Introduction: The PREVENT (Predicting Risk of Cardiovascular Disease Events) equations estimate 10-year absolute risks for atherosclerotic CVD (ASCVD), heart failure (HF), and CVD (ASCVD + HF). Of PREVENT inputs, chronological age explains most of the variance in risk estimates. Grim Age acceleration (Grim2AA) is an epigenetic age measure that predicts morbidity and mortality; however, whether it contributes to risk prediction is not known. Hypothesis: Incorporating Grim2AA-adjusted age into PREVENT base equations improves 10-year risk discrimination, calibration, and reclassification. Methods: We analyzed data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective, multicenter U.S. cohort. We included participants free of CVD with available clinical and Grim2AA measures in midlife (year 20 visit). Grim2AA-adjusted age (Grim2AA + chronological age) replaced chronological age in PREVENT-CVD, PREVENT-ASCVD, and PREVENT-HF base models. Model performance was assessed using C-statistics and calibration, comparing Grim2AA-adjusted age–based vs. original models. We assessed reclassification using the Partial Likelihood Ratio Test. Results: Among the 2,432 participants included, 42.3% were men and 43.4% were Black, with a mean chronological age of 45.2 ± 3.6 years and a mean Grim2AA of 0.13 ± 5.14 years. During a median follow-up of 17.8 (interquartile range 16.9–18.0) years, 147 ASCVD, 173 CVD, and 42 HF events occurred. In univariate models, predicted risk with original and Grim2AA-adjusted PREVENT measures were each significantly associated with CVD outcomes. Each 1-SD Grim2AA-adjusted PREVENT was associated with ASCVD (1.53 [1.43–1.64]), CVD (1.50 [1.42–1.58]), and HF (1.34 [1.26–1.43]) events. There was no difference in overall predictive utility when Grim2AA-adjusted age was integrated in place of chronological age (C-statistic 0.76 [0.72–0.83] vs 0.76 [0.71–0.82]; Δ<0.01; Figure 1) for PREVENT-CVD. Findings were similar for PREVENT-ASCVD and PREVENT-HF models, with no improvement in calibration or reclassification. Results were similar among the subset of participants with Grim2AA ≥ 2 years. Conclusions: Grim2AA does not improve CVD risk estimation of the PREVENT equations. Further research is needed to determine whether other biological age measures can enhance CVD risk assessment.

Background: Heart failure (HF) consists of two subtypes: heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) with heterogeneous age of onset and risk factor profiles. Characterizing the distribution of age of onset and baseline risk factors for each HF subtype in contemporary samples may provide insight into early disease presentation and guide preventive strategies. Methods: We assembled a contemporary cohort of adults aged 30 years and older with a diagnosis of HF in 2024 using electronic health record (EHR) data from an integrated U.S health system that includes eleven hospitals. HF diagnoses were defined as ≥1 inpatient or ≥2 outpatient standardized ICD diagnosis codes. We excluded patients without an echocardiogram within three years of diagnosis. Two subgroups were defined by ejection fraction as the HFpEF strata (EF ≥50%) and the HFrEF strata (EF <50%). We examined age (30-49, 50-64, ≥65 years) and burden of risk factors (obesity, hypertension, diabetes, and chronic kidney disease) across subgroups. Results: Our EHR-based cohort included 6980 in the HFpEF cohort and 3347 in the HFrEF cohort. The distribution of age differed for HFpEF and HFrEF. Among HFpEF, 4.3% were aged 30-49 years, 16.9% 50-64 years, and 78.8% ≥65 years. For HFrEF, 10.6% were aged 30-49 years, 26.8% 50-64 years, and 62.6% ≥65 years. Risk factor burden was high in both HF subtypes (Table) with hypertension being nearly universal, especially above age 50. Conclusions: We characterized a contemporary real-world HFpEF and HFrEF cohort. Risk factor burden is substantial across all age groups, even with early-onset HF; this emphasizes the need for targeted prevention and management strategies beginning in young adulthood.

