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

Exploring the shared genetic landscape of diabetes and cardiovascular disease: findings and future implications

Diabetes is a rapidly growing global health concern projected to affect one in eight adults by 2045, which translates to roughly 783 million people. The profound metabolic alterations often present in dysglycaemia significantly increase the risk of cardiovascular complications. While genetic susceptibility plays a crucial role in diabetes and its vascular complications, identifying genes and molecular mechanisms that influence both diseases simultaneously has proven challenging. A key reason for this challenge is the pathophysiological heterogeneity underlying these diseases, with multiple processes contributing to different forms of diabetes and specific cardiovascular complications. This molecular heterogeneity has limited the effectiveness of large-scale genome-wide association studies (GWAS) in identifying shared underlying mechanisms. Additionally, our limited knowledge of the causal genes, cell types and disease-relevant states through which GWAS signals operate has hindered the discovery of common molecular pathways. This review highlights recent advances in genetic epidemiology, including studies of causal associations that have uncovered genetic and molecular factors influencing both dysglycaemia and cardiovascular complications. We explore how disease subtyping approaches can be critical in pinpointing the unique molecular signatures underlying both diabetes and cardiovascular complications. Finally, we address critical research gaps and future opportunities to advance our understanding of both diseases and translate these discoveries into tangible benefits for patient care and population health.

Cross-Ancestry Associations of Spontaneous Coronary Artery Dissection Genetic Risk With Coronary Atherosclerosis and Migraine Headache

BACKGROUND

Research studies of spontaneous coronary artery dissection (SCAD) have been primarily focused on European-ancestry individuals, with limited recognition and investigation in non-European-ancestry individuals. While SCAD has not been well ascertained in non-European-ancestry groups, pleiotropic associated traits identified in those of European ancestry have been assessed in individuals of other ancestries. Whether these traits are associated with the complex genetic architecture of SCAD in those of non-European ancestry has not been previously investigated.

METHODS

We investigated the associations of an established SCAD polygenic score with multiple vascular diseases in ≈900 000 ancestrally diverse participants of large-scale studies. Individual-level data from the UK Biobank and the Million Veteran Program and summary statistics of publicly available databases were analyzed.

RESULTS

A set of associations between SCAD polygenic score and related vascular diseases were replicated in non-European samples. Notable associations with the SCAD polygenic score included (1) coronary artery disease, myocardial infarction, and migraine headache in a Hispanic group (coronary artery disease: odds ratio [OR], 0.93 [95% CI, 0.90-0.95]; P=2.35×10-7; myocardial infarction: OR, 0.88 [95% CI, 0.80-0.96]; P=5.73×10-3; migraine headache: OR, 1.03 [95% CI, 1.01-1.06]; P=1.86×10-2) of the Million Veteran Program; (2) headache in an African-ancestry group (OR, 1.22 [95% CI, 1.06-1.41]; P=6.94×10-3) and a South Asian-ancestry group (OR, 1.18 [95% CI, 1.02-1.37]; P=2.43×10-2) of the UK Biobank; and (3) coronary artery disease, myocardial infarction, and migraine headache in East Asian-ancestry cohorts (coronary artery disease: OR, 0.95 [95% CI, 0.93-0.98]; P=2.66×10-3; myocardial infarction: OR, 0.86 [95% CI, 0.83-0.89]; P=9.51×10-16; migraine headache: OR, 1.27 [95% CI, 1.10-1.47]; P=1.03×10-3).

CONCLUSIONS

Pleiotropic associations of SCAD polygenic risk with related vascular diseases previously identified in European-ancestry groups showed notable, largely consistent patterns in non-European-ancestry groups.

Identification of hub biomarkers in coronary artery disease patients using machine learning and bioinformatic analyses

Understanding the molecular underpinnings of CAD is essential for developing effective therapeutic strategies. This study aims to identify and analyze differentially expressed hub biomarkers in the peripheral blood of CAD patients. Based on RNA-seq datasets from the Gene Expression Omnibus database, machine learning algorithms including LASSO, RF, and SVM-RFE were applied. Furthermore, the hub biomarkers were enriched to ascertain their roles in immune cell expression and signaling pathways through GO, KEGG, GSVE, and GSVA. An in vivo experiment was conducted to verify the hub biomarkers. Eleven hub biomarkers (ITM2B, GNA15, PLAU, GNG11, HIST1H2BH, SLC11A1, RPS7, DDIT4, CD83, GNLY, and S100A12) were identified and associated with CD8 + T cells and NK cells. They were mainly involved in immune responses, cardiac muscle contraction, oxidative phosphorylation, and apoptotic signaling pathways. Moreover, ITM2B had the most importance and significance to be the biomarker of CAD patients. In conclusion, these findings point to the possibility of ITM2B as a biomarker on the inflammatory pathogenesis of CAD and suggest new options for therapeutic intervention.

Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes

With the continuous advancements in high-throughput genome sequencing technologies and the development of innovative bioinformatics tools, bacterial genome-wide association studies (BGWAS) have emerged as a transformative approach for investigating the genetic variations underlying diverse bacterial phenotypes at the population genome level. This review provides a comprehensive overview of the application of BGWAS in elucidating genetic determinants of bacterial drug resistance, pathogenicity, host specificity, biofilm formation, and probiotic fermentation characteristics. We systematically summarize the BGWAS workflow, including study design, data analysis pipelines, and the bioinformatics software employed at various stages. Furthermore, we highlight specialized tools tailored for BGWAS and discuss their unique features and applications. We also discuss confounding factors that can influence the accuracy and reliability of BGWAS results, including population structure, linkage disequilibrium, and multiple testing. By incorporating recent advancements, this review serves as a comprehensive reference for researchers utilizing BGWAS to uncover the genetic basis of bacterial phenotypes.

Environmental pollutants and atherosclerosis: Epigenetic mechanisms linking genetic risk and disease

Over the past half-century, significant strides have been made to identify key risk factors, genetic mechanisms, and treatments for atherosclerosis. Yet, coronary artery disease (CAD) remains a leading global public health challenge. While the heritability of CAD is well-documented, there is increasing focus on the role of environmental exposures, such as smoking, air pollution, and heavy metals, on global CAD risk. Recent research has shed light on the interplay between genetic variation and environmental factors, offering insights into gene-environment (GxE) interactions. Moreover, emerging evidence suggests that environmental toxicants can profoundly impact the epigenome, altering gene regulation beyond the genetic sequence itself, revealing novel mechanisms underlying disease. Epigenetic changes - such as modifications in DNA methylation, chromatin structure, and non-coding RNA function - are now recognized as key molecular determinants of atherosclerosis. These observations have created a foundational paradigm that environment, genetics, and epigenetic mechanisms influence risk through a highly complex interaction regulating cellular phenotype, pathology, and disease progression. In this review, we explore the mechanisms by which environmental exposures influence the epigenome and contribute to the regulation of atherosclerotic disease. Additionally, we examine the transgenerational epigenetic effects of these exposures on disease risk. Advancing our understanding of these mechanisms is essential for informing public health strategies aimed at mitigating harmful environmental exposures and reducing the global burden of cardiovascular disease.

Improving Cardiovascular Health Through the Consideration of Social Factors in Genetics and Genomics Research: A Scientific Statement From the American Heart Association

Cardiovascular health (CVH) is affected by genetic, social, and genomic factors across the life course, yet little research has focused on the interrelationships among them. An extensive body of work has documented the impact of social determinants of health at both the structural and individual levels on CVH, highlighting pathways in which racism, housing, violence, and neighborhood environments adversely affect CVH and contribute to disparities in cardiovascular disease. Genetic factors have also been identified as contributors to risk for cardiovascular disease. Emerging evidence suggests that social factors can interact with genetic susceptibility to affect disease risk. Increasingly, social factors have been shown to affect epigenetic markers such as DNA methylation, which can regulate gene and protein expression. This is a potential biological mechanism through which exposure to poor social determinants of health becomes physically embodied at the molecular level, potentially contributing to the development of suboptimal CVH and chronic disease, thus reinforcing and propagating health disparities. The objective of this statement is to highlight and summarize key literature that has examined the joint associations between social, genetic, and genomic factors and CVH and cardiovascular disease.

Recent developments in population biobanks and the genetic architecture of complex disease

Population biobanks have radically transformed our understanding of complex disease genetics. Recent technological advances and the inclusion of diverse populations have accelerated the discovery and interpretation of variant associations. For instance, population-scale whole-genome sequencing now allows deep exploration of rare and structural variant associations, while multi-omics approaches integrating genome-wide association studies with proteomics, metabolomics, and advanced statistical methods like Mendelian randomization provide nuanced insights into genetic disease mechanisms. Additionally, cross-biobank collaborations and meta-analyses have been particularly impactful, dramatically increasing the statistical power for discovery. These efforts have identified novel genetic associations across numerous complex diseases, with significant contributions from non-European populations. However, data integration complexities, privacy concerns, and methodological limitations continue to constrain research. Here we review how recent advances have contributed to genetic discovery.

