Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals

BACKGROUND

DNA methylation is a dynamic epigenetic mechanism that occurs at cytosine-phosphate-guanine dinucleotide (CpG) sites. Epigenome-wide association studies (EWAS) investigate the strength of association between methylation at individual CpG sites and health outcomes. Although blood methylation may act as a peripheral marker of common disease states, previous EWAS have typically focused only on individual conditions and have had limited power to discover disease-associated loci. This study examined the association of blood DNA methylation with the prevalence of 14 disease states and the incidence of 19 disease states in a single population of over 18,000 Scottish individuals.

METHODS AND FINDINGS

DNA methylation was assayed at 752,722 CpG sites in whole-blood samples from 18,413 volunteers in the family-structured, population-based cohort study Generation Scotland (age range 18 to 99 years). EWAS tested for cross-sectional associations between baseline CpG methylation and 14 prevalent disease states, and for longitudinal associations between baseline CpG methylation and 19 incident disease states. Prevalent cases were self-reported on health questionnaires at the baseline. Incident cases were identified using linkage to Scottish primary (Read 2) and secondary (ICD-10) care records, and the censoring date was set to October 2020. The mean time-to-diagnosis ranged from 5.0 years (for chronic pain) to 11.7 years (for Coronavirus Disease 2019 (COVID-19) hospitalisation). The 19 disease states considered in this study were selected if they were present on the World Health Organisation's 10 leading causes of death and disease burden or included in baseline self-report questionnaires. EWAS models were adjusted for age at methylation typing, sex, estimated white blood cell composition, population structure, and 5 common lifestyle risk factors. A structured literature review was also conducted to identify existing EWAS for all 19 disease states tested. The MEDLINE, Embase, Web of Science, and preprint servers were searched to retrieve relevant articles indexed as of March 27, 2023. Fifty-four of approximately 2,000 indexed articles met our inclusion criteria: assayed blood-based DNA methylation, had >20 individuals in each comparison group, and examined one of the 19 conditions considered. First, we assessed whether the associations identified in our study were reported in previous studies. We identified 69 associations between CpGs and the prevalence of 4 conditions, of which 58 were newly described. The conditions were breast cancer, chronic kidney disease, ischemic heart disease, and type 2 diabetes mellitus. We also uncovered 64 CpGs that associated with the incidence of 2 disease states (COPD and type 2 diabetes), of which 56 were not reported in the surveyed literature. Second, we assessed replication across existing studies, which was defined as the reporting of at least 1 common site in >2 studies that examined the same condition. Only 6/19 disease states had evidence of such replication. The limitations of this study include the nonconsideration of medication data and a potential lack of generalizability to individuals that are not of Scottish and European ancestry.

CONCLUSIONS

We discovered over 100 associations between blood methylation sites and common disease states, independently of major confounding risk factors, and a need for greater standardisation among EWAS on human disease.

Allele-Specific Epigenetic Regulation of FURIN Expression at a Coronary Artery Disease Susceptibility Locus

Genome-wide association studies have revealed an association between the genetic variant rs17514846 in the FURIN gene and coronary artery disease. We investigated the mechanism through which rs17514846 modulates FURIN expression. An analysis of isogenic monocytic cell lines showed that the cells of the rs17514846 A/A genotype expressed higher levels of FURIN than cells of the C/C genotype. Pyrosequencing showed that the cytosine (in a CpG motif) at the rs17514846 position on the C allele was methylated. Treatment with the DNA methylation inhibitor 5-aza-2'-deoxycytidine increased FURIN expression. An electrophoretic mobility super-shift assay with a probe corresponding to the DNA sequence at and around the rs17514846 position of the C allele detected DNA-protein complex bands that were altered by an anti-MeCP2 antibody. A chromatin immunoprecipitation assay with the anti-MeCP2 antibody showed an enrichment of the DNA sequence containing the rs17514846 site. siRNA-mediated knockdown of MeCP2 caused an increase in FURIN expression. Furthermore, MeCP2 knockdown increased monocyte migration and proliferation, and this effect was diminished by a FURIN inhibitor. The results of our study suggest that DNA methylation inhibits FURIN expression and that the coronary artery disease-predisposing variant rs17514846 modulates FURIN expression and monocyte migration via an allele-specific effect on DNA methylation.

Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and informs causal proteins for Alzheimer's disease

The integration of quantitative trait loci (QTL) with disease genome-wide association studies (GWAS) has proven successful at prioritizing candidate genes at disease-associated loci. QTL mapping has mainly been focused on multi-tissue expression QTL or plasma protein QTL (pQTL). Here we generated the largest-to-date cerebrospinal fluid (CSF) pQTL atlas by analyzing 7,028 proteins in 3,107 samples. We identified 3,373 independent study-wide associations for 1,961 proteins, including 2,448 novel pQTLs of which 1,585 are unique to CSF, demonstrating unique genetic regulation of the CSF proteome. In addition to the established chr6p22.2-21.32 HLA region, we identified pleiotropic regions on chr3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron-specificity and neurological development. We also integrated this pQTL atlas with the latest Alzheimer's disease (AD) GWAS through PWAS, colocalization and Mendelian Randomization and identified 42 putative causal proteins for AD, 15 of which have drugs available. Finally, we developed a proteomics-based risk score for AD that outperforms genetics-based polygenic risk scores. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.

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.

A Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization

Background

Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups.

Methods

We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHD in the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHD in 176,988 individuals across 9 cohorts of diverse genetic ancestry.

Results

Multi-ancestry PRSP+T outperformed ancestry specific PRSP+T across a range of tuning values. In training stage, for all ancestry groups, PRSCSx performed better than PRSP+T and multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+T demonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSx showed stronger associacion with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]).

Conclusions

Utilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHD in most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.

Genetic and non-genetic components of family history of stroke and heart disease: a population-based study among adopted and non-adopted individuals

Background

It is increasingly clear that genetic and non-genetic factors account for the association of family history with disease risk in offspring. We sought to distinguish the genetic and non-genetic contributions of family history of stroke and heart disease on incident events by examining adopted and non-adopted individuals.

Methods

We examined associations between family history of stroke and heart disease with incident stroke and myocardial infarction (MI) in 495,640 participants of the UK Biobank (mean age 56.5 years, 55% female) stratified by early childhood adoption status into adoptees (n=5,747) and non-adoptees (n=489,893). We estimated hazard ratios (HRs) per affected nuclear family member, and for polygenic risk scores (PRS) for stroke and MI in Cox models adjusted for baseline age and sex.

Results

12,518 strokes and 23,923 MIs occurred over a 13-year follow-up. In non-adoptees, family history of stroke and heart disease were associated with increased stroke and MI risk, with the strongest association of family history of stroke for incident stroke (HR 1.16 [1.12, 1.19]) and family history of heart disease for incident MI (HR 1.48 [1.45, 1.50]). In adoptees, family history of stroke associated with incident stroke (HR 1.41 [1.06, 1.86]), but family history of heart disease did not associate with incident MI (p>0.5). PRS showed strong disease-specific associations in adoptees and non-adoptees. In non-adoptees, the stroke PRS mediated 6% risk between family history of stroke and incident stroke, and the MI PRS mediated 13% risk between family history of heart disease and MI.

Conclusions

Family history of stroke and heart disease increase risk for their respective conditions. Family history of stroke contains a substantial proportion of potentially modifiable non-genetic risk, indicating a need for further research to elucidate these elements for novel prevention strategies, whereas family history of heart disease represents predominantly genetic risk.

Current State and Future of Polygenic Risk Scores in Cardiometabolic Disease: A Scoping Review

A polygenic risk score (PRS) is derived from a genome-wide association study and represents an aggregate of thousands of single-nucleotide polymorphisms that provide a baseline estimate of an individual's genetic risk for a specific disease or trait at birth. However, it remains unclear how PRSs can be used in clinical practice. We provide an overview of the PRSs related to cardiometabolic disease and discuss the evidence supporting their clinical applications and limitations. The Preferred Reporting Items For Systematic Reviews and Meta-Analysis Extension for Scoping Reviews protocol was used to conduct a scoping review of the MEDLINE, EMBASE, and CENTRAL databases. Across the 4863 studies screened, 82 articles met the inclusion criteria. The most common PRS related to coronary artery disease, followed by hypertension and cerebrovascular disease. Limited ancestral diversity was observed in the study sample populations. Most studies included only individuals of European ancestry. The predictive performance of most PRSs was similar to or superior to traditional risk factors. More than half of the included studies reported an integrated risk model combining a derived PRS and clinical risk tools such as the Framingham Risk Score and Pooled Cohort Equations. The inclusion of a PRS into a clinical risk model tended to improve predictive accuracy consistently. This scoping review is the first of its kind and reports strong evidence for the clinical utility of PRSs in coronary artery disease, hypertension, cerebrovascular disease, and atrial fibrillation. However, most PRSs are generated in cohorts of European ancestry, which likely contributes to a lack of PRS transferability across different ancestral groups. Future prospective studies should focus on further establishing the clinical utility of PRSs and ensuring diversity is incorporated into genome-wide association study cohorts.

