Plasma proteins associated with plant-based diets: Results from the Atherosclerosis Risk in Communities (ARIC) study and Framingham Heart Study (FHS).

BACKGROUND & AIMS: Plant-based diets are associated with a lower risk of chronic diseases. Large-scale proteomics can identify objective biomarkers of plant-based diets, and improve our understanding of the pathways that link plant-based diets to health outcomes. This study investigated the plasma proteome of four different plant-based diets [overall plant-based diet (PDI), provegetarian diet, healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI)] in the Atherosclerosis Risk in Communities (ARIC) Study and replicated the findings in the Framingham Heart Study (FHS) Offspring cohort. METHODS: ARIC Study participants at visit 3 (1993-1995) with completed food frequency questionnaire (FFQ) data and proteomics data were divided into internal discovery (n = 7690) and replication (n = 2543) data sets. Multivariable linear regression was used to examine associations between plant-based diet indices (PDIs) and 4955 individual proteins in the discovery sample. Then, proteins that were internally replicated in the ARIC Study were tested for external replication in FHS (n = 1358). Pathway overrepresentation analysis was conducted for diet-related proteins. C-statistics were used to predict if the proteins improved prediction of plant-based diet indices beyond participant characteristics. RESULTS: In ARIC discovery, a total of 837 diet-protein associations (PDI = 233; provegetarian = 182; hPDI = 406; uPDI = 16) were observed at false discovery rate (FDR) < 0.05. Of these, 453 diet-protein associations (PDI = 132; provegetarian = 104; hPDI = 208; uPDI = 9) were internally replicated. In FHS, 167/453 diet-protein associations were available for external replication, of which 8 proteins (PDI = 1; provegetarian = 0; hPDI = 8; uPDI = 0) replicated. Complement and coagulation cascades, cell adhesion molecules, and retinol metabolism were over-represented. C-C motif chemokine 25 for PDI and 8 proteins for hPDI modestly but significantly improved the prediction of these indices individually and collectively (P value for difference in C-statistics<0.05 for all tests). CONCLUSIONS: Using large-scale proteomics, we identified potential candidate biomarkers of plant-based diets, and pathways that may partially explain the associations between plant-based diets and chronic conditions.

Physical Activity, Cardiovascular Status, Mortality, and Prediabetes in Hispanic and Non-Hispanic Adults.

Importance: Data are limited on the association of physical activity (PA) with incident cardiovascular disease (CVD) and mortality in prediabetes, especially in racial and ethnic minority groups, including Hispanic and Latino populations. Objective: To determine the association of PA with incident CVD and mortality by prediabetes status among Hispanic or Latino and non-Hispanic adults. Design, Setting, and Participants: This cohort study included data from 2 cohorts of adults with prediabetes or normoglycemia who were free of CVD at baseline visit: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from baseline examination through 2017, with median (IQR) follow-up of 7.8 (7.2-8.5) years, and the Framingham Heart Study (FHS) with non-Hispanic participants from index examination through 2019, with median (IQR) follow-up of 9.6 (8.1-10.7) years. Analyses were conducted between September 1, 2022, and January 10, 2024. Exposure: The primary exposure was baseline accelerometry-measured moderate to vigorous PA, insufficient vs sufficient to meet 2018 Physical Activity Guidelines for Americans (PAG) in both cohorts; additional accelerometer-measured exposures in HCHS/SOL were steps per day, sedentary behavior, and counts per min. Main Outcomes and Measures: The outcome was a composite of incident CVD or all-cause mortality, whichever came first. Results: This cohort study included 13 223 participants: from HCHS/SOL, there were 9456 adults (all self-identified Hispanic or Latino ethnicity; survey-adjusted mean [SD] age, 38.3 [13.9] years, unweighted counts 5673 (60.0%) female; 4882 [51.6%] with normoglycemia; 4574 [48.4%] with prediabetes), and from FHS there were 3767 adults (3623 [96.2%] non-Hispanic and 140 [3.7%] Hispanic or Latino ethnicity, with 4 [0.1%] participants missing ethnicity; mean [SD] age, 54.2 [13.6] years; 2128 (56.5%) female; 2739 [72.7%] with normoglycemia; 1028 [27.3%] with prediabetes). Not meeting PAG was associated with higher risk of the composite outcome among participants with normoglycemia (vs PAG met; hazard ratio [HR], 1.85 [95% CI, 1.12-3.06]), but not among participants with prediabetes (HR, 1.07 [95% CI, 0.72-1.58]). For HCHS/SOL, no statistically significant association was found between the composite outcome and other PA metrics, although estimated HRs tended to be higher for lower activity in the normoglycemia group but not for the prediabetes group (eg, for steps less than vs at least 7000 per day, the HR was 1.58 [95% CI, 0.85-2.93] for normoglycemia vs 1.08 [95% CI 0.67-1.74] for prediabetes). While there was also no association in HCHS/SOL between the composite outcome and sedentary behavior, results were similar in the prediabetes group (HR per 30 minutes per day of sedentary behavior, 1.05 [95% CI 0.99-1.12]) and in the normoglycemia group (HR, 1.07 [95% CI 0.98-1.16]). Conclusions and Relevance: In this cohort study of US Hispanic or Latino and non-Hispanic adults, lower moderate to vigorous PA levels were associated with CVD or mortality among participants with normoglycemia but not participants with prediabetes. Adults with prediabetes may benefit from reducing sedentary behavior and improving multiple lifestyle factors beyond improving moderate to vigorous PA alone.

