Gene-Environment Interactions for Cardiovascular Disease

Interaction of accelerometer-measured physical activity and genetic risk on cardiovascular diseases: a prospective cohort study from UK Biobank

Objectives

This study aimed to evaluate the interactions of physical activity and polygenic risk score (PRS) on risks of atrial fibrillation, coronary heart disease (CHD), hypertension, and ischaemic stroke.

Methods

This study included 91 629 participants from UK Biobank in this study, all of whom had worn a wrist-worn accelerometer for 7 consecutive days. We computed total volume of physical activity (TPA) and time spent in moderate to vigorous intensity physical activity (MVPA) and light intensity physical activity (LPA). Cox proportional hazard models were used to evaluate associations of physical activity with the four cardiovascular outcomes. Interactions between physical activity and PRS were investigated on multiplicative and additive scales.

Results

During a median follow-up of 7.9 years, 3811 atrial fibrillation, 3994 CHD, 7345 hypertension and 1001 ischaemic stroke cases were recorded. TPA, MVPA and LPA were all negatively associated with risks of the four cardiovascular outcomes, generally independent of genetic risk. Association between LPA and atrial fibrillation was U-shaped among low-PRS stratum (p=0.01), and association between TPA and hypertension was attenuated with genetic risk increasing (p=0.02). Attributable risk (AR) of inactivity was higher in the high-PRS population. For example, increasing MVPA resulted in a twofold greater reduction in CHD cases among individuals with high PRS (AR=2.17%) than among those with low PRS (AR=1.09%).

Conclusions

Increasing physical activity, including LPA, was associated with a reduced risk of cardiovascular diseases. The extent of this benefit may differ among individuals with different genetic risks.

Impact of Gene-Smoking Interaction on Risk of Atherosclerosis: Molecular Study of Prothrombin (F2) Gene rs1799963 G/A Polymorphism in Atherosclerotic Patients

Atherosclerosis is a multifactorial disease influenced by genetic and lifestyle factors (e.g., smoking). The rs1799963 G/A polymorphism in the prothrombin (F2) gene is associated with thrombosis and cardiovascular diseases. However, the interaction between this genetic variant and smoking on the risk of atherosclerosis has not been thoroughly investigated. This study aims to explore the impact of rs1799963 polymorphism-smoking interaction on the risk of atherosclerosis. For this, control (n = 40) and angiographically confirmed atherosclerotic patients (n = 82) were recruited from District Sargodha, Pakistan. All subjects were genotyped for rs1799963 G/A variants by in-house developed tri-ARMS-PCR assay. Statistical analysis was performed to evaluate the interaction between rs1799963 polymorphism and smoking in relation to atherosclerosis risk. Risk of atherosclerosis was increased by the individual effects of F2 rs1799963 G allele [OR 2.96 (95% CI:1.8-8.08) p = 0.034] and smoking [OR 3.9 (95% CI:1.4-10.8) p = 0.008]. Subjects harboring rs1799963 G allele and who were active smokers had ~ 20 times higher risk of atherosclerosis. Synergy index indicated that combined effect of smoking and rs1799963 G allele was higher than their individual effects, which had a positive interaction with atherosclerosis [synergy index = 2.125 (95% CI: 1.66-2.59)]. These findings suggest a strong interaction between F2 rs1799963 polymorphism and smoking for atherosclerosis. The presence of rs1799963 G allele in conjunction with active smoking status greatly increases the risk of atherosclerosis.