RNA-binding proteins in vascular inflammation and atherosclerosis

Atherosclerotic cardiovascular disease (ASCVD) remains the major cause of premature death and disability worldwide, even when patients with an established manifestation of atherosclerotic heart disease are optimally treated according to the clinical guidelines. Apart from the epigenetic control of transcription of the genetic information to messenger RNAs (mRNAs), gene expression is tightly controlled at the post-transcriptional level before the initiation of translation. Although mRNAs are traditionally perceived as the messenger molecules that bring genetic information from the nuclear DNA to the cytoplasmic ribosomes for protein synthesis, emerging evidence suggests that processes controlling RNA metabolism, driven by RNA-binding proteins (RBPs), affect cellular function in health and disease. Over the recent years, vascular endothelial cell, smooth muscle cell and immune cell RBPs have emerged as key co- or post-transcriptional regulators of several genes related to vascular inflammation and atherosclerosis. In this review, we provide an overview of cell-specific function of RNA-binding proteins involved in all stages of ASCVD and how this knowledge may be used for the development of novel precision medicine therapeutics.

Exploring the genetic basis of coronary artery disease using functional genomics

Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.

Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events

Importance

Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts.

Objective

To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model.

Design, Setting, and Participants

Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands.

Exposure

Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score.

Main Outcomes and Measures

Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed.

Results

The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years).

Conclusions and Relevance

In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.

Evaluation of the Performance of the RECODe Equation with the Addition of Polygenic Risk Scores for Adverse Cardiovascular Outcomes in Individuals with Type II Diabetes

Aims/Hypothesis

Individuals with T2D are at an increased risk of developing cardiovascular complications; early identification of individuals can lead to an alteration of the natural history of the disease. Current approaches to risk prediction tailored to individuals with T2D are exemplified by the RECODe algorithms which predict CVD outcomes among individuals with T2D. Recent efforts to improve CVD risk prediction among the general population have included the incorporation of polygenic risk scores (PRS). This paper aims to investigate the utility of the addition of a coronary artery disease (CAD), stroke and heart failure risk score to the current RECODe model for disease stratification.

Methods

We derived PRS using summary statistics for ischemic stroke (IS) from the coronary artery disease (CAD) and heart failure (HF) and tested prediction accuracy in the Penn Medicine Biobank (PMBB). A Cox proportional hazards model was used for time-to-event analyses within our cohort, and we compared model discrimination for the RECODe model with and without a PRS using AUC.

Results

The RECODe model alone demonstrated an AUC [95% CI] of 0.67 [0.62-0.72] for ASCVD; the addition of the three PRS to the model demonstrated an AUC [95% CI] of 0.66 [0.63-0.70]. A z-test to compare the AUCs of the two models did not demonstrate a detectable difference between the two models (p=0.97).

Conclusions/Interpretation

In the present study, we demonstrate that although PRS associate with CVD outcomes independent of traditional risk factors among individuals with T2D, the addition of PRS to contemporary clinical risk models does not specifically improve the predictive performance as compared to the baseline model.