Current use of estrogen-containing oral contraceptives or hormone therapy and risk of COVID-19 infection and hospitalization: a population-based cohort study.

This population-based cohort study evaluated the association between current use of oral contraceptives (OC) among women under 50 years (n=306,541), and hormone therapy (HT) among women aged 50 or older (n=323,203), and COVID-19 infection and hospitalization. Current OC/HT use was recorded monthly using prescription dispensing data. COVID-19 infections were identified March 2020-February 2021. COVID-19 infection and hospitalization were identified through diagnosis codes and laboratory tests. Weighted generalized estimating equations models estimated multivariable-adjusted odds ratios (aORs) for COVID-19 infection associated with time-varying OC/HT use. Among women with COVID-19, logistic regression models evaluated OC/HT use and COVID-19 hospitalization. Over 12 months, 11,727 (3.8%) women <50 years and 8,661 (2.7%) women ≥50 years experienced COVID-19 infections. There was no evidence of an association between OC use and infection (aOR=1.05; 95%CI: 0.97, 1.12). There was a modest association between HT use and infection (aOR=1.19; 95%CI: 1.03, 1.38). Women using OC had a 39% lower risk of hospitalization (aOR=0.61; 95%CI: 0.38, 1.00), but there was no association of HT use with hospitalization (aOR=0.89; 95%CI: 0.51, 1.53). These findings do not suggest a meaningfully greater risk of COVID-19 infection associated with OC or HT use. OC use may be associated with lower COVID-19 hospitalization risk.

A general framework for developing computable clinical phenotype algorithms.

OBJECTIVE: To present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machine learning and natural language processing methods to incorporate rich electronic health record data. MATERIALS AND METHODS: Drawing on extensive prior phenotyping experiences and insights derived from 3 algorithm development projects conducted specifically for this purpose, our team with expertise in clinical medicine, statistics, informatics, pharmacoepidemiology, and healthcare data science methods conceptualized stages of development and corresponding sets of principles, strategies, and practical guidelines for improving the algorithm development process. RESULTS: We propose 5 stages of algorithm development and corresponding principles, strategies, and guidelines: (1) assessing fitness-for-purpose, (2) creating gold standard data, (3) feature engineering, (4) model development, and (5) model evaluation. DISCUSSION AND CONCLUSION: This framework is intended to provide practical guidance and serve as a basis for future elaboration and extension.

High Throughput Plasma Proteomics and Risk of Heart Failure and Frailty in Late Life.

Importance: Heart failure (HF) and frailty frequently coexist and may share a common pathobiology, although the underlying mechanisms remain unclear. Understanding these mechanisms may provide guidance for preventing and treating both conditions. Objective: To identify shared pathways between incident HF and frailty in late life using large-scale proteomics. Design, Setting, and Participants: In this cohort study, 4877 aptamers (Somascan v4) were measured among participants in the community-based longitudinal Atherosclerosis Risk In Communities (ARIC) cohort study at visit 3 (V3; 1993-1995; n = 10 638) and at visit 5 (V5; 2011-2013; n = 3908). Analyses were externally replicated among 3189 participants in the Cardiovascular Health Study (CHS). Data analysis was conducted from February 2022 to June 2023. Exposures: Protein aptamers, measured at study V3 and V5. Main Outcomes and Measures: Outcomes assessed included incident HF hospitalization after V3 and after V5, prevalent frailty at V5, and incident frailty between V5 and visit 6 (V6; 2016-2017; n = 4131). Frailty was assessed using the Fried criteria. Analyses were adjusted for age, gender, race, field center, hypertension, diabetes, smoking status, body mass index, estimated glomerular filtration rate, prevalent coronary heart disease, prevalent atrial fibrillation, and history of myocardial infarction. Mendelian randomization (MR) analysis was performed to assess potential causal effects of candidate proteins on HF and frailty. Results: A total of 4877 protein aptamers were measured among 10 638 participants at V3 (mean [SD] age, 60 [6] years; 4886 [46%] men). Overall, 286 proteins were associated with incident HF after V3 (822 events; P < 1.0 × 10-5), 83 of which were also associated with incident after V5 (336 events; P < 1.7 × 10-4). Among HF-free participants at V5 (n = 3908; mean [SD] age, 75 [5] years; 1861 [42%] men), 48 of 83 HF-associated proteins were associated with prevalent frailty (223 cases; P < 6.0 × 10-4), 18 of which were also associated with incident frailty at V6 (152 cases; P < 1.0 × 10-3). These proteins enriched fibrosis and inflammation pathways and demonstrated stronger associations with incident HF with preserved ejection fraction (HFpEF) than HF with reduced ejection fraction. All 18 proteins were associated with both prevalent frailty and incident HF in CHS. MR identified potential causal effects of several proteins on frailty and HF. Conclusions and Relevance: In this study, the proteins associated with risk of HF and frailty enrich for pathways related to inflammation and fibrosis as well as risk of HFpEF. Several of these proteins could potentially contribute to the shared pathophysiology of frailty and HF.

Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.

Importance: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. Objective: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. Design, Setting, and Participants: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. Exposures: LDL-C, cumulative past LDL-C, FH variant status. Main Outcomes and Measures: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Results: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. Conclusions and Relevance: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.

Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). Results: One variant in the known HTN locus, KCNK3, was a top finding in the multi-ethnic analysis (p = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Center's DNA repository data. Aggregate gene-based signals included the genes AGTPBP, MYL4, PDCD4, BBS9, ERG, and IER3. Discussion: Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.