Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes

Identification of SNPs and Candidate Genes Associated with Monocyte/Lymphocyte Ratio and Neutrophil/Lymphocyte Ratio in Duroc × Erhualian F2 Population

Understanding the pig immune function is crucial for disease-resistant breeding and potentially for human health research due to shared immune system features. Immune cell ratios, like monocyte/lymphocyte ratio (MLR) and neutrophil/lymphocyte ratio (NLR), offer a more comprehensive view of immune status compared to individual cell counts. However, research on pig immune cell ratios remains limited. This study investigated MLR and NLR in a Duroc × Erhualian F2 resource population. Heritability analysis revealed high values (0.649 and 0.688 for MLR and NLR, respectively), suggesting a strong genetic component. Furthermore, we employed an ensemble-like GWAS (E-GWAS) strategy and functional annotation analysis to identify 11 MLR-associated and 6 NLR-associated candidate genes. These genes were significantly enriched in immune-related biological processes. These findings provide novel genetic markers and candidate genes associated with porcine immunity, thereby providing valuable insights for addressing biosecurity and animal welfare concerns in the pig industry.

Genome-wide discovery for biomarkers using quantile regression at biobank scale

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. Conventional GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. We draw attention here to an alternative, lesser known approach, namely quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest. Quantile regression can be applied efficiently at biobank scale, while having some unique advantages such as (1) identifying variants with heterogeneous effects across quantiles of the phenotype distribution; (2) accommodating a wide range of phenotype distributions including non-normal distributions, with invariance of results to trait transformations; and (3) providing more detailed information about genotype-phenotype associations even for those associations identified by conventional GWAS. We show in simulations that quantile regression is powerful across both homogeneous and various heterogeneous models. Applications to 39 quantitative traits in the UK Biobank demonstrate that quantile regression can be a helpful complement to linear regression in GWAS and can identify variants with larger effects on high-risk subgroups of individuals but with lower or no contribution overall.

An individualized Bayesian method for estimating genomic variants of hypertension

BACKGROUND

Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual.

RESULTS

We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve.

CONCLUSIONS

The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Genomic Variation Affecting MPV and PLT Count in Association with Development of Ischemic Stroke and Its Subtypes

Platelets play a significant role in the pathophysiology of ischemic stroke since they are involved in the formation of intravascular thrombus after erosion or rupture of the atherosclerotic plaques. Platelet (PLT) count and mean platelet volume (MPV) are the two significant parameters that affect the functions of platelets. In the current study, MPV and PLT count was evaluated using flow cytometry and a cell counter. SonoClot analysis was carried out to evaluate activated clot timing (ACT), clot rate (CR), and platelet function (PF). Genotyping was carried out using GSA and Sanger sequencing, and expression analysis was performed using RT-PCR. In silico analysis was carried out using the GROMACS tool and UNAFold. The interaction of significant proteins with other proteins was predicted using the STRING database. Ninety-six genes were analyzed, and a significant association of THPO (rs6141) and ARHGEF3 (rs1354034) was observed with the disease and its subtypes. Altered genotypes were associated significantly with increased MPV, decreased PLT count, and CR. Expression analysis revealed a higher expression in patients bearing the variant genotypes of both genes. In silico analysis revealed that mutation in the THPO gene leads to the reduced compactness of protein structure. mRNA encoded by mutated ARHGEF3 gene increases the half-life of mRNA. The two significant proteins interact with many other proteins, especially the ones involved in platelet activation, aggregation, erythropoiesis, megakaryocyte maturation, and cytoskeleton rearrangements, suggesting that they could be important players in the determination of MPV values. In conclusion, the current study demonstrated the role of higher MPV affected by genetic variation in the development of IS and its subtypes. The results of the current study also indicate that higher MPV can be used as a biomarker for the disease and altered genotypes, and higher MPV can be targeted for better therapeutic outcomes.

The importance of polymorphisms in the genes encoding glutathione S-transferase isoenzymes in development of selected cancers and cardiovascular diseases

Glutathione S-transferases are a family of enzymes, whose main role is to detoxify cells from many exogenous factors, such as xenobiotics or carcinogens. It has also been proven that changes in the genes encoding these enzymes may affect the incidence of selected cancers and cardiovascular diseases. The aim of this study was to review the most important reports related to the role of glutathione S-transferases in the pathophysiology of two of the most common diseases in modern society - cancers and cardiovascular diseases. It was shown that polymorphisms in the genes encoding glutathione S-transferases are associated with the development of these diseases. However, depending on the ethnic group, the researchers obtained divergent results related to this field. In the case of the GSTP1 A/G gene polymorphism was shown an increased incidence of breast cancer in Asian women, while this relationship in European and African women was not found. Similarly. In the case of cardiovascular diseases, the differences in the influence of GSTM1, GSTT1, GSTP1 and GSTA1 polymorphisms on their development or lack of it depending on the continent were shown. These examples show that the development of the above-mentioned diseases is not only influenced by genetic changes, but their pathophysiology is more complex. The mere presence of a specific genotype within a studied polymorphism may not predispose to cancer, but in combination with environmental factors, which often depend on the place of residence, it may elevate the chance of developing the selected disease.