Dietary patterns and physical activity in young South Asians and white Europeans and their potential implications for cardiovascular risk

Individuals of South Asian (SA) ethnicity have greater risk of developing cardiovascular disease (CVD) relative to white Europeans (WEs). Factors which generally contribute to increased CVD risk include physical inactivity and poor dietary habits, including high intake of salt and saturated fat. Contrastingly, diets rich in fibre, antioxidants and polyphenols are considered cardioprotective. The current questionnaire-based study aimed to examine whether the dietary habits and physical activity levels of young adult SAs living in the UK may contribute to their increased CVD risk in comparison to age-matched WEs. All participants (80 healthy individuals, 40 SA/ 40 WE (gender-balanced, aged 18-26 years) completed questionnaires to assess: general health; habitual physical activity levels, assessed by the International Physical Activity Questionnaire; and dietary patterns, assessed by EPIC-food frequency questionnaire and three-day food diaries. SAs had higher sitting times (SA: 469 ± 19.4, WE: 387 ± 21.5 min/day, p = 0.0107) and were less physically active (SA: 2050 ± 1110, WE: 4850 ± 2810 MET mins/day, p < 0.0001) than WEs. Further, SAs had lower consumption of cardioprotective nutrients, such as fibre (p = 0.0183), folate (p = 0.0242), vitamin C (p = 0.0105) and phytochemicals, such as flavonoids (p = 0.0644). SAs also consumed less alcohol (p < 0.0001), fat (p = 0.0066), sugar (p = 0.0218) and sodium (p = 0.0011) compared to WEs. These findings suggest that lower consumption of nutrients and phytochemicals that are cardioprotective, rather than excess consumption of fat, sugar and sodium, amongst young SAs may contribute to their increased CVD risk. Young SA individuals may also reduce their future CVD risk by increasing their physical activity.

Variants in candidate genes and their interactions with smoking on the risk of acute coronary syndrome

INTRODUCTION

Multiple genetic and environmental factors interact with the development of acute coronary syndrome. Smoking is one of the environmental factors that might alter the metabolic pathways shared by genes associated with this condition.

OBJECTIVE

To investigate the association of acute coronary syndrome with genetic variants related to inflammation, lipid metabolism, and platelet aggregation among subjects from the northeastern region of Colombia. The effects of interactions between polymorphisms and smoking were also evaluated.

MATERIALS AND METHODS

We analyzed data from 330 acute coronary syndrome cases and 430 controls. Associations between 20 polymorphisms and acute coronary syndrome were evaluated using logistic regression, adjusting for confounders. Gene and smoking interaction terms were calculated, and variants were analyzed separately in smokers and non-smokers for their association with acute coronary syndrome.

RESULTS

Two variants were associated with acute coronary syndrome, rs10455872 in the LPA gene (OR = 2.69; 95% CI: 1.61-4.49) and rs429358 in the APOE gene (OR = 1.93; 95% CI: 1.30-2.87). We identified smoking interactions with the variants rs6511720 in the LDLR gene (p = 0.04) and rs2227631 in the SERPINE1 gene (p = 0.02), with significant effects in non-smokers (rs6511720: OR = 0.40; 95% CI: 0.19-0.88; and rs2227631: OR = 0.69; 95% CI: 0.48-1.00), but not in smokers (rs6511720: OR = 1.28; 95% CI: 0.66-2.46; and rs2227631: OR = 1.30; 95% CI: 0.91-1.87).

CONCLUSIONS

Variants in the candidate genes LPA and APOE are associated with an increased risk of acute coronary syndrome in a population from northeastern Colombia. The effects of rs6511720 in LDLR and rs2227631 in SERPINE1 differ according to smoking habits and are significant in non-smokers. These results are helpful for early risk screening of acute coronary syndrome, mainly in individuals without defined conventional risk factors.

Striving Towards Equity in Cardiovascular Genomics Research

PURPOSE OF REVIEW

Our review emphasizes recent advancements and persisting gaps in cardiovascular genomics, particularly highlighting how emerging studies involving underrepresented populations have uncovered new genetic variants associated with cardiovascular diseases.

RECENT FINDINGS

Initiatives like the H3Africa project, the Million Veterans Program, and the All of Us Research Program are working to address this gap by focusing on underrepresented groups. Additionally, emerging research is centering on the interplay between genetic factors and socio-environmental determinants of health, which disproportionately impact marginalized communities. As cardiovascular genomics research grows, increasing the inclusion of underrepresented populations is essential for gaining a more comprehensive understanding of genetic variability. This will lead to more accurate and clinically meaningful strategies for preventing and treating cardiovascular diseases across all ancestral backgrounds and diverse populations.

