Discovery and refinement of loci associated with lipid levels

MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels

The hepatic low-density lipoprotein receptor (LDLR) pathway is essential for clearing circulating LDL-cholesterol (LDL-C). While the transcriptional regulation of LDLR is well-characterized, the post-transcriptional mechanisms which govern LDLR expression are just beginning to emerge. Here, we developed a high-throughput genome-wide screening assay to systematically identify microRNAs (miRNAs) that regulate LDLR activity in human hepatic cells. From this screen, we characterize miR-148a as a negative regulator of LDLR expression and activity, and define a novel SREBP1-mediated pathway by which miR-148a regulates LDL-C uptake. Importantly, inhibition of miR-148a increases hepatic LDLR expression and decreases plasma LDL-C in vivo. We also provide evidence that miR-148a regulates hepatic ABCA1 expression and circulating HDL-C levels. Collectively, these studies uncover miR-148a as an important regulator of hepatic LDL-C clearance through direct regulation of LDLR expression, and demonstrate the therapeutic potential of inhibiting miR-148a to ameliorate the elevated LDL-C/HDL-C ratio, a prominent risk factor for cardiovascular disease.

Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood

Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.

Effects of Polymorphisms in APOA4-APOA5-ZNF259-BUD13 Gene Cluster on Plasma Levels of Triglycerides and Risk of Coronary Heart Disease in a Chinese Han Population

Background/Aim

Recent genome-wide association studies have identified several loci influencing lipid levels. The present study focused on the triglycerides (TG)-associated locus, the APOA4-APOA5-ZNF259-BUD13 gene cluster on chromosome 11, to explore the role of genetic variants in this gene cluster in the development of increasing TG levels and coronary heart disease (CHD).

Methodology/Principal Findings

Six single nucleotide polymorphisms (SNPs), rs4417316, rs651821, rs6589566, rs7396835, rs964184 and rs17119975, in the APOA4-APOA5-ZNF259-BUD13 gene cluster were selected and genotyped in 5374 healthy Chinese subjects. There were strong significant associations between the six SNPs and TG levels (P<1.0×10⁻⁸). Moreover, a weighted genotype score was found to be associated with TG levels (P = 3.28×10⁻¹³). The frequencies of three common haplotypes were observed to be significantly different between the high TG group and the low TG group (P<0.05). However, no significant effects were found for the SNPs regarding susceptibility to CHD in the Chinese case-control populations.

Conclusions/Significance

This study highlights the genotypes, genotype scores and haplotypes of the APOA4-APOA5-ZNF259-BUD13 gene cluster that were associated with TG levels in a Chinese population; however, the genetic variants in this gene cluster did not increase the risk of CHD in the Chinese population.

Sparse meta-analysis with high-dimensional data

Meta-analysis plays an important role in summarizing and synthesizing scientific evidence derived from multiple studies. With high-dimensional data, the incorporation of variable selection into meta-analysis improves model interpretation and prediction. Existing variable selection methods require direct access to raw data, which may not be available in practical situations. We propose a new approach, sparse meta-analysis (SMA), in which variable selection for meta-analysis is based solely on summary statistics and the effect sizes of each covariate are allowed to vary among studies. We show that the SMA enjoys the oracle property if the estimated covariance matrix of the parameter estimators from each study is available. We also show that our approach achieves selection consistency and estimation consistency even when summary statistics include only the variance estimators or no variance/covariance information at all. Simulation studies and applications to high-throughput genomics studies demonstrate the usefulness of our approach.

Perspectives on pharmacogenomics of antiretroviral medications and HIV-associated comorbidities

PURPOSE OF REVIEW

To summarize current knowledge and provide perspective on relationships between human genetic variants, antiretroviral medications, and aging-related complications of HIV-1 infection.

RECENT FINDINGS

Human genetic variants have been convincingly associated with interindividual variability in antiretroviral toxicities, drug disposition, and aging-associated complications in HIV-1 infection. Screening for HLA-B5701 to avoid abacavir hypersensitivity reactions has become a routine part of clinical care, and has markedly improved drug safety. There are well established pharmacogenetic associations with other agents (efavirenz, nevirapine, atazanavir, dolutegravir, and others), but this knowledge has yet to have substantial impact on HIV-1 clinical care. As metabolic complications including diabetes mellitus, dyslipidemia, osteoporosis, and cardiovascular disease are becoming an increasing concern among individuals who are aging with well controlled HIV-1 infection, human genetic variants that predispose to these complications also become more relevant in this population.

SUMMARY

Pharmacogenetic knowledge has already had considerable impact on antiretroviral prescribing. With continued advances in the field of human genomics, the impact of pharmacogenomics on HIV-1 clinical care and research is likely to continue to grow in importance and scope.

Genetic Variation Determines PPARγ Function and Anti-diabetic Drug Response In Vivo

SNPs affecting disease risk often reside in non-coding genomic regions. Here, we show that SNPs are highly enriched at mouse strain-selective adipose tissue binding sites for PPARγ, a nuclear receptor for anti-diabetic drugs. Many such SNPs alter binding motifs for PPARγ or cooperating factors and functionally regulate nearby genes whose expression is strain selective and imbalanced in heterozygous F1 mice. Moreover, genetically determined binding of PPARγ accounts for mouse strain-specific transcriptional effects of TZD drugs, providing proof of concept for personalized medicine related to nuclear receptor genomic occupancy. In human fat, motif-altering SNPs cause differential PPARγ binding, provide a molecular mechanism for some expression quantitative trait loci, and are risk factors for dysmetabolic traits in genome-wide association studies. One PPARγ motif-altering SNP is associated with HDL levels and other metabolic syndrome parameters. Thus, natural genetic variation in PPARγ genomic occupancy determines individual disease risk and drug response.

The Gut Microbiome Contributes to a Substantial Proportion of the Variation in Blood Lipids

Supplemental Digital Content is available in the text.