Quantile Regression for biomarkers in the UK Biobank

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. An alternative and easy to apply approach is quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest by modeling conditional quantiles within a regression framework. Quantile regression can be applied efficiently at biobank scale using standard statistical packages in much the same way as linear regression, while having some unique advantages such as identifying variants with heterogeneous effects across different quantiles, including non-additive effects and variants involved in gene-environment interactions; accommodating a wide range of phenotype distributions with invariance to trait transformation; and overall providing more detailed information about the underlying genotype-phenotype associations. Here, we demonstrate the value of quantile regression in the context of GWAS by applying it to 39 quantitative traits in the UK Biobank (n > 300 , 000 individuals). Across these 39 traits we identify 7,297 significant loci, including 259 loci only detected by quantile regression. We show that quantile regression can help uncover replicable but unmodelled gene-environment interactions, and can provide additional key insights into poorly understood genotype-phenotype correlations for clinically relevant biomarkers at minimal additional cost.

VEGF-A related SNPs: a cardiovascular context

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Currently, cardiovascular disease risk algorithms play a role in primary prevention. However, this is complicated by a lack of powerfully predictive biomarkers that could be observed in individuals before the onset of overt symptoms. A key potential biomarker for heart disease is the vascular endothelial growth factor (VEGF-A), a molecule that plays a pivotal role in blood vessel formation. This molecule has a complex biological role in the cardiovascular system due to the processes it influences, and its production is impacted by various CVD risk factors. Research in different populations has shown single nucleotide polymorphisms (SNPs) may affect circulating VEGF-A plasma levels, with some variants associated with the development of CVDs, as well as CVD risk factors. This minireview aims to give an overview of the VEGF family, and of the SNPs reported to influence VEGF-A levels, cardiovascular disease, and other risk factors used in CVD risk assessments.

Health inequity in genomic personalized medicine in underrepresented populations: a look at the current evidence

Improvements in sequencing technology coupled with dramatic declines in the cost of genome sequencing have led to a proportional growth in the size and number of genetic datasets since the release of the human genetic sequence by The Human Genome Project (HGP) international consortium. The HGP was undeniably a significant scientific success, a turning point in human genetics and the beginning of human genomics. This burst of genetic information has led to a greater understanding of disease pathology and the potential of employing this data to deliver more precise patient care. Hence, the recognition of high-penetrance disease-causing mutations which encode drivers of disease has made the management of most diseases more specific. Nonetheless, while genetic scores are becoming more extensively used, their application in the real world is expected to be limited due to the lack of diversity in the data used to construct them. Underrepresented populations, such as racial and ethnic minorities, low-income individuals, and those living in rural areas, often experience greater health disparities and worse health outcomes compared to the general population. These disparities are often the result of systemic barriers, such as poverty, discrimination, and limited access to healthcare. Addressing health inequity in underrepresented populations requires addressing the underlying social determinants of health and implementing policies and programs which promoted health equity and reduce disparities. This can include expanding access to affordable healthcare, addressing poverty and unemployment, and promoting policies that combat discrimination and racism.

Big Data in Gastroenterology Research

Studying individual data types in isolation provides only limited and incomplete answers to complex biological questions and particularly falls short in revealing sufficient mechanistic and kinetic details. In contrast, multi-omics approaches to studying health and disease permit the generation and integration of multiple data types on a much larger scale, offering a comprehensive picture of biological and disease processes. Gastroenterology and hepatobiliary research are particularly well-suited to such analyses, given the unique position of the luminal gastrointestinal (GI) tract at the nexus between the gut (mucosa and luminal contents), brain, immune and endocrine systems, and GI microbiome. The generation of 'big data' from multi-omic, multi-site studies can enhance investigations into the connections between these organ systems and organisms and more broadly and accurately appraise the effects of dietary, pharmacological, and other therapeutic interventions. In this review, we describe a variety of useful omics approaches and how they can be integrated to provide a holistic depiction of the human and microbial genetic and proteomic changes underlying physiological and pathophysiological phenomena. We highlight the potential pitfalls and alternatives to help avoid the common errors in study design, execution, and analysis. We focus on the application, integration, and analysis of big data in gastroenterology and hepatobiliary research.

Molecular Quantitative Trait Locus Mapping in Human Complex Diseases

Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.

LPL, FNDC5 and PPARγ gene polymorphisms related to body composition parameters and lipid metabolic profile in adolescents from Southern Italy

Background

Plasma lipid profile and anthropometric variables are known to be under strong genetic control and the identification of genetic variants associated with bioclinical parameters is of considerable public health importance. In this study, a young cohort of healthy individuals was genotyped for genes related to health and pathological conditions, to analyze the association of single nucleotide polymorphisms (SNPs) with different bioclinical parameters, adherence to the Mediterranean Diet (MD) and physical activity, studying the role of lifestyle and body composition parameters on biochemical metabolic profile.

