Association of apolipoprotein B and apolipoprotein A1 levels with social determinants of health and coronary artery disease mortality in the United Kingdom Biobank - is there a need for consideration?

BACKGROUND: A higher prevalence of cardiovascular risk factors has previously been shown to be associated with adverse social determinants of health (SDoH) and to explain some of their impact on cardiovascular risk. Whether there is a relationship between lipid parameters, specifically apolipoprotein B (apoB), apolipoprotein A1 (apoA1), their ratio (apoB/apoA1), and SDoH, and whether coronary artery disease (CAD) mortality risk associated with circulating apoB and apoA1 is modified by SDoH was unclear. METHODS: We investigated associations of apoA1, apoB, and apoB/apoA1 with the level of education and household income and their joint impact on CAD mortality in participants of the UK Biobank (UKB) with and without prevalent CAD at enrollment. Hazard ratios for CAD mortality were estimated after adjusting for SDoH and clinical covariates. RESULTS: In 292 804 participants without established CAD, apoB, and the apoB/apoA1 ratio were inversely associated with level of education and household income, whereas apoA1 was positively associated with household income. Adjustment for education level and household income coupled with the number of people living in the household did not attenuate the association between the apolipoprotein levels and incident CAD mortality rates. In a cohort of 13 826 participants with prevalent CAD, apoA1 levels were inversely associated with level of education. Higher apoB levels were only associated with greater CAD mortality risk after adjustment for risk factors. Risk estimation for CAD death through circulating apoA1 levels requires accounting for significant differences by sex. CONCLUSION: Circulating lipid parameters are associated with SDoH in individuals without CAD. CAD mortality risk estimation through apoA1 and apoB levels does not require accounting for SDoH.

High Variability of Body Mass Index Is Independently Associated With Incident Heart Failure.

BACKGROUND: Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF. METHODS AND RESULTS: In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99 368 White participants with ≥3 BMI measures during >2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized SD and coefficient of variation. The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, adjusting for confounding factors and participant-specific rate of BMI change. Higher BMI variability measured in both SD and coefficient of variation was significantly associated with higher risk in HF incidence (SD: hazard ratio [HR], 1.05 [95% CI, 1.03-1.08], P<0.0001; coefficient of variation: HR, 1.07 [95% CI, 1.04-1.10], P<0.0001). CONCLUSIONS: Longitudinal health records capture BMI fluctuation, which independently predicts HF incidence.

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

OBJECTIVE: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥ 90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and they resembled T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes.

Importance: Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes. Objective: To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts. Design, Setting, and Participants: This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023. Exposure: BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline. Main Outcomes and Measures: The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI. Results: Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11). Conclusions and Relevance: This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.

Maternal and Offspring Fatty Acid Desaturase Variants, Prenatal DHA Supplementation, and Dietary n-6:n-3 Fatty Acid Ratio in Relation to Cardiometabolic Health in Mexican Children.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) in fatty acid desaturase (FADS) genes may modify dietary fatty acid requirements and influence cardiometabolic health (CMH). OBJECTIVES: We evaluated the role of selected variants in maternal and offspring FADS genes on offspring CMH at the age of 11 y and assessed interactions of genotype with diet quality and prenatal docosahexaenoic acid (DHA) supplementation. METHODS: We used data from offspring (n = 203) born to females who participated in a randomized controlled trial of DHA supplementation (400 mg/d) from midgestation to delivery. We generated a metabolic syndrome (MetS) score from body mass index, high-density lipoprotein cholesterol, triglycerides, systolic blood pressure, and fasting glucose and identified 6 distinct haplotypes from 5 offspring FADS SNPs. Dietary n-6 (ω-6):n-3 fatty acid ratios were derived from 24-h recall data (n = 141). We used generalized linear models to test associations of offspring diet and FADS haplotypes with MetS score and interactions of maternal and offspring FADS SNP rs174602 with prenatal treatment group and dietary n-6:n-3 ratio on MetS score. RESULTS: Associations between FADS haplotypes and MetS score were null. Offspring SNP rs174602 did not modify the association of prenatal DHA supplementation with MetS score. Among children with TT or TC genotype for SNP rs174602 (n = 88), those in the highest n-6:n-3 ratio tertile (>8.61) had higher MetS score relative to the lowest tertile [<6.67) (Δ= 0.36; 95% confidence interval (CI): 0.03, 0.69]. Among children with CC genotype (n = 53), those in the highest n-6:n-3 ratio tertile had a lower MetS score relative to the lowest tertile (Δ= -0.23; 95% CI: -0.61, 0.16). CONCLUSIONS: There was evidence of an interaction of offspring FADS SNP rs174602 with current dietary polyunsaturated fatty acid intake, but not with prenatal DHA supplementation, on MetS score. Further studies may help to determine the utility of targeted supplementation strategies and dietary recommendations based on genetic profile.