BACKGROUND:Atrial fibrillation (AF) is the most common arrhythmia in dilated cardiomyopathy (DCM) and is associated with adverse outcomes. However, the genetic determinants of AF risk and its prognostic significance across genotyped DCM subtypes remain unknown. METHODS:In this observational cohort study, we analyzed 3117 genotyped patients with DCM from the SHaRe (Sarcomeric Human Cardiomyopathy Registry). AF prevalence, incidence, and clinical characteristics were assessed by genotype. Patients were classified as genotype-positive [G(+)] if they had a pathogenic or likely pathogenic variant in a DCM-associated gene, and genotype-negative [G(-)] if genetic testing was negative. Factors associated with incident AF were evaluated using Cox regression. AF was modeled as a time-dependent variable to evaluate associations with clinical outcomes. RESULTS:Among 3117 genotyped patients with DCM (mean age, 48±15 years; 39% were female; and 35% were G[+]), 12.3% (n=384) had prevalent AF. Of 2491 patients without prevalent AF and with follow-up, 312 (12.5%) developed AF during a median of 4.5 years (interquartile range, 1.6-9.0). Among 2851 patients with follow-up, cumulative AF prevalence was 23.6%. LMNA had the highest AF incidence (7.6/100 patient-years) and cumulative AF prevalence (56.7%) and was the only genotype independently associated with incident AF compared with that in G(-) patients (hazard ratio, 5.52 [95% CI, 3.84-7.95]; P<0.001). TTN had an AF incidence of 2.1 per 100 patient-years and cumulative AF prevalence of 24.4%, comparable to that in G(-) patients. Older age, male sex, and prior heart failure hospitalization were also independently associated with incident AF. AF was independently associated with a higher risk of the composite clinical outcome (hazard ratio, 1.58 [95% CI, 1.29-1.94]; P<0.001), including heart failure, ventricular arrhythmias, and all-cause mortality. CONCLUSIONS:In this large genotyped DCM cohort, AF burden and incident AF risk varied across genotypes. Only LMNA was associated with an increased risk of incident AF. AF onset was independently associated with adverse outcomes, supporting genotype-guided AF surveillance and management in DCM.

Background: The recent PREVENT-HF risk equations were developed to estimate 10-year risk of overall HF. While HF with preserved vs reduced ejection fraction (HFpEF; HFrEF) have common risk factors, distinct differences in risk conferred by older age, obesity, and coronary artery disease are known. In this context, we sought to evaluate the performance of PREVENT-HF equations relative to HFpEF vs HFrEF. Methods: We examined participants from 4 pooled community-based cohort studies: the Multi-Ethnic Study of Atherosclerosis (MESA), Framingham Heart Study (FHS) offspring exam 6, Cardiovascular Heart Study (CHS), and Prevention of Renal and Vascular End-stage Disease (PREVEND) study. We excluded those with ages <30 and >79 years, prevalent HF, prevalent CVD, and missing key clinical information. We compared the performance of the PREVENT-HF equation in predicting incident HFpEF vs HFrEF at 10 years using Uno’s C-statistics and area under receiver operating characteristic (AUROC). Results: Among 22,061 participants (age 59 ± 14 years, 54% women, BMI 27 ± 5 kg/m 2 ), 322 developed HFpEF and 464 HFrEF during a median follow-up of 10 years. The PREVENT-HF risk equation performed well for both HFpEF (c-statistic 0.81, 95% CI 0.80-0.83) and HFrEF (c-statistic 0.78 (95% CI 0.76-0.80), with similar improvement compared with age and sex alone (HFpEF: c-statistic 0.78, 95% CI 0.76-0.80; HFrEF: c-statistic 0.75, 95% CI 0.73-0.76, P<0.001 for delta for both). The AUROC remained stable across 1-10 years demonstrating consistently strong discrimination for both HFpEF and HFrEF. Time-dependent AUCs were generally higher for HFpEF compared with HFrEF, indicating slightly better discrimination for HFpEF across all time horizons ( Figure ). Conclusions: Our findings demonstrate overall similar performance of the PREVENT-HF risk model with respect to HFpEF and HFrEF. Future studies on subtype-specific risk models may improve upon current risk prediction tools for overall HF.