Evidence suggests that the gut microbiome is involved in the development of cardiovascular disease, with the host–microbe interaction regulating immune and metabolic pathways. However, there was no firm evidence for associations between microbiota and metabolic risk factors for cardiovascular disease from large-scale studies in humans. In particular, there was no strong evidence for association between cardiovascular disease and aberrant blood lipid levels.

Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality

Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted ¹H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases.

Human metabolism is influenced by genetic and environmental factors defining a person’s metabolic individuality. This individuality is linked to personal differences in the ability to react on metabolic challenges and in the susceptibility to specific diseases. By investigating how common variants in genetic regions (loci) affect individual blood metabolite levels, the substantial contribution of genetic inheritance to metabolic individuality has been demonstrated previously. Meanwhile, more than 150 loci influencing metabolic homeostasis in blood are known. Here we shift the focus to genetic variants that modulate urinary metabolite excretion, for which only 11 loci were reported so far. In the largest genetic study on urinary metabolites to date, we identified 15 additional loci. Most of the 26 loci also affect blood metabolite levels. This shows that the metabolic individuality seen in blood is also reflected in urine, which is expected when urine is regarded as “diluted blood”. Nonetheless, we also found loci that appear to primarily influence metabolite excretion. For instance, we identified genetic variants near a gene of a transporter that change the capability for renal re-absorption of the transporter’s substrate. Thus, our findings could help to elucidate molecular mechanisms influencing kidney function and the body’s detoxification capabilities.

Tribbles-1 regulates hepatic lipogenesis through posttranscriptional regulation of C/EBPα

Variants near the gene TRIB1 are significantly associated with several plasma lipid traits, circulating liver enzymes, and the development of coronary artery disease in humans; however, it is not clear how its protein product tribbles-1 regulates lipid metabolism. Here, we evaluated mice harboring a liver-specific deletion of Trib1 (Trib1_LSKO) to elucidate the role of tribbles-1 in mammalian hepatic lipid metabolism. These mice exhibited increased hepatic triglyceride (TG) content, lipogenic gene transcription, and de novo lipogenesis. Microarray analysis revealed altered transcription of genes that are downstream of the transcription factor C/EBPα, and Trib1_LSKO mice had increased hepatic C/EBPα protein. Hepatic overexpression of C/EBPα in WT mice phenocopied Trib1_LSKO livers, and hepatic knockout of Cebpa in Trib1_LSKO mice revealed that C/EBPα is required for the increased lipogenesis. Using ChIP-Seq, we found that Trib1_LSKO mice had increased DNA-bound C/EBPα near lipogenic genes and the Trib1 gene, which itself was transcriptionally upregulated by C/EBPα overexpression. Together, our results reveal that tribbles-1 regulates hepatic lipogenesis through posttranscriptional regulation of C/EBPα, which in turn transcriptionally upregulates Trib1. These data suggest an important role for C/EBPα in mediating the lipogenic effects of hepatic Trib1 deletion and provide insight into the association between TRIB1 and plasma lipids, and liver traits in humans.

A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

A guide to genome-wide association analysis and post-analytic interrogation

This tutorial is a learning resource that outlines the basic process and provides specific software tools for implementing a complete genome‐wide association analysis. Approaches to post‐analytic visualization and interrogation of potentially novel findings are also presented. Applications are illustrated using the free and open‐source R statistical computing and graphics software environment, Bioconductor software for bioinformatics and the UCSC Genome Browser. Complete genome‐wide association data on 1401 individuals across 861,473 typed single nucleotide polymorphisms from the PennCATH study of coronary artery disease are used for illustration. All data and code, as well as additional instructional resources, are publicly available through the Open Resources in Statistical Genomics project: http://www.stat-gen.org. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Epigenomic mapping and effect sizes of noncoding variants associated with psychotropic drug response

AIM

To provide insight into potential regulatory mechanisms of gene expression underlying addiction, analgesia, psychotropic drug response and adverse drug events, genome-wide association studies searching for variants associated with these phenotypes has been undertaken with limited success. We undertook analysis of these results with the aim of applying epigenetic knowledge to aid variant discovery and interpretation.

METHODS

We applied conditional imputation to results from 26 genome-wide association studies and three candidate gene-association studies. The analysis workflow included data from chromatin conformation capture, chromatin state annotation, DNase I hypersensitivity, hypomethylation, anatomical localization and biochronicity. We also made use of chromatin state data from the epigenome roadmap, transcription factor-binding data, spatial maps from published Hi-C datasets and 'guilt by association' methods.

RESULTS

We identified 31 pharmacoepigenomic SNPs from a total of 2024 variants in linkage disequilibrium with lead SNPs, of which only 6% were coding variants. Interrogation of chromatin state using our workflow and the epigenome roadmap showed agreement on 34 of 35 tissue assignments to regulatory elements including enhancers and promoters. Loop boundary domains were inferred by association with CTCF (CCCTC-binding factor) and cohesin, suggesting proximity to topologically associating domain boundaries and enhancer clusters. Spatial interactions between enhancer-promoter pairs detected both known and previously unknown mechanisms. Addiction and analgesia SNPs were common in relevant populations and exhibited large effect sizes, whereas a SNP located in the promoter of the SLC1A2 gene exhibited a moderate effect size for lithium response in bipolar disorder in patients of European ancestry. SNPs associated with drug-induced organ injury were rare but exhibited the largest effect sizes, consistent with the published literature.

CONCLUSION

This work demonstrates that an in silico bioinformatics-based approach using integrative analysis of a diversity of molecular and morphological data types can discover pharmacoepigenomic variants that are suitable candidates for further validation in cell lines, animal models and human clinical trials.