Sex differences in gut microbiota, hypertension, and cardiovascular risk

The intricate ecosystem of the gut microbiome exhibits sex-specific differences, influencing the susceptibility to cardiovascular diseases (CVD). Imbalance within the gut microbiome compromises the gut barrier, activates inflammatory pathways, and alters the production of metabolites, all of which initiate chronic diseases including CVD. In particular, the interplay between lifestyle choices, hormonal changes, and metabolic byproducts uniquely affects sex-specific gut microbiomes, potentially shaping the risk profiles for hypertension and CVD differently in men and women. Understanding the gut microbiome's role in CVD risk offers informative reasoning behind the importance of developing tailored preventative strategies based on sex-specific differences in CVD risk. Furthermore, insight into the differential impact of social determinants and biological factors on CVD susceptibility emphasizes the necessity for more nuanced approaches. This review also outlines specific dietary interventions that may enhance gut microbiome health, offering a glimpse into potential therapeutic avenues for reducing CVD risk that require greater awareness. Imbalance in natural gut microbiomes may explain etiologies of chronic diseases; we advocate for future application to alter the gut microbiome as possible treatment of the aforementioned diseases. This review mentions the idea of altering the gut microbiome through interventions such as fecal microbiota transplantation (FMT), a major application of microbiome-based therapy that is first-line for Clostridium difficile infections and patient-specific probiotics highlights more innovative approaches to hypertension and CVD prevention. Through increased analysis of gut microbiota compositions along with patient-centric probiotics and microbiome transfers, this review advocates for future preventative strategies for hypertension.

Interaction between walkability and fine particulate matter on ischemic heart disease: A prospective cohort study in China

BACKGROUND

Previous studies have suggested that neighborhoods characterized by higher walkability are related to a reduced risk of ischemic heart disease (IHD), whereas exposure to PM2.5 is positively associated with risk of IHD. Nevertheless, their joint impact on IHD warrants further investigation.

METHODS

This prospective cohort study was performed in Yinzhou, Ningbo, China, comprising 47,516 participants. Individual-level walkability and PM2.5 were evaluated using a commercial walkability database and a land use regression (LUR) model, respectively. Hazard ratios (HRs) and 95 % confidence intervals (95 % CIs) were calculated using two Cox proportional hazards models: one based on two-year average PM2.5 levels prior to baseline, and the other incorporating time-varying PM2.5 assessed on a monthly scale. Dose-response relationships were explored using restricted cubic spline (RCS) functions. Interactions on both additive and multiplicative scales were assessed via relative excess risk due to interaction (RERI) and likelihood-ratio tests. Joint effects were explored and visualized using a 3D wireframe plot.

RESULTS

Over a median follow-up of 5.14 years, 1735 incident cases of IHD were identified. Adjusted HRs (95 % CIs) were 1.56 (1.34-1.81) per 10 μg/m3 increase in PM2.5 and 0.96 (0.94-0.98) per 10-unit increase in walkability, with both exposures exhibiting non-linear dose-response relationships. Walkability and PM2.5 were positively correlated (rs = 0.12, P < 0.001), and a multiplicative interaction was detected (Pinteraction = 0.019).

CONCLUSION

Walkability was inversely associated with risk of IHD, whereas exposure to PM2.5 was positively associated with IHD. Notably, the pernicious effects of PM2.5 could be attenuated in areas with higher levels of walkability. Our findings underscore the significance of walkable urban design, air quality improvement, as preventive strategies for IHD.