OBJECTIVE:The association of gestational diabetes mellitus (GDM) subtypes with maternal cardiometabolic health is not known. We examined whether GDM subtypes were differentially associated with cardiometabolic health 10-14 years after delivery. RESEARCH DESIGN AND METHODS:We used data from the prospective Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study. The exposure was GDM subtype (insulin deficient, insulin resistant, mixed defect, unclassified). The outcomes were prediabetes or diabetes and, secondarily, hypertension, dyslipidemia, metabolic syndrome, and predicted cardiovascular disease. RESULTS:Of 4,693 women, 3.0% had insulin-deficient, 9.0% insulin-resistant, 1.6% mixed-defect, and 0.7% unclassified GDM. Compared with no GDM, all GDM subtypes except unclassified were associated with higher risk of prediabetes or diabetes (adjusted risk ratios 2.14-2.88), metabolic syndrome, and predicted cardiovascular disease. Only insulin-resistant GDM was associated with dyslipidemia. CONCLUSIONS:All GDM subtypes were associated with an increased risk of prediabetes or diabetes, metabolic syndrome, and high predicted cardiovascular disease 10-14 years after delivery.

Background The American Heart Association's Predicting Risk of Cardiovascular Disease Events model offers a modern, race‐free approach to risk prediction, but its subgroup fairness and the added value of social determinants of health (SDOH) remain underexplored. Methods To evaluate Predicting Risk of Cardiovascular Disease Events in 10‐year atherosclerotic cardiovascular disease prediction regarding fairness and value of SDOH predictors, we conducted a retrospective cohort study of 554 675 adults aged 30 to 79 years, using deidentified electronic health records from Truveta, a multisystem US data platform. Subgroup fairness was assessed using percentile calibration plots and Cross Concordance Index metric. The incremental value of SDOH was evaluated by comparing discrimination, calibration, and fairness across models. Results The 10‐year atherosclerotic cardiovascular disease event rate was 1.8%. Most subgroups exhibited consistent calibration and the Cross Concordance Index values. The most pronounced disparities were observed between White and Asian participants (event rate: 10.3% versus 6.6% at the 95th percentile; Cross Concordance Index=0.849 versus 0.679), and private and public insurance groups (event rate: 0.7% versus 1.5% at the 25th percentile; Cross Concordance Index=0.578 versus 0.859). Adding SDOH predictors had minimal effects on model performance. Conclusions Predicting Risk of Cardiovascular Disease Events showed fairness across most demographic and SDOH subgroups, supporting its practical use to predict atherosclerotic cardiovascular disease risk. Adding SDOH predictors offered minimal incremental benefit, reinforcing the original equations' utility as a reliable and fair tool for general populations.

Background: Chronic, low-grade inflammation is increasingly recognized as an important mechanism underlying the development of cardiovascular, kidney, and metabolic (CKM) conditions. However, whether it is associated with CKM syndrome progression is uncertain. Methods: In the prospective Coronary Artery Risk Development in Young Adults (CARDIA) study, which recruited young adults (aged 18-30 years) between 1985-1986. For this study, baseline was defined at a follow-up visit in 1992 when high-sensitivity C-reactive protein (hsCRP) was measured. CKM syndrome stages were characterized according to adapted American Heart Association criteria at follow-up visits 3- and 28-years after hsCRP measurement. The association between hsCRP and progression of CKM syndrome (transition to ≥1 higher stages) over 25 years was examined. Results: Among 2,952 participants with available hsCRP and without established cardiovascular disease (mean age, 35±4 years), 1,005 (34%) had a hsCRP level ≥2 mg/dL and 740 (25%) had a hsCRP level ≥3 mg/dL. Among those alive at follow-up, 76% experienced any CKM syndrome progression and 40% experienced any regression. Participants with higher hsCRP levels had more advanced CKM syndrome stages at baseline (41% vs. 25% with CKM stages ≥2 if hsCRP ≥2 vs. <2 mg/dL, respectively) and at follow-up ( Figure, A ). After covariate adjustment, higher baseline hsCRP was incrementally associated with a higher rate of CKM syndrome progression (aHR per doubling of hsCRP, 1.04; 95% CI, 1.02-1.07; P =0.002). Baseline CKM syndrome stage (0 vs. ≥1) did not appear to modify the association between higher hsCRP and CKM syndrome progression ( P interaction =0.27) ( Figure, B ). Similar findings were observed when hsCRP was dichotomized at ≥3 vs. <3 mg/dL (aHR, 1.11, 95% CI, 1.00-1.24; P =0.05), but not at ≥2 vs. <2 mg/dL (aHR, 1.06, 95% CI, 0.96-1.16; P =0.28). Conclusions: Elevated hsCRP levels were common among young adults and modestly associated with CKM syndrome onset and progression over 25 years. These findings suggest low-grade inflammation may incrementally portend worsening CKM health over time.