Methods

Association analysis of single variants in the genes of lipoprotein lipase (LPL), fibronectin type III domain containing protein 5 (FNDC5), and peroxisome proliferator-activated receptor-gamma (PPARγ) and haplotype analyses were performed.

Results

Multiple (n = 14) common variants in the three genes demonstrated a significant effect on plasma lipoprotein-lipid levels and/or on biochemical parameters in our sample. Specifically, SNPs were related to lipid metabolism (rs3866471, rs4922115, rs11570892, rs248, rs316, rs1059507, rs1801282) or glycemic profile (rs3208305) or anthropometric parameters (rs3480, rs726344, rs1570569) for a total of 26 significant associations (P < 0.01 and/or P < 0.05) and two haplotypes, for the first time, were strongly associated with lipid and body composition parameters. Interestingly, we identified twenty-four new variants not previously described in the literature and a novel significant association between rs80143795 and body composition.

Conclusions

In this study we confirm the association between these SNPs on lipid metabolism and body parameters also in a young cohort, indicating the important role of these genetic factors as determinants of health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03314-w.

Association of Metabolic Syndrome with Aerobic Exercise and LPL rs3779788 Polymorphism in Taiwan Biobank Individuals

PURPOSE

The Lipoprotein lipase (LPL) gene is a significant contributor to dyslipidemia. It has shown associations with several conditions including atherosclerosis, obesity, and metabolic syndrome (MetS). We assessed the interactive association between MetS and rs3779788 of the LPL gene based on aerobic exercise.

MATERIALS AND METHODS

Data were available for 7532 Taiwan Biobank (TWB) participants recruited between 2008 and 2016. We used multiple logistic regression to determine the odds ratios (OR) for MetS and their 95% confident intervals (C.I.). Potential variables included LPL rs3779788, aerobic exercise, sex, age, education, marital status, body mass index (BMI), smoking, alcohol consumption, midnight snacking, vegetarian diet, coffee, dietary fat, and tea drinking.

RESULTS

Aerobic exercise was protective against MetS (OR, 0.858; 95% C.I., 0.743-0.991). Compared to CC/CT genotype, the OR for developing MetS was 0.875, (95% C.I., 0.571-1.341) in TT individuals. The test for interaction was significant for the rs3779788 variant and aerobic exercise (p = 0.0484). In our group analyses, the OR for MetS was 0.841 (95% C.I., 0.727-0.974) in CC/CT and 4.076 (95% C.I., 1.158-14.346) in TT individuals who did aerobic exercise compared to those who did not.

CONCLUSION

Our study indicated that aerobic exercise improved metabolic syndrome in Taiwanese adults with rs3779788 CC/CT genotype relative to those with TT genotype.

Multi-omics approaches for revealing the complexity of cardiovascular disease

The development and progression of cardiovascular disease (CVD) can mainly be attributed to the narrowing of blood vessels caused by atherosclerosis and thrombosis, which induces organ damage that will result in end-organ dysfunction characterized by events such as myocardial infarction or stroke. It is also essential to consider other contributory factors to CVD, including cardiac remodelling caused by cardiomyopathies and co-morbidities with other diseases such as chronic kidney disease. Besides, there is a growing amount of evidence linking the gut microbiota to CVD through several metabolic pathways. Hence, it is of utmost importance to decipher the underlying molecular mechanisms associated with these disease states to elucidate the development and progression of CVD. A wide array of systems biology approaches incorporating multi-omics data have emerged as an invaluable tool in establishing alterations in specific cell types and identifying modifications in signalling events that promote disease development. Here, we review recent studies that apply multi-omics approaches to further understand the underlying causes of CVD and provide possible treatment strategies by identifying novel drug targets and biomarkers. We also discuss very recent advances in gut microbiota research with an emphasis on how diet and microbial composition can impact the development of CVD. Finally, we present various biological network analyses and other independent studies that have been employed for providing mechanistic explanation and developing treatment strategies for end-stage CVD, namely myocardial infarction and stroke.

Association between lipoprotein lipase gene polymorphisms and cardiovascular disease risk factors in European adolescents: The Healthy Lifestyle in Europe by Nutrition in Adolescence study

OBJECTIVES

To examine the association of lipoprotein lipase (LPL) polymorphisms with cardiovascular disease (CVD) risk factors in European adolescents, along with the influence of physical activity on these associations.

METHODS

A total of 13 LPL polymorphisms were genotyped in 1.057 European adolescents (12-18 years old) from the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study. Serum lipids, glucose, insulin, and leptin (LEP) levels were measured and a CVD risk score was computed. We also measured body weight and height, waist and hip circumferences, and triceps and subscapular skinfold thickness. Physical activity was objectively measured by accelerometry for 7 days.