Associations Between Physical Capability Markers and Risk of Coronary Artery Disease: A Prospective Study of 439,295 UK Biobank Participants

Background: The relationship between sarcopenia and the incidence of coronary artery disease (CAD) is not well understood. This study aimed to investigate this relationship and the modifying effect of potential risk factors. Methods: We conducted a prospective study including 439,295 individuals from the UK Biobank. The primary outcome was the incidence of CAD. The main physical capability markers for sarcopenia, grip strength and muscle mass, were investigated as risk factors of interest. Grip strength was measured using a Jamar J00105 (Lafayette, IN, USA) hydraulic hand dynamometer, while muscle mass was estimated through bioelectrical impedance. Cox proportional hazard models were employed to analyze the associations between the exposures and the risk of CAD. Results: A total of 41,564 incident cases of CAD were identified after a median follow-up of 13.15 years (IQR 12.29-13.88 years). Compared with the lowest quintile of grip strength, the adjusted HRs for incidences of CAD from the second to the fifth quintile were 0.81 (95% CI: 0.79-0.83), 0.71 (95% CI: 0.69-0.73), 0.61 (95% CI: 0.60-0.63), and 0.49 (95% CI: 0.48-0.51). The association remained significant in subgroup analysis and interactions were observed between the two exposures and sex, age, smoking status, inflammatory diseases, metabolic syndrome, and genetic predisposition (all p for interactions < 0.05). Conclusions: Physical capability markers of sarcopenia, grip strength and muscle mass, were independently associated with a dose-response decreased risk for CAD incidence, regardless of genetic predisposition and potential modifying risk factors.

A multi-trait genome-wide association study of coronary artery disease and subclinical atherosclerosis traits

Measures of subclinical atherosclerosis, such as coronary artery calcification (CAC) and carotid intima-media thickness (CIMT), reflect the underlying pathophysiology of coronary artery disease (CAD) and are genetically correlated with CAD and related risk factors. Leveraging summary statistics from genome-wide association studies of CAD, CIMT, CAC, type 2 diabetes, low-density lipoprotein cholesterol, and systolic blood pressure, we performed 15 separate multi-trait GWAS to identify shared susceptibility loci and elucidate the pleiotropic architecture underlying atherosclerosis. We identified 442 shared risk loci across all analyses that met an experiment-wide Bonferroni threshold of 3.3 × 10-9, uncovering 195 novel atherosclerosis loci. Multi-trait colocalization confirmed a shared causal signal in 25 shared novel loci for atherosclerosis. Trait-eQTL colocalization identified evidence of a shared causal signal in arterial, subcutaneous adipose, and cardiac tissues, implicating genes such as PRRX2, BNC2, CLIC4, SCAI, and PPP6C, and pathways related to vascular remodeling, inflammation, and metabolic regulation.

Dissecting the Genetic Architecture of Intracranial Aneurysms

BACKGROUND

The genetic risk of intracranial aneurysm (IA) development has been ascribed to the genetic risk of smoking exposure and hypertension. The relationship of IA to other cardiovascular traits and the contribution of IA risk loci to aberrant gene programs within cerebrovascular cell types remains unclear.

METHODS

We performed a genome-wide association study in the Million Veteran Program and Finnish cohort study testing association of roughly 25 million DNA variants with unruptured IA (4694 cases and 877 091 controls) in individuals of European, African, and Hispanic ancestries. Meta-analysis with publicly available summary statistics generated a final cohort of 15 438 cases and 1 183 973 controls. We constructed a cerebrovascular single-nuclear RNA sequencing data set and integrated IA summary statistics to prioritize candidate causal cell types. We constructed a polygenic risk score to identify patients at risk of developing IA.

RESULTS

We identified 5 novel associations with IA, increasing the number of known susceptibility loci to 22. At these susceptibility loci, we prioritized 17 candidate causal genes. We found a significant positive genetic correlation of IA with coronary artery disease and abdominal aortic aneurysm. Integration of an IA gene set with cerebrovascular single-nuclear RNA sequencing data revealed a significant association with pericytes and smooth muscle cells. Finally, a polygenic risk score was significantly associated with IA across European (odds ratio, 1.87 [95% CI, 1.61-2.17]; P=8.8×10-17), African (odds ratio, 1.62 [95% CI, 1.19-2.15]; P=1.2×10-3), and Hispanic (odds ratio, 2.28 [95% CI, 1.47-3.38]; P=1.0×10-4) ancestries.

CONCLUSIONS

Here, we identify 5 novel loci associated with IA. Integration of summary statistics with cerebrovascular single-nuclear RNA sequencing reveals an association of cell types involved in matrix production. We validated a polygenic risk score that predicts IA, controlling for demographic variables including smoking status and blood pressure. Our findings suggest that a deficit in matrix production may drive IA pathogenesis independent of hypertension and smoking.

Meta-prediction of coronary artery disease risk

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide, and accurately predicting individual risk is critical for prevention. Here we aimed to integrate unmodifiable risk factors, such as age and genetics, with modifiable risk factors, such as clinical and biometric measurements, into a meta-prediction framework that produces actionable and personalized risk estimates. In the initial development of the model, ~2,000 predictive features were considered, including demographic data, lifestyle factors, physical measurements, laboratory tests, medication usage, diagnoses and genetics. To power our meta-prediction approach, we stratified the UK Biobank into two primary cohorts: first, a prevalent CAD cohort used to train predictive models for cross-sectional prediction at baseline and prospective estimation of contributing risk factor levels and diagnoses (baseline models) and, second, an incident CAD cohort using, in part, these baseline models as meta-features to train a final CAD incident risk prediction model. The resultant 10-year incident CAD risk model, composed of 15 derived meta-features with multiple embedded polygenic risk scores, achieves an area under the curve of 0.84. In an independent test cohort from the All of Us research program, this model achieved an area under the curve of 0.81 for predicting 10-year incident CAD risk, outperforming standard clinical scores and previously developed integrative models. Moreover, this framework enables the generation of individualized risk reduction profiles by quantifying the potential impact of standard clinical interventions. Notably, genetic risk influences the extent to which these interventions reduce overall CAD risk, allowing for tailored prevention strategies.

The interleukin gene landscape: understanding its influence on inflammatory mechanisms in apical periodontitis

Apical periodontitis is a common inflammatory illness caused by microbial infections in the root canal system, which destroys the periapical tissue. This disease's course and severity are highly regulated by a complex interaction of host immunological responses and genetic variables, particularly interleukin (IL) gene polymorphisms. These genetic variants influence cytokine production, the inflammatory cascade, and the ability to resolve infections. Polymorphisms in important cytokines (e.g., IL-1β, IL-6, IL-10, TNF-α, and IL-17) have been linked to worsening or reducing inflammation, affecting the clinical presentation and chronicity of apical periodontitis. A thorough examination of the molecular and clinical consequences of interleukin polymorphisms in apical periodontitis is given in this article. It emphasizes their function in regulating bone resorption, tissue degradation, and immune cell signaling. Their value in enhancing diagnostic precision, forecasting disease susceptibility, and directing treatment approaches is demonstrated by the incorporation of genetic insights into clinical practice. Targeted therapies, like immunomodulatory drugs and cytokine inhibitors, have great potential to reduce inflammation and encourage periapical healing. Future studies should focus on population-based research to examine genetic variability across ethnic groups, functional investigations to clarify the mechanisms behind polymorphism-driven cytokine regulation, and longitudinal studies to evaluate illness trajectories. Furthermore, developments in precision medicine and bioinformatics could completely transform patient-specific strategies by providing customized treatments and diagnostics. This review highlights the necessity of a multidisciplinary strategy that integrates immunology, genetics, and clinical practice to maximize apical periodontitis therapy and enhance dental health outcomes worldwide.

CXCL12 drives natural variation in coronary artery anatomy across diverse populations

Coronary arteries have a specific branching pattern crucial for oxygenating heart muscle. Among humans, there is natural variation in coronary anatomy with respect to perfusion of the inferior/posterior left heart, which can branch from either the right arterial tree, the left, or both-a phenotype known as coronary dominance. Using angiographic data for >60,000 US veterans of diverse ancestry, we conducted a genome-wide association study of coronary dominance, revealing moderate heritability and identifying ten significant loci. The strongest association occurred near CXCL12 in both European- and African-ancestry cohorts, with downstream analyses implicating effects on CXCL12 expression. We show that CXCL12 is expressed in human fetal hearts at the time dominance is established. Reducing Cxcl12 in mice altered coronary dominance and caused septal arteries to develop away from Cxcl12 expression domains. These findings indicate that CXCL12 patterns human coronary arteries, paving the way for "medical revascularization" through targeting developmental pathways.