Background: Based on data largely from ambulatory epidemiological cohorts, the prevalence of heart failure with preserved ejection fraction (HFpEF) has increased substantially in the past decade, particularly among women. However, contemporary trends and sex differences in the distribution of HF subtypes among US patients newly hospitalized with HF remains unknown. Here, we aimed to evaluate contemporary trends and sex differences in the distribution of HF subtypes among US patients newly hospitalized with HF in a national registry. Methods: Using the Get With The Guidelines®-Heart Failure registry, we assessed temporal trends in the proportions of heart failure subtypes (HFpEF; EF ≥ 50%; HF with mildly reduced/reduced EF [HFmr/rEF]; EF < 50%) in patients hospitalized with incident HF between 2005 and 2022. Linear regression was used to assess annual changes in the prevalence of HFpEF among hospitalizations with incident HF. Results: Of 372,623 patients with incident HF hospitalizations across 1,081 facilities, 184,977 (49.6%) had HFpEF, 180,731 (48.5%) were women, and 245,561 (65.9%) were age 65 years or older. Over the 18-year period, women with incident HF had a higher proportion with HFpEF (60.5%) versus men (39.3) (risk ratio = 1.54; 95% confidence interval [CI]: 1.53 – 1.55; p<0.001). Among women hospitalized with incident HF, the proportion with HFpEF increased from 51% in 2005 to 61% in 2022, an annual change of 0.39% (95% CI: 0.32% - 0.45%; p trend <0.001) per year. Over the same period among men, the proportion with HFpEF rose from 28% to 41%, an annual change of 0.61% (0.55%, 0.67%; p trend <0.001) per year. Conclusions: By 2022, approximately 50% of patients hospitalized with incident HF had HFpEF. More women with incident HF had HFpEF than men, but men had greater annual increase in the proportion of HFpEF among incident HF hospitalizations. Greater efforts for targeted prevention of HFpEF, particularly for women, are needed.

Background: Preeclampsia is a leading cause of maternal-fetal morbidity and strongly linked to future cardiovascular disease. Prediction and prevention remain limited, in part due to preeclampsia heterogeneity and poorly defined biological subtypes. Better delineation of preeclampsia subtypes could inform strategies to reduce preeclampsia and its short- and long-term morbidity. We aimed to identify novel clinical and biomarker defined subtypes of preeclampsia using unsupervised machine learning and evaluate their associations with postpartum cardiovascular health. Methods: Participants with preeclampsia, defined per ACOG criteria, were identified from the multicenter, prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (NuMoM2b)-Heart Health Study. Participants with pre-pregnancy hypertension were excluded. Clinical and demographic data, placental and cardiovascular biomarkers, and proteomic profiles were analyzed. Two-stage feature selection (Boruta SHAP and volcano filtering) identified informative proteomic markers, integrated with clinical variables. UMAP dimensionality reduction and Gaussian Mixture Model clustering (optimized by silhouette scores) identified subtypes, followed by refinement to maximize between-cluster variance. The resulting subgroups represented phenotypically and biologically distinct preeclampsia endotypes. Postpartum incident hypertension (>=130/80 mmHg or medication use at 2-7 years) was compared across subtypes using modified Poisson regression. Results: Among 298 women with preeclampsia, three subtypes emerged (Figure 1): (1) cardiometabolic – higher body mass index, blood pressure, and maternal inflammatory markers; (2) placentally-mediated – elevated placental analytes and normal maternal cardiometabolic features; and (3) mixed – intermediate cardiometabolic and placental analyte profiles. All subtypes showed high risk of incident hypertension versus women without adverse pregnancy outcomes (n=755). Risk was highest in the cardiometabolic subtype (RR 3.09 [95%CI 2.39-3.97]), followed by placentally mediated (RR 1.97 [1.43-2.73]) and mixed (RR 1.62 [0.98-2.67]) (global Wald test p<0.001; Figure 2). Conclusion: Preeclampsia comprises biologically distinct subtypes with heightened but differential postpartum cardiovascular risk. Recognition of this heterogeneity provides new insights into pathophysiology and may advance precision prevention of preeclampsia and its long-term cardiovascular sequelae.

