BackgroundThe roles of chronic kidney disease and acute kidney injury (AKI) as determinants of short- and long-term survival following myocardial infarction (MI) have not been well investigated.MethodsA retrospective analysis of electronic health record data was conducted for U.S. veterans between 2002 and 2015, with up to 15 years of follow-up after MI. Eligible participants included 49,150 veterans with a serum creatinine measurement prior to MI hospitalization. AKI stage was determined by the change between the pre-hospitalization creatinine level and the peak in-hospital measurement. The associations of AKI, estimated glomerular filtration rate (eGFR), and troponin I ratios with survival were evaluated using Cox proportional hazards models.ResultsCompared to the no-AKI group, the hazard ratios (HRs) and 95% confidence intervals (CIs) for 30-day mortality were 3.12 (2.87–3.39), 5.12 (4.65–5.65), and 7.81 (6.93–8.81) across worsening stages of AKI. For 15-year mortality, the HRs were 1.76 (1.68–1.85), 2.33 (2.17–2.50), and 2.66 (2.37–2.99). Compared to those with eGFR >60 mL/min/1.73 m², HRs (95% CI) for 30-day mortality were 1.23 (1.13–1.33), 1.46 (1.33–1.59), and 1.92 (1.72–2.13) across decreasing eGFR levels. For 15-year mortality, HRs were 1.21 (1.17–1.25), 1.55 (1.49–1.61), and 2.13 (2.03–2.24). Mortality rates increased with rising troponin I (cTnI) ratios, particularly for 30-day mortality.ConclusionsAKI, baseline eGFR, and troponin levels were associated with both short- and long-term survival following MI. AKI during MI hospitalization was a particularly strong determinant of short-term mortality.

Introductory Paragraph Rheumatoid arthritis (RA) is a heritable and common autoimmune condition. To date, most genetic associations were derived from individuals with either European or East Asian ancestries. Here, we applied a multimodal automated phenotyping strategy to define RA and performed a genome-wide association study (GWAS) of RA in the Million Veteran Program (MVP), including underrepresented African American (AFR) and Admixed American (AMR) populations. Meta-analyses with previous RA cohorts identified 152 autosomal genome-wide significant loci, of which 31 were novel. Inclusion of multi-ancestry data dramatically improved fine-mapping resolution. Functional characterization of these loci using single-cell transcriptomic and chromatin data suggested new RA genes such as CHD7 and CD247 . We identified underappreciated functional roles of fine-grained immune cell states other than T cells, such as B cell and myeloid cell states. We observed that multi-ancestry polygenic risk scores using our data demonstrated better predictive ability, especially for AFR and AMR 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.

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.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

ImportanceBody 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.ObjectiveTo evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts.Design, Setting, and ParticipantsThis 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.ExposureBMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline.Main Outcomes and MeasuresThe 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.ResultsAmong 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 RelevanceThis 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.

BACKGROUND: Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. METHODS: We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; n cases =51 929; n controls =39 980) and subsequent arterial ischemic stroke (AIS; n cases =45 120; n controls =46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization. RESULTS: Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64–0.85]; P =3.69×10 −8 ) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37–1.67]; P =3.77×10 −8 ) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66–0.88]; adjusted P =0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24–1.60]; adjusted P =0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. CONCLUSIONS: We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.

Background. Mendelian randomization (MR) studies have been described as naturally occurring randomized controlled trials (RCTs). However, MR often deviates from appropriate RCT design principles and relies heavily on two-sample approaches. We used data from the Million Veteran Program (MVP) to empirically evaluate the impact of study design choices and use of one- versus two-sample MR in a study of lipids and coronary artery disease. Methods. Our MR study included MVP participants of European descent with no history of coronary artery disease or contraindications to low-density lipoprotein cholesterol (LDL-C)-related therapies. We sequentially modified the eligibility criteria, study duration and follow-up to reflect common study design decisions for MR. In all designs, we used one- and two-sample approaches to estimate 10-year risks of coronary artery disease per 39 mg/dL increase in LDL-C or 15.6 mg/dL increase in high-density lipoprotein cholesterol (HDL-C). Results. For LDL-C, one-sample estimates varied across designs (odds ratios from 1.50 [95% CI: 1.34,1.68] to 2.23 [95% CI: 1.93,2.59]) and were most sensitive to the inclusion of prevalent outcome events in the analysis. Odds ratios obtained via two-sample MR were attenuated (1.13 [95% CI: 1.01,1.26] to 1.30 [95% CI: 1.15,1.46]). For HDL-C, we observed inverse or null relationships and estimates were qualitatively similar across all designs (odds ratios from 0.76 [95% CI: 0.68,0.86] to 0.93 [95% CI: 0.65,1.34]). Conclusions. MR estimates can, in practice, be impacted by decisions in study design due to trade-offs between different biases, and investigators should evaluate the sensitivity of their estimates to different design decisions.