Development and utility of a clinical research informatics application for participant recruitment and workflow management for a return of results pilot trial in familial hypercholesterolemia in the Million Veteran Program.

Objective: The development of clinical research informatics tools and workflow processes associated with re-engaging biobank participants has become necessary as genomic repositories increasingly consider the return of actionable research results. Materials and Methods: Here we describe the development and utility of an informatics application for participant recruitment and enrollment management for the Veterans Affairs Million Veteran Program Return Of Actionable Results Study, a randomized controlled pilot trial returning individual genetic results associated with familial hypercholesterolemia. Results: The application is developed in Python-Flask and was placed into production in November 2021. The application includes modules for chart review, medication reconciliation, participant contact and biospecimen logging, survey recording, randomization, and documentation of genetic counseling and result disclosure. Three primary users, a genetic counselor and two research coordinators, and 326 Veteran participants have been integrated into the system as of February 23, 2023. The application has successfully handled 3367 task requests involving greater than 95 000 structured data points. Specifically, application users have recorded 326 chart reviews, 867 recruitment telephone calls, 158 telephone-based surveys, and 61 return of results genetic counseling sessions, among other available study tasks. Conclusion: The development of usable, customizable, and secure informatics tools will become increasingly important as large genomic repositories begin to return research results at scale. Our work provides a proof-of-concept for developing and using such tools to aid in managing the return of results process within a national biobank.

Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. To increase the understanding of the underlying mechanisms, we performed a meta-analysis of the associations between 4860 circulating proteins and risk of fractures using two large cohorts, including 6430 participants with 643 incident hip fractures. We identified 23 proteins/aptamers associated with incident hip fractures. Two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR were most strongly associated with hip fracture risk. High levels of several inflammation-related proteins were also associated with increased hip fracture risk. Pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. Future mechanistic studies should investigate the underlying biology of these novel protein biomarkers which may be potential drug targets.

Psychological Distress and the Risk of Adverse Cardiovascular Outcomes in Patients With Coronary Heart Disease.

BACKGROUND: Psychological distress is a recognized risk factor in patients with coronary heart disease (CHD), but its clinical significance is unclear. OBJECTIVES: The purpose of this study was to determine if an index of psychological distress is independently associated with adverse outcomes and significantly contributes to risk prediction. METHODS: Pooled analysis of 2 prospective cohort studies of patients with stable CHD (N = 891). A psychological distress score was constructed using measures of depression, anxiety, anger, perceived stress, and post-traumatic stress disorder, measured at baseline. The study endpoint included cardiovascular death or first or recurrent nonfatal myocardial infarction or hospitalization for heart failure at 5.9 years. RESULTS: In both cohorts, first and recurrent events occurred more often among those in the highest tertile of distress score than those in the lowest tertile. After combining the 2 cohorts, compared with the lowest tertile, the hazards ratio for having a distress score in the highest tertile was 2.27 (95% CI: 1.69-3.06), and for the middle tertile, it was 1.52 (95% CI: 1.10-2.08). Adjustment for demographics and clinical risk factors only slightly weakened the associations. When the distress score was added to a traditional clinical risk model, C-statistic, net reclassification index, and integrative discrimination index all significantly improved. CONCLUSIONS: Among patients with CHD, a composite measure of psychological distress was significantly associated with an increased risk of adverse events and significantly improved risk prediction.

Sex-stratified genome-wide association and transcriptome-wide Mendelian randomization studies reveal drug targets of heart failure.