Introduction: Early menarche (<12 years), menopause (<40 years), and a short reproductive lifespan (<35 years), have been associated with increased CVD risk. It is unclear whether these reproductive factors are independently associated with CVD risk or if associations are modified by adiposity. Purpose: Examine whether early menarche, menopause, and a short reproductive lifespan are independently associated with incident CVD and examine heterogeneity by obesity status. Methods: Postmenopausal women enrolled into the WHI observational study or trials with ages at menarche and menopause recalled at baseline were included. Reproductive lifespan was defined as the difference between age at menopause and menarche. Obesity was defined as either a waist circumference (WC) of ≥88 cm or a body mass index (BMI) of ≥30 kg/m 2 at enrollment. Incident CVD was a composite outcome including incidence of coronary artery disease, heart failure, peripheral artery disease, and stroke. Multivariable cox regression models assessed associations of reproductive characteristics and incident CVD, adjusting for lifestyle, demographic, and clinical factors. Interactions of reproductive factors, WC, and BMI were also examined. Results: At enrollment, participants (N=119182) were on average 68.2±7.1 years with a WC of 85.9±13.6 cm and BMI of 27.7±5.8 kg/m 2 . Over a median follow-up of 12.6 years, there were 12,731 (10.7%) incident CVD cases. Mean ages at menarche and menopause were 12.6±1.5 and 48.2±6.3 years, yielding an average reproductive lifespan of 35.6±6.4 years. Early menarche (HR: 1.15, 95% CI: 1.07-1.23), menopause (HR: 1.24, 95% CI: 1.12-1.38), and a short reproductive lifespan (HR: 1.15, 95% CI: 1.08-1.23) were significantly associated with increased risk of incident CVD. Excess menopausal adiposity significantly modified association of early menarche and CVD only ( Table ). Conclusions: Among postmenopausal women, age at reproductive transitions and duration of reproductive lifespan were independently associated with incident CVD. Future research should examine whether prioritizing weight management earlier in the life course, especially among those with menarche before age 12, impacts CVD risk and can inform public health strategies.

AIMS:Circulating ketone bodies (KB) have emerged as a potential adjunctive biomarker for incident heart failure (HF) risk and might provide incremental information beyond established biomarkers. A multi-marker risk score may improve risk stratification of incident HF in the community. The authors aim to develop a risk score using N-terminal proB-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin (hs-cTnT) and a unique systemic biomarker of KB to predict HF among participants without cardiovascular disease. METHODS AND RESULTS:A multi-marker score was developed incorporating NT-proBNP ≥ 125 pg/mL, hs-cTnT ≥ 14 ng/L, and total KB ≥ 75th percentile (316 μmol/L), with one point allocated for each abnormal marker among Multi-Ethnic Study of Atherosclerosis participants. Multivariable Cox model was used to assess the association between multi-marker risk score and the risk of incident HF. Among 6748 participants, there were 383 incident HF events over a median follow-up of 15.7 years. The three biomarkers exhibited poor correlation with one another (r < 0.06 for all). The addition of KB to NT-proBNP and hs-cTnT to identify incident HF improved 5- and 10-year risk prediction (C-statistic 0.74 vs. 0.77, P = 0.02 and 0.70 vs. 0.73, P = 0.02, respectively). There was no evidence of miscalibration using the multi-marker score for predicting 5- and 10-year HF risk (P > 0.05). A graded association was observed between the multi-marker score and risk of HF independent of established clinical factors. CONCLUSION:The addition of plasma KB to a clinical risk score using biomarkers of cardiac injury and stress may further improve the prediction of incident HF.

