- Ancillary Studies
- Network Map
Reducing sedentary behavior is a new strategy that may improve cardiovascular health among young women, a group recently identify as having accelerated, sex-specific cardiovascular risk development that is even higher when the woman has experienced an adverse pregnancy outcome. This project seeks to thoroughly and efficiently investigate relationships between sedentary behavior and all-day activity patterns with ideal cardiovascular health components (blood pressure, body mass index, cholesterol, and glucose) by conducting an ancillary study set within an existing longitudinal cohort of more than 4,000 young women (i.e., Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-Be Heart Health Study [nuMoM2b-HHS]). By adding gold standard sedentary behavior measurement, using emerging statistical methods in physical activity epidemiology, and adding measurement of subclinical cardiovascular mechanisms that could link sedentary behavior to cardiovascular disease outcomes, this study has high potential impact to inform novel behavioral interventions that may reduce cardiovascular risk development among young women.
Aim 1 (Full Cohort, with HHS2 visit): Determine the impact of APOs on maternal cognition 10-15 years after delivery.
Aim 2 (Sub-Cohort, CUIMC single center, N=250): Determine the impact of APOs on imaging biomarkers of maternal VCID detected on brain magnetic resonance imaging (MRI).
Exploratory Aim: Use deep pregnancy phenotyping, including maternal characteristics, biomarkers of ischemic placental disease and APOs, to predict future markers of VCID.
Aim 1: Determine whether the association between APOs and subclinical CVD is independent of early pregnancy BP.
Aim 2: Determine whether APOs are associated with subclinical CVD after accounting for post-pregnancy BP.
Aim 3: Identify proteomic pathways in early pregnancy that are associated with both APOs and subclinical CVD to uncover potential mechanisms linking APOs and CVD.
Aim 1: Evaluate the effect of allostatic load index trajectories on the relationship between self-identified race and post-pregnancy cardiovascular health.
Aim 2: Evaluate the association between DNA methylation trajectory and post-pregnancy cardiovascular health.
This analysis will help to understand factors among reproductive age women that contribute to health issues like high blood pressure and diabetes during their pregnancies. It will also aim to understand factors that increase their risk of illnesses that would require serious attention, such as intensive care admission and blood transfusion during pregnancy or birth.
To do so, we will create a valid, complete reproductive history of women in the nuMoM2b-HHS study. Using this information, we will identify markers of heart health, such as weight gain from early in their first pregnancy through 8-15 years afterwards, that affect the risk of health issues during pregnancies.
The proteomics supplement is designed to understand whether a large number of blood proteins, measured toward the end of the first trimester of pregnancy, can be helpful in the early prediction of pregnancy complications. These complications include pre-eclampsia, high blood pressure of pregnancy, pre-term birth, and small for gestational age babies. We measured more than 5000 proteins in blood samples that were collected in an earlier study of 10,000 pregnant women during their first pregnancy. The underlying goal is to identify signals early enough in the course of pregnancy to be able to prevent the occurrence of these important complications of pregnancy.
The goal of this study is to understand the relationships between the social construct of race, perceived stress during early pregnancy, and development of preeclampsia (dangerously high blood pressure during pregnancy that can be deadly or can lead to early development of heart disease). Individuals who are Black are more likely to develop preeclampsia than any other racial group and the exact reason why is not understood. The experience of being an individual who is Black in America is tied to centuries of White supremacy. The ongoing issues of systemic and personal racism in America often results in individuals who are Black experiencing greater levels of stress than any other racial group. High levels of stress are associated with developing preeclampsia and have been shown to change how our genes work by affecting a biological process called DNA methylation. We are using self-reported perceived stress and DNA methylation data collected during early pregnancy from 400 study participants to better understand differences in development of preeclampsia by race. Completing this study is an important step toward the long-term goal of reducing the high occurrence of preeclampsia among individuals who are Black.
Aim 1: To determine if cannabis use as determined by biological sampling is associated with increased odds of CV disease 2-7 years after an individual’s first pregnancy after adjustment for tobacco use.
Aim 2: To evaluate if cannabis use modifies the relationship between adverse pregnancy outcomes and CV health 2-7 years after an individual’s first pregnancy.
Aim 3: To evaluate if differences in cannabis use by race and ethnicity or socioeconomic class contribute to observed differences in CV health 2-7 years after an individual’s first pregnancy.
Aim 1. Determine if women who experienced preeclampsia in the index pregnancy have increased early markers of VCID on brain magnetic resonance imaging (MRI), compared to women with no history of adverse pregnancy outcomes.
Aim 2. Use the NIH Toolbox Cognition Battery to evaluate neurocognitive function, and correlate cognition with brain MRI findings, in women who did and did not experience preeclampsia in their index pregnancies.
It is the goal of this administrative supplement application to bring the full nuMoM2b and nuMoM2b-HHS data, including omics data not yet deposited, onto BioData Catalyst and into alignment with FAIR principles. Upon completion, the data will be located