer Development and Metabolic Disorders

Numerous human diseases arise from alterations of genetic information, most notably DNA mutations. Thought to be merely the intermediate between DNA and protein, changes in RNA sequence were an afterthought until the discovery of RNA editing 30 years ago. RNA editing alters RNA sequence without altering the sequence or integrity of genomic DNA. The most common RNA editing events are A-to-I changes mediated by adenosine deaminase acting on RNA (ADAR), and C-to-U editing mediated by apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1). Both A-to-I and C-to-U editing were first identified in the context of embryonic development and physiological homeostasis. The role of RNA editing in human disease has only recently started to be understood. In this review, the impact of RNA editing on the development of cancer and metabolic disorders will be examined. Distinctive functions of each RNA editase that regulate either A-to-I or C-to-U editing will be highlighted in addition to pointing out important regulatory mechanisms governing these processes. The potential of developing novel therapeutic approaches through intervention of RNA editing will be explored. As the role of RNA editing in human disease is elucidated, the clinical utility of RNA editing targeted therapies will be needed. This review aims to serve as a bridge of information between past findings and future directions of RNA editing in the context of cancer and metabolic disease.

Genome-wide association meta-analysis yields 20 loci associated with gallstone disease

Gallstones are responsible for one of the most common diseases in the Western world and are commonly treated with cholecystectomy. We perform a meta-analysis of two genome-wide association studies of gallstone disease in Iceland and the UK, totaling 27,174 cases and 736,838 controls, uncovering 21 novel gallstone-associated variants at 20 loci. Two distinct low frequency missense variants in SLC10A2, encoding the apical sodium-dependent bile acid transporter (ASBT), associate with an increased risk of gallstone disease (Pro290Ser: OR = 1.36 [1.25-1.49], P = 2.1 × 10-12, MAF = 1%; Val98Ile: OR = 1.15 [1.10-1.20], P = 1.8 × 10-10, MAF = 4%). We demonstrate that lower bile acid transport by ASBT is accompanied by greater risk of gallstone disease and highlight the role of the intestinal compartment of the enterohepatic circulation of bile acids in gallstone disease susceptibility. Additionally, two low frequency missense variants in SERPINA1 and HNF4A and 17 common variants represent novel associations with gallstone disease.

Interethnic analyses of blood pressure loci in populations of East Asian and European descent

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, the authors perform discovery GWAS for BP in East Asians and meta-analysis in East Asians and Europeans and report ancestry-specific BP SNPs and selection signals.

Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations

OBJECTIVES

Large-scale association studies that mainly involve European populations identified many genetic loci related to high-density lipoprotein cholesterol (HDL-C) levels, one of the most important indicators of the risk for cardiovascular diseases. The question with intense speculation of whether the effect estimates obtained from European populations for different HDL-C level-related SNPs are applicable to the Roma ethnicity, the largest minority group in Europe with a South Asian origin, was addressed in the present study.

DESIGN

The associations between 21 SNPs (in the genes LIPC(G), CETP, GALNT2, HMGCP, ABCA1, KCTD10 and WWOX) and HDL-C levels were examined separately in adults of the Hungarian general (N = 1542) and Roma (N = 646) populations by linear regression. Individual effects (direction and size) of single SNPs on HDL-C levels were computed and compared between the study groups and with data published in the literature.

RESULTS

Significant associations between SNPs and HDL-C levels were more frequently found in general subjects than in Roma subjects (11 SNPs in general vs. 4 SNPs in Roma). The CETP gene variants rs1532624, rs708272 and rs7499892 consistently showed significant associations with HDL-C levels across the study groups (p ˂ 0.05), indicating a possible causal variant(s) in this region. Although nominally significant differences in effect size were found for three SNPs (rs693 in gene APOB, rs9989419 in gene CETP, and rs2548861 in gene WWOX) by comparing the general and Roma populations, most of these SNPs did not have a significant effect on HDL-C levels. The β coefficients for SNPs in the Roma population were found to be identical both in direction and magnitude to the effect obtained previously in large-scale studies on European populations.

CONCLUSIONS

The effect of the vast majority of the SNPs on HDL-C levels could be replicated in the Hungarian general and Roma populations, which indicates that the effect size measurements obtained from the literature can be used for risk estimation for both populations.