Next-Gen Therapeutics: Pioneering Drug Discovery with iPSCs, Genomics, AI, and Clinical Trials in a Dish

In the high-stakes arena of drug discovery, the journey from bench to bedside is hindered by a daunting 92% failure rate, primarily due to unpredicted toxicities and inadequate therapeutic efficacy in clinical trials. The FDA Modernization Act 2.0 heralds a transformative approach, advocating for the integration of alternative methods to conventional animal testing, including cell-based assays that employ human induced pluripotent stem cell (iPSC)-derived organoids, and organ-on-a-chip technologies, in conjunction with sophisticated artificial intelligence (AI) methodologies. Our review explores the innovative capacity of iPSC-derived clinical trial in a dish models designed for cardiovascular disease research. We also highlight how integrating iPSC technology with AI can accelerate the identification of viable therapeutic candidates, streamline drug screening, and pave the way toward more personalized medicine. Through this, we provide a comprehensive overview of the current landscape and future implications of iPSC and AI applications being navigated by the research community and pharmaceutical industry.

Exposure to Air Pollutants and Myocardial Infarction Incidence: A UK Biobank Study Exploring Gene-Environment Interaction

BACKGROUND

Unraveling gene-environment interaction can provide a novel insight into early disease prevention. Nevertheless, current understanding of the interplay between genetic predisposition and air pollution in relation to myocardial infarction (MI) risk remains limited. Furthermore, the potential long-term influence of air pollutants on MI incidence risk warrants more conclusive evidence in a community population.

OBJECTIVE

We investigated interactions between genetic predisposition and exposure to air pollutants on MI incidence.

METHODS

This study incorporated a sample of 456,354 UK Biobank participants and annual mean air pollution (PM 2.5 , PM 10 , NO 2 , and NO x ) from the UK Department for Environment, Food and Rural Affairs (2006-2021). The Cox proportional hazards model was employed to explore MI incidence after chronic air pollutants exposure. By quantifying genetic risk through the calculation of polygenic risk score (PRS), this study further examined the interactions between genetic risk and exposure to air pollutants in the development of MI on both additive and multiplicative scales.

RESULTS

Among 456,354 participants, 9,114 incident MI events were observed during a median follow-up of 12.08 y. Chronic exposure to air pollutants was linked with an increased risk of MI occurrence. Specifically, the hazard ratios (per interquartile range) were 1.12 (95% CI: 1.10, 1.13) for PM 2.5 , 1.20 (95% CI: 1.19, 1.22) for PM 10 , 1.13 (95% CI: 1.12, 1.15) for NO 2 , and 1.12 (95% CI: 1.11, 1.13) for NO x . In terms of the joint effects, participants with high PRS and high level of air pollution exposure exhibited the greatest risk of MI among all study participants (∼ 255 % to 324%). Remarkably, both multiplicative and additive interactions were detected in the ambient air pollutants exposure and genetic risk on the incidence of MI.

DISCUSSION

There were interactions between exposure to ambient air pollutants and genetic susceptibility on the risk of MI onset. Moreover, the joint effects of these two exposures were greater than the effect of each factor alone. https://doi.org/10.1289/EHP14291.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study

BACKGROUND AND AIMS

Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown.

METHODS

This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset.

RESULTS

Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx.

CONCLUSIONS

In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Fine Particulate Matter Exposure, Genetic Susceptibility, and the Risk of Incident Stroke: A Prospective Cohort Study

BACKGROUND

Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors.

METHODS

This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM2.5) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM2.5 and polygenic risk score with incident stroke and the potential effect modifications.

RESULTS

Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride.

CONCLUSIONS

Long-term exposure to PM2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke.

Genetic Susceptibility Modifies Relationships Between Air Pollutants and Stroke Risk: A Large Cohort Study

BACKGROUND

The extent to which genetic susceptibility modifies the associations between air pollutants and the risk of incident stroke is still unclear. This study was designed to investigate the separate and joint associations of long-term exposure to air pollutants and genetic susceptibility on stroke risk.

METHODS

The participants of this study were recruited by the UK Biobank between 2006 and 2010. These participants were followed up from the enrollment until the occurrence of stroke events or censoring of data. Hazard ratios (HRs) and 95% CIs for stroke events associated with long-term exposure to air pollutants were estimated by fitting both crude and adjusted Cox proportional hazards models. Additionally, the polygenic risk score was calculated to estimate whether the polygenic risk score modifies the associations between exposure to air pollutants and incident stroke.