RESULTS

The rs1534649, rs258, rs320, and rs328 polymorphisms were associated with several CVD risk factors (ie, body mass index, triglycerides [TG], LEP, and cholesterol/high-density lipoprotein [HDL], low-density lipoprotein [LDL]/HDL, TG/HDL ratios). TG and TG/HDL were associated with haplotype blocks 3 (rs282, rs285 polymorphisms) and 4 (rs3126, rs320, rs328, rs10099160 polymorphisms), being the latter also associated with the CVD risk score. Physical activity modulated the association of adiposity with rs1534649 and rs258 polymorphisms.

CONCLUSIONS

Polymorphisms rs1534649, rs258, rs320 and rs328, and two haplotypes of LPL were significantly associated with CVD risk factors in European adolescents. Higher levels of moderate to vigorous physical activity may attenuate the effects of rs1534649 and rs258 polymorphisms on adiposity.

Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease

BACKGROUND

Fibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.

METHODS AND FINDINGS

We evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.

CONCLUSIONS

A small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.

Coiled-coil domain-containing 80 accelerates atherosclerosis development through decreasing lipoprotein lipase expression via ERK1/2 phosphorylation and TET2 expression

Recent studies showed that coiled-coil domain-containing 80 (CCDC80) has a positive link with atherosclerosis and that plasma CCDC80 levels are positively correlated with the levels of fasting plasma triglycerides (TG) in obese individuals. The underlying mechanisms, however, are unclear. Using Hematoxylin-eosin (H&E) and Oil Red O staining, we found that CCDC80 overexpression in vivo significantly increased plasma lipid contents, decreased the expression and activity of lipoprotein lipase (LPL), and accelerated the development of atherosclerosis. Conversely, knockdown of CCDC80 decreased plaque lesions area. In vitro, qRT-PCR and western blot results showed that CCDC80 overexpression significantly decreased, while CCDC80 knockdown increased, LPL expression in cultured vascular smooth muscle cells (VSMCs). Further, we found that CCDC80 reduced LPL expression via inhibiting the phosphorylation of extracellular regulated protein kinase 1/2 (ERK1/2) and also increased the methylation of LPL promoter via down-regulating Tet methylcytosine dioxygenase 2 (TET2). Our results also revealed that CCDC80 significantly down-regulated TET2 expression through decreasing the phosphorylation of ERK1/2. In addition, we found that CCDC80 decreased binding of TET2 to forkhead box O3 (FOXO3a) but had no effect on FOXO3a expression. On the other hand, and that FOXO3a was partially involved in TET2-regulated LPL expression. CCDC80 down-regulated ERK1/2 phosphorylation and decreased expression of TET2 and its interaction with FOXO3a, leading to a reduction of LPL expression and acceleration of atherosclerosis.

LPA Gene Polymorphisms and Gene Expression Associated with Coronary Artery Disease

The aim of our study was to investigate the influence of LPA gene polymorphisms for CAD risk and Lp(a) in a case-control study of Chinese Han population. In addition, we further analyzed the effect of LPA gene expression on plasma levels of Lp(a) and CAD risk. First, five SNPs (rs1367211, rs3127596, rs6415085, rs9347438, and rs9364559) in LPA gene were genotyped using the SEQUENOM Mass-ARRAY system in two groups. Second, we used quantitative real-time PCR to examine the mRNA expression levels of LPA gene in 92 cases and 32 controls. Results showed that the frequency of rs6415085-T allele was significantly higher in case group than that in control group (P < 0.05). Haplotypes were not associated with CAD risk (P > 0.05). And cases with the TT/TG genotype had significantly higher plasma Lp(a) levels compared with those that have the rs6415085 GG genotype (P < 0.05). Additionally, the mRNA expression levels in case group are significantly higher than that in control group (P < 0.05). Our study confirmed that rs6415085 was associated with CAD and increased plasma Lp(a) levels. And increased mRNA expression level of LPA gene may be a mechanism in development of CAD.

Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies

Supplemental Digital Content is available in the text.

Background—

Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications.

Methods and Results—

To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine–guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15–1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (P_TC=0.004, P_HDL-C=0.008 and P_{triglycerides}=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol–related differentially methylated locus.

Conclusions—

We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol transport in blood in relation to occurrence of cardiovascular disease events.

Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood

Transcript co-expression is regulated by a combination of shared genetic and environmental factors. Here, we estimate the proportion of co-expression that is due to shared genetic variance. To do so, we estimated the genetic correlations between each pairwise combination of 2469 transcripts that are highly heritable and expressed in whole blood in 1748 unrelated individuals of European ancestry. We identify 556 pairs with a significant genetic correlation of which 77% are located on different chromosomes, and report 934 expression quantitative trait loci, identified in an independent cohort, with significant effects on both transcripts in a genetically correlated pair. We show significant enrichment for transcription factor control and physical proximity through chromatin interactions as possible mechanisms of shared genetic control. Finally, we construct networks of interconnected transcripts and identify their underlying biological functions. Using genetic correlations to investigate transcriptional co-regulation provides valuable insight into the nature of the underlying genetic architecture of gene regulation.