Opportunities and challenges of local ancestry in genetic association analyses

Recently, admixed populations make up an increasing percentage of the US and global populations, and the admixture is not uniform over space or time or across genomes. Therefore, it becomes indispensable to evaluate local ancestry in addition to global ancestry to improve genetic epidemiological studies. Recent advances in representing human genome diversity, coupled with large-scale whole-genome sequencing initiatives and improved tools for local ancestry inference, have enabled studies to demonstrate that incorporating local ancestry information enhances both genetic association analyses and polygenic risk predictions. Along with the opportunities that local ancestry provides, there exist challenges preventing its full usage in genetic analyses. In this review, we first summarize methods for local ancestry inference and illustrate how local ancestry can be utilized in various analyses, including admixture mapping, association testing, and polygenic risk score construction. In addition, we discuss current challenges in research involving local ancestry, both in terms of the inference itself and its role in genetic association studies. We further pinpoint some future study directions and methodology development opportunities to help more effectively incorporate local ancestry in genetic analyses. It is worth the effort to pursue those future directions and address these analytical challenges because the appropriate use of local ancestry estimates could help mitigate inequality in genomic medicine and improve our understanding of health and disease outcomes.

Female-biased vascular smooth muscle cell gene regulatory networks predict MYH9 as a key regulator of fibrous plaque phenotype

Atherosclerosis, a chronic inflammatory condition driving coronary artery disease (CAD), manifests in two primary plaque types: unstable atheromatous plaques and stable fibrous plaques. While significant research has focused on atheromatous plaques, recent studies emphasize the growing importance of fibrous plaques, particularly in females under 50 years of age, where erosion on fibrous plaques significantly contributes to coronary thrombosis. The molecular mechanisms underlying sex differences in atherosclerotic plaque characteristics, including vascular smooth muscle cell (VSMC) contributions, remain understudied. Therefore, we utilized sex-specific gene regulatory networks (GRNs) derived from VSMC gene expression data from 119 male and 32 female heart transplant donors to identify molecular drivers of fibrous plaques. GRN analysis revealed two female-biased networks in VSMC, GRN floralwhite and GRN yellowgreen , enriched for inflammatory signaling and actin remodeling pathways, respectively. Single-cell RNA sequencing of carotid plaques from female and male patients confirmed the sex specificity of these networks in VSMCs. Further sub cellular phenotyping of the single-cell RNA sequencing revealed a sex-specific gene expression signature within GRN yellowgreen for VSMCs enriched for contractile and vasculature development pathways. Bayesian network modeling of the GRN yellowgreen identified MYH9 as a key driver gene. Indeed, elevated MYH9 protein expression in atherosclerotic plaques was associated with higher smooth muscle cell content and lower lipid content in female plaques, suggesting its involvement in fibrous plaque formation. Further proteomic analysis confirmed MYH9's upregulation in female fibrous plaques only and its correlation with stable plaque features. These findings provide novel insights into sex-specific molecular mechanisms regulating fibrous plaque formation.

Effect of Disclosing a Polygenic Risk Score for Coronary Heart Disease on Adverse Cardiovascular Events

BACKGROUND

In the Myocardial Infarction Genes clinical trial (URL: https://www.clinicaltrials.gov; Unique identifier: NCT01936675), participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (Framingham risk score group, n=103) or an integrated risk score (integrated risk score group [IRSg], n=104) that additionally included a polygenic risk score. After 6 months, IRSg participants had higher statin initiation and lower low-density lipoprotein cholesterol. We conducted a post hoc 10-year follow-up analysis to investigate whether disclosure of a polygenic risk score for CHD was associated with a reduction in major adverse cardiovascular events (MACE).

METHODS

Participants were followed from randomization in October 2013 to September 2023 to ascertain MACE, testing for CHD, and changes in risk factors. The primary outcome was time to first MACE, defined as cardiovascular death, nonfatal myocardial infarction, coronary revascularization, and nonfatal stroke. Statistical analyses included Cox proportional hazards regression and linear mixed-effects models.

RESULTS

We followed all participants who completed the trial, 100 in Framingham risk score group and 103 in IRSg (mean age at the end of follow-up, 68.2±5.2; 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in Framingham risk score group and 2 in IRSg (hazard ratio, 0.20 [95% CI, 0.04-0.94]; P=0.042). In Framingham risk score group, 47 (47%) underwent at least 1 diagnostic test for CHD, compared with 30 (29%) in IRSg (hazard ratio, 0.51 [95% CI, 0.32-0.81]; P=0.004). A higher proportion of IRSg participants were on statin therapy during the first 4 years postrandomization and had a greater reduction in low-density lipoprotein cholesterol for up to 3 years postrandomization. No significant differences were observed between 2 groups in other traditional cardiovascular risk factors during follow-up.

CONCLUSIONS

Disclosure of an integrated risk score that included a polygenic risk score to individuals at intermediate risk for CHD was associated with lower MACE incidence after 10 years, likely due to higher statin initiation, leading to lower low-density lipoprotein cholesterol levels.

Elevated Remnant and LDL Cholesterol and the Risk of Peripheral Artery Disease: A Mendelian Randomization Study

BACKGROUND

Elevated remnant cholesterol and low-density lipoprotein (LDL) cholesterol both increase the risk of coronary artery disease (CAD), but it is not known if the same is true for peripheral artery disease (PAD).

OBJECTIVES

This study tested the hypothesis that elevated remnant cholesterol and LDL cholesterol, each independent of the other, have causal effects on risk of PAD.

METHODS

The authors constructed genetic scores from variants near genes known to directly affect levels of remnant cholesterol and LDL cholesterol, identified through a genome-wide association study of individuals in the UK Biobank. Univariable (remnant cholesterol and LDL cholesterol genetic scores separately) and multivariable (remnant cholesterol and LDL cholesterol genetic scores combined) Mendelian randomization were used to estimate the causal effects of higher remnant cholesterol and LDL cholesterol levels on ORs for PAD (n = 38,414 cases and 758,308 controls) and CAD (n = 221,445 cases and 770,615 controls).

RESULTS

Increments in remnant and LDL genetic scores corresponding to 1 mmol/L (39 mg/dL) higher remnant and LDL cholesterol, respectively, were associated with univariable ORs for PAD of 2.72 (95% CI: 2.10-3.52) and 1.37 (95% CI: 1.25-1.51); corresponding multivariable ORs were 2.16 (95% CI: 1.49-3.12) and 1.14 (95% CI: 1.00-1.30). For CAD, corresponding univariable ORs were 2.92 (95% CI: 2.34-3.64) and 1.67 (95% CI: 1.56-1.79), whereas multivariable ORs were 1.86 (95% CI: 1.39-2.47) and 1.44 (95% CI: 1.29-1.60). Scaled to 1 SD increments in remnant cholesterol and LDL cholesterol, corresponding univariable ORs were 1.37 (95% CI: 1.27-1.49) and 1.29 (95% CI: 1.20-1.39) for PAD, and 1.40 (95% CI: 1.31-1.51) and 1.51 (95% CI: 1.43-1.59) for CAD; corresponding multivariable ORs were 1.28 (95% CI: 1.14-1.43) and 1.11 (95% CI: 1.00-1.23) for PAD, and 1.22 (95% CI: 1.11-1.33) and 1.34 (95% CI: 1.23-1.46) for CAD.

CONCLUSIONS

Elevated remnant cholesterol had a causal effect on risk of PAD even after accounting for elevated LDL cholesterol, whereas most of the causal effect of elevated LDL cholesterol on risk of PAD was dependent on simultaneously elevated remnant cholesterol. These results indicate that remnant cholesterol may be the major cholesterol fraction responsible for increased risk of PAD. Future studies should investigate the biological mechanisms behind these findings to find improved therapies for prevention and treatment of PAD.

Integrative analysis of single-cell transcriptomics and genetic associations identify cell states associated with vascular disease

BACKGROUND

Vascular diseases are accompanied by alterations in cellular phenotypes which underlie disease pathogenesis, with single-cell technologies aiding in the discovery of cellular heterogeneity among endothelial cell (EC) and vascular smooth muscle cell (VSMC) populations. In atherosclerotic disease, VSMCs are hypothesized to transition between contractile and synthetic states; however, the specific vascular subpopulations and intermediate cell states responsible for early vascular dysfunction remain unclear.