Background: The American Heart Association’s Predicting Risk of Cardiovascular Disease Events (PREVENT) model offers a modern, race-free approach to risk prediction from a large contemporary cohort, but its fairness across subgroups and the added value of social determinants of health (SDOH) predictors remain underexplored in large real-world settings. Methods: We conducted a retrospective cohort study of 554,675 adults aged 30–79 years without baseline CVD, using de-identified electronic health records from Truveta, a multi-system U.S. clinical data platform (Figure 1). We evaluated three models, including the original PREVENT equations, and retrained PREVENT models (coefficients re-estimated in the Truveta cohort) with and without social determinants of health (SDOH) predictors. The primary outcome was 10-year ASCVD events. Model evaluation focused on two aspects: (1) Fairness across subgroups assessed using (a) percentile calibration plots, comparing Kaplan–Meier (KM)-estimated event rates across predicted risk percentiles within demographic and SDOH subgroups, and (b) the cross concordance index (xCI), quantifying how consistently models ranked earlier events across and within subgroups. (2) Incremental value of SDOH assessed by comparing discrimination, calibration, and fairness between retrained PREVENT models with and without SDOH predictors. Results: The 10-year ASCVD event rate was 1.8%. Most subgroups exhibited consistent calibration (Figure 2) and xCI values (Figure 3). The most pronounced disparities were observed between Whites and Asians (event rate: 10.3% vs. 6.6% at the 95th percentile; xCI = 0.849 vs. 0.679), college-educated and non–college-educated individuals (event rate: 14.2% vs. 10.7% at the 95th percentile; xCI = 0.645 vs. 0.935), and private and public insurance groups (event rate: 0.7% vs. 1.5% at the 25th percentile; xCI = 0.578 vs. 0.859). Across all subgroups, the inclusion of SDOH predictors in the PREVENT model had minimal impact on discrimination and calibration performance, with most changes being small and directionally inconsistent. Conclusions: PREVENT showed fairness across demographic and SDOH subgroups, supporting its practical use to predict ASCVD risk. Adding SDOH predictors or recalibrating offered minimal incremental benefit, reinforcing the original PREVENT equations’ utility as a reliable, fair tool for diverse populations.

Background: The prevalence and prognostic impact of metabolic dysfunction-associated steatotic liver disease (MASLD), overall and across the cardiovascular-kidney-metabolic (CKM) spectrum, is uncertain. Methods: In the prospective Coronary Artery Risk Development in Young Adults (CARDIA) study, abdominal computed tomography was performed at a follow-up examination in 2010. MASLD was defined as hepatic steatosis (≤51 Hounsfield units) and ≥1 cardiometabolic criteria, without other causes of hepatic steatosis. The association between MASLD (vs. no MASLD) and clinical outcomes was evaluated. Subgroup analyses were repeated by CKM stage. Results: Among 2,600 participants with sufficient data (mean age, 50±10 years), 89% had CKM syndrome stage ≥1 ( Figure, A ); 24% had MASLD, with higher prevalence at higher CKM syndrome stages ( Figure, B ). After covariate adjustment, MASLD was associated with a higher rate of all-cause death (aHR, 1.90; 95% CI, 1.22-2.98), without heterogeneity across CKM stages ( P interaction =0.78) ( Figure, C ). MASLD was associated with a higher rate of incident cardiovascular events (aHR, 1.81; 95% CI, 1.23-2.65), observed primarily in those with CKM stages 0-1 ( P interaction =0.032) ( Figure, C ). Conclusions: MASLD impacted 1 in 4 middle-aged adults and was associated with cardiovascular and mortality events, particularly at earlier CKM stages. These findings suggest early MASLD recognition and intervention across the CKM spectrum may reduce long-term adverse outcomes.