The prevalence of heart failure (HF) subtypes, which are classified by left ventricular ejection fraction (LVEF), demonstrate significant sex differences. Here, we perform sex-stratified genome-wide association studies (GWASs) on LVEF and transcriptome-wide Mendelian randomization (MR) on LVEF, all-cause HF, HF with reduced ejection fraction (HFrEF), and HF with preserved ejection fraction (HFpEF). The sex-stratified GWASs of LVEF identified three sex-specific loci that were exclusively detected in the sex-stratified GWASs. Three drug target genes show sex-differential effects on HF/HFrEF via influencing LVEF, with NPR2 as the target gene for the HF drug Cenderitide under phase 2 clinical trial. Our study highlights the importance of considering sex-differential genetic effects in sex-balanced diseases such as HF and emphasizes the value of sex-stratified GWASs and MR in identifying putative genetic variants, causal genes, and candidate drug targets for HF, which is not identifiable using a sex-combined strategy.

Metabolomic signatures of ideal cardiovascular health in black adults.

Plasma metabolomics profiling is an emerging methodology to identify metabolic pathways underlying cardiovascular health (CVH). The objective of this study was to define metabolomic profiles underlying CVH in a cohort of Black adults, a population that is understudied but suffers from disparate levels of CVD risk factors. The Morehouse-Emory Cardiovascular (MECA) Center for Health Equity study cohort consisted of 375 Black adults (age 53 ± 10, 39% male) without known CVD. CVH was determined by the AHA Life's Simple 7 (LS7) score, calculated from measured blood pressure, body mass index (BMI), fasting blood glucose and total cholesterol, and self-reported physical activity, diet, and smoking. Plasma metabolites were assessed using untargeted high-resolution metabolomics profiling. A metabolome wide association study (MWAS) identified metabolites associated with LS7 score after adjusting for age and sex. Using Mummichog software, metabolic pathways that were significantly enriched in metabolites associated with LS7 score were identified. Metabolites representative of these pathways were compared across clinical domains of LS7 score and then developed into a metabolomics risk score for prediction of CVH. We identified novel metabolomic signatures and pathways associated with CVH in a cohort of Black adults without known CVD. Representative and highly prevalent metabolites from these pathways included glutamine, glutamate, urate, tyrosine and alanine, the concentrations of which varied with BMI, fasting glucose, and blood pressure levels. When assessed in conjunction, these metabolites were independent predictors of CVH. One SD increase in the novel metabolomics risk score was associated with a 0.88 higher LS7 score, which translates to a 10.4% lower incident CVD risk. We identified novel metabolomic signatures of ideal CVH in a cohort of Black Americans, showing that a core group of metabolites central to nitrogen balance, bioenergetics, gluconeogenesis, and nucleotide synthesis were associated with CVH in this population.

Impact of 8 lifestyle factors on mortality and life expectancy among United States veterans: The Million Veteran Program.

BACKGROUND: Lifestyle medicine has been proposed as a way to address the root causes of chronic disease and their associated health care costs. OBJECTIVE: This study aimed to estimate mortality risk and longevity associated with individual lifestyle factors and comprehensive lifestyle therapy. METHODS: Age- and sex-specific mortality rates were calculated on the basis of 719,147 veterans aged 40-99 y enrolled in the Veteran Affairs Million Veteran Program (2011-2019). Hazard ratios and estimated increase in life expectancy were examined among a subgroup of 276,132 veterans with complete data on 8 lifestyle factors at baseline. The 8 lifestyle factors included never smoking, physical activity, no excessive alcohol consumption, restorative sleep, nutrition, stress management, social connections, and no opioid use disorder. RESULTS: On the basis of 1.12 million person-years of follow-up, 34,247 deaths were recorded. Among veterans who adopted 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, the adjusted hazard ratios for mortality were 0.74 (0.60-0.90), 0.60 (95% CI: 0.49, 0.73), 0.50 (95% CI: 0.41, 0.61), 0.43 (95% CI: 0.35, 0.52), 0.35 (95% CI: 0.29, 0.43), 0.27 (95% CI: 0.22, 0.33), 0.21 (95% CI: 0.17, 0.26), and 0.13 (95% CI: 0.10, 0.16), respectively, as compared with veterans with no adopted lifestyle factors. The estimated life expectancy at age 40 y was 23.0, 26.5, 28.8, 30.8, 32.7, 35.1, 38.3, 41.3, and 47.0 y among males and 27.0, 28.8, 33.1, 38.0, 39.2, 41.4, 43.8, 46.3, and 47.5 y for females who adopted 0, 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, respectively. The difference in life expectancy at age 40 y was 24.0 y for male veterans and 20.5 y for female veterans when comparing adoption of 8-9 lifestyle factors. CONCLUSIONS: A combination of 8 lifestyle factors is associated with a significantly lower risk of premature mortality and an estimated prolonged life expectancy.