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality and disability in the United States. Spatiotemporal modeling of disease incidence may guide prevention efforts toward regions most at risk in the future. Methods: We examined spatiotemporal trends in composite CVD events, defined as myocardial infarction, ischemic stroke, atrial fibrillation, heart failure, coronary artery disease, or cardiovascular death, using electronic health records from 9,718,107 U.S. Veterans who used VA healthcare facilities from 2003-2018. Age-standardized annual incidence by state was modeled using the Bernardinelli model, a Bayesian Poisson regression with linear temporal trends for the US and individual states. Results: There were 626,271 CVD events over 16 years of follow up and annual incidence fell gradually from 11.5% in 2003 to 6.6% in 2018. Incidence among all US veterans decreased an estimated 3.1% [95% CI: -3.3%, -2.9%] per year (RR year = 0.969). State-level incidences also decreased monotonically over the follow-up period (Figure panel A ), ranging from an absolute decrease 5.0% (RI) to 1.7% (OR). Estimated incidence for the five states most above (RI, FL, NC, MT, LA) and most below (OR, NV, CT, OK, MI) the national trend are plotted against the US average in Figure panel B . These outlying states differed significantly from the overall trend (posterior probabilities ≥ 99.7%), and the magnitude of trend was loosely correlated with initial incidence rate (in 2003). Notably, four states crossed the national average over the study period: CT and OK started below average in 2003 but ended above in 2018, whereas RI and NC started with high incidence and ended with below average incidence in 2018. Conclusions: Among US veterans, there was significant geographic variation in the rate of decline of incident CVD from 2003-2018. Future research will investigate the mechanisms underpinning the observed trends, particularly prevalence and control of risk factors.

Background and Hypothesis: The American Heart Association (AHA) recently proposed the Life’s Essential 8 (LE8) score as an enhanced measurement tool for cardiovascular health. No studies to date have estimated its association with the risk for atherosclerotic cardiovascular disease (ASCVD) incidence and prognosis. Methods: A prospective cohort study of 384,518 Veterans enrolled in the VA Million Veteran Program (MVP) (2011-2021). LE8 score was developed using AHA guidelines. Primary outcome was total ASCVD. Secondary outcome was hard ASCVD which included non-fatal myocardial infarction, non-fatal stroke, and fatal CVD. Results: Based on 1.16 million person-years of follow-up among Veterans with no ASCVD at baseline, 46,295 Veterans had ASCVD events during follow-up. LE8 score was associated with ASCVD and its subtypes in a linear dose-response manner (Figure 1A). The overall population-attributable fractions for all non-ideal LE8 scores was 59% (95%CI: 51%-66%) for ASCVD, where non-ideal blood pressure was most influential (Figure 1B). Based on 0.6 million person-years of follow-up among patients with ASCVD at baseline, the hazard ratio for incident or recurrent hard ASCVD was 0.52 (95%CI: 0.48-0.56) comparing veterans with ≥650 to those with LE8 score <350, with a dose-response linear association pattern. Conclusions: Based on 1.76 million person years of follow-up among Veterans, a high LE8 score was associated with a significantly lower ASCVD risk and a lower likelihood of developing adverse cardiovascular events regardless of ASCVD status at baseline. Theoretically, an ideal LE8 could potentially prevent almost 59% of ASCVD in this study. Our results support the importance of AHA’s promotion of LE8.

Importance:Primary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation.Objective:To determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population.Design, Setting, and Participants:This was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023.Exposures:PRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status.Main Outcomes and Measures:Incident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events.Results:A total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, -0.07% to 3.30%).Conclusions and Relevance:Study results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.