Introduction and Objective: Subtypes of gestational diabetes mellitus (GDM) have been described but their association with subsequent maternal cardiometabolic health remains uncertain. We examined whether GDM subtypes were differentially associated with cardiometabolic health 10-14 years after delivery. Methods: An exploratory secondary analysis from the prospective Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS). GDM was classified as insulin-deficient, insulin-resistant, mixed-defect and unclassified compared with no GDM (reference). The primary outcome was prediabetes or type 2 diabetes, and secondarily hypertension, dyslipidemia, metabolic syndrome, and predicted cardiovascular disease risk. Modified Poisson models adjusted for pregnancy covariates. Results: Of 4,156 assessed individuals, 3.0% had insulin-deficient GDM, 8.0% had insulin-resistant, 1.4% had mixed-defect and 0.7% were unclassified. The increased risk of prediabetes and diabetes (TABLE 1) was similar in magnitude regardless of GDM subtype. Individuals with insulin-deficient, insulin-resistant, and mixed-defect GDM were at increased risk of metabolic syndrome and high predicted risk of cardiovascular disease, but not dyslipidemia or hypertension. Conclusion: Individuals across GDM subtypes had a similar risk of prediabetes or diabetes, and adverse cardiometabolic outcomes, 10-14 years after delivery. Disclosure C.P. Field: None. W. Grobman: None. J. Wu: None. A. Kuang: Stock/Shareholder; Current; Dexcom, Inc. M.B. Landon: None. D. Scholtens: None. W. Lowe: None. N. Shah: None. J. Josefson: None. S. Khan: None. K. Venkatesh: None. Funding The Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study (HAPO FUS) was conducted by the HAPO FUS Investigators and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The HAPO Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and American Diabetes Association. The data from the HAPO FUS reported here were supplied by the NIDDK Central Repository. This manuscript was prepared in collaboration with some of the investigators of the HAPO FUS and does not necessarily reflect the opinions or views of the HAPO FUS, the NIDDK Central Repository, or the NIDDK. Dr. Venkatesh was supported by the Care Innovation and Community Improvement Program at The Ohio State University. Dr Khan was supported by NHLBI grant #HL161514.

Importance:Adverse pregnancy outcomes (APOs) confer risk for maternal cardiovascular disease, but the role of APOs in cardiovascular health (CVH) of offspring across the life course is unknown. Objective:To examine associations of APO exposure with CVH and early arterial injury among offspring in young adulthood. Design, Setting, and Participants:This longitudinal cohort study used data from the Future of Families and Child Well-Being Study and Future of Families-Cardiovascular Health Among Young Adults study, conducted in 20 US cities from February 1998 to September 2000, with follow-up until September 2023. Participants were mother-child dyads enrolled at the child's birth; offspring were followed up until young adulthood (year 22). Data were analyzed from June 2024 to June 2025. Exposures:Hypertensive disorders of pregnancy (HDP), gestational diabetes (GD), and preterm birth (PTB), ascertained by pregnancy medical records. Main Outcomes and Measures:Offspring CVH assessed by the American Heart Association's Life's Essential 8 (LE8) score, individual clinical cardiovascular risk factors, and arterial injury assessed by carotid ultrasonography at year 22 after birth. Results:Among 1333 offspring participants (729 [55%] female; mean [SD] age in early adulthood, 22.4 [0.7] years), 128 (10%) had HDP exposure, 67 (5%) had GD exposure, and 137 (10%) had PTB exposure. In analyses adjusted for sociodemographic factors, HDP exposure was associated with higher body mass index (adjusted β, 2.80; 95% CI, 1.07-4.53), higher diastolic blood pressure (adjusted β, 2.29; 95% CI, 0.17-4.41), and higher glycated hemoglobin (HbA1c) level (adjusted β, 0.21; 95% CI, 0.02-0.41) in early adulthood. PTB was associated with higher HbA1c level (adjusted β, 0.29; 95% CI, 0.15-0.43). GD exposure was associated with a lower LE8 blood pressure score (adjusted β, -6.59; 95% CI, -13.95 to -0.16). HDP exposure was associated with higher mean carotid intima-media thickness (adjusted β, 0.02; 95% CI, 0.01-0.03) and lower carotid grayscale median (adjusted β, -3.68; 95% CI, -6.30 to -1.05). Exposure to GD was associated with higher mean carotid intima-media thickness (adjusted β, 0.02; 95% CI, 0.00-0.04). Conclusions and Relevance:In this longitudinal cohort study of mother-child dyads enrolled at the child's birth, exposure to APOs during gestation, particularly HDP, was associated with suboptimal CVH and arterial injury among offspring in early adulthood. The findings suggest optimizing pregnancy health may support offspring CVH into early adulthood.