METHODS

We integrated newly generated and published single-nuclear RNA-sequencing (snRNA-seq) datasets to analyze normal (n = 7), aneurysmal (n = 9), and atherosclerotic (n = 2) flash-frozen human ascending thoracic aortas. Cell types and subtypes were defined using both top marker genes and canonical gene markers. Disease enrichment and relevant cell types were identified using newly developed computational tools to integrate GWAS data from multiple vascular disease-relevant studies with the single nuclei aortic expression profiles.

RESULTS

Nuclear dissociation and snRNA-seq identified ten distinct transcriptomic clusters from the integrated analysis representing all major vascular cell populations. Three distinct VSMC populations emerged that exhibited differential expression of extracellular matrix, contractile and pro-proliferative genes. Aneurysmal specimens were enriched for one fibroblast and one VSMC subpopulation compared to healthy tissue. RNA-trajectory analysis inferred a phenotypic continuum of gene expression between VSMC A and VSMC B or C and between two of the identified fibroblast types. VSMCs and Fibroblast C exhibited the greatest cell type-specific enrichment of genes mapped to GWAS loci for coronary artery disease (CAD), blood pressure, and migraine. Cell type-specific enrichment scores were more robust among the transcriptional profiles from non-diseased vascular tissue.

CONCLUSIONS

Our use of single-cell isolation and new computational methods prioritizes the cell types that most contribute to vascular disease pathogenesis. Specifically, tissue dissociation and single-nuclear transcriptomics better represent all vascular cell types, from which we demonstrate enrichment of pro-proliferative VSMCs in TAA and further implicate phenotypic switching as a likely pathologic mechanism. Integrated analysis of cell-specific gene expression and vascular disease GWAS data implicate genes and pathways associated with fibroblast and VSMC cell-state transitions.

Exploring the impact of graded alcohol use on atherogenic lipid profiles among Latinos with underlying chronic liver disease

BACKGROUND

Alcohol use and hepatitis C virus (HCV) often coexist and are associated with cardiovascular disease. One of the underlying drivers is dyslipidemia. We assessed lipid and lipoprotein levels and the relationship between alcohol use and atherogenic lipid profiles, specifically small dense low-density lipoprotein cholesterol (sdLDL-C), in Latinos with and without HCV.

METHODS

From June 1, 2002, to January 1, 2016, 150 Latino adults underwent demographic, clinical, metabolic, lipid/lipoprotein, and genetic evaluations. Linear regression (adjusted for age, sex, and recent alcohol use) assessed factors associated with sdLDL-C.

RESULTS

Participant characteristics were as follows: median age 44 years, 64% male, 39% HCV+, and alcohol use in the last 12 months was 19% heavy and 47% moderate. Ancestries were as follows: 52% European, 40% Native American (NA), and 4.3% African. 29% had non-CC PNPLA3, 89% non-CC TM6SF2, and 73% non-CC IL-28b genotypes. High-density lipoprotein (HDL) cholesterol, HDL-3, apolipoprotein A-1, and lipoprotein-associated phospholipase A2 levels differed by alcohol use groups (p < 0.05). On multivariable analysis, female sex (est. -6.08, p < 0.001), HCV+ status (est. -8.49, p < 0.001), and heavy alcohol use (vs. none) (est. -4.32, p = 0.03) were associated with lower, while NA ancestry (est. 0.92; p = 0.01) and adipose tissue insulin resistance (est. 3.30, p < 0.001) were associated with higher sdLDL-C levels. The positive association between NA ancestry and sdLDL-C was dampened by the presence of a non-CC IL28b genotype (interaction est. -1.95, p = 0.01).

CONCLUSIONS

In this Latino cohort, ancestry and metabolic dysfunction, independent of alcohol use and HCV, were associated with atherogenic risk. In addition to HCV treatment in this population, cardiometabolic health should be optimized.

[Role of genetics in precision medicine of coronary artery disease]

Coronary artery disease (CAD) develops multifactorially through an interplay of lifestyle, environmental and genetic factors. Smoking, hypertension, hyperlipidemia, obesity and diabetes mellitus are modifiable risk factors for CAD. In addition, both rare mutations and multiple frequently occurring genetic variants can cause CAD, whereby the heritability of CAD is ca. 50%. Genetic diagnostics enable the early identification of affected children and adults and, based on a greatly increased cardiovascular risk, initiation of preventive treatment. In recent years, genome-wide association studies have identified hundreds of significant variants that together greatly increase the risk of CAD. In the general population the many frequently occurring risk alleles in combination with modifiable risk factors result in a widespread genetic predisposition to CAD. Their relevance arises in the context of an integrative risk assessment, whereby the additional genetic risk can be calculated by polygenic risk scores (PRS), which provide a hazard ratio that can be multiplied with the clinically determined risk. This overview article discusses the diagnostic principles of rare and frequent genetic causes of CAD as well as their implications in the precision treatment of the disease.

Common-variant and rare-variant genetic architecture of heart failure across the allele-frequency spectrum

Heart failure is a complex trait, influenced by environmental and genetic factors, affecting over 30 million individuals worldwide. Here we report common-variant and rare-variant association studies of all-cause heart failure and examine how different classes of genetic variation impact its heritability. We identify 176 common-variant risk loci at genome-wide significance in 2,358,556 individuals and cluster these signals into five broad modules based on pleiotropic associations with anthropomorphic traits/obesity, blood pressure/renal function, atherosclerosis/lipids, immune activity and arrhythmias. In parallel, we uncover exome-wide significant associations for heart failure and rare predicted loss-of-function variants in TTN, MYBPC3, FLNC and BAG3 using exome sequencing of 376,334 individuals. We find that total burden heritability of rare coding variants is highly concentrated in a small set of Mendelian cardiomyopathy genes, while common-variant heritability is diffusely spread throughout the genome. Finally, we show that common-variant background modifies heart failure risk among carriers of rare pathogenic truncating variants in TTN. Together, these findings discern genetic links between dysregulated metabolism and heart failure and highlight a polygenic component to heart failure not captured by current clinical genetic testing.

A genome-wide association study of imaging-defined atherosclerosis

Imaging-defined atherosclerosis represents an intermediate phenotype of atherosclerotic cardiovascular disease (ASCVD). Genome-wide association studies (GWAS) on directly measured coronary plaques using coronary computed tomography angiography (CCTA) are scarce. In the so far largest population-based cohort with CCTA data, we performed a GWAS on coronary plaque burden as determined by the segment involvement score (SIS) in 24,811 European individuals. We identified 20 significant independent genetic markers for SIS, three of which were found in loci not implicated in ASCVD before. Further GWAS on coronary artery calcification showed similar results to that of SIS, whereas a GWAS on ultrasound-assessed carotid plaques identified both shared and non-shared loci with SIS. In two-sample Mendelian randomization studies using SIS-associated markers in UK Biobank and CARDIoGRAMplusC4D, one extra coronary segment with atherosclerosis corresponded to 1.8-fold increased odds of myocardial infarction. This GWAS data can aid future studies of causal pathways in ASCVD.

Exploring associations between estrogen and gene candidates identified by coronary artery disease genome-wide association studies

Introduction

Coronary artery disease (CAD) is the leading cause of death around the world, with epidemiological sex and gender differences in prevalence, pathophysiology and outcomes. It has been hypothesized that sex steroids, like estrogen, may contribute to these sex differences. There is a relatively large genetic component to developing CAD, with heritability estimates ranging between 40%-60%. In the last two decades, genome-wide association studies (GWAS) have contributed substantially to advancing the understanding of genetic candidates contributing to CAD. The aim of this study was to determine if genes discovered in CAD GWASs are affected by estrogen via direct modulation or indirect down-stream targets.

Methods

A scoping review was conducted using MEDLINE and EMBASE for studies of atherosclerotic coronary artery disease and a genome-wide association study (GWAS) design. Analysis was limited to candidate genes with corresponding single nucleotide polymorphisms (SNPs) surpassing genome-wide significance and had been mapped to genes by study authors. The number of studies that conducted sex-stratified analyses with significant genes were quantified. A literature search of the final gene lists was done to examine any evidence suggesting estrogen may modulate the genes and/or gene products.

Results

There were 60 eligible CAD GWASs meeting inclusion criteria for data extraction. Of these 60, only 36 had genome-wide significant SNPs reported, and only 3 of these had significant SNPs from sex-stratified analyses mapped to genes. From these 36 studies, a total of 61 genes were curated, of which 26 genes (43%) were found to have modulation by estrogen. All 26 were discovered in studies that adjusted for sex. 12/26 genes were also discovered in studies that conducted sex-stratified analyses. 12/26 genes were classified as having a role in lipid synthesis, metabolism and/or lipoprotein mechanisms, while 11/26 were classified as having a role in vascular integrity, and 3/26 were classified as having a role in thrombosis.