Background: Heart failure (HF) incidence has increased over past decades and is associated with poor quality of life, increased comorbidities, and high treatment costs. Prevention for HF warrant a major public health priority. Aim: To quantify the association of Life’s Essential 8 (LE8) score with HF. Methods: LE8 score (0-800) was developed based on the AHA guidelines among 348,311 Veterans who enrolled in the VA Million Veteran Program (MVP) (2011-2021) and free of HF at baseline. Cox proportional hazard models were used to calculate the hazard ratios (HR) with their 95% confidence intervals (CI) for first incident HF event, and HF subtypes (HF with reduced ejection fracture (HFrEF) and HF with preserved EF (HFpEF)) across categories of LE8 score. The population attributable fraction (PAF) was calculated to estimate the proportional reduction in HF events that would occur if LE8 was changed to the ideal level. Results: A total of 31,397 HF events were recorded over 1.8 million person-years of follow-up. LE8 score was negatively associated with incidence of HF, HFrEF and HRpEF, even after extensive adjustment for potential confounders ( Figure 1A ). The multivariate-adjusted HR for HF was 0.76 (95% CI: 0.73-0.78), 0.63 (0.61-0.65), 0.52 (0.50-0.54), 0.41 (0.39-0.43), 0.34 (0.32-0.36), 0.28 (0.27-0.30), and 0.23 (0.21-0.25), respectively, among Veterans whose LE8 score was 350-, 400-, 450-, 500-, 550-, 600- and ≥650, respectively, as compared to those with LE8 score <350. The PAF for HF was 7.1%, 10.3%, 15.1%, 15.8%, 17.1%, 17.5% 18.4%, and 49.1% for not ideal sleep, diet, lipid, activity, BMI, smoking, glucose/HbA1c, and blood pressure, respectively, with an estimated joint PAF of 83.2% for total HF, 79.5% for HFrEF and 90.1% for HFpEF for not ideal of any LE8 ( Figure 1B ). Conclusion: Greater adherence to a healthy LE8 lifestyle could be a key component in prevention of HF among Veterans. Assuming everyone follows a lifestyle meet ideal LE8, majority of HF cases will be prevented.

Objective: Body mass index (BMI) is a commonly used estimate of obesity that is a complex multifactorial trait resulting from genetic and lifestyle factors. Weight gain and loss could correlate with adverse biological processes. Prior studies have reported that increased BMI variability predicts future adverse cardiovascular events. However, there have been no prior studies that have investigated this association in patients without cancer or preexisting cardiovascular disease among multiple ethnicities. Using the Million Veteran Program (MVP), a mega-biobank with longitudinal health record data from a large US healthcare system, we evaluated the association between BMI variability and incident cardiovascular events in an ethnically diverse longitudinal cohort (2011-2019). Methods: We studied 92,363 adults free of cardiovascular disease and cancer at baseline. BMI was longitudinally assessed from the baseline visit. BMI variability was assessed using the standard deviation (SD) and coefficient of variation (CV) of each participant. Cardiovascular disease (CVD) risk factors including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking status, diabetes status and statin use were assessed as covariates. We followed patients for the composite CVD events of incident non-fatal myocardial infarction, acute ischemic stroke, and cardiovascular death. Cox proportional hazards modeling was used to examine the association between BMI variability and incident CVD events after adjustment for dichotomous and continuous measures. We also assessed if results were affected sensitive to adjustment for the BMI polygenic score. Results: The cohort (88% men) included 60,180 non-Hispanic White (NHW), 22,488 non-Hispanic Black (NHB), and 9,695 Hispanic (HIS) participants with mean age 56.8 years. Patients were followed from 2011 to 2019. We observed 4,855 composite CVD events. The CV of BMI was associated with incident composite CVD across all groups, but to a stronger degree for Hispanic participants. Among the NHW, each SD increase of CV (indicative of greater BMI variability) was associated with a 15% rise in the risk of CVD events (i.e HR 1.15, 95%CI, 1.11-1.19 after adjustment of covariates. Among the NHB and HIS, results were similar: HR, 1.16 (95%CI, 1.09 - 1.22) and HR, 1.24 (95%CI, 1.12-1.38), respectively. In sensitivity analyses, we found that BMI variability is similarly predictive of the composite outcome after adjustment for BMI polygenic score. Conclusions and Relevance: Increased BMI variability is an independent risk factor for future CVD events.