Dysfunctional HDL and atherosclerotic cardiovascular disease

High-density lipoproteins (HDLs) protect against atherosclerosis by removing excess cholesterol from macrophages through the ATP-binding cassette transporter A1 (ABCA1) and ATP-binding cassette transporter G1 (ABCG1) pathways involved in reverse cholesterol transport. Factors that impair the availability of functional apolipoproteins or the activities of ABCA1 and ABCG1 could, therefore, strongly influence atherogenesis. HDL also inhibits lipid oxidation, restores endothelial function, exerts anti-inflammatory and antiapoptotic actions, and exerts anti-inflammatory actions in animal models. Such properties could contribute considerably to the capacity of HDL to inhibit atherosclerosis. Systemic and vascular inflammation has been proposed to convert HDL to a dysfunctional form that has impaired antiatherogenic effects. A loss of anti-inflammatory and antioxidative proteins, perhaps in combination with a gain of proinflammatory proteins, might be another important component in rendering HDL dysfunctional. The proinflammatory enzyme myeloperoxidase induces both oxidative modification and nitrosylation of specific residues on plasma and arterial apolipoprotein A-I to render HDL dysfunctional, which results in impaired ABCA1 macrophage transport, the activation of inflammatory pathways, and an increased risk of coronary artery disease. Understanding the features of dysfunctional HDL or apolipoprotein A-I in clinical practice might lead to new diagnostic and therapeutic approaches to atherosclerosis.

Pathway-Based Genome-Wide Association Studies for Plasma Triglycerides in Obese Females and Normal-Weight Controls

Pathway-based analysis as an alternative approach can provide complementary information to single-marker genome-wide association studies (GWASs), which always ignore the epistasis and does not have sufficient power to find rare variants. In this study, using genotypes from a genome-wide association study (GWAS), pathway-based association studies were carried out by a modified Gene Set Enrichment Algorithm (GSEA) method (GenGen) for triglyceride in 1028 unrelated European-American extremely obese females (BMI≥35kg/m²) and normal-weight controls (BMI<25kg/m²), and another pathway association analysis (ICSNPathway) was also used to verify the GenGen result in the same data. The GO0009110 pathway (vitamin anabolism) was among the strongest associations with triglyceride (empirical P<0.001); the result remained significant after FDR correction (P = 0.022). MMAB, an obesity-related locus, included in this pathway. The ABCG1 and BCL6 gene was found in several triglyceride-related pathways (empirical P<0.05), which were also replicated by ICSNPathway (empirical P<0.05, FDR<0.05). We also performed single-marked GWAS using PLINK for TG levels (log-transformed). Significant associations were found between ASTN2 gene SNPs and plasma triglyceride levels (rs7035794, P = 2.24×10⁻¹⁰). Our study suggested that vitamin anabolism pathway, BCL6 gene pathways and ASTN2 gene may contribute to the genetic variation of plasma triglyceride concentrations.

Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care.

Prediction of Causal Candidate Genes in Coronary Artery Disease Loci

OBJECTIVE

Genome-wide association studies have to date identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes.

APPROACH AND RESULTS

All annotated genes in the loci were evaluated with respect to protein-coding single-nucleotide polymorphism and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in noncoding regions, with 41% affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead single-nucleotide polymorphism. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously.

CONCLUSIONS

Our results substantially revise the list of likely candidates for CAD and suggest that genome-wide association studies efforts in other diseases may benefit from similar bioinformatics analyses.

Current Applications of Genetic Risk Scores to Cardiovascular Outcomes and Subclinical Phenotypes

Genetic risk scores are a useful tool for examining the cumulative predictive ability of genetic variation on cardiovascular disease. Important considerations for creating genetic risk scores include the choice of genetic variants, weighting, and comparability across ethnicities. Genetic risk scores that use information from genome-wide meta-analyses can successfully predict cardiovascular outcomes and subclinical phenotypes, yet there is limited clinical utility of these scores beyond traditional cardiovascular risk factors in many populations. Novel uses of genetic risk scores include evaluating the genetic contribution of specific intermediate traits or risk factors to cardiovascular disease, risk prediction in high-risk populations, gene-by-environment interaction studies, and Mendelian randomization studies. Though questions remain about the ultimate clinical utility of the genetic risk score, further investigation in high-risk populations and new ways to combine genetic risk scores with traditional risk factors may prove to be fruitful.

Differential Genetic Effects on Statin-Induced Changes Across Low-Density Lipoprotein-Related Measures

BACKGROUND

Statin therapy influences not only low-density lipoprotein (LDL) cholesterol levels but also LDL-related biomarkers, including non-high-density lipoprotein cholesterol (non-HDL-C), apolipoprotein B, total number of LDL particles, and mean LDL particle size. Recent studies have identified many genetic loci influencing circulating lipid levels and statin-induced LDL cholesterol reduction. However, it is unknown how these genetic variants influence statin-induced changes in LDL subfractions and non-HDL-C.

METHODS AND RESULTS

One hundred sixty candidate single-nucleotide polymorphisms for effects on circulating lipid levels or statin-induced LDL-cholesterol lowering were tested for association with response of LDL subfractions and non-HDL-C to rosuvastatin or placebo for 1 year among 7046 participants from the Justification for Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial. Of the 51 single-nucleotide polymorphisms associated with statin response for ≥ 1 of the LDL subfractions or non-HDL-C, 20 single-nucleotide polymorphisms could be clustered according to effects predominantly on LDL particle size, predominantly on LDL particle number, and on apolipoprotein B but not on LDL cholesterol or non-HDL-C.

CONCLUSIONS

These differential associations point to pathways of LDL response to statin therapy and possibly to mechanisms of statin-dependent cardiovascular disease risk reduction.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681.

Genetic Variants Associated with Lipid Profiles in Chinese Patients with Type 2 Diabetes

Dyslipidemia is a strong risk factor for cardiovascular disease among patients with type 2 diabetes (T2D). The aim of this study was to identify lipid-related genetic variants in T2D patients of Han Chinese ancestry. Among 4,908 Chinese T2D patients who were not taking lipid-lowering medications, single nucleotide polymorphisms (SNPs) in seven genes previously found to be associated with lipid traits in genome-wide association studies conducted in populations of European ancestry (ABCA1, GCKR, BAZ1B, TOMM40, DOCK7, HNF1A, and HNF4A) were genotyped. After adjusting for multiple covariates, SNPs in ABCA1, GCKR, BAZ1B, TOMM40, and HNF1A were identified as significantly associated with triglyceride levels in T2D patients (P < 0.05). The associations between the SNPs in ABCA1 (rs3890182), GCKR (rs780094), and BAZ1B (rs2240466) remained significant even after correction for multiple testing (P = 8.85×10⁻³, 7.88×10⁻⁷, and 2.03×10⁻⁶, respectively). BAZ1B (rs2240466) also was associated with the total cholesterol level (P = 4.75×10⁻²). In addition, SNP rs157580 in TOMM40 was associated with the low-density lipoprotein cholesterol level (P = 6.94×10⁻³). Our findings confirm that lipid-related genetic loci are associated with lipid profiles in Chinese patients with type 2 diabetes.

Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies

Localization of causal variants underlying known risk loci is one of the main research challenges following genome-wide association studies. Risk loci are typically dissected through fine-mapping experiments in trans-ethnic cohorts for leveraging the variability in the local genetic structure across populations. More recent works have shown that genomic functional annotations (i.e., localization of tissue-specific regulatory marks) can be integrated for increasing fine-mapping performance within single-population studies. Here, we introduce methods that integrate the strength of association between genotype and phenotype, the variability in the genetic backgrounds across populations, and the genomic map of tissue-specific functional elements to increase trans-ethnic fine-mapping accuracy. Through extensive simulations and empirical data, we have demonstrated that our approach increases fine-mapping resolution over existing methods. We analyzed empirical data from a large-scale trans-ethnic rheumatoid arthritis (RA) study and showed that the functional genetic architecture of RA is consistent across European and Asian ancestries. In these data, we used our proposed methods to reduce the average size of the 90% credible set from 29 variants per locus for standard non-integrative approaches to 22 variants.

Clique-Based Clustering of Correlated SNPs in a Gene Can Improve Performance of Gene-Based Multi-Bin Linear Combination Test

Gene-based analysis of multiple single nucleotide polymorphisms (SNPs) in a gene region is an alternative to single SNP analysis. The multi-bin linear combination test (MLC) proposed in previous studies utilizes the correlation among SNPs within a gene to construct a gene-based global test. SNPs are partitioned into clusters of highly correlated SNPs, and the MLC test statistic quadratically combines linear combination statistics constructed for each cluster. The test has degrees of freedom equal to the number of clusters and can be more powerful than a fully quadratic or fully linear test statistic. In this study, we develop a new SNP clustering algorithm designed to find cliques, which are complete subnetworks of SNPs with all pairwise correlations above a threshold. We evaluate the performance of the MLC test using the clique-based CLQ algorithm versus using the tag-SNP-based LDSelect algorithm. In our numerical power calculations we observed that the two clustering algorithms produce identical clusters about 40~60% of the time, yielding similar power on average. However, because the CLQ algorithm tends to produce smaller clusters with stronger positive correlation, the MLC test is less likely to be affected by the occurrence of opposing signs in the individual SNP effect coefficients.

Insights into blood lipids from rare variant discovery

Large-scale genome wide screens have discovered over 160 common variants associated with plasma lipids, which are risk factors often linked to heart disease. A large fraction of lipid heritability remains unexplained, and it is hypothesized that rare variants of functional consequence may account for some of the missing heritability. Finding lipid-associated variants that occur less frequently in the human population poses a challenge, primarily due to lack of power and difficulties to identify and test them. Interrogation of the protein-coding regions of the genome using array and sequencing techniques has led to important discoveries of rare variants that affect lipid levels and related disease risk. Here, we summarize the latest methods and findings that contribute to our current understanding of rare variant lipid genetics.

Analysis of a cardiovascular disease genetic risk score in the Diabetes Heart Study

AIMS

It remains unclear whether the high cardiovascular disease (CVD) burden in people with type 2 diabetes (T2D) is associated with genetic variants that contribute to CVD in general populations. Recent studies have examined genetic risk scores of single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies for their cumulative contribution to CVD-related traits. Most analyses combined SNPs associated with a single phenotypic class, e.g., lipids. In the present analysis, we examined a more comprehensive risk score comprised of SNPs associated with a broad range of CVD risk phenotypes.

METHODS

The composite risk score was analyzed for potential associations with subclinical CVD, self-reported CVD events, and mortality in 983 T2D-affected individuals of European descent from 466 Diabetes Heart Study (DHS) families. Genetic association was examined using marginal models with generalized estimating equations for subclinical CVD and prior CVD events and Cox proportional hazards models with sandwich-based variance estimation for mortality; analyses were adjusted for age and sex.

RESULTS

An increase in genetic risk score was significantly associated with higher levels of coronary artery calcified plaque (p = 1.23 × 10(-4)); however, no significant associations with self-reported myocardial infarction and CVD events and all-cause and CVD mortality were observed.

CONCLUSIONS

These results suggest that a genetic risk score of SNPs associated with CVD events and risk factors does not significantly account for CVD risk in the DHS, highlighting the limitations of applying current genetic markers for CVD in individuals with diabetes.

Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study

BACKGROUND

Observational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS.