Covariance of gene expression pairs is due to a combination of shared genetic and environmental factors. Here the authors estimate the genetic correlation between highly heritable pairs and identify transcription factor control and chromatin interactions as possible mechanisms of correlation.

SNP in human ARHGEF3 promoter is associated with DNase hypersensitivity, transcript level and platelet function, and Arhgef3 KO mice have increased mean platelet volume

Genome-wide association studies have identified a genetic variant at 3p14.3 (SNP rs1354034) that strongly associates with platelet number and mean platelet volume in humans. While originally proposed to be intronic, analysis of mRNA expression in primary human hematopoietic subpopulations reveals that this SNP is located directly upstream of the predominantly expressed ARHGEF3 isoform in megakaryocytes (MK). We found that ARHGEF3, which encodes a Rho guanine exchange factor, is dramatically upregulated during both human and murine MK maturation. We show that the SNP (rs1354034) is located in a DNase I hypersensitive region in human MKs and is an expression quantitative locus (eQTL) associated with ARHGEF3 expression level in human platelets, suggesting that it may be the causal SNP that accounts for the variations observed in human platelet traits and ARHGEF3 expression. In vitro human platelet activation assays revealed that rs1354034 is highly correlated with human platelet activation by ADP. In order to test whether ARHGEF3 plays a role in MK development and/or platelet function, we developed an Arhgef3 KO/LacZ reporter mouse model. Reflecting changes in gene expression, LacZ expression increases during MK maturation in these mice. Although Arhgef3 KO mice have significantly larger platelets, loss of Arhgef3 does not affect baseline MK or platelets nor does it affect platelet function or platelet recovery in response to antibody-mediated platelet depletion compared to littermate controls. In summary, our data suggest that modulation of ARHGEF3 gene expression in humans with a promoter-localized SNP plays a role in human MKs and human platelet function—a finding resulting from the biological follow-up of human genetic studies. Arhgef3 KO mice partially recapitulate the human phenotype.

Mapping eQTLs with RNA-seq reveals novel susceptibility genes, non-coding RNAs and alternative-splicing events in systemic lupus erythematosus

Studies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more comprehensive set of eQTLs and illuminate the underlying molecular consequence. We examine the functional outcome of 39 variants associated with Systemic Lupus Erythematosus (SLE) through the integration of GWAS and eQTL data from the TwinsUK microarray and RNA-Seq cohort in lymphoblastoid cell lines. We use conditional analysis and a Bayesian colocalisation method to provide evidence of a shared causal-variant, then compare the ability of each quantification type to detect disease relevant eQTLs and eGenes. We discovered the greatest frequency of candidate-causal eQTLs using exon-level RNA-Seq, and identified novel SLE susceptibility genes (e.g. NADSYN1 and TCF7) that were concealed using microarrays, including four non-coding RNAs. Many of these eQTLs were found to influence the expression of several genes, supporting the notion that risk haplotypes may harbour multiple functional effects. Novel SLE associated splicing events were identified in the T-reg restricted transcription factor, IKZF2, and other candidate genes (e.g. WDFY4) through asQTL mapping using the Geuvadis cohort. We have significantly increased our understanding of the genetic control of gene-expression in SLE by maximising the leverage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-junction quantifications. We conclude that to better understand the true functional consequence of regulatory variants, quantification by RNA-Seq should be performed at the exon-level as a minimum, and run in parallel with gene and splice-junction level quantification.

Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

Subcutaneous adipose tissue stores excess lipids and maintains energy balance. We performed expression quantitative trait locus (eQTL) analyses by using abdominal subcutaneous adipose tissue of 770 extensively phenotyped participants of the METSIM study. We identified cis-eQTLs for 12,400 genes at a 1% false-discovery rate. Among an approximately 680 known genome-wide association study (GWAS) loci for cardio-metabolic traits, we identified 140 coincident cis-eQTLs at 109 GWAS loci, including 93 eQTLs not previously described. At 49 of these 140 eQTLs, gene expression was nominally associated (p < 0.05) with levels of the GWAS trait. The size of our dataset enabled identification of five loci associated (p < 5 × 10^-8) with at least five genes located >5 Mb away. These trans-eQTL signals confirmed and extended the previously reported KLF14-mediated network to 55 target genes, validated the CIITA regulation of class II MHC genes, and identified ZNF800 as a candidate master regulator. Finally, we observed similar expression-clinical trait correlations of genes associated with GWAS loci in both humans and a panel of genetically diverse mice. These results provide candidate genes for further investigation of their potential roles in adipose biology and in regulating cardio-metabolic traits.

Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

BACKGROUND

The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain.

METHODS AND FINDINGS

We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination.

CONCLUSIONS

We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.