Discussion

This study provides further evidence of the relationship between estrogen, genetic risk and the development of CAD. More sex-stratified research will need to be conducted to further characterize estrogen's relation to sex differences in the pathology and progression of CAD.

Endothelial cell-related genetic variants identify LDL cholesterol-sensitive individuals who derive greater benefit from aggressive lipid lowering

The role of endothelial cell (EC) dysfunction in contributing to an individual's susceptibility to coronary atherosclerosis and how low-density lipoprotein cholesterol (LDL-C) concentrations might modify this relationship have not been previously studied. Here, from an examination of genome-wide significant single nucleotide polymorphisms associated with coronary artery disease (CAD), we identified variants with effects on EC function and constructed a 35 single nucleotide polymorphism polygenic risk score comprising these EC-specific variants (EC PRS). The association of the EC PRS with the risk of incident cardiovascular disease was tested in 3 cohorts: a primary prevention population in the UK Biobank (UKBB; n = 348,967); a primary prevention cohort from a trial that tested a statin (JUPITER, n = 8,749); and a secondary prevention cohort that tested a PCSK9 inhibitor (FOURIER, n = 14,298). In the UKBB, the EC PRS was independently associated with the risk of incident CAD (adjusted hazard ratio (aHR) per 1 s.d. of 1.24 (95% CI 1.21-1.26), P < 2 × 10-16). Moreover, LDL-C concentration significantly modified this risk: the aHR per 1 s.d. was 1.26 (1.22-1.30) when LDL-C was 150 mg dl-1 but 1.00 (0.85-1.16) when LDL-C was 50 mg dl-1 (Pinteraction = 0.004). The clinical benefit of LDL-C lowering was significantly greater in individuals with a high EC PRS than in individuals with low or intermediate EC PRS, with relative risk reductions of 68% (HR 0.32 (0.18-0.59)) versus 29% (HR 0.71 (0.52-0.95)) in the primary prevention cohort (Pinteraction = 0.02) and 33% (HR 0.67 (0.53-0.83)) versus 8% (HR 0.92 (0.82-1.03)) in the secondary prevention cohort (Pinteraction = 0.01). We conclude that EC PRS quantifies an independent axis of CAD risk that is not currently captured in medical practice and identifies individuals who are more sensitive to the atherogenic effects of LDL-C and who would potentially derive substantially greater benefit from aggressive LDL-C lowering.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetics of cardiovascular outcomes in individuals with chronic kidney disease: the Chronic Renal Insufficiency Cohort (CRIC) study

Genome-wide association studies (GWAS) identified multiple loci for cardiovascular disease, but their relevance to individuals with chronic kidney disease (CKD), who are at higher risk of cardiovascular disease, is unknown. In this study, we performed GWAS analyses of coronary heart disease (CHD) or all-cause stroke in African (AFR) and European (EUR) American participants with CKD of the Chronic Renal Insufficiency Cohort (CRIC). Mixed- effect logistic regression models were race-stratified and adjusted for age, sex, site of recruitment, estimated glomerular filtration rate (eGFR), and principal components, followed by meta-analysis. We attempted replication in participants from two biobanks with biomarker or ICD-10 (International Classification of Diseases, 10th Revision) diagnostic codes for CKD. We assessed the association of single nucleotide variants (SNVs) at known CHD and stroke loci in CRIC and tested the genetic correlation among CRIC, a biobank-based cohort and published GWAS of cardiovascular disease. Among 3,588 CRIC participants, 1,203 had CHD and 535 had all-cause stroke. We identified six SNVs across three loci ( LINC02744 , AZIN1- AS1 , and ATP6V0A4 ) associated with all-cause stroke, and two intronic SNVs at the PPARG locus associated with CHD. However, SNV associations were not significant in replication studies. Published SNVs for CHD or stroke were not associated with cardiovascular outcomes in CRIC. When testing the genetic correlations between published GWAS and CRIC GWAS, they were significant for CHD (genetic correlations (rg) range of 0.39 to 0.51, p-value< 0.007). These findings suggest some differences in the genetic architecture of CHD and stroke among individuals with CKD compared to those from the general population, although large numbers of CKD participants are needed to assess if findings are related to participant selection and CKD severity, or non-traditional risk factors in people with CKD.

Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci

Coronary artery disease (CAD) is the leading cause of death worldwide. Recently, hundreds of genomic loci have been shown to increase CAD risk, however, the molecular mechanisms underlying signals from CAD risk loci remain largely unclear. We sought to pinpoint the candidate causal coding and non-coding genes of CAD risk loci in a cell type-specific fashion. We integrated the latest statistics of CAD genetics from over one million individuals with epigenetic data from 45 relevant cell types to identify genes whose regulation is affected by CAD-associated single nucleotide variants (SNVs) via epigenetic mechanisms. Applying two statistical approaches, we identified 1,580 genes likely involved in CAD, about half of which have not been associated with the disease so far. Enrichment analysis and phenome-wide association studies linked the novel candidate genes to disease-specific pathways and CAD risk factors, corroborating their disease relevance. We showed that CAD-SNVs are enriched to regulate gene expression by affecting the binding of transcription factors (TFs) with cellular specificity. Of all the candidate genes, 23.5% represented non-coding RNAs (ncRNA), which likewise showed strong cell type specificity. We conducted a proof-of-concept biological validation for the novel CAD ncRNA gene IQCH-AS1 . CRISPR/Cas9-based gene knockout of IQCH-AS1 , in a human preadipocyte strain, resulted in reduced preadipocyte proliferation, less adipocyte lipid accumulation, and atherogenic cytokine profile. The cellular data are in line with the reduction of IQCH-AS1 in adipose tissues of CAD patients and the negative impact of risk alleles on its expression, suggesting IQCH-AS1 to be protective for CAD. Our study not only pinpoints CAD candidate genes in a cell type-specific fashion but also spotlights the roles of the understudied ncRNA genes in CAD genetics.

Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

Unveiling the Genetic Landscape of Coronary Artery Disease Through Common and Rare Structural Variants

BACKGROUND

Genome-wide association studies have identified several hundred susceptibility single nucleotide variants for coronary artery disease (CAD). Despite single nucleotide variant-based genome-wide association studies improving our understanding of the genetics of CAD, the contribution of structural variants (SVs) to the risk of CAD remains largely unclear.

METHOD AND RESULTS

We leveraged SVs detected from high-coverage whole genome sequencing data in a diverse group of participants from the National Heart Lung and Blood Institute's Trans-Omics for Precision Medicine program. Single variant tests were performed on 58 706 SVs in a study sample of 11 556 CAD cases and 42 907 controls. Additionally, aggregate tests using sliding windows were performed to examine rare SVs. One genome-wide significant association was identified for a common biallelic intergenic duplication on chromosome 6q21 (P=1.54E-09, odds ratio=1.34). The sliding window-based aggregate tests found 1 region on chromosome 17q25.3, overlapping USP36, to be significantly associated with coronary artery disease (P=1.03E-10). USP36 is highly expressed in arterial and adipose tissues while broadly affecting several cardiometabolic traits.

CONCLUSIONS

Our results suggest that SVs, both common and rare, may influence the risk of coronary artery disease.

A Comprehensive Review of the Genetics of Dyslipidemias and Risk of Atherosclerotic Cardiovascular Disease

Dyslipidemias are often diagnosed based on an individual's lipid panel that may or may not include Lp(a) or apoB. But these values alone omit key information that can underestimate risk and misdiagnose disease, which leads to imprecise medical therapies that reduce efficacy with unnecessary adverse events. For example, knowing whether an individual's dyslipidemia is monogenic can granularly inform risk and create opportunities for precision therapeutics. This review explores the canonical and non-canonical causes of dyslipidemias and how they impact atherosclerotic cardiovascular disease (ASCVD) risk. This review emphasizes the multitude of genetic causes that cause primary hypercholesterolemia, hypertriglyceridemia, and low or elevated high-density lipoprotein (HDL)-cholesterol levels. Within each of these sections, this review will explore the evidence linking these genetic conditions with ASCVD risk. Where applicable, this review will summarize approved therapies for a particular genetic condition.