Identification of 12 novel loci that confer susceptibility to early-onset dyslipidemia

The circulating concentrations of triglycerides, high density lipoprotein (HDL)-cholesterol, and low density lipoprotein (LDL)-cholesterol have a substantial genetic component, and the heritability of early-onset dyslipidemia might be expected to be higher compared with late-onset forms. In the present study, exome-wide association studies (EWASs) were performed for early-onset hypertriglyceridemia, hypo-HDL-cholesterolemia, and hyper-LDL-cholesterolemia, with the aim to identify genetic variants that confer susceptibility to these conditions in the Japanese population. A total of 8,073 individuals aged ≤65 years were enrolled in the study. The EWASs for hypertriglyceridemia (2,664 cases and 5,294 controls), hypo-HDL-cholesterolemia (974 cases and 7,085 controls), and hyper-LDL-cholesterolemia (2,911 cases and 5,111 controls) were performed with Illumina Human Exome-12 v1.2 DNA Analysis BeadChip or Infinium Exome-24 v1.0 BeadChip arrays. The association of allele frequencies for 31,198, 31,133, or 31,175 single nucleotide polymorphisms (SNPs) to hypertriglyceridemia, hypo-HDL-cholesterolemia, or hyper-LDL-cholesterolemia, respectively, was examined with Fisher’s exact test. To compensate for multiple comparisons of genotypes with each of the three conditions, Bonferroni’s correction was applied for statistical significance of association. The results demonstrated that 25, 28 and 65 SNPs were significantly associated with hypertriglyceridemia, hypo-HDL-cholesterolemia and hyper-LDL-cholesterolemia, respectively. Multivariable logistic regression analysis with adjustment for age and sex revealed that all 25, 28 and 65 of these SNPs were significantly associated with hypertriglyceridemia, hypo-HDL-cholesterolemia and hyper-LDL-cholesterolemia, respectively. Following examination of the association of the identified SNPs to serum concentrations of triglycerides, HDL-cholesterol, or LDL-cholesterol, linkage disequilibrium of the SNPs, and results of previous genome-wide association studies, we newly identified chromosomal region 19p12 as a susceptibility locus for hypertriglyceridemia, eight loci (MOB3C-TMOD4, LPGAT1, EHD3, COL6A3, ZNF860-CACNA1D, COL6A5, DCLRE1C, ZNF77) for hypo-HDL-cholesterolemia, and three loci (KIAA0319-FAM65B, UBD, LOC105375015) for hyper-LDL-cholesterolemia. The present study thus identified 12 novel loci that may confer susceptibility to early-onset dyslipidemia. Determination of genotypes for the SNPs at these loci may prove informative for assessment of genetic risk for hypertriglyceridemia, hypo-HDL-cholesterolemia, or hyper-LDL-cholesterolemia in the Japanese population.

Genome-wide association study identifies novel recessive genetic variants for high TGs in an Arab population

Abnormal blood lipid levels are influenced by genetic and lifestyle/dietary factors. Although many genetic variants associated with blood lipid traits have been identified in Europeans, similar data in Middle Eastern populations are limited. We performed a genome-wide association study with Arab individuals (discovery cohort: 1,353; replication cohort: 1,176) from Kuwait to identify possible associations of genetic variants with high lipid levels. We used Illumina HumanOmniExpress BeadChip and candidate SNP genotyping in the discovery and replication phases, respectively. For association tests, we used genetic models that were based on additive and recessive modes of inheritance. High triglycerides (TGs) were recessively associated with six risk variants (rs1002487/RPS6KA1, rs11805972/LAD1) rs7761746/Or5v1, rs39745/CTTNBP2-LSM8, rs2934952/PGAP3, and rs9626773/RP11-191L9.4-CERK) at genome-wide significance (P  6.12E-09), and another six variants (rs10873925/ST6GALNAC5, rs4663379/SPP2-ARL4C, rs10033119/NPY1R, rs17709449/LINC00911-FLRT2, rs11654954/CDK12-NEUROD2, and rs9972882/STARD3) were associated at borderline significance (P  5.0E-08). High TG was also additively associated with rs11654954. All of the 12 identified markers are novel and are harbored in runs of homozygosity. Literature evidence supports the involvement of these gene loci in lipid-related processes. This study in an Arab population augments international efforts to identify genetic regulation of lipid traits.

Angiopoietin-Like 3 (ANGPTL3) and Atherosclerosis: Lipid and Non-Lipid Related Effects