METHODS AND FINDINGS

We identified single nucleotide polymorphisms (SNPs) associated with 25-hydroxyvitamin D (25OHD) level from SUNLIGHT, the largest (n = 33,996) genome-wide association study to date for vitamin D. Four SNPs were genome-wide significant for 25OHD level (p-values ranging from 6 × 10-10 to 2 × 10-109), and all four SNPs lay in, or near, genes strongly implicated in separate mechanisms influencing 25OHD. We then ascertained their effect on 25OHD level in 2,347 participants from a population-based cohort, the Canadian Multicentre Osteoporosis Study, and tested the extent to which the 25OHD-decreasing alleles explained variation in 25OHD level. We found that the count of 25OHD-decreasing alleles across these four SNPs was strongly associated with lower 25OHD level (n = 2,347, F-test statistic = 49.7, p = 2.4 × 10-12). Next, we conducted an MR study to describe the effect of genetically lowered 25OHD on the odds of MS in the International Multiple Sclerosis Genetics Consortium study, the largest genetic association study to date for MS (including up to 14,498 cases and 24,091 healthy controls). Alleles were weighted by their relative effect on 25OHD level, and sensitivity analyses were performed to test MR assumptions. MR analyses found that each genetically determined one-standard-deviation decrease in log-transformed 25OHD level conferred a 2.0-fold increase in the odds of MS (95% CI: 1.7-2.5; p = 7.7 × 10-12; I2 = 63%, 95% CI: 0%-88%). This result persisted in sensitivity analyses excluding SNPs possibly influenced by population stratification or pleiotropy (odds ratio [OR] = 1.7, 95% CI: 1.3-2.2; p = 2.3 × 10-5; I2 = 47%, 95% CI: 0%-85%) and including only SNPs involved in 25OHD synthesis or metabolism (ORsynthesis = 2.1, 95% CI: 1.6-2.6, p = 1 × 10-9; ORmetabolism = 1.9, 95% CI: 1.3-2.7, p = 0.002). While these sensitivity analyses decreased the possibility that pleiotropy may have biased the results, residual pleiotropy is difficult to exclude entirely.

CONCLUSIONS

A genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.

The Influence of Known Genetic Variants on Subclinical Cardiovascular Outcomes in Childhood

Background—

Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) for subclinical cardiovascular outcomes in adults. We examined the influence of these variants on the same outcomes in childhood.

Methods and Results—

In a population-based prospective cohort study among 4137 children, we examined the associations of SNPs, individually and incorporated in genetic risk scores, which were identified in adults for cardiac (2 SNPs for left ventricular end-diastolic diameter and 5 SNPs for aortic root diameter) and blood pressure outcomes (29 SNPs for systolic and diastolic blood pressure, 22 SNPs for mean arterial pressure, and 10 SNPs for pulse pressure) with the same outcomes in children (median age of 6.0 years [95% range, 4.5–8.7]). Weighted and unweighted risk scores for aortic root diameter were associated with childhood aortic root diameter (difference per additional average risk allele 0.09 mm [95% CI: 0.05, 0.13]). Weighted and unweighted risk scores for pulse pressure were associated with childhood pulse pressure (difference per additional average risk allele 0.22 mm Hg [95% CI: 0.08, 0.35] and 0.18 mm Hg [95% CI: 0.05, 0.31], respectively), but not with childhood systolic or diastolic blood pressure or mean arterial pressure. The risk scores for blood pressure and mean arterial pressure were not associated with any of the childhood blood pressure outcomes.

Conclusions—

Genetic risk scores based on SNPs for aortic root diameter and pulse pressure in adults are associated with the same outcomes in children. SNPs related to cardiovascular outcomes in adulthood at least partly influence cardiovascular development from early life onwards.

Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

OBJECTIVE

Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS

We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS

We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h).

CONCLUSIONS

Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

BACKGROUND/AIMS

Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections.

METHODS

To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839).

RESULTS

Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population.

CONCLUSION

Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Associations of lipid levels susceptibility loci with coronary artery disease in Chinese population

Background

Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) that were associated with blood lipid levels in Caucasians. This study investigated whether these loci influenced lipid levels and whether they were associated with the risk of coronary artery disease (CAD) and its angiographic severity in Chinese population.

Methods

Six SNPs were genotyped in 1100 CAD cases and 1069 controls using the high-resolution melting (HRM) method. Coronary atherosclerosis severity was assessed by the vessel scores and the Gensini scoring system.

Results

Among the 6 SNPs and the genetic risks scores (GRS), the minor alleles of HNF1A rs1169288 (odd ratio (OR) = 1.18, 95 % confidence interval (CI) 1.05–1.33, P = 0.006) and MADD-FOLH1 rs7395662 (OR = 1.20, 95 % CI 1.07–1.36, P = 0.002) as well as the GRS (P = 1.06 × 10^-5) were significantly associated with increased risk of CAD after false discovery rate (FDR) correction. The vessel (P = 0.013) and Gensini scores (β = 0.113, P = 0.002) differed among CAD patients with different SNP rs1169288 C > T genotypes. The multiple linear regression analyses using an additive model revealed that the minor allele C of SNP rs1169288 (β = 0.060, P = 0.001) and the GRS (β = 0.033, P = 3.59 × 10^-4) were significantly associated with increased total cholesterol (TC) levels, the minor allele A of SNP rs7395662 (β = -0.024, P = 0.007) and the GRS (β = -0.013, P = 0.004) were significantly associated with decreased high-density lipoprotein cholesterol (HDL-c) levels.

Conclusions

The present study demonstrated that SNPs rs1169288, rs7395662 and the GRS were significantly associated with lipid levels and the risk of CAD in Chinese population. Furthermore, the allele C of SNP rs1169288 increased the odds of coronary atherosclerosis severity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-015-0079-1) contains supplementary material, which is available to authorized users.

Association of polymorphisms in the MAFB gene and the risk of coronary artery disease and ischemic stroke: a case-control study

BACKGROUND

The v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog B gene (MAFB) has been associated with serum lipid levels in the Eurpean population, but little is known about such association in the Chinese population or in atherosclerosis-related patients. Therefore, the purpose of the present study was to assess the association of the single nucleotide polymorphisms (SNPs) in the MAFB and serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese population.

METHODS

A total of 1,065 unrelated patients (CAD, 525 and IS, 540) and 539 healthy controls were recruited in this study. Genotypes of the MAFB rs2902940 and rs6102059 SNPs were determined by the Snapshot technology platform.

RESULTS

The rs2902940AA genotype was associated with an increased risk of CAD (adjusted OR = 1.63, 95% CI = 1.07-2.48, P = 0.023) and IS (adjusted OR = 1.69, 95% CI = 1.09-2.61, P = 0.017). The rs2902940GA/AA genotypes were also associated with an increased risk of CAD (adjusted OR = 1.56, 95% CI = 1.04-2.32, P = 0.030 for GA/AA vs. GG) and IS (adjusted OR = 1.72, 95% CI = 1.14-2.60, P = 0.010 for GA/AA vs. GG). Significant interactions were observed only in those with higher body mass index (BMI), hypertension and diabetes (P < 0.05). The subjects with rs2902940GA/AA genotypes in controls had lower serum ApoAI levels than the subjects with GG genotype (P = 0.024).