Integrative proteogenomic analysis identifies COL6A3-derived endotrophin as a mediator of the effect of obesity on coronary artery disease

Obesity strongly increases the risk of cardiometabolic diseases, yet the underlying mediators of this relationship are not fully understood. Given that obesity strongly influences circulating protein levels, we investigated proteins mediating the effects of obesity on coronary artery disease, stroke and type 2 diabetes. By integrating two-step proteome-wide Mendelian randomization, colocalization, epigenomics and single-cell RNA sequencing, we identified five mediators and prioritized collagen type VI α3 (COL6A3). COL6A3 levels were strongly increased by body mass index and increased coronary artery disease risk. Notably, the carboxyl terminus product of COL6A3, endotrophin, drove this effect. COL6A3 was highly expressed in disease-relevant cell types and tissues. Finally, we found that body fat reduction could reduce plasma levels of COL6A3-derived endotrophin, indicating a tractable way to modify endotrophin levels. In summary, we provide actionable insights into how circulating proteins mediate the effects of obesity on cardiometabolic diseases and prioritize endotrophin as a potential therapeutic target.

Comparing Alzheimer's genes in African, European, and Amerindian induced pluripotent stem cell-derived microglia

INTRODUCTION

Genome-wide association studies (GWAS) studies in Alzheimer's disease (AD) demonstrate ancestry-specific loci. Previous studies in the regulatory architecture have only been conducted in Europeans (EUs), thus studies in additional ancestries are needed. Given the prevalence of AD genes expressed in microglia, we initiated our studies in induced pluripotent stem cell (iPSC) -derived microglia.

METHODS

We created iPSC-derived microglia from 13 individuals of either high Amerindian (AI), African (AF), or EU global ancestry, including both AD and controls. RNA-seq, ATAC-seq, and pathway analyses were compared between ancestries in both AD and non-AD genes.

RESULTS

Twelve AD genes were differentially expressed genes (DEGs) and/or accessible between ancestries, including ABI3, CTSB, and MS4A6A. A total of 5% of all genes had differential ancestral expression, but differences in accessibility were less than 1%. The DEGs were enriched in known AD pathways.

DISCUSSION

This resource will be valuable in evaluating AD in admixed populations and other neurological disorders and understanding the AD risk differences between populations.

HIGHLIGHTS

First comparison of the genomics of AI, AF, and EU microglia. Report differences in expression and accessibility of AD genes between ancestries. Ancestral expression differences are greater than differences in accessibility. Good transcriptome correlation was seen between brain and iPSC-derived microglia. Differentially expressed AD genes were in known AD pathways.

The mechanisms of Chr.9p21.3 risk locus in coronary artery disease: where are we today?

Despite the advancements and release of new therapeutics in the past few years, cardiovascular diseases (CVDs) have remained the number one cause of death worldwide. Genetic variation of a 9p21.3 genomic locus has been identified as the most significant and robust genetic CVD risk marker on the population level, with the strongest association with coronary artery disease (CAD) and other diseases, including diabetes and cancer. Several mechanisms of 9p21.3 in CVDs have been proposed, but their effects on CVDs have remained elusive. Moreover, most of the single nucleotide polymorphisms (SNPs) associated with CAD are located on a sequence of a long noncoding RNA (lncRNA) called ANRIL. ANRIL has several linear and circular splicing isoforms, which seem to have different effects and implications for CVDs. The mechanisms of the 9p21.3 locus and the interplay of its coding and noncoding transcripts in different diseases require further research. Circular RNAs have generally raised interest due to their beneficial features as biomarkers and therapeutic molecules. Here, we review the literature of 9p21.3 from its identification in 2007 and draw the current knowledge on its function, implications in CVDs, and therapeutic potential.

Using omics data and genome editing methods to decipher GWAS loci associated with coronary artery disease

Coronary artery disease (CAD) is due to atherosclerosis, a pathophysiological process that involves several cell-types and results in the accumulation of lipid-rich plaque that disrupt the normal blood flow through the coronary arteries to the heart. Genome-wide association studies have identified 1000s of genetic variants robustly associated with CAD or its traditional risk factors (e.g. blood pressure, blood lipids, type 2 diabetes, smoking). However, gaining biological insights from these genetic discoveries remain challenging because of linkage disequilibrium and the difficulty to interpret the functions of non-coding regulatory elements in the human genome. In this review, we present different statistical methods (e.g. Mendelian randomization) and molecular datasets (e.g. expression or protein quantitative trait loci) that have helped connect CAD-associated variants with genes, biological pathways, and cell-types or tissues. We emphasize that these various strategies make predictions, which need to be validated in orthologous systems. We discuss specific examples where the integration of omics data with GWAS results has prioritized causal CAD variants and genes. Finally, we review how targeted and genome-wide genome editing experiments using the CRISPR/Cas9 toolbox have been used to characterize new CAD genes in human cells. Researchers now have the statistical and bioinformatic methods, the molecular datasets, and the experimental tools to dissect comprehensively the loci that contribute to CAD risk in humans.

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

Polygenic risk score, dietary inflammatory potential, and incident coronary heart disease

AIMS

Dietary inflammatory potential and genetic factors are reported as being linked to coronary heart disease (CHD). We aimed to investigate their joint association with CHD incidence.

METHODS AND RESULTS

We included 51 889 British participants from the UK Biobank who completed the 24-h dietary assessment at baseline. We used reduced rank regression and stepwise linear regression analyses to generate an empirical dietary inflammatory pattern (EDIP) score to assess dietary inflammatory potential. A polygenic risk score (PRS) for CHD was constructed based on 1.7 million genetic variants. During a median follow-up of 11 years, 1346 incident cases of CHD were observed. High EDIP scores significantly increased the risk of CHD with the hazard ratio (HR) [95% confidence interval (CI)] of 1.26 (1.10-1.45) for high EDIP scores (T3) compared with low EDIP scores (T1). Interestingly, we observed a gradient in the risk of CHD across PRS categories, with the HRs of 1.12 (95% CI: 0.73-1.71), 1.20 (95% CI: 1.01-1.43), and 1.42 (95% CI: 1.10-1.83) in low (Q1), intermediate (Q2-4), and high (Q5) PRS categories, respectively. When the joint effect was examined, individuals with high PRS (Q5) and high EDIP scores (T3) would have the highest risk of CHD with a HR of 3.87 (95% CI: 2.74-5.46) compared with individuals with both low PRS (Q1) and low EDIP scores.

CONCLUSION

High dietary inflammatory potential was associated with a higher CHD risk, especially in those with high PRS, suggesting that a comprehensive assessment of inflammatory diet and genetic factors may be beneficial in the prevention of CHD.

Genetically predicted lipoprotein(a) associates with coronary artery plaque severity independent of low-density lipoprotein cholesterol

AIMS

Elevated lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular disease, but the mechanisms of risk are debated. Studies have found inconsistent associations between Lp(a) and measurements of atherosclerosis. We aimed to assess the relationship between Lp(a), low-density lipoprotein cholesterol (LDL-C), and coronary artery plaque severity.

METHODS AND RESULTS

The study population consisted of participants of the Million Veteran Program who have undergone an invasive angiogram. The primary exposure was genetically predicted Lp(a) estimated by a polygenic score. Genetically predicted LDL-C was also assessed for comparison. The primary outcome was coronary artery plaque severity categorized as normal, non-obstructive disease, one-vessel disease, two-vessel disease, and three-vessel or left main disease. Among 18 927 adults of genetically inferred European ancestry and 4039 adults of genetically inferred African ancestry, we observed consistent associations between genetically predicted Lp(a) and obstructive coronary plaque, with effect sizes trending upward for increasingly severe categories of disease. Associations were independent of risk factors, clinically measured LDL-C and genetically predicted LDL-C. However, we did not find strong or consistent evidence for an association between genetically predicted Lp(a) and risk for non-obstructive plaque.

CONCLUSION

Genetically predicted Lp(a) is positively associated with coronary plaque severity independent of LDL-C, consistent with Lp(a) promoting atherogenesis. However, the effects of Lp(a) may be greater for progression of plaque to obstructive disease than for the initial development of non-obstructive plaque. A limitation of this study is that Lp(a) was estimated using genetic markers and could not be directly assayed nor could apo(a) isoform size.

Low C-Reactive Protein Alleles in Hepatocyte Nuclear Factor 1A Are Associated With an Increased Risk of Cardiovascular Disease

CONTEXT

Rare variants in HNF1A cause both maturity onset diabetes of the young 3 (HNF1A-MODY) and reduced serum C-reactive protein (CRP) levels. Common variants of HNF1A are associated with serum CRP and type 2 diabetes mellitus (T2DM), but inconsistently with cardiovascular disease (CVD).

OBJECTIVE

Our study aimed to investigate the association of low CRP alleles in HNF1A with CVD and indirectly evaluate the CVD risk of HNF1A-MODY patients because of unavailability of enough cases to study their clinical outcomes.