Does Elevated High-Density Lipoprotein Cholesterol Protect Against Cardiovascular Disease?

High-density lipoprotein (HDL) contributes to reverse cholesterol transport, which is 1 of the main explanations for the described inverse association between HDL-cholesterol (HDL-C) and atherosclerotic cardiovascular disease (ASCVD) risk. However, efforts to therapeutically raise HDL-C levels with niacin, fibrates, or cholesteryl ester transfer protein inhibitors have not demonstrated a reduction in ASCVD events when compared with placebo among individuals treated with statins. Furthermore, mendelian randomization studies suggest that HDL-C is unlikely to be a direct biologic variable impacting ASCVD risk. More recently, observations from well-conducted epidemiologic studies have indicated a nonlinear U-shaped relationship between HDL-C and subclinical atherosclerosis, and that very high HDL-C (≥80 mg/dL in men, ≥100 mg/dL in women) is paradoxically associated with higher all-cause and ASCVD-related mortality. These observations suggest that HDL-C is not a universal protective factor for atherosclerosis. Thus, there are several opportunities for reframing the contribution of HDL-C to ASCVD risk and related clinical calculators. Here, we examine our growing understanding of HDL-C and its role in ASCVD risk assessment, treatment, and prevention. We discuss the biological functions of HDL-C and its normative values in relation to demographics and lifestyle markers. We then summarize original studies that observed a protective association between HDL-C and ASCVD risk and more recent evidence indicating an elevated ASCVD risk at very high HDL-C levels. Through this process, we advance the discussion regarding the future role of HDL-C in ASCVD risk assessment and identify knowledge gaps pertaining to the precise role of HDL-C in atherosclerosis and clinical ASCVD.

Associations of inflammation-related proteome with demographic and clinical characteristics of people with HIV in South Africa.

PURPOSE: Elevated levels of inflammation associated with human immunodeficiency virus (HIV) infection are one of the primary causes for the burden of age-related diseases among people with HIV (PWH). Circulating proteins can be used to investigate pathways to inflammation among PWH. EXPERIMENTAL DESIGN: We profiled 73 inflammation-related protein markers and assessed their associations with chronological age, sex, and CD4+ cell count among 87 black South African PWH before antiretroviral therapy (ART). RESULTS: We identified 1, 1, and 14 inflammatory proteins significantly associated with sex, CD4+ cell count, and age respectively. Twelve out of 14 age-associated proteins have been reported to be associated with age in the general population, and 4 have previously shown significant associations with age for PWH. Furthermore, many of the age-associated proteins such as CST5, CCL23, SLAMF1, MMP-1, MCP-1, and CDCP1 have been linked to chronic diseases such as cardiovascular disease and neurocognitive decline in the general population. We also found a synergistic interaction between male and older age accounting for excessive expression of CST5. CONCLUSIONS AND CLINICAL RELEVANCE: We found that advanced age may lead to the elevation of multiple inflammatory proteins among PWH. We also demonstrated the potential utility of proteomics for evaluating and characterizing the inflammatory status of PWH.

Development of Portable Electronic Health Record Based Algorithms to Identify Individuals with Diabetic Retinopathy.

Objectives: To develop, validate and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHR)s. Methods : We developed and validated EHR-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in three independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet one of three criteria: 1) two or more dates with any DR ICD-9/10 code documented in the EHR, or 2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or 3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology exam. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology exam. Results: The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.97 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV=0.94; NPV=0.86) and lower in MGB (PPV=0.84; NPV=0.76). In comparison, use of DR definition as implemented in Phenome-wide association study (PheWAS) in VUMC, yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62,000 DR cases with genetic data including 14,549 African Americans and 6,209 Hispanics with DR. Conclusions/Discussion: We demonstrate the robustness of the algorithms at three separate health-care centers, with a minimum PPV of 0.84 and substantially improved NPV than existing high-throughput methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls.