RESULTS

A total of 502 480 subjects were included in this study. After exclusion, 452 196 participants were taken into the final analysis. During a median follow-up time of 11.7 years, 11 334 stroke events were observed, with a mean age of 61.60 years, and men accounted for 56.2% of the total cases. Long-term exposures to particulate matter with an aerodynamic diameter smaller than 2.5 µm (adjusted HR, 1.70 [95% CI, 1.43-2.03]) or particulate matter with an aerodynamic diameter smaller than 10 µm (adjusted HR, 1.50 [95% CI, 1.36-1.66]), nitrogen dioxide (adjusted HR, 1.10 [95% CI, 1.07-1.12]), and nitrogen oxide (adjusted HR, 1.04 [95% CI, 1.02-1.05]) were pronouncedly associated with increased risk of stroke. Meanwhile, participants with high genetic risk and exposure to high air pollutants had ≈45% (31%, 61%; particulate matter with an aerodynamic diameter smaller than 2.5 µm), 48% (33%, 65%; particulate matter with an aerodynamic diameter smaller than 10 µm), 51% (35%, 69%; nitrogen dioxide), and 39% (25%, 55%; nitrogen oxide) higher risk of stroke compared with those with low genetic risk and exposure to low air pollutants, respectively. Of note, we observed additive and multiplicative interactions between genetic susceptibility and air pollutants on stroke events.

CONCLUSIONS

Chronic exposure to air pollutants was associated with an increased risk of stroke, especially in populations at high genetic risk.

Parental cardiovascular disease and cardiovascular disease risk factors in the offspring: The Diet, Cancer and Health cohorts

BACKGROUND AND AIMS

Cardiovascular disease (CVD) aggregates in families and offspring with parental CVD may have adverse risk factor levels long time before the potential onset of CVD. We compared risk factor levels in offspring of parents with atherosclerotic CVD (ASCVD) and parents with no ASCVD at different parental ages at onset.

METHODS

The study included 5751 participants (median age: 50 years) of the Diet, Cancer and Health - Next Generations study. Measurements included blood pressure, body composition and lipid fractions. Information on parental ASCVD and age at disease onset was obtained through register linkage. Parental ASCVD was defined as myocardial infarction, ischemic stroke or peripheral artery disease occurring <70 years, prematurely (mothers: <65 years fathers: <55 years), divided into age categories or using a broader classification of CVD. Linear regression models using Generalized Estimating Equations were used for analysis. Analyses were adjusted for age, sex, education, smoking, alcohol intake, physical activity and some additionally for BMI.

RESULTS

Offspring with parental ASCVD had a higher blood pressure, waist circumference, BMI, visceral adipose tissue, percentage of body fat and non-HDL cholesterol levels, but not other lipid levels, compared to offspring with no parental ASCVD (all p < 0.01). Overall, the same patterns were observed for parental ASCVD occurring prematurely and using a broader CVD classification.

CONCLUSIONS

Offspring with parental ASCVD had a higher blood pressure, higher body composition measures and higher non-HDL cholesterol levels compared to offspring with no parental ASCVD. Findings were overall consistent across different classifications of parental ASCVD.

A review of factors influencing sensitive skin: an emphasis on built environment characteristics

Background

Sensitive skin (SS) is a condition characterized by hyperreactivity. Impacting around 37 percent of the worldwide population and exerting an influence on the quality of life for affected individuals. Its prevalence rate has increased due to factors such as elevating stress levels and deteriorating environmental conditions. The exposome factors influencing SS have extended from demographic, biological attributes, and lifestyle to external environments. Built environments (BEs) have demonstrated as root drivers for changes in behaviors and environmental exposure which have the potential to trigger SS, but the review of the associations between BEs and SS is currently lacking.