Genetic and clinical studies have demonstrated that loss-of-function variants in the angiopoietin-like 3 (ANGPTL3) gene are associated with decreased plasma levels of triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), which leads to a significant reduction in cardiovascular risk. For this reason, ANGPTL3 is considered an important new pharmacological target for the treatment of cardiovascular diseases (CVDs) together with more conventional lipid lowering therapies, such as statins and anti proprotein convertase subtilisin/kexin type 9 (PCSK9) monoclonal antibodies. Experimental evidence demonstrates that anti-ANGPTL3 therapies have an important anti-atherosclerotic effect. Results from phase I clinical trials with a monoclonal anti-ANGPTL3 antibody (evinacumab) and anti-sense oligonucleotide (ASO) clearly show a significant lipid lowering effect. In addition, from the analysis of the protein structure of ANGPTL3, it has been hypothesized that, beyond its inhibitory activity on lipoprotein and endothelial lipases, this molecule may have a pro-inflammatory, pro-angiogenic effect and a negative effect on cholesterol efflux, implying additional pro-atherosclerotic properties. In the future, data from phase II clinical trials and additional experimental evidence will help to define the efficacy and the additional anti-atherosclerotic properties of anti-ANGPTL3 therapies beyond the already available lipid lowering therapies.

GWAS Reveal Targets in Vessel Wall Pathways to Treat Coronary Artery Disease

Coronary artery disease (CAD) is the leading cause of mortality worldwide and poses a considerable public health burden. Recent genome-wide association studies (GWAS) have revealed >100 genetic loci associated with CAD susceptibility in humans. While a number of these loci harbor gene targets of currently approved therapies, such as statins and PCSK9 inhibitors, the majority of the annotated genes at these loci encode for proteins involved in vessel wall function with no known drugs available. Importantly many of the associated genes linked to vascular (smooth muscle, endothelial, and macrophage) cell processes are now organized into distinct functional pathways, e.g., vasodilation, growth factor responses, extracellular matrix and plaque remodeling, and inflammation. In this mini-review, we highlight the most recently identified loci that have predicted roles in the vessel wall and provide genetic context for pre-existing therapies as well as new drug targets informed from GWAS. With the development of new modalities to target these pathways, (e.g., antisense oligonucleotides, CRISPR/Cas9, and RNA interference) as well as the computational frameworks to prioritize or reposition therapeutics, there is great opportunity to close the gap from initial genetic discovery to clinical translation for many patients affected by this common disease.

Characterization of LncRNA expression profile and identification of novel LncRNA biomarkers to diagnose coronary artery disease

BACKGROUND AND AIMS

Dysregulation of long non-coding RNAs (lncRNAs) has been proven to be involved in the pathogenesis of coronary artery disease (CAD). However, it remains to be extensively explored. Thus, the present study aims to study expression patterns, biological functions, and diagnostic value of lncRNAs in CAD.

METHODS

Using microarray, we performed the transcriptome-wide lncRNA and mRNAs expression profile of peripheral blood mononuclear cells (PBMCs) of 93 CAD patients and 48 healthy controls. Gene Ontology (GO) and pathway analysis for differentially expressed mRNAs were used to investigate underlying biological associations of differentially expressed lncRNAs, and path-net was created to depict interactions of significant pathways. qRT-PCR was used to validate selected lncRNAs in 412 CAD patients and 295 healthy controls. Receiver operating characteristic (ROC) curve analysis was performed to evaluate whether lncRNAs could be used in the diagnosis of CAD patients. Finally, the functional significance of validated lncRNAs was determined in THP-1-derived macrophages.

RESULTS

We identified 1210 lncRNAs and 890 mRNAs differentially expressed from the expression profile and validated 7 lncRNAs. Two novel lncRNA biomarkers, ENST00000444488.1 and uc010yfd.1, together with CAD risk factors, had the better performance for discrimination of CAD patients from healthy controls, and ENST00000444488.1 could diagnose acute myocardial infarction (AMI) patients. The knockdown of 20 ENST00000444488.1, uc010yfd.1, ASO3973 and ENST00000602558.1 affected the expression of inflammation-related genes and their nearby genes in THP-1-derived macrophages, respectively.

CONCLUSIONS

We offered a transcriptome-wide overview of aberrantly expressed lncRNAs in CAD patients, and identified two novel lncRNA biomarkers for diagnosing CAD. Loss of validated lncRNAs regulated the expression of inflammation-related genes and their nearby genes.

Association of 48 type 2 diabetes susceptibility loci with fasting plasma glucose and lipid levels in Chinese Hans

AIM

Dozens of susceptibility loci have been identified by type 2 diabetes (T2D) genome wide association study (GWAS) in Europeans. In our previous studies, we systematically evaluated the association of 48 susceptibility loci with T2D risk in Chinese Hans. Because dyslipidemia and hyperglycemia are implicated in the pathogenic process of T2D, we further evaluated whether these 48 single nucleotide polymorphisms (SNPs) were related to fasting plasma glucose (FPG) or lipid levels in Chinese Hans.

METHODS

The 48 SNPs were genotyped by using the Taqman OpenArray Genotyping System and iPLEX Sequenom MassARRAY platform. Multiple linear regression was used to assess the relationship between genetic variants and FPG and lipid levels among 3281 non-diabetic, healthy Chinese Hans.