DNA methylation in lung cells is associated with asthma endotypes and genetic risk

The epigenome provides a substrate through which environmental exposures can exert their effects on gene expression and disease risk, but the relative importance of epigenetic variation on human disease onset and progression is poorly characterized. Asthma is a heterogeneous disease of the airways, for which both onset and clinical course result from interactions between host genotype and environmental exposures, yet little is known about the molecular mechanisms for these interactions. We assessed genome-wide DNA methylation using the Infinium Human Methylation 450K Bead Chip and characterized the transcriptome by RNA sequencing in primary airway epithelial cells from 74 asthmatic and 41 nonasthmatic adults. Asthma status was based on doctor's diagnosis and current medication use. Genotyping was performed using various Illumina platforms. Our study revealed a regulatory locus on chromosome 17q12-21 associated with asthma risk and epigenetic signatures of specific asthma endotypes and molecular networks. Overall, these data support a central role for DNA methylation in lung cells, which promotes distinct molecular pathways of asthma pathogenesis and modulates the effects of genetic variation on disease risk and clinical heterogeneity.

Genetic and environmental risk factors for atherosclerosis regulate transcription of phosphatase and actin regulating gene PHACTR1

Background and aims

Coronary artery disease (CAD) risk is associated with non-coding genetic variants at the phosphatase and actin regulating protein 1(PHACTR1) gene locus. The PHACTR1 gene encodes an actin-binding protein with phosphatase regulating activity. The mechanism whereby PHACTR1 influences CAD risk is unknown. We hypothesized that PHACTR1 would be expressed in human cell types relevant to CAD and regulated by atherogenic or genetic factors.

Methods and results

Using immunohistochemistry, we demonstrate that PHACTR1 protein is expressed strongly in human atherosclerotic plaque macrophages, lipid-laden foam cells, adventitial lymphocytes and endothelial cells. Using a combination of genomic analysis and molecular techniques, we demonstrate that PHACTR1 is expressed as multiple previously uncharacterized transcripts in macrophages, foam cells, lymphocytes and endothelial cells. Immunoblotting confirmed a total absence of PHACTR1 in vascular smooth muscle cells. Real-time quantitative PCR showed that PHACTR1 is regulated by atherogenic and inflammatory stimuli. In aortic endothelial cells, oxLDL and TNF-alpha both upregulated an intermediate length transcript. A short transcript expressed only in immune cells was upregulated in macrophages by oxidized low-density lipoprotein, and oxidized phospholipids but suppressed by lipopolysaccharide or TNF-alpha. In primary human macrophages, we identified a novel expression quantitative trait locus (eQTL) specific for this short transcript, whereby the risk allele at CAD risk SNP rs9349379 is associated with reduced PHACTR1 expression, similar to the effect of an inflammatory stimulus.

Conclusions

Our data demonstrate that PHACTR1 is a key atherosclerosis candidate gene since it is regulated by atherogenic stimuli in macrophages and endothelial cells and we identify an effect of the genetic risk variant on PHACTR1 expression in macrophages that is similar to that of an inflammatory stimulus.

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PHACTR1 is expressed as two transcripts in both immune and endothelial cells in human atherosclerotic plaque.

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Oxidized-LDL upregulates a short PHACTR1 transcript, but suppresses an intermediate length transcript in macrophages.

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Lipopolysaccharide and TNF-alpha cause the opposite effect with strong suppression of the short transcript in macrophages.

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The coronary artery disease risk SNP, rs9349379, is associated with expression of the short transcript in macrophages.

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The effect of the coronary artery disease risk allele on PHACTR1 mirrors that of inflammatory stimuli.

Positive Selection on a Regulatory Insertion-Deletion Polymorphism in FADS2 Influences Apparent Endogenous Synthesis of Arachidonic Acid

Long chain polyunsaturated fatty acids (LCPUFA) are bioactive components of membrane phospholipids and serve as substrates for signaling molecules. LCPUFA can be obtained directly from animal foods or synthesized endogenously from 18 carbon precursors via the FADS2 coded enzyme. Vegans rely almost exclusively on endogenous synthesis to generate LCPUFA and we hypothesized that an adaptive genetic polymorphism would confer advantage. The rs66698963 polymorphism, a 22-bp insertion–deletion within FADS2, is associated with basal FADS1 expression, and coordinated induction of FADS1 and FADS2 in vitro. Here, we determined rs66698963 genotype frequencies from 234 individuals of a primarily vegetarian Indian population and 311 individuals from the US. A much higher I/I genotype frequency was found in Indians (68%) than in the US (18%). Analysis using 1000 Genomes Project data confirmed our observation, revealing a global I/I genotype of 70% in South Asians, 53% in Africans, 29% in East Asians, and 17% in Europeans. Tests based on population divergence, site frequency spectrum, and long-range haplotype consistently point to positive selection encompassing rs66698963 in South Asian, African, and some East Asian populations. Basal plasma phospholipid arachidonic acid (ARA) status was 8% greater in I/I compared with D/D individuals. The biochemical pathway product–precursor difference, ARA minus linoleic acid, was 31% and 13% greater for I/I and I/D compared with D/D, respectively. This study is consistent with previous in vitro data suggesting that the insertion allele enhances n-6 LCPUFA synthesis and may confer an adaptive advantage in South Asians because of the traditional plant-based diet practice.

Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome

Considerable progress towards an understanding of complex diseases has been made in recent years due to the development of high-throughput genotyping technologies. Using microarrays that contain millions of single-nucleotide polymorphisms (SNPs), Genome Wide Association Studies (GWASs) have identified SNPs that are associated with many complex diseases or traits. For example, as of February 2015, 2111 association studies have identified 15,396 SNPs for various diseases and traits, with the number of identified SNP-disease/trait associations increasing rapidly in recent years. However, it has been difficult for researchers to understand disease risk from GWAS results. This is because most GWAS-identified SNPs are located in non-coding regions of the genome. It is important to consider that the GWAS-identified SNPs serve only as representatives for all SNPs in the same haplotype block, and it is equally likely that other SNPs in high linkage disequilibrium (LD) with the array-identified SNPs are causal for the disease. Because it was hoped that disease-associated coding variants would be identified if the true casual SNPs were known, investigators have expanded their analyses using LD calculation and fine-mapping. However, such analyses also identified risk-associated SNPs located in non-coding regions. Thus, the GWAS field has been left with the conundrum as to how a single-nucleotide change in a non-coding region could confer increased risk for a specific disease. One possible answer to this puzzle is that the variant SNPs cause changes in gene expression levels rather than causing changes in protein function. This review provides a description of (1) advances in genomic and epigenomic approaches that incorporate functional annotation of regulatory elements to prioritize the disease risk-associated SNPs that are located in non-coding regions of the genome for follow-up studies, (2) various computational tools that aid in identifying gene expression changes caused by the non-coding disease-associated SNPs, and (3) experimental approaches to identify target genes of, and study the biological phenotypes conferred by, non-coding disease-associated SNPs.

CardioGenBase: A Literature Based Multi-Omics Database for Major Cardiovascular Diseases

Cardiovascular diseases (CVDs) account for high morbidity and mortality worldwide. Both, genetic and epigenetic factors are involved in the enumeration of various cardiovascular diseases. In recent years, a vast amount of multi-omics data are accumulated in the field of cardiovascular research, yet the understanding of key mechanistic aspects of CVDs remain uncovered. Hence, a comprehensive online resource tool is required to comprehend previous research findings and to draw novel methodology for understanding disease pathophysiology. Here, we have developed a literature-based database, CardioGenBase, collecting gene-disease association from Pubmed and MEDLINE. The database covers major cardiovascular diseases such as cerebrovascular disease, coronary artery disease (CAD), hypertensive heart disease, inflammatory heart disease, ischemic heart disease and rheumatic heart disease. It contains ~1,500 cardiovascular disease genes from ~2,4000 research articles. For each gene, literature evidence, ontology, pathways, single nucleotide polymorphism, protein-protein interaction network, normal gene expression, protein expressions in various body fluids and tissues are provided. In addition, tools like gene-disease association finder and gene expression finder are made available for the users with figures, tables, maps and venn diagram to fit their needs. To our knowledge, CardioGenBase is the only database to provide gene-disease association for above mentioned major cardiovascular diseases in a single portal. CardioGenBase is a vital online resource to support genome-wide analysis, genetic, epigenetic and pharmacological studies.

Genetic Contribution of Variants near SORT1 and APOE on LDL Cholesterol Independent of Obesity in Children

Objective

To assess potential effects of variants in six lipid modulating genes (SORT1, HMGCR, MLXIPL, FADS2, APOE and MAFB) on early development of dyslipidemia independent of the degree of obesity in children, we investigated their association with total (TC), low density lipoprotein (LDL-C), high density lipoprotein (HDL-C) cholesterol and triglyceride (TG) levels in 594 children. Furthermore, we evaluated the expression profile of the candidate genes during human adipocyte differentiation.

Results

Expression of selected genes increased 10¹ to >10⁴ fold during human adipocyte differentiation, suggesting a potential link with adipogenesis. In genetic association studies adjusted for age, BMI SDS and sex, we identified significant associations for rs599839 near SORT1 with TC and LDL-C and for rs4420638 near APOE with TC and LDL-C. We performed Bayesian modelling of the combined lipid phenotype of HDL-C, LDL-C and TG to identify potentially causal polygenic effects on this multi-dimensional phenotype and considering obesity, age and sex as a-priori modulating factors. This analysis confirmed that rs599839 and rs4420638 affect LDL-C.

Conclusion

We show that lipid modulating genes are dynamically regulated during adipogenesis and that variants near SORT1 and APOE influence lipid levels independent of obesity in children. Bayesian modelling suggests causal effects of these variants.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Myocardial Infarction-Associated SNP at 6p24 Interferes With MEF2 Binding and Associates With PHACTR1 Expression Levels in Human Coronary Arteries

OBJECTIVE

Coronary artery disease (CAD), including myocardial infarction (MI), is the main cause of death in the world. Genome-wide association studies have identified dozens of single nucleotide polymorphisms (SNPs) associated with CAD/MI. One of the most robust CAD/MI genetic associations is with intronic SNPs in the gene PHACTR1 on chromosome 6p24. How these PHACTR1 SNPs influence CAD/MI risk, and whether PHACTR1 itself is the causal gene at the locus, is currently unknown.