Objective

This review aims to achieve two primary objectives: (1) Examine exposome factors that exert influence on SS at the individual and environmental levels. (2) Develop a theoretical framework that establishes a connection between BEs and SS, thereby offering valuable insights into the impact of the built environment on this condition.

Methods

An extensive literature search was carried out across multiple fields, including sociology, epidemiology, basic medicine, clinical medicine, and environmental research, with a focus on SS. To identify pertinent references, renowned databases such as PubMed, Web of Science, and CNKI were utilized.

Results

SS is the outcome of interactions between individual attributes and environmental factors. These influencing factors can be categorized into five distinct classes: (1) demographic and socioeconomic characteristics including age, gender, and race; (2) physiological and biological attributes such as emotional changes, skin types, sleep disorders, and menstrual cycles in women; (3) behavioral factors, such as spicy diet, cosmetic use, alcohol consumption, and physical exercise; (4) natural environmental features, including climate conditions and air pollution; (5) built environmental features such as population density, green space availability, road network density, and access to public transportation, also have the potential to affect the condition.

Conclusion

The importance of interdisciplinary integration lies in its ability to ascertain whether and how BEs are impacting SS. By elucidating the role of BEs in conjunction with other factors in the onset of SS, we can provide guidance for future research endeavors and the formulation of interventions aimed at mitigating the prevalence of SS.

Artificial Intelligence for Risk Assessment on Primary Prevention of Coronary Artery Disease

Purpose of Review

Coronary artery disease (CAD) is a common and etiologically complex disease worldwide. Current guidelines for primary prevention, or the prevention of a first acute event, include relatively simple risk assessment and leave substantial room for improvement both for risk ascertainment and selection of prevention strategies. Here, we review how advances in big data and predictive modeling foreshadow a promising future of improved risk assessment and precision medicine for CAD.

Recent Findings

Artificial intelligence (AI) has improved the utility of high dimensional data, providing an opportunity to better understand the interplay between numerous CAD risk factors. Beyond applications of AI in cardiac imaging, the vanguard application of AI in healthcare, recent translational research is also revealing a promising path for AI in multi-modal risk prediction using standard biomarkers, genetic and other omics technologies, a variety of biosensors, and unstructured data from electronic health records (EHRs). However, gaps remain in clinical validation of AI models, most notably in the actionability of complex risk prediction for more precise therapeutic interventions.

Summary

The recent availability of nation-scale biobank datasets has provided a tremendous opportunity to richly characterize longitudinal health trajectories using health data collected at home, at laboratories, and through clinic visits. The ever-growing availability of deep genotype-phenotype data is poised to drive a transition from simple risk prediction algorithms to complex, “data-hungry,” AI models in clinical decision-making. While AI models provide the means to incorporate essentially all risk factors into comprehensive risk prediction frameworks, there remains a need to wrap these predictions in interpretable frameworks that map to our understanding of underlying biological mechanisms and associated personalized intervention. This review explores recent advances in the role of machine learning and AI in CAD primary prevention and highlights current strengths as well as limitations mediating potential future applications.

The contribution of the exposome to the burden of cardiovascular disease

Large epidemiological and health impact assessment studies at the global scale, such as the Global Burden of Disease project, indicate that chronic non-communicable diseases, such as atherosclerosis and diabetes mellitus, caused almost two-thirds of the annual global deaths in 2020. By 2030, 77% of all deaths are expected to be caused by non-communicable diseases. Although this increase is mainly due to the ageing of the general population in Western societies, other reasons include the increasing effects of soil, water, air and noise pollution on health, together with the effects of other environmental risk factors such as climate change, unhealthy city designs (including lack of green spaces), unhealthy lifestyle habits and psychosocial stress. The exposome concept was established in 2005 as a new strategy to study the effect of the environment on health. The exposome describes the harmful biochemical and metabolic changes that occur in our body owing to the totality of different environmental exposures throughout the life course, which ultimately lead to adverse health effects and premature deaths. In this Review, we describe the exposome concept with a focus on environmental physical and chemical exposures and their effects on the burden of cardiovascular disease. We discuss selected exposome studies and highlight the relevance of the exposome concept for future health research as well as preventive medicine. We also discuss the challenges and limitations of exposome studies.