CONCLUSIONS

The rs2902940A allele carriers in the MAFB conferred a decreased serum ApoAI level in controls and an increased risk of CAD and IS. The rs2902940GA/AA genotypes interacted with higher BMI, hypertension and diabetes to contribute the risk of CAD and IS.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Genetic meta-analysis of 15,901 African Americans identifies variation in EXOC3L1 is associated with HDL concentration

Meta-analyses of European populations has successfully identified genetic variants in over 150 loci associated with lipid levels, but results from additional ethnicities remain limited. Previously, we reported two novel lipid loci identified in a sample of 7,657 African Americans using a gene-centric array including 50,000 SNPs in 2,100 candidate genes. Initial discovery and follow-up of signals with P < 10(-5) in additional African American samples confirmed CD36 and ICAM1. Using an additional 8,244 African American female samples from the Women's Health Initiative SNP Health Association Resource genome-wide association study dataset, we further examined the previous meta-analyses results by attempting to replicate 20 additional putative lipid signals with P < 10(-4). Replication confirmed rs868213, located in a splice donor region of exocyst complex component 3-like 1 (EXOC3L1) as a novel signal for HDL (additive allelic effect β = 0.02; P = 1.4 × 10(-8); meta-analyses of discovery and replication). EXOC3L1 is strongly expressed in vascular endothelium and forms part of the exocyst complex, a key facilitator of the trafficking of lipid receptors. Increasing sample sizes for genetic studies in nonEuropean populations will continue to improve our understanding of lipid metabolism.

Asparaginase treatment side-effects may be due to genes with homopolymeric Asn codons (Review-Hypothesis)

The present treatment of childhood T-cell leukemias involves the systemic administration of prokary-otic L-asparaginase (ASNase), which depletes plasma Asparagine (Asn) and inhibits protein synthesis. The mechanism of therapeutic action of ASNase is poorly understood, as are the etiologies of the side-effects incurred by treatment. Protein expression from genes bearing Asn homopolymeric coding regions (N-hCR) may be particularly susceptible to Asn level fluctuation. In mammals, N-hCR are rare, short and conserved. In humans, misfunctions of genes encoding N-hCR are associated with a cluster of disorders that mimic ASNase therapy side-effects which include impaired glycemic control, dislipidemia, pancreatitis, compromised vascular integrity, and neurological dysfunction. This paper proposes that dysregulation of Asn homeostasis, potentially even by ASNase produced by the microbiome, may contribute to several clinically important syndromes by altering expression of N-hCR bearing genes. By altering amino acid abundance and modulating ribosome translocation rates at codon repeats, the microbiomic environment may contribute to genome decoding and to shaping the proteome. We suggest that impaired translation at poly Asn codons elevates diabetes risk and severity.

Iron and hepcidin as risk factors in atherosclerosis: what do the genes say?

Background

Previous reports suggested a role for iron and hepcidin in atherosclerosis. Here, we evaluated the causality of these associations from a genetic perspective via (i) a Mendelian randomization (MR) approach, (ii) study of association of atherosclerosis-related single nucleotide polymorphisms (SNPs) with iron and hepcidin, and (iii) estimation of genomic correlations between hepcidin, iron and atherosclerosis.

Results

Analyses were performed in a general population sample. Iron parameters (serum iron, serum ferritin, total iron-binding capacity and transferrin saturation), serum hepcidin and genome-wide SNP data were available for N = 1,819; non-invasive measurements of atherosclerosis (NIMA), i.e., presence of plaque, intima media thickness and ankle-brachial index (ABI), for N = 549. For the MR, we used 12 iron-related SNPs that were previously identified in a genome-wide association meta-analysis on iron status, and assessed associations of individual SNPs and quartiles of a multi-SNP score with NIMA. Quartile 4 versus quartile 1 of the multi-SNP score showed directionally consistent associations with the hypothesized direction of effect for all NIMA in women, indicating that increased body iron status is a risk factor for atherosclerosis in women. We observed no single SNP associations that fit the hypothesized directions of effect between iron and NIMA, except for rs651007, associated with decreased ferritin concentration and decreased atherosclerosis risk. Two of six NIMA-related SNPs showed association with the ratio hepcidin/ferritin, suggesting that an increased hepcidin/ferritin ratio increases atherosclerosis risk. Genomic correlations were close to zero, except for hepcidin and ferritin with ABI at rest [−0.27 (SE 0.34) and −0.22 (SE 0.35), respectively] and ABI after exercise [−0.29 (SE 0.34) and −0.30 (0.35), respectively]. The negative sign indicates an increased atherosclerosis risk with increased hepcidin and ferritin concentrations.

Conclusions

Our results suggest a potential causal role for hepcidin and ferritin in atherosclerosis, and may indicate that iron status is causally related to atherosclerosis in women.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0246-4) contains supplementary material, which is available to authorized users.

Contribution of Rare and Common Genetic Variants to Plasma Lipid Levels and Carotid Stiffness and Geometry: A Substudy of the Paris Prospective Study 3

BACKGROUND

We assess the contribution of common and rare putatively functional genetic variants (most of them coding) present on the Illumina exome Beadchip to the variability of plasma lipids and stiffness of the common carotid artery.