APPROACH AND RESULTS

Using genetic fine-mapping and DNA resequencing experiments, we prioritized an intronic SNP (rs9349379) in PHACTR1 as causal variant. We showed that this variant is an expression quantitative trait locus for PHACTR1 expression in human coronary arteries. Experiments in endothelial cell extracts confirmed that alleles at rs9349379 are differentially bound by the transcription factors myocyte enhancer factor-2. We engineered a deletion of this myocyte enhancer factor-2-binding site using CRISPR/Cas9 genome-editing methodology. Heterozygous endothelial cells carrying this deletion express 35% less PHACTR1. Finally, we found no evidence that PHACTR1 expression levels are induced when stimulating human endothelial cells with vascular endothelial growth factor, tumor necrosis factor-α, or shear stress.

CONCLUSIONS

Our results establish a link between intronic SNPs in PHACTR1, myocyte enhancer factor-2 binding, and transcriptional functions at the locus, PHACTR1 expression levels in coronary arteries and CAD/MI risk. Because PHACTR1 SNPs are not associated with the traditional risk factors for CAD/MI (eg, blood lipids or pressure, diabetes mellitus), our results suggest that PHACTR1 may influence CAD/MI risk through as yet unknown mechanisms in the vascular endothelium.

Identification of common genetic variants controlling transcript isoform variation in human whole blood

An understanding of the genetic variation underlying transcript splicing is essential to dissect the molecular mechanisms of common disease. The available evidence from splicing quantitative trait locus (sQTL) studies has been limited to small samples. We performed genome-wide screening to identify SNPs that might control mRNA splicing in whole blood collected from 5,257 Framingham Heart Study participants. We identified 572,333 cis sQTLs involving 2,650 unique genes. Many sQTL-associated genes (40%) undergo alternative splicing. Using the National Human Genome Research Institute (NHGRI) genome-wide association study (GWAS) catalog, we determined that 528 unique sQTLs were significantly enriched for 8,845 SNPs associated with traits in previous GWAS. In particular, we found 395 (4.5%) GWAS SNPs with evidence of cis sQTLs but not gene-level cis expression quantitative trait loci (eQTLs), suggesting that sQTL analysis could provide additional insights into the functional mechanism underlying GWAS results. Our findings provide an informative sQTL resource for further characterizing the potential functional roles of SNPs that control transcript isoforms relevant to common diseases.

Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection

Cervical artery dissection (CeAD), a mural hematoma in a carotid or vertebral artery, is a major cause of ischemic stroke in young adults although relatively uncommon in the general population (incidence of 2.6/100,000 per year). Minor cervical traumas, infection, migraine and hypertension are putative risk factors, and inverse associations with obesity and hypercholesterolemia are described. No confirmed genetic susceptibility factors have been identified using candidate gene approaches. We performed genome-wide association studies (GWAS) in 1,393 CeAD cases and 14,416 controls. The rs9349379[G] allele (PHACTR1) was associated with lower CeAD risk (odds ratio (OR) = 0.75, 95% confidence interval (CI) = 0.69-0.82; P = 4.46 × 10(-10)), with confirmation in independent follow-up samples (659 CeAD cases and 2,648 controls; P = 3.91 × 10(-3); combined P = 1.00 × 10(-11)). The rs9349379[G] allele was previously shown to be associated with lower risk of migraine and increased risk of myocardial infarction. Deciphering the mechanisms underlying this pleiotropy might provide important information on the biological underpinnings of these disabling conditions.

Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis

BACKGROUND

Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis.

METHODS

We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS.

RESULTS

GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10-6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10-24) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10-72).

CONCLUSIONS

Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases.

Biomarkers of coronary artery disease: the promise of the transcriptome

The last years have witnessed tremendous technical advances in the field of transcriptomics that enable the simultaneous assessment of nearly all transcripts expressed in a tissue at a given time. These advances harbor the potential to gain a better understanding of the complex biological systems and for the identification and development of novel biomarkers. This article will review the current knowledge of transcriptomics biomarkers in the cardiovascular field and will provide an overview about the promises and challenges of the transcriptomics approach for biomarker identification.

How Gene Networks Can Uncover Novel CVD Players

Cardiovascular diseases (CVD) are complex, involving numerous biological entities from genes and small molecules to organ function. Placing these entities in networks where the functional relationships among the constituents are drawn can aid in our understanding of disease onset, progression and prevention. While networks, or interactomes, are often classified by a general term, say lipids or inflammation, it is a more encompassing class of network that is more informative in showing connections among the active entities and allowing better hypotheses of novel CVD players to be formulated. A range of networks will be presented whereby the potential to bring new objects into the CVD milieu will be exemplified.