Genotype-by-socioeconomic status interaction influences heart disease risk scores and carotid artery thickness in Mexican Americans: the predominant role of education in comparison to household income and socioeconomic index

Background: Socioeconomic status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for cardiovascular disease (CVD). We analyzed Mexican American Family Studies (MAFS) data to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an important determinant of variation in CVD risk factors. Methods: We employed a linear mixed model to investigate GxE in Mexican American extended families. We studied two proxies for CVD [Pooled Cohort Equation Risk Scores/Framingham Risk Scores (FRS/PCRS) and carotid artery intima-media thickness (CA-IMT)] in relation to socioeconomic status as determined by Duncan's Socioeconomic Index (SEI), years of education, and household income. Results: We calculated heritability for FRS/PCRS and carotid artery intima-media thickness. There was evidence of GxE due to additive genetic variance heterogeneity and genetic correlation for FRS, PCRS, and CA-IMT measures for education (environment) but not for household income or SEI. Conclusion: The genetic effects underlying CVD are dynamically modulated at the lower end of the SES spectrum. There is a significant change in the genetic architecture underlying the major components of CVD in response to changes in education.

Improving Genetic Association Studies with a Novel Methodology that Unveils the Hidden Complexity of All-Cause Heart Failure

Motivation

Genome-Wide Association Studies (GWAS) commonly assume phenotypic and genetic homogeneity that is not present in complex conditions. We designed Transformative Regression Analysis of Combined Effects (TRACE), a GWAS methodology that better accounts for clinical phenotype heterogeneity and identifies gene-by-environment (GxE) interactions. We demonstrated with UK Biobank (UKB) data that TRACE increased the variance explained in All-Cause Heart Failure (AHF) via the discovery of novel single nucleotide polymorphism (SNP) and SNP-by-environment (i.e. GxE) interaction associations. First, we transformed 312 AHF-related ICD10 codes (including AHF) into continuous low-dimensional features (i.e., latent phenotypes) for a more nuanced disease representation. Then, we ran a standard GWAS on our latent phenotypes to discover main effects and identified GxE interactions with target encoding. Genes near associated SNPs subsequently underwent enrichment analysis to explore potential functional mechanisms underlying associations. Latent phenotypes were regressed against their SNP hits and the estimated latent phenotype values were used to measure the amount of AHF variance explained.

Results

Our method identified over 100 main GWAS effects that were consistent with prior studies and hundreds of novel gene-by-smoking interactions, which collectively accounted for approximately 10% of AHF variance. This represents an improvement over traditional GWAS whose results account for a negligible proportion of AHF variance. Enrichment analyses suggested that hundreds of miRNAs mediated the SNP effect on various AHF-related biological pathways. The TRACE framework can be applied to decode the genetics of other complex diseases.

Availability

All code is available at https://github.com/EpistasisLab/latent_phenotype_project.

Molecular mechanisms of environmental exposures and human disease

A substantial proportion of disease risk for common complex disorders is attributable to environmental exposures and pollutants. An appreciation of how environmental pollutants act on our cells to produce deleterious health effects has led to advances in our understanding of the molecular mechanisms underlying the pathogenesis of chronic diseases, including cancer and cardiovascular, neurodegenerative and respiratory diseases. Here, we discuss emerging research on the interplay of environmental pollutants with the human genome and epigenome. We review evidence showing the environmental impact on gene expression through epigenetic modifications, including DNA methylation, histone modification and non-coding RNAs. We also highlight recent studies that evaluate recently discovered molecular processes through which the environment can exert its effects, including extracellular vesicles, the epitranscriptome and the mitochondrial genome. Finally, we discuss current challenges when studying the exposome - the cumulative measure of environmental influences over the lifespan - and its integration into future environmental health research.