METHODS

A literature search was performed using PubMed, Embase, and Cochrane Library databases from inception to December 2023. All relevant studies concerning the association of HNF1A with CRP, CVD, lipids, and T2DM were included. Odds ratios (ORs), 95% CIs, and study characteristics were extracted.

RESULTS

Three common coding variants of HNF1A (rs1169288, rs2464196, and rs1169289) were examined. The minor alleles of these variants correlated with low CRP levels (OR 0.89; 95% CI, 0.86-0.91; OR 0.89; 95% CI, 0.88-0.91; OR 0.89; 95% CI, 0.88-0.91, respectively). Their low CRP alleles were associated with increased risk of CVD (OR 1.03; 95% CI, 1.03-1.04), higher low-density lipoprotein cholesterol levels (OR 1.07; 95% CI, 1.04-1.10), and elevated risk of T2DM (OR 1.04; 95%, CI 1.01-1.08).

CONCLUSION

Our study revealed an association between low CRP alleles in HNF1A and a high CVD risk, which indicated that antidiabetic drugs with CV benefits such as glucagon-like peptide-1 receptor agonists should be recommended as a first-line choice for HNF1A-MODY.

Research Progress and Clinical Translation Potential of Coronary Atherosclerosis Diagnostic Markers from a Genomic Perspective

Objective: Coronary atherosclerosis (CAD) is characterized by arterial intima lipid deposition, chronic inflammation, and fibrous tissue proliferation, leading to arterial wall thickening and lumen narrowing. As the primary cause of coronary heart disease and acute coronary syndrome, CAD significantly impacts global health. Recent genetic studies have demonstrated CAD's polygenic and multifactorial nature, providing molecular insights for early diagnosis and risk assessment. This review analyzes recent advances in CAD-related genetic markers and evaluates their diagnostic potential, focusing on their applications in diagnosis and risk stratification within precision medicine. Methods: We conducted a systematic review of CAD genomic studies from PubMed and Web of Science databases, analyzing findings from genome-wide association studies (GWASs), gene sequencing, transcriptomics, and epigenomics research. Results: GWASs and sequencing studies have identified key genetic variations associated with CAD, including JCAD/KIAA1462, GUCY1A3, PCSK9, and SORT1, which regulate inflammation, lipid metabolism, and vascular function. Transcriptomic and epigenomic analyses have revealed disease-specific gene expression patterns, DNA methylation signatures, and regulatory non-coding RNAs (miRNAs and lncRNAs), providing new approaches for early detection. Conclusions: While genetic marker research in CAD has advanced significantly, clinical implementation faces challenges including marker dynamics, a lack of standardization, and integration with conventional diagnostics. Future research should prioritize developing standardized guidelines, conducting large-scale prospective studies, and enhancing multi-omics data integration to advance genomic diagnostics in CAD, ultimately improving patient outcomes through precision medicine.

Comparison of methods for building polygenic scores for diverse populations

Polygenic scores (PGSs) are a promising tool for estimating individual-level genetic risk of disease based on the results of genome-wide association studies (GWASs). However, their promise has yet to be fully realized because most currently available PGSs were built with genetic data from predominantly European-ancestry populations, and PGS performance declines when scores are applied to target populations different from the populations from which they were derived. Thus, there is a great need to improve PGS performance in currently under-studied populations. In this work we leverage data from two large and diverse cohorts the Million Veterans Program (MVP) and All of Us (AoU), providing us the unique opportunity to compare methods for building PGSs for multi-ancestry populations across multiple traits. We build PGSs for five continuous traits and five binary traits using both multi-ancestry and single-ancestry approaches with popular Bayesian PGS methods and both MVP META GWAS results and population-specific GWAS results from the respective African, European, and Hispanic MVP populations. We evaluate these scores in three AoU populations genetically similar to the respective African, Admixed American, and European 1000 Genomes Project superpopulations. Using correlation-based tests, we make formal comparisons of the PGS performance across the multiple AoU populations. We conclude that approaches that combine GWAS data from multiple populations produce PGSs that perform better than approaches that utilize smaller single-population GWAS results matched to the target population, and specifically that multi-ancestry scores built with PRS-CSx outperform the other approaches in the three AoU populations.

Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores

Importance

Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized.

Objective

To characterize the individual-level agreement of CHD PRSs that perform similarly at the population level.

Design, Setting, and Participants

Cross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data.

Exposures

Polygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples.

Main Outcomes and Measures

PRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ.

Results

A total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement.

Conclusions and Relevance

CHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians.

The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity

The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to the most comprehensive database of human GWAS results. Currently, it contains close to 7 000 publications for >15 000 traits, from which more than 625 000 lead associations have been curated. Additionally, 85 000 full genome-wide summary statistics datasets-containing association data for all variants in the analysis-are available for downstream analyses such as meta-analysis, fine-mapping, Mendelian randomisation or development of polygenic risk scores. As a centralised repository for GWAS results, the GWAS Catalog sets and implements standards for data submission and harmonisation, and encourages the use of consistent descriptors for traits, samples and methodologies. We share processes and vocabulary with the PGS Catalog, improving interoperability for a growing user group. Here, we describe the latest changes in data content, improvements in our user interface, and the implementation of the GWAS-SSF standard format for summary statistics. We address the challenges of handling the rapid increase in large-scale molecular quantitative trait GWAS and the need for sensitivity in the use of population and cohort descriptors while maintaining data interoperability and reusability.

Exploring the Role of Glycine Metabolism in Coronary Artery Disease: Insights from Human Genetics and Mouse Models

Background: Circulating glycine levels have been associated with reduced risk of coronary artery disease (CAD) in humans but these associations have not been observed in all studies. We evaluated whether the relationship between glycine levels and atherosclerosis was causal using genetic analyses in humans and feeding studies in mice. Methods: Serum glycine levels were evaluated for association with risk of CAD in the UK Biobank. Genetic determinants of glycine levels were identified through a genome-wide association study (GWAS) and used to evaluate the causal relationship between glycine and risk of CAD by Mendelian randomization (MR). A dietary supplementation study was carried out with atherosclerosis-prone apolipoprotein E deficient (ApoE-/-) mice to determine the effects of increased circulating glycine levels on cardiometabolic traits and aortic lesion formation. Results: Among 105,718 UK Biobank subjects, elevated serum glycine levels were associated with significantly reduced risk of prevalent CAD (Quintile 5 vs. Quintile 1 OR = 0.76, 95% CI 0.67-0.87; p < 0.0001) and incident CAD (Quintile 5 vs. Quintile 1 HR = 0.70, 95% CI 0.65-0.77; p < 0.0001) after adjustment for age, sex, ethnicity, anti-hypertensive and lipid-lowering medications, blood pressure, kidney function, and diabetes. A GWAS meta-analysis with 230,947 subjects identified 61 loci for glycine levels, of which 26 were novel. MR analyses provided modest evidence that genetically elevated glycine levels were causally associated with reduced systolic blood pressure and risk of type 2 diabetes, but did not provide significant evidence for an association with decreased risk of CAD. Glycine supplementation in mice had no effects on cardiometabolic traits or atherosclerotic lesion development. Conclusions: While expanding the genetic architecture of glycine metabolism, MR analyses and in vivo feeding studies did not provide evidence that the clinical association of this amino acid with atherosclerosis represents a causal relationship.

Genetic Insights Into Coronary Microvascular Disease

Coronary microvascular disease (CMVD) affects the coronary pre-arterioles, arterioles, and capillaries and can lead to blood supply-demand mismatch and cardiac ischemia. CMVD can present clinically as ischemia or myocardial infarction with no obstructive coronary arteries (INOCA or MINOCA, respectively). Currently, therapeutic options for CMVD are limited, and there are no targeted therapies. Genetic studies have emerged as an important tool to gain rapid insights into the molecular mechanisms of human diseases. For example, coronary artery disease (CAD) genome-wide association studies (GWAS) have enrolled hundreds of thousands of patients and have identified > 320 loci, elucidating CAD pathogenic pathways and helping to identify therapeutic targets. Here, we review the current landscape of genetic studies of CMVD, consisting mostly of genotype-first approaches. We then present the hypothesis that CAD GWAS have enrolled heterogenous populations and may be better characterized as ischemic heart disease (IHD) GWAS. We discuss how several of the genetic loci currently associated with CAD may be involved in the pathogenesis of CMVD. Genetic studies could help accelerate progress in understanding CMVD pathophysiology and identifying putative therapeutic targets. Larger phenotype-first genomic studies into CMVD with adequate sex and ancestry representation are needed. Given the extensive CAD genetic and functional validation data, future research should leverage these loci as springboards for CMVD genomic research.