METHODS AND RESULTS

Measurements were obtained from 2283 men and 1398 women, and after filtering and exclusion of monomorphic variants, 32,827 common (minor allele frequency >0.01) and 68,770 rare variants were analyzed. A large fraction of the heritability of plasma lipids is attributable to variants present on the array, especially for triglycerides (fraction of variance attributable to measured genotypes: V(G)/V(p)=31.4%, P<3.1×10(-11)) and high-density lipoprotein cholesterol (V(G)/V(p)=26.4%, P<4.2×10(-12)). Plasma lipids were associated with common variants located in known candidate genes, but no implication of rare variants could be established. Gene sets for plasma lipids, blood pressure, and coronary artery disease were defined on the basis of recent meta-analyses of genome-wide association studies. We observed a strong association between the plasma lipids gene set and plasma lipid variables, but none of the 3 genome-wide association studies gene sets was associated with the carotid parameters. Significant V(G)/V(p) ratios were observed for external (14.5%, P<2.7×10(-5)) and internal diameter (13.4%, P<4.3×10(-4)), stiffness (12.5%, P<8.0×10(-4)), intima-media thickness (10.6%, P<7.9×10(-4)), and wall cross-sectional area (13.2%, P<2.4×10(-5)). A significant association was observed between the common rs2903692 polymorphism of the CLEC16A gene and the internal diameter (P<4.3×10(-7)).

CONCLUSIONS

These results suggest an involvement of CLEC16A, a gene that has been reported to be associated with immune disorders, in the modulation of carotid vasodilatation.

A genetic variant in the seed region of miR-4513 shows pleiotropic effects on lipid and glucose homeostasis, blood pressure, and coronary artery disease

MicroRNAs (miRNA) play a crucial role in the regulation of diverse biological processes by post-transcriptional modulation of gene expression. Genetic polymorphisms in miRNA-related genes can potentially contribute to a wide range of phenotypes. The effect of such variants on cardiometabolic diseases has not yet been defined. We systematically investigated the association of genetic variants in the seed region of miRNAs with cardiometabolic phenotypes, using the thus far largest genome-wide association studies on 17 cardiometabolic traits/diseases. We found that rs2168518:G>A, a seed region variant of miR-4513, associates with fasting glucose, low-density lipoprotein-cholesterol, total cholesterol, systolic and diastolic blood pressure, and risk of coronary artery disease. We experimentally showed that miR-4513 expression is significantly reduced in the presence of the rs2168518 mutant allele. We sought to identify miR-4513 target genes that may mediate these associations and revealed five genes (PCSK1, BNC2, MTMR3, ANK3, and GOSR2) through which these effects might be taking place. Using luciferase reporter assays, we validated GOSR2 as a target of miR-4513 and further demonstrated that the miRNA-mediated regulation of this gene is changed by rs2168518. Our findings indicate a pleiotropic effect of miR-4513 on cardiometabolic phenotypes and may improve our understanding of the pathophysiology of cardiometabolic diseases.

The Use of Non-Variant Sites to Improve the Clinical Assessment of Whole-Genome Sequence Data

Genetic testing, which is now a routine part of clinical practice and disease management protocols, is often based on the assessment of small panels of variants or genes. On the other hand, continuous improvements in the speed and per-base costs of sequencing have now made whole exome sequencing (WES) and whole genome sequencing (WGS) viable strategies for targeted or complete genetic analysis, respectively. Standard WGS/WES data analytical workflows generally rely on calling of sequence variants respect to the reference genome sequence. However, the reference genome sequence contains a large number of sites represented by rare alleles, by known pathogenic alleles and by alleles strongly associated to disease by GWAS. It’s thus critical, for clinical applications of WGS and WES, to interpret whether non-variant sites are homozygous for the reference allele or if the corresponding genotype cannot be reliably called. Here we show that an alternative analytical approach based on the analysis of both variant and non-variant sites from WGS data allows to genotype more than 92% of sites corresponding to known SNPs compared to 6% genotyped by standard variant analysis. These include homozygous reference sites of clinical interest, thus leading to a broad and comprehensive characterization of variation necessary to an accurate evaluation of disease risk. Altogether, our findings indicate that characterization of both variant and non-variant clinically informative sites in the genome is necessary to allow an accurate clinical assessment of a personal genome. Finally, we propose a highly efficient extended VCF (eVCF) file format which allows to store genotype calls for sites of clinical interest while remaining compatible with current variant interpretation software.

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci

Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3' UTR regulation. We also showed that (1) 15%-36% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.

Quantitative Trait Locus Analysis of SIX1-SIX6 With Retinal Nerve Fiber Layer Thickness in Individuals of European Descent

PURPOSE

To perform a quantitative trait locus (QTL) analysis and evaluate whether a locus between SIX1 and SIX6 is associated with retinal nerve fiber layer (RNFL) thickness in individuals of European descent.

DESIGN

Observational, multicenter, cross-sectional study.

METHODS

A total of 231 participants were recruited from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. Association of rs10483727 in SIX1-SIX6 with global and sectoral RNFL thickness was performed. Quantitative trait analysis with the additive model of inheritance was analyzed using linear regression. Trend analysis was performed to evaluate the mean global and sectoral RNFL thickness with 3 genotypes of interest (T/T, C/T, C/C). All models were adjusted for age and sex.

RESULTS

Direction of association between T allele and RNFL thickness was consistent in the global and different sectoral RNFL regions. Each copy of the T risk allele in rs10483727 was associated with -0.16 μm thinner global RNFL thickness (β = -0.16, 95% confidence interval: -0.28 to -0.03; P = .01). Similar patterns were found for the sectoral regions, including inferior (P = .03), inferior-nasal (P = .017), superior-nasal (P = .0025), superior (P = .002) and superior-temporal (P = .008). The greatest differences were observed in the superior and inferior quadrants, supporting clinical observations for RNFL thinning in glaucoma. Thinner global RNFL was found in subjects with T/T genotypes compared to subjects with C/T and C/C genotypes (P = .044).

CONCLUSIONS

Each copy of the T risk allele has an additive effect and was associated with thinner global and sectoral RNFL. Findings from this QTL analysis further support a genetic contribution to glaucoma pathophysiology.

Genetic Predisposition to Dyslipidemia and Risk of Preeclampsia

BACKGROUND

Large epidemiologic studies support the role of dyslipidemia in preeclampsia; however, the etiology of preeclampsia or whether dyslipidemia plays a causal role remains unclear. We examined the association between the genetic predisposition to dyslipidemia and risk of preeclampsia using validated genetic markers of dyslipidemia.