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.

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven ( CAMK2D , PRKD1 , PRKD3 , MAPK3 , TNFSF12 , APOC3 and NAE1 ) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Background: The American Heart Association (AHA) recently proposed the Life’s Essential 8 (LE8) score as an enhanced measurement tool for cardiovascular health. For the blood glucose metric in LE8, persons with diabetes mellitus (DM) and a hemoglobin A1c (HbA1c) <7% receive higher points (40 out of 100) and successively fewer with increasing HbA1c. However, some studies have found that having a HbA1c <6% in DM patients was associated with a higher risk of mortality, especially cardiovascular (CVD) death. Aim: We sought to categorize DM with HbA1c <7% into two groups (<6% vs . 6-6.9%) and compare their associations with risk for a major adverse cardiovascular event (MACE) to better inform DM HbA1c cut points and LE8 scoring. Methods: Prospective cohort study of 213,760 Veterans enrolled in the VA Million Veteran Program (MVP) (2011-2021) who had a HbA1c measurement and were free of 5 point-MACE (fatal CVD, non-fatal myocardial infarction [MI], non-fatal stroke, non-fatal heart failure and non-fatal atrial fibrillation [Afib]) at baseline. Results: During a mean follow-up of 4.9 years, we identified 38,151 instances of MACE, including 9,665 MI, 2,837 stroke, 5,523 fatal CVD, 16,543 heart failure, and 18,114 Afib. Compared to diabetic patients with HbA1c of 6-6.9%, diabetic patients with a very low HbA1c level (<6%) had significantly higher risk of MACE [Hazard Ratio (HR): 1.15; 95%CI: 1.09-1.21], which was comparable to diabetic patients with HbA1c of 7-7.9% [HR: 1.14 (95%CI: 1.09-1.18)]. Similar results were observed for the associations between HbA1c and risk for stroke, heart failure, Afib and fatal CVD (Figure 1). Conclusions: Our results confirm previous findings that a very low HbA1c level among diabetic patients was associated with a higher risk for MACE. Based on our findings, we suggest further categorization of diabetic patients with HbA1c below 7% (i.e., <6% and 6-6.9%) and subsequent adjustment in LE8 scoring (i.e., from 40 to 30 points) for HbA1c.

Objective: This is a large prospective study aimed to develop risk prediction models of CVD and all-cause mortality in patients who survived MI. Methods: Using 2002-2012 national electronic health record data from the Veterans Health Administration, sex-specific risk prediction models for CVD and all-cause death were developed from the 5-year follow-up data of 100,601 first MI survivors aged >30 years. Model performance was evaluated using a 5-fold cross-validation approach. Results: We followed 98,657 male and 1,944 female MI survivors up to 5 years (407,199 person-years). There were 31,622 deaths (men 31,147, women 475) and 12,901 CVD deaths (men 12,752, women 149) observed during follow up. Among men, greater age, current smoking, diabetes, atrial fibrillation, heart failure, peripheral artery disease, geographic region, and lower BMI (<20kg/m 2 ) were associated with increased risk of subsequent CVD and all-cause-mortality, while statin treatment, hypertension medication, beta-blocker, eGFR level, and high BMI (≥25 kg/m 2 ) were significantly associated with reduced risk of CVD and all-cause-mortality. Similar associations were generally observed among women. We observed U-shaped relations between total cholesterol and outcomes, and HDL cholesterol and outcomes. The prediction models demonstrated good discrimination and calibration. The estimated Harrell’s C-statistics of the final models versus the cross-validation estimates were similar, ranging from 0.75 to 0.81. The predicted risk of death was well-calibrated compared to observed risk. Conclusions: We developed and validated risk prediction models of 5-year risk for CVD and all-cause death for patients following MI. Traditional risk factors, co-morbidity, lack of blood pressure or lipid treatment, and geographic region were all associated with greater risk of CVD and all-cause mortality.