Identification of shared genetic etiology of cardiovascular and cerebrovascular diseases through common cardiometabolic risk factors

Cardiovascular diseases (CVDs) and cerebrovascular diseases (CeVDs) are closely related vascular diseases, sharing common cardiometabolic risk factors (RFs). Although pleiotropic genetic variants of these two diseases have been reported, their underlying pathological mechanisms are still unclear. Leveraging GWAS summary data and using genetic correlation, pleiotropic variants identification, and colocalization analyses, we identified 11 colocalized loci for CVDs-CeVDs-BP (blood pressure), CVDs-CeVDs-LIP (lipid traits), and CVDs-CeVDs-cIMT (carotid intima-media thickness) triplets. No shared causal loci were found for CVDs-CeVDs-T2D (type 2 diabetes) or CVDs-CeVDs-BMI (body mass index) triplets. The 11 loci were mapped to 12 genes, namely CASZ1, CDKN1A, TWIST1, CDKN2B, ABO, SWAP70, SH2B3, LRCH1, FES, GOSR2, RPRML, and LDLR, where both GOSR2 and RPRML were mapped to one locus. They were enriched in pathways related to cellular response to external stimulus and regulation of the phosphate metabolic process and were highly expressed in endothelial cells, epithelial cells, and smooth muscle cells. Multi-omics analysis revealed methylation of two genes (CASZ1 and LRCH1) may play a causal role in the genetic pleiotropy. Notably, these pleiotropic loci are highly enriched in the targets of antihypertensive drugs, which further emphasizes the role of the blood pressure regulation pathway in the shared etiology of CVDs and CeVDs.

Six genetic variants are associated with cardiovascular disease independently from canonical risk factors: a new method to refine GWAS results based on the UKBiobank phenotype database

This paper describes a novel methodology based on GWAS filtering, aimed to find novel phenotypes associated to genetic loci independently of canonical risk factors using the large database of UK Biobank. Genome wide association studies (GWAS) is an untargeted methodology able to identify novel gene variants associated with diseases. Novel gene-phenotype associations might be discovered by this method. UKBiobank was interrogated by an automated routine to search associations between hundreds of phenotypes and single nucleotide polymorphisms (SNPs) resulting from GWAS, using Cardiovascular Disease as investigated trait. Six gene variants associated with CVD, independently of canonical risk factors, were identified using a variants database of more than 400k genotyped subjects (rs9349379 PHACTR1;intragenic_variant, rs74617384 LPA; intron_variant, rs4977574 CDKN2B-AS1;intron_variant, rs11191846 STN1;intron_variant, rs3184504, SH2B3;missense_variant, rs2929155 ADAMTS7;synonymous_variant). Novel clinical and biochemical phenotypes have been associated to the variants. The phenotypical characterization of the loci helped to propose mechanistic links that could explain their connection to CVD.

Cytokine Gene Variants as Predisposing Factors for the Development and Progression of Coronary Artery Disease: A Systematic Review

Coronary artery disease (CAD) is the most prevalent form of cardiovascular disease. A growing body of research shows that interleukins (ILs), such as IL-8, IL-18 and IL-16, elicit pro-inflammatory responses and may play critical roles in the pathologic process of CAD. Single nucleotide polymorphisms (SNPs), capable of generating functional modifications in IL genes, appear to be associated with CAD risk. This study aims to evaluate the associations of ten previously identified SNPs of the three cytokines with susceptibility to or protection of CAD. A systematic review and meta-analysis were conducted using Pubmed, EMBASE, WOS, CENTRAL, CNKI, CBM, Weipu, WANFANG Data and Google Scholar databases for relevant literature published up to September 2024. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for the four genetic models of the investigated SNPs in overall and subgroups analyses. Thirty-eight articles from 16 countries involving 14574 cases and 13001 controls were included. The present meta-analysis revealed no significant association between CAD and IL-8-rs2227306 or five IL-16 SNPs (rs8034928, rs3848180, rs1131445, rs4778889 and rs11556218). However, IL-8-rs4073 was significantly associated with an increased risk of CAD across all genetic models. In contrast, three IL-18 (rs187238, rs1946518 and rs1946519) variants containing minor alleles were associated with decreased risks of CAD under all models. Subgroups analyses by ethnicity indicated that IL-8-rs4073 conferred a significantly higher risk of CAD among Asians, including East, South and West Asians (allelic OR = 1.46, homozygous OR = 1.96, heterozygous OR = 1.47, dominant OR = 1.65), while it showed an inversely significant association with CAD risk in Caucasians (homozygous OR = 0.82, dominant OR = 0.85). Additionally, IL-18-rs187238 and IL-18-rs1946518 were significantly associated with reduced CAD risks in East Asians (for rs187238: allelic OR = 0.72, homozygous OR = 0.33, heterozygous OR = 0.73, dominant OR = 0.71; for rs1946518: allelic OR = 0.62, homozygous OR = 0.38, heterozygous OR = 0.49, dominant OR = 0.45). IL-18-rs187238 also demonstrated protective effects in Middle Eastern populations (allelic OR = 0.76, homozygous OR = 0.63, heterozygous OR = 0.72, dominant OR = 0.71). No significant associations were observed in South Asians or Caucasians for these IL-18 SNPs. Consistent with the overall analysis results, subgroups analyses further highlighted a significant association between IL-8-rs4073 and increased risk of acute coronary syndrome (heterozygous OR = 0.72). IL-18-rs187238 was significantly associated with decreased risks of myocardial infarction (MI) (allelic OR = 0.81, homozygous OR = 0.55, dominant OR = 0.80) and multiple vessel stenosis (allelic OR = 0.54, heterozygous OR = 0.45, dominant OR = 0.45). Similarly, IL-18-rs1946518 was significantly associated with reduced MI risk (allelic OR = 0.75, heterozygous OR = 0.68). These findings support the role of cytokine gene IL-8 and IL-18 variants as predisposing factors for the development and progression of CAD.

Genome-Wide European Ancestry Study Identifies Coronary Artery Disease-Associated Loci Through Gene-Sex Hormone Interaction

BACKGROUND

Although sex differences in coronary artery disease (CAD) risk have been observed, little is known about the role of sex hormones in CAD genetics. Accounting for sex hormone levels may help identify CAD-risk loci and extend our knowledge of its genetic architecture.

METHODS AND RESULTS

A total of 365 662 individuals of European ancestry enrolled in the UK Biobank were considered. Genetic interaction of total testosterone, bioavailable testosterone, and SHBG (sex hormone-binding globulin) were evaluated. Gene-environment interactions in millions of samples software was used to conduct sex-stratified genome-wide interaction analysis with prevalent CAD as the outcome. Participant age at enrollment and principal components 1 to 10 were adjusted as covariates. We identified 45 loci in men and 8 loci in women that reached genome-wide significance (P < 5 × 10-8) for CAD. Ten of the loci identified (5 loci in both men and women) were through joint effects and would not have been picked up using a traditional genome-wide association study. Two of the joint effect loci in women were independently identified with significant single nucleotide polymorphism-total testosterone interactions.

CONCLUSIONS

This genome-wide gene-sex hormone interaction study identified genomic-risk loci that may contribute to the differential CAD risk between men and women, which otherwise would not have been discovered in a traditional genome-wide association study solely including marginal genetic effects.

Gene Therapy in Cardiovascular Disease: Recent Advances and Future Directions in Science: A Science Advisory From the American Heart Association

Cardiovascular disease remains the foremost cause of morbidity and mortality globally, affecting millions of individuals. Recent discoveries illuminate the substantial role of genetics in cardiovascular disease pathogenesis, encompassing both monogenic and polygenic mechanisms and identifying tangible targets for gene therapies. Innovative strategies have emerged to rectify pathogenic variants that cause monogenic disorders such as hypertrophic, dilated, and arrhythmogenic cardiomyopathies and hypercholesterolemia. These include delivery of exogenous genes to supplement insufficient protein levels caused by pathogenic variants or genome editing to correct, delete, or modify mutant sequences to restore protein function. However, effective delivery of gene therapy to specified cells presents formidable challenges. Viral vectors, notably adeno-associated viruses and nonviral vectors such as lipid and engineered nanoparticles, offer distinct advantages and limitations. Additional risks and obstacles remain, including treatment durability, tissue-specific targeting, vector-associated adverse events, and off-target effects. Addressing these challenges is an ongoing imperative; several clinical gene therapy trials are underway, and many more first-in-human studies are anticipated. This science advisory reviews core concepts of gene therapy, key obstacles, patient risks, and ongoing research endeavors to enable clinicians to understand the complex landscape of this emerging therapy and its remarkable therapeutic potential to benefit cardiovascular disease.