Association Between Symptoms of Chronic Psychological Distress and Myocardial Ischemia Induced by Mental Stress in Patients With Coronary Artery Disease.

Background Mental stress-induced myocardial ischemia is a frequent phenomenon in patients with coronary artery disease and is associated with a greater risk of future cardiovascular events. The association between chronic symptoms of psychological distress and mental stress-induced ischemia is not clear. Methods and Results We used a composite score of psychological distress derived from symptoms of depression, posttraumatic stress disorder, anxiety, anger, and perceived general stress. Participants underwent myocardial perfusion imaging with both mental (public speaking task) and conventional (exercise or pharmacological) stress testing. Overall, 142 (15.9%) patients experienced mental stress-induced myocardial ischemia. After adjusting for demographic factors, medical history, and medication use, patients in the highest tertile of psychological distress score had 35% higher odds of having mental stress-induced ischemia compared to those in the lowest tertile (odds ratio [OR], 1.35 [95% CI, 1.06-2.22]). Stratified analyses showed that the association between psychological distress score and mental stress-induced myocardial ischemia was significantly associated only within the subgroup of patients with a prior myocardial infraction, with patients with a prior myocardial infarction in the highest tertile having a 93% higher odds of developing myocardial ischemia with mental stress (95% CI, 1.07-3.60). There was no significant association between psychological distress and conventional stress-induced ischemia (OR, 1.19 [95% CI, 0.87-1.63]). Conclusions Among patients with a history of myocardial infarction, a higher level of psychosocial distress is associated with mental stress-induced myocardial ischemia but not with ischemia induced by a conventional stress test.

Effects of prenatal docosahexaenoic acid supplementation on offspring cardiometabolic health at 11 years differs by maternal single nucleotide polymorphism rs174602: follow-up of a randomized controlled trial in Mexico.

BACKGROUND: There is limited evidence regarding long-term effects of prenatal docosahexaenoic acid (DHA) supplementation on offspring cardiometabolic health (CMH). Inconsistent results may be attributable to variants of fatty acid desaturase (FADS) genes. OBJECTIVE: We aimed to evaluate the effect of prenatal DHA supplementation on offspring CMH and investigate effect modification by maternal FADS2 single nucleotide polymorphism (SNP) rs174602. METHODS: We used follow-up data from a double-blind, randomized controlled trial in Mexico in which pregnant females received 400 mg/d of algal DHA or placebo from midgestation until delivery. The study sample included 314 offspring with data at age 11 y and maternal FADS genetic data (DHA: n = 160; Placebo: n = 154). We derived a Metabolic Syndrome (MetS) score from body mass index, HDL, triglycerides, fasting glucose concentrations, and systolic blood pressure. Generalized linear models were used to evaluate the effect of the intervention on offspring MetS score and test interactions between treatment group and genotype, adjusting for maternal, offspring, and household factors. RESULTS: Offspring MetS score did not differ significantly by treatment group. We observed evidence of effect modification by maternal SNP rs174602 (P = 0.001); offspring of maternal TT genotype who received DHA had lower MetS score relative to the placebo group (DHA (mean ± standard error of the mean (SEM)): -0.21 ± 0.11, n = 21; Placebo: 0.05 ± 0.11, n = 23; Δ= -0.26 (95% CI: -0.55, 0.04), P = 0.09); among CC maternal genotype carriers, offspring of mothers who received DHA had higher MetS score (0.18 ± 0.06, n = 62) relative to the placebo group (-0.05 ± 0.06, n = 65, Δ=0.24 (0.06, 0.41), P < 0.01). CONCLUSION: The effect of prenatal DHA supplementation on offspring MetS score differed by maternal FADS SNP rs174602. These findings further support incorporating genetic analysis of FADS polymorphisms in DHA supplementation trials. CLINICAL TRIAL DETAILS: This trial was registered at clinicaltrials.gov as NCT00646360.

Correction for Collider Bias in the Genome-wide Association Study of Diabetes-Related Heart Failure due to Bidirectional Relationship between Heart Failure and Type 2 Diabetes.