METHODS

Preeclampsia cases (n = 164) and normotensive controls (n = 110) were selected from live birth certificates to nulliparous Iowa women during the period August 2002 to May 2005. Disease status was verified by medical chart review. Genetic predisposition to dyslipidemia was estimated by 4 genetic risk scores (GRS) (total cholesterol (TC), LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), and triglycerides) on the basis of established loci for blood lipids. Logistic regression analyses were used to evaluate the relationships between each of the 4 genotype scores and preeclampsia. Replication analyses were performed in an independent, US population of preeclampsia cases (n = 516) and controls (n = 1,097) of European ancestry.

RESULTS

The GRS related to higher levels of TC, LDL-C, and triglycerides demonstrated no association with the risk of preeclampsia in either the Iowa or replication population. The GRS related to lower HDL-C was marginally associated with an increased risk for preeclampsia (odds ratio (OR) = 1.03, 95% confidence interval (CI) = 0.99-1.07; P = 0.10). In the independent replication population, the association with the HDL-C GRS was also marginally significant (OR = 1.03, 95% CI: 1.00-1.06; P = 0.04).

CONCLUSIONS

Our data suggest a potential effect between the genetic predisposition to dyslipidemic levels of HDL-C and an increased risk of preeclampsia, and, as such, suggest that dyslipidemia may be a component along the causal pathway to preeclampsia.

Evaluation of polygenic cause in Korean patients with familial hypercholesterolemia - A study supported by Korean Society of Lipidology and Atherosclerosis

BACKGROUND/OBJECTIVE

Familial hypercholesterolemia (FH) is an autosomal dominant disorder caused by mutations in LDLR, APOB, or PCSK9. Polygenicity is a plausible cause in mutation-negative FH patients based on LDL cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs) identified by the Global Lipids Genetics Consortium (GLGC). However, there are limited data regarding the polygenic cause of FH in Asians.

METHODS

We gathered data from 66 mutation-negative and 31 mutation-positive Korean FH patients, as well as from 2274 controls who participated in the Korean Health Examinee (HEXA) shared control study. We genotyped the patients for six GLGC SNPs and four East Asian LDL-C-associated SNPs and compared SNP scores among patient groups and controls.

RESULTS

Weighted mean 6- and 4-SNP scores (0.67 [SD = 0.07] and 0.46 [0.11], respectively) were both significantly associated with LDL-C levels in controls (p = 2.1 × 10(-4), R(2) = 0.01 and p = 5.0 × 10(-12), R(2) = 0.02, respectively). Mutation-negative FH patients had higher 6-SNP (0.72 [0.07]) and 4-SNP (0.49 [0.08]) scores than controls (p = 1.8 × 10(-8) and p = 3.6 × 10(-3), respectively). We also observed higher scores in mutation-positive FH patients compared with controls, but the difference did not reach statistical significance.

CONCLUSION

The present study demonstrates the utility of SNP score analysis for identifying polygenic FH in Korean patients by showing that small-effect common SNPs may cumulatively elevate LDL-C levels.

Sex-Specific Parental Effects on Offspring Lipid Levels

Background

Plasma lipid levels are highly heritable traits, but known genetic loci can only explain a small portion of their heritability.

Methods and Results

In this study, we analyzed the role of parental levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TGs) in explaining the values of the corresponding traits in adult offspring. We also evaluated the contribution of nongenetic factors that influence lipid traits (age, body mass index, smoking, medications, and menopause) alone and in combination with variability at the genetic loci known to associate with TC, LDL-C, HDL-C, and TG levels. We performed comparisons among different sex-specific regression models in 416 families from the Framingham Heart Study and 304 from the SardiNIA cohort. Models including parental lipid levels explain significantly more of the trait variation than models without these measures, explaining up to ≈39% of the total trait variation. Of this variation, the parent-of-origin effect explains as much as ≈15% and it does so in a sex-specific way. This observation is not owing to shared environment, given that spouse-pair correlations were negligible (<1.5% explained variation in all cases) and is distinct from previous genetic and acquired factors that are known to influence serum lipid levels.

Conclusions

These findings support the concept that unknown genetic and epigenetic contributors are responsible for most of the heritable component of the plasma lipid phenotype, and that, at present, the clinical utility of knowing age-matched parental lipid levels in assessing risk of dyslipidemia supersedes individual locus effects. Our results support the clinical utility of knowing parental lipid levels in assessing future risk of dyslipidemia.

Increased high-density lipoprotein cholesterol levels in mice with XX versus XY sex chromosomes

OBJECTIVE

The molecular mechanisms underlying sex differences in dyslipidemia are poorly understood. We aimed to distinguish genetic and hormonal regulators of sex differences in plasma lipid levels.

APPROACH AND RESULTS

We assessed the role of gonadal hormones and sex chromosome complement on lipid levels using the four core genotypes mouse model (XX females, XX males, XY females, and XY males). In gonadally intact mice fed a chow diet, lipid levels were influenced by both male-female gonadal sex and XX-XY chromosome complement. Gonadectomy of adult mice revealed that the male-female differences are dependent on acute effects of gonadal hormones. In both intact and gonadectomized animals, XX mice had higher HDL cholesterol (HDL-C) levels than XY mice, regardless of male-female sex. Feeding a cholesterol-enriched diet produced distinct patterns of sex differences in lipid levels compared with a chow diet, revealing the interaction of gonadal and chromosomal sex with diet. Notably, under all dietary and gonadal conditions, HDL-C levels were higher in mice with 2 X chromosomes compared with mice with an X and Y chromosome. By generating mice with XX, XY, and XXY chromosome complements, we determined that the presence of 2 X chromosomes, and not the absence of the Y chromosome, influences HDL-C concentration.

CONCLUSIONS

We demonstrate that having 2 X chromosomes versus an X and Y chromosome complement drives sex differences in HDL-C. It is conceivable that increased expression of genes escaping X-inactivation in XX mice regulates downstream processes to establish sexual dimorphism in plasma lipid levels.