Multiomic Analysis and CRISPR Perturbation Screens Identify Endothelial Cell Programs and Novel Therapeutic Targets for Coronary Artery Disease

Endothelial cells (EC) are an important mediator of atherosclerosis and vascular disease. Their exposure to atherogenic risk factors such as hypertension and serum cholesterol leads to endothelial dysfunction and many disease-associated processes. Identifying which of these multiple EC functions is causally related to disease risk has been challenging. There is evidence from in vivo models and human sequencing studies that dysregulation of nitric oxide production directly affects risk of coronary artery disease. Human genetics can help prioritize the other EC functions with causal relationships because germline mutations are acquired at birth and serve as a randomized test of which pathways affect disease risk. Though several coronary artery disease risk variants have been linked to EC function, this process has been slow and laborious. Unbiased analyses of EC dysfunction using multiomic approaches promise to identify the causal genetic mechanisms responsible for vascular disease. Here, we review the data from genomic, epigenomic, and transcriptomic studies that prioritize EC-specific causal pathways. New methods that CRISPR (clustered regularly interspaced short palindromic repeats) perturbation technology with genomic, epigenomic, and transcriptomic analysis promise to speed up the characterization of disease-associated genetic variation. We summarize several recent studies in ECs which use high-throughput genetic perturbation to identify disease-relevant pathways and novel mechanisms of disease. These genetically validated pathways can accelerate the identification of drug targets for the prevention and treatment of atherosclerosis.

FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells

BACKGROUND

Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci.

METHODS

We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells.

RESULTS

We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling.

CONCLUSIONS

Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.

Atherogenesis in Apoe-/- and Ldlr-/- Mice with a Genetically Resistant Background

Apoe-deficient (Apoe-/-) and Ldlr-deficient (Ldlr-/-) mice are two common animal models of hypercholesterolemia and atherosclerosis. The two models differ in lipid and glucose metabolism and other mechanisms involved in atherogenesis. Here we examined atherosclerotic lesion formation in the two models with an atherosclerosis-resistant C3H/HeJ (C3H) background. 3-month-old C3H-Ldlr-/- and C3H-Apoe-/- mice developed minimal atherosclerotic lesions in the aortic root when fed a chow diet. After 12 weeks on a Western diet, C3H-Ldlr-/- mice developed 3-fold larger lesions than C3H-Apoe-/- mice in the aortic root (127,386 ± 13,439 vs. 41,542 ± 5075 μm2/section; p = 0.00028), but neither knockout formed any lesion in the carotid artery. After being ligated near its bifurcation, the common carotid artery developed intimal lesions in both knockouts 4 weeks after ligation, significantly larger in C3H-Ldlr-/- than C3H-Apoe-/- mice (68,721 ± 2706 vs. 47,472 ± 8146 μm2/section; p = 0.028). Compared to C3H-Apoe-/- mice, C3H-Ldlr-/- mice showed a 50% reduction in plasma MCP-1 levels, similar levels of malondialdehyde, an oxidative stress biomarker, on both chow and Western diets, but higher small dense LDL levels on the Western diet. These results suggest a more significant role for small dense LDL than inflammation and oxidative stress in the different susceptibility of the mouse models to atherosclerosis.

Embedded racism: Inequitable niche construction as a neglected evolutionary process affecting health

Racial health disparities are a pervasive feature of modern experience and structural racism is increasingly recognized as a public health crisis. Yet evolutionary medicine has not adequately addressed the racialization of health and disease, particularly the systematic embedding of social biases in biological processes leading to disparate health outcomes delineated by socially defined race. In contrast to the sheer dominance of medical publications which still assume genetic 'race' and omit mention of its social construction, we present an alternative biological framework of racialized health. We explore the unifying evolutionary-ecological principle of niche construction as it offers critical insights on internal and external biological and behavioral feedback processes environments at every level of the organization. We Integrate insights of niche construction theory in the context of human evolutionary and social history and phenotype-genotype modification, exposing the extent to which racism is an evolutionary mismatch underlying inequitable disparities in disease. We then apply ecological models of niche exclusion and exploitation to institutional and interpersonal racial constructions of population and individual health and demonstrate how discriminatory processes of health and harm apply to evolutionarily relevant disease classes and life-history processes in which socially defined race is poorly understood and evaluated. Ultimately, we call for evolutionary and biomedical scholars to recognize the salience of racism as a pathogenic process biasing health outcomes studied across disciplines and to redress the neglect of focus on research and application related to this crucial issue.