Subclinical cardiovascular outcomes of acute exposure to fine particulate matter and its constituents: A glutathione S-transferase polymorphism-based longitudinal study

To explore the acute subclinical cardiovascular effects of fine particulate matter (PM2.5) and its constituents, a longitudinal study with 61 healthy young volunteers was conducted in Xinxiang, China. Linear mixed-effect models were used to analyze the association of PM2.5 and its constituents with cardiovascular outcomes, respectively, including blood pressure (BP), heart rate (HR), serum levels of high-sensitivity C-reactive protein (hs-CRP), 8-hydroxy-2'-deoxyguanosine (8-OHdG), tissue-type plasminogen activator (t-PA), and platelet-monocyte aggregation (PMA). Additionally, the modifying effects of glutathione S-transferase mu 1 (GSTM1) and glutathione S-transferase theta 1 (GSTT1) polymorphisms were examined. A 10 μg/m3 increase in PM2.5 was associated with -1.04 (95 % CI: -1.86 to -0.22) mmHg and -0.90 (95 % CI: -1.69 to -0.11) mmHg decreases in diastolic BP (DBP) and mean arterial BP (MABP) along with 1.83 % (95 % CI: 0.59-3.08 %), 5.93 % (95 % CI: 0.70-11.16 %) increases in 8-OHdG and hs-CRP, respectively. Ni content was positively associated with the 8-OHdG levels whereas several other metals presented negative association with 8-OHdG and HR. Intriguingly, GSTT1+/GSTTM1+ subjects showed higher susceptibility to PM2.5-induced alterations of DBP and PMA, and GSTT1-/GSTM1+ subjects showed higher alteration on t-PA. Taken together, our findings indicated that short-term PM2.5 exposure induced oxidative stress, systemic inflammation, autonomic alterations, and fibrinolysis in healthy young subjects. Among multiple examined metal components Ni appeared to positively associated with systematic oxidative stress. In addition, GST-sufficient subjects might be more prone to PM2.5-induced autonomic alterations.

The association of genetic susceptibility to smoking with cardiovascular disease mortality and the benefits of adhering to a DASH diet: The Singapore Chinese Health Study

BACKGROUND

Understanding the genetic predisposition to cardiovascular disease (CVD) may help to improve clinical intervention strategies. Lifestyle factors, such as diet, may differ among ethnic groups and may, in turn, modify individuals' risks to diseases.

OBJECTIVES

We examined the genetic predisposition to ever smoking in relation to CVD mortality and assessed whether such an association could be modified by dietary intake.

METHODS

A total of 23,760 Chinese adults from the Singapore Chinese Heath Study who were free of cancer and CVD at recruitment (1993-1998) were included in the study. A weighted genetic risk score (wGRS) was calculated to define the genetically determined regular smoking behavior (never or ever). Multivariable-adjusted Cox regression models were used to assess the association between the wGRS and CVD mortality. We also conducted a 1-sample Mendelian randomization analysis for ever smoking and CVD mortality.

RESULTS

Over a mean of 22.6 years of follow-up, 2301 CVD deaths were identified. A genetic predisposition to ever smoking was significantly associated with CVD mortality; the multivariable-adjusted HR of CVD mortality was 1.07 (95% CI: 1.03-1.12), with a per-SD increment in the wGRS. However, the Mendelian randomization analysis did not support a causal relationship between ever smoking and CVD mortality (OR, 1.13; 95% CI: 0.87-1.45). Additionally, the Dietary Approaches to Stop Hypertension (DASH) score significantly modified the association between the smoking wGRS and CVD mortality; the association between a genetic predisposition to smoking and CVD mortality was only observed among individuals with a low DASH score (P-interaction = 0.004).

CONCLUSIONS

A genetic predisposition to smoking was associated with CVD mortality in the Chinese population. In addition, we detected a significant interaction showing higher CVD mortality related to genetically determined smoking among those with lower DASH scores.