Aims: Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) across demographic groups. On the other hand, metabolic impairment, including elevated T2D incidence is a hallmark of HF pathophysiology. We investigated the bidirectional relationship between T2D and HF, and identified genetic associations with diabetes-related HF after correction for potential collider bias. Methods: We performed a genome-wide association study (GWAS) of HF to identify genetic instrumental variables (GIVs) for HF, and to enable bidirectional Mendelian Randomization (MR) analysis between T2D and HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted GWAS of diabetes-related HF with correction for collider bias. Results: We first identified 61 genomic loci, including 24 novel loci, significantly associated with all-cause HF in 114,275 HF cases and over 1.5 million controls of European ancestry. Combined with the summary statistics of a T2D GWAS, we obtained 59 and 82 GIVs for HF and T2D, respectively. Using a two-sample bidirectional MR approach, we estimated that T2D increased HF risk (OR 1.07, 95% CI 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to prevalent HF affecting incidence of T2D. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program, and replicated the associations in the UK Biobank study. Conclusion: We identified novel HF-associated loci to enable bidirectional MR study of T2D and HF. Our MR findings support T2D as a HF risk factor and provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci. Evaluation of collider bias should be a critical component when conducting GWAS of complex disease phenotypes such as diabetes-related cardiovascular complications.

Association of systemic inflammation with posttraumatic stress disorder after a myocardial infarction.

Background: Adverse mental health conditions including depression, posttraumatic stress disorder (PTSD), and anxiety are prevalent among patients who survive myocardial infarctions (MI) and are associated with adverse outcomes. The mechanisms underlying these associations, however, are not well understood. Inflammatory pathways may mediate the cardiovascular outcomes of patients with mental health disorders. We examined the bidirectional association between PTSD symptoms and inflammatory biomarkers in a young/middle-aged post MI population. We further examined how this association may differ between women and men as well as between Black and non-Black individuals. Methods: Participants included individuals with early onset MI between the ages 25 and 60. Mental health scores for depression, PTSD, perceived stress, and anxiety as well as inflammatory biomarkers, interleukin-6 (IL-6) and high sensitivity C-reactive protein (hsCRP), were collected at baseline and at six-month follow up. We examined the bidirectional changes in mental health symptoms and inflammatory biomarkers between baseline and follow-up. Results: Among 244 patients in the study (mean age: 50.8, 48.4% female, 64.3% Black), the geometric means for IL-6 level and hsCRP at rest were 1.7 pg/mL and 2.76 mg/L, respectively. Mental health scores at baseline did not consistently predict changes in inflammatory biomarkers at follow-up. However, baseline levels of both IL-6 and hsCRP were robustly associated with an increase in re-experiencing PTSD symptoms at 6 months: in adjusted linear mixed models, there was a 1.58-point increase in re-experiencing PTSD symptoms per unit of baseline hsCRP (p = 0.01) and 2.59-point increase per unit of baseline IL-6 (p = 0.02). Once the analysis was stratified by race, the association was only noted in Black individuals. Baseline inflammation was not associated with change in any of the other mental health symptom scores. Conclusion: Markers of inflammation are associated with an increase in post-event PTSD symptoms in younger or middle-aged patients who experienced an MI, especially Black patients. These results suggest a mechanistic link between inflammation and the development of PTSD among individuals with cardiovascular disease.

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

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

Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program.

Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a multi-population meta-analysis for 2,068 traits derived from electronic health records of 635,969 participants in the Million Veteran Program (MVP), a longitudinal cohort study of diverse U.S. Veterans genetically similar to the respective African (121,177), Admixed American (59,048), East Asian (6,702), and European (449,042) superpopulations defined by the 1000 Genomes Project. We identified 38,270 independent variants associating with one or more traits at experiment-wide P<4.6×10-11 significance; fine-mapping 6,318 signals identified from 613 traits to single-variant resolution. Among these, a third (2,069) of the associations were found only among participants genetically similar to non-European reference populations, demonstrating the importance of expanding diversity in genetic studies. Our work provides a comprehensive atlas of phenome-wide genetic associations for future studies dissecting the architecture of complex traits in diverse populations.