Dissecting the polygenic basis of atherosclerosis via disease-associated cell state signatures

Coronary artery disease (CAD) is a pandemic disease where up to half of the risk is explained by genetic factors. Advanced insights into the genetic basis of CAD require deeper understanding of the contributions of different cell types, molecular pathways, and genes to disease heritability. Here, we investigate the biological diversity of atherosclerosis-associated cell states and interrogate their contribution to the genetic risk of CAD by using single-cell and bulk RNA sequencing (RNA-seq) of mouse and human lesions. We identified 12 disease-associated cell states that we characterized further by gene set functional profiling, ligand-receptor prediction, and transcription factor inference. Importantly, Vcam1+ smooth muscle cell state genes contributed most to SNP-based heritability of CAD. In line with this, genetic variants near smooth muscle cell state genes and regulatory elements explained the largest fraction of CAD-risk variance between individuals. Using this information for variant prioritization, we derived a hybrid polygenic risk score (PRS) that demonstrated improved performance over a classical PRS. Our results provide insights into the biological mechanisms associated with CAD risk, which could make a promising contribution to precision medicine and tailored therapeutic interventions in the future.

Discovery of Transacting Long Noncoding RNAs That Regulate Smooth Muscle Cell Phenotype

BACKGROUND

Smooth muscle cells (SMC), the major cell type in atherosclerotic plaques, are vital in coronary artery diseases (CADs). SMC phenotypic transition, which leads to the formation of various cell types in atherosclerotic plaques, is regulated by a network of genetic and epigenetic mechanisms and governs the risk of disease. The involvement of long noncoding RNAs (lncRNAs) has been increasingly identified in cardiovascular disease. However, SMC lncRNAs have not been comprehensively characterized, and their regulatory role in SMC state transition remains unknown.

METHODS

A discovery pipeline was constructed and applied to deeply strand-specific RNA sequencing from perturbed human coronary artery SMC with different disease-related stimuli, to allow for the detection of novel lncRNAs. The functional relevance of a select few novel lncRNAs were verified in vitro.

RESULTS

We identified 4579 known and 13 655 de novo lncRNAs in human coronary artery SMC. Consistent with previous long noncoding RNA studies, these lncRNAs overall have fewer exons, are shorter in length than protein-coding genes (pcGenes), and have relatively low expression level. Genomic location of these long noncoding RNA is disproportionately enriched near CAD-related TFs (transcription factors), genetic loci, and gene regulators of SMC identity, suggesting the importance of their function in disease. Two de novo lncRNAs, ZIPPOR (ZEB-interacting suppressor) and TNS1-AS2 (TNS1-antisense 2), were identified by our screen. Combining transcriptional data and in silico modeling along with in vitro validation, we identified CAD gene ZEB2 as a target through which these lncRNAs exert their function in SMC phenotypic transition.

CONCLUSIONS

Expression of a large and diverse set of lncRNAs in human coronary artery SMC are highly dynamic in response to CAD-related stimuli. The dynamic changes in expression of these lncRNAs correspond to alterations in transcriptional programs that are relevant to CAD, suggesting a critical role for lncRNAs in SMC phenotypic transition and human atherosclerotic disease.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10-5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10-6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10-7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

Molecular mechanisms of coronary artery disease risk at the PDGFD locus

Genome wide association studies for coronary artery disease (CAD) have identified a risk locus at 11q22.3. Here, we verify with mechanistic studies that rs2019090 and PDGFD represent the functional variant and gene at this locus. Further, FOXC1/C2 transcription factor binding at rs2019090 is shown to promote PDGFD transcription through the CAD promoting allele. With single cell transcriptomic and histology studies with Pdgfd knockdown in an SMC lineage tracing male atherosclerosis mouse model we find that Pdgfd promotes expansion, migration, and transition of SMC lineage cells to the chondromyocyte phenotype. Pdgfd also increases adventitial fibroblast and pericyte expression of chemokines and leukocyte adhesion molecules, which is linked to plaque macrophage recruitment. Despite these changes there is no effect of Pdgfd deletion on overall plaque burden. These findings suggest that PDGFD mediates CAD risk by promoting deleterious phenotypic changes in SMC, along with an inflammatory response that is primarily focused in the adventitia.

Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes.

Study Design Overview

Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes

BACKGROUND

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes.

METHODS

We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome.

RESULTS

We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL (TERF2IP), and another locus colocalized with SMC-specific eQTL (ALKBH8). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs.

CONCLUSIONS

Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch

BACKGROUND

Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease.

METHODS

In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait.