RESULTS

After adjusting for age, gender, body mass index (BMI), smoking status and drinking status, the T allele of rs13266634 in the SLC30A8 gene was significantly associated with decreased glucose level (β = -0.0119, P = 8.05 × 10^-5), whereas the T allele of rs896854 in the TP53INP1 gene was associated with increased triglyceride (TG) level (β = 0.0342, P = 9.61 × 10^-4) and decreased high-density lipoprotein cholesterol (HDL-C) level (β = -0.015, P = 3.24 × 10^-3) after Bonferroni correction. We also conducted a meta-analysis consisted of 11 studies and confirmed that SNP rs896854 in the TP53INP1 gene was associated with T2D risk.

CONCLUSION

Our findings indicated that SNP rs13266634 in SLC30A8 was associated with glucose level and SNP rs896854 in TP53INP1 was associated with lipid level.

Genetic alterations in the NO-cGMP pathway and cardiovascular risk

In the past ten years, several chromosomal loci have been identified by genome-wide association studies to influence the risk of coronary artery disease (CAD) and its risk factors. The GUCY1A3 gene encoding the α₁ subunit of the soluble guanylyl cyclase (sGC) resides at one of these loci and has been strongly associated with blood pressure and CAD risk. More recently, further genes in the pathway encoding the endothelial nitric oxide synthase, the phosphodiesterases 3A and 5A, and the inositol 1,4,5-trisphosphate receptor I-associated protein (IRAG), i.e., NOS3, PDE3A, PDE5A, and MRVI1, respectively, were likewise identified as CAD risk genes. In this review, we highlight the genetic findings linking variants in NO-cGMP signaling and cardiovascular disease, discuss the potential underlying mechanisms which might propagate the development of atherosclerosis, and speculate about therapeutic implications.

Integrative genomics identifies new genes associated with severe COPD and emphysema

BACKGROUND

Genome-wide association studies have identified several genetic risk loci for severe chronic obstructive pulmonary disease (COPD) and emphysema. However, these studies do not fully explain disease heritability and in most cases, fail to implicate specific genes. Integrative methods that combine gene expression data with GWAS can provide more power in discovering disease-associated genes and give mechanistic insight into regulated genes.

METHODS

We applied a recently described method that imputes gene expression using reference transcriptome data to genome-wide association studies for two phenotypes (severe COPD and quantitative emphysema) and blood and lung tissue gene expression datasets. We further tested the potential causality of individual genes using multi-variant colocalization.

RESULTS

We identified seven genes significantly associated with severe COPD, and five genes significantly associated with quantitative emphysema in whole blood or lung. We validated results in independent transcriptome databases and confirmed colocalization signals for PSMA4, EGLN2, WNT3, DCBLD1, and LILRA3. Three of these genes were not located within previously reported GWAS loci for either phenotype. We also identified genetically driven pathways, including those related to immune regulation.

CONCLUSIONS

An integrative analysis of GWAS and gene expression identified novel associations with severe COPD and quantitative emphysema, and also suggested disease-associated genes in known COPD susceptibility loci.

TRIAL REGISTRATION

NCT00608764 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: November 2007, Date Registered: January 28, 2008 (retrospectively registered); NCT00292552 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: December 2005, Date Registered: February 14, 2006 (retrospectively registered).

WDR11-mediated Hedgehog signalling defects underlie a new ciliopathy related to Kallmann syndrome

WDR11 has been implicated in congenital hypogonadotropic hypogonadism (CHH) and Kallmann syndrome (KS), human developmental genetic disorders defined by delayed puberty and infertility. However, WDR11's role in development is poorly understood. Here, we report that WDR11 modulates the Hedgehog (Hh) signalling pathway and is essential for ciliogenesis. Disruption of WDR11 expression in mouse and zebrafish results in phenotypic characteristics associated with defective Hh signalling, accompanied by dysgenesis of ciliated tissues. Wdr11-null mice also exhibit early-onset obesity. We find that WDR11 shuttles from the cilium to the nucleus in response to Hh signalling. WDR11 regulates the proteolytic processing of GLI3 and cooperates with the transcription factor EMX1 in the induction of downstream Hh pathway gene expression and gonadotrophin-releasing hormone production. The CHH/KS-associated human mutations result in loss of function of WDR11. Treatment with the Hh agonist purmorphamine partially rescues the WDR11 haploinsufficiency phenotypes. Our study reveals a novel class of ciliopathy caused by WDR11 mutations and suggests that CHH/KS may be a part of the human ciliopathy spectrum.