RESULTS

Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome-wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 (P=1.2×10-26), IGFBP3 (P=4.8×10-18), and PHACTR1 (P=1.4×10-13), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident cardiovascular disease and all-cause death in UK Biobank participants without available photoplethysmography data.

CONCLUSIONS

We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.

Genetic and modifiable risk factors combine multiplicatively in common disease

BACKGROUND

The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized.

OBJECTIVES

We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors.

METHODS

We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions.

RESULTS

In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer.

CONCLUSIONS

Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed.

Molecular mechanisms of coronary artery disease risk at the PDGFD locus

Platelet derived growth factor (PDGF) signaling has been extensively studied in the context of vascular disease, but the genetics of this pathway remain to be established. Genome wide association studies (GWAS) for coronary artery disease (CAD) have identified a risk locus at 11q22.3, and we have verified with fine mapping approaches that the regulatory variant rs2019090 and PDGFD represent the functional variant and putative functional gene. Further, FOXC1/C2 transcription factor (TF) binding at rs2019090 was found to promote PDGFD transcription through the CAD promoting allele. Employing a constitutive Pdgfd knockout allele along with SMC lineage tracing in a male atherosclerosis mouse model we mapped single cell transcriptomic, cell state, and lesion anatomical changes associated with gene loss. These studies revealed that Pdgfd promotes expansion, migration, and transition of SMC lineage cells to the chondromyocyte phenotype and vascular calcification. This is in contrast to protective CAD genes TCF21, ZEB2, and SMAD3 which we have shown to promote the fibroblast-like cell transition or perturb the pattern or extent of transition to the chondromyocyte phenotype. Further, Pdgfd expressing fibroblasts and pericytes exhibited greater expression of chemokines and leukocyte adhesion molecules, consistent with observed increased macrophage recruitment to the plaque. Despite these changes there was no effect of Pdgfd deletion on SMC contribution to the fibrous cap or overall lesion burden. These findings suggest that PDGFD mediates CAD risk through promoting SMC expansion and migration, in conjunction with deleterious phenotypic changes, and through promoting an inflammatory response that is primarily focused in the adventitia where it contributes to leukocyte trafficking to the diseased vessel wall.

Polygenic risk scores for the prediction of cardiometabolic disease

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.

Downregulation of Circulating Hsa-miR-200c-3p Correlates with Dyslipidemia in Patients with Stable Coronary Artery Disease

Coronary heart disease (CHD), one of the leading causes of disability and death worldwide, is a multifactorial disease whose early diagnosis is demanding. Thus, biomarkers predicting the occurrence of this pathology are of great importance from a clinical and therapeutic standpoint. By means of a pilot study on peripheral blood cells (PBMCs) of subjects with no coronary lesions (CTR; n = 2) and patients with stable CAD (CAD; n = 2), we revealed 61 differentially methylated regions (DMRs) (18 promoter regions, 24 genes and 19 CpG islands) and 14.997 differentially methylated single CpG sites (DMCs) in CAD patients. MiRNA-seq results displayed a peculiar miRNAs profile in CAD patients with 18 upregulated and 32 downregulated miRNAs (FC ≥ ±1.5, p ≤ 0.05). An integrated analysis of genome-wide DNA methylation and miRNA-seq results indicated a significant downregulation of hsa-miR-200c-3p (FCCAD = −2.97, p ≤ 0.05) associated to the hypermethylation of two sites (genomic coordinates: chr12:7073122-7073122 and chr12:7072599-7072599) located intragenic to the miR-200c/141 genomic locus (encoding hsa-miR-200c-3p) (p-value = 0.009) in CAD patients. We extended the hsa-miR-200c-3p expression study in a larger cohort (CAD = 72, CTR = 24), confirming its reduced expression level in CAD patients (FCCAD = −2; p = 0.02). However, when we analyzed the methylation status of the two CpG sites in the same cohort, we failed to identify significant differences. A ROC curve analysis showed good performance of hsa-miR-200c-3p expression level (AUC = 0.65; p = 0.02) in distinguishing CAD from CTR. Moreover, we found a significant positive correlation between hsa-miR-200c-3p expression and creatinine clearance (R2 = 0.212, p < 0.005, Pearson r = 0.461) in CAD patients. Finally, a phenotypic correlation performed in the CAD group revealed lower hsa-miR-200c-3p expression levels in CAD patients affected by dyslipidemia (+DLP, n = 58) (p < 0.01). These results indicate hsa-miR-200c-3p as potential epi-biomarker for the diagnosis and clinical progression of CAD and highlight the importance of deeper studies on the expression of this miRNA to understand its functional role in coronary artery disease development.

Integrating Theory with Education about Genetic Risk for Alcohol Use Disorder: The Effects of a Brief Online Educational Tool on Elements of the Health Belief Model

Introduction

The utility of genetic risk information relies on the assumption that individuals will use the information to change behavior to reduce risk of developing health problems. Educational interventions designed to target elements of the Health Belief Model have shown to be effective in promoting behaviors for positive outcomes.

Methods

A randomized controlled trial (RCT) was conducted in 325 college students to assess whether a brief, online educational intervention altered elements of the Health Belief Model that are known to be associated with motivations and intentions to change behavior. The RCT included a control condition, an intervention condition that received information about alcohol use disorder (AUD), and an intervention condition that received information about polygenic risk scores and AUD. We used t tests and ANOVA methods to compare differences in beliefs related to the Health Belief Model across study conditions and demographic characteristics.

Results

Providing educational information did not impact worry about developing AUD, perceived susceptibility and severity of developing alcohol problems, or perceived benefits and barriers of risk-reducing actions. Individuals in the condition that received educational information about polygenic risk scores and AUD reported higher perceived chance of developing AUD than individuals in the control condition (adj. p < 0.01). Sex, race/ethnicity, family history, and drinking status were associated with several components of the Health Belief Model.

Conclusion

Findings from this study demonstrate the need to better design and refine the educational information intended to accompany the return of genetic feedback for AUD to better promote risk-reducing behaviors.

Re-Addressing Dementia by Network Medicine and Mechanism-Based Molecular Endotypes

Alzheimer's disease (AD) and other forms of dementia are together a leading cause of disability and death in the aging global population, imposing a high personal, societal, and economic burden. They are also among the most prominent examples of failed drug developments. Indeed, after more than 40 AD trials of anti-amyloid interventions, reduction of amyloid-β (Aβ) has never translated into clinically relevant benefits, and in several cases yielded harm. The fundamental problem is the century-old, brain-centric phenotype-based definitions of diseases that ignore causal mechanisms and comorbidities. In this hypothesis article, we discuss how such current outdated nosology of dementia is a key roadblock to precision medicine and articulate how Network Medicine enables the substitution of clinicopathologic phenotypes with molecular endotypes and propose a new framework to achieve precision and curative medicine for patients with neurodegenerative disorders.

X chromosome associations with chronic obstructive pulmonary disease and related phenotypes: an X chromosome-wide association study

BACKGROUND

The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations.

METHODS

Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case-control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses.

RESULTS

Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV₁/FVC ([Formula: see text] 0.020, SE 0.004, p 4.97 × 10^-08), with suggestive evidence of association with FEV₁ ([Formula: see text] 0.092, SE 0.018, p 3.40 × 10^-07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions.

CONCLUSIONS

This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

Genome-Wide Transcriptional Profiling Reveals PHACTR1 as a Novel Molecular Target of Resveratrol in Endothelial Homeostasis

Atherosclerosis is a chronic inflammatory vascular disease in which endothelial cells play an important role in maintaining vascular homeostasis. Endotheliitis caused by endothelial dysfunction (ED) is the key cause for the development of cardiovascular and cerebrovascular diseases as well as other vascular system diseases. Resveratrol (RES), a multi-functional polyphenol present in edible plants and fruits, prevents cardiovascular disease by regulating a variety of athero-relevant signaling pathways. By transcriptome profiling of RES-treated human umbilical vein endothelial cells (HUVECs) and in-depth bioinformatic analysis, we observed that differentially expressed genes (DEGs) were enriched in KEGG pathways of fluid shear stress and atherosclerosis, suggesting that the RES may serve as a good template for a shear stress mimetic drug that hold promise in combating atherosclerosis. A heat map and multiple datasets superimposed screening revealed that RES significantly down-regulated phosphatase and actin modulator 1 (PHACTR1), a pivotal coronary artery disease risk gene associated with endothelial inflammation and polyvascular diseases. We further demonstrate that RES down-regulated the gene and protein expression of PHACTR1 and inhibited TNF-α-induced adhesion of THP-1 monocytes to activated endothelial cells via suppressing the expression of PHACTR1. Taken together, our study reveals that PHACTR1 represents a new molecular target for RES to maintain endothelial cell homeostasis and prevent atherosclerotic cardiovascular disease.

Genetic variation in 9p21, dietary patterns, and insulin sensitivity

Background: Single nucleotide polymorphisms in the 9p21 region have been associated with cardiovascular disease and to a lesser extent insulin sensitivity. Previous studies have focused on older populations, and few have examined the impact of gene-diet interactions. The objective of this study was to determine the interaction between dietary patterns and 9p21 genotypes on insulin sensitivity in young adults from different ethnic groups.

Methods: Subjects were 1,333 participants aged 20–29 years from the Toronto Nutrigenomics and Health Study (405 men and 928 women; 776 Caucasians and 557 East Asians). Fasting blood was collected to measure glucose, insulin, c-reactive protein and serum lipids, as well as to isolate DNA for genotyping subjects for five SNPs in 9p21 (rs10757274, rs10757278, rs1333049, rs2383206, and rs4977574). Insulin resistance (HOMA-IR) and beta-cell dysfunction (HOMA-Beta) were calculated from fasting insulin and glucose concentrations. The Toronto-modified Harvard 196-item semi-quantitative food frequency questionnaire was used to measure dietary intake over 1 month and principal components analysis was used to identify three dietary patterns (Prudent, Western and Eastern). ANOVA and ANCOVA were used to examine gene-diet interactions on markers of insulin sensitivity.

Results: Significant gene-diet interactions on insulin sensitivity using HOMA-IR were observed with all five SNPs, which remained significant after adjusting for covariates (p < 0.05). Among those who were homozygous for the 9p21 risk allele (rs1333049), fasting insulin was 40% higher in those who were consuming a low-prudent diet compared to those consuming a high-prudent diet (p < 0.05). No differences were observed between those following a low versus high-prudent diet among those who did not carry a 9p21 risk allele. Similar findings were observed with HOMA-Beta, however, the association was only significant for rs10757274 (p = 0.04).

Conclusion: Our findings suggest that a prudent dietary pattern may protect against the effects of 9p21 risk genotypes on insulin sensitivity.

Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population

Trace elements are micronutrients that are required in very small quantities through diet but are crucial for the prevention of acute and chronic diseases. Despite the fact that initial studies demonstrated inverse associations between some of the most important essential trace elements (Zn, Cu, Se, and Mn) and cardiovascular disease, several recent studies have reported a direct association with cardiovascular risk factors due to the fact that these elements can act as both antioxidants and pro-oxidants, depending on several factors. This study aims to investigate the association between plasma and urine concentrations of trace elements and cardiovascular risk factors in a general population from the Mediterranean region, including 484 men and women aged 18−80 years and considering trace elements individually and as joint exposure. Zn, Cu, Se, and Mn were determined in plasma and urine using an inductively coupled plasma mass spectrometer (ICP-MS). Single and combined analysis of trace elements with plasma lipid, blood pressure, diabetes, and anthropometric variables was undertaken. Principal component analysis, quantile-based g-computation, and calculation of trace element risk scores (TERS) were used for the combined analyses. Models were adjusted for covariates. In single trace element models, we found statistically significant associations between plasma Se and increased total cholesterol and systolic blood pressure; plasma Cu and increased triglycerides and body mass index; and urine Zn and increased glucose. Moreover, in the joint exposure analysis using quantile g-computation and TERS, the combined plasma levels of Zn, Cu, Se (directly), and Mn (inversely) were strongly associated with hypercholesterolemia (OR: 2.03; 95%CI: 1.37−2.99; p < 0.001 per quartile increase in the g-computation approach). The analysis of urine mixtures revealed a significant relationship with both fasting glucose and diabetes (OR: 1.91; 95%CI: 1.01−3.04; p = 0.046). In conclusion, in this Mediterranean population, the combined effect of higher plasma trace element levels (primarily Se, Cu, and Zn) was directly associated with elevated plasma lipids, whereas the mixture effect in urine was primarily associated with plasma glucose. Both parameters are relevant cardiovascular risk factors, and increased trace element exposures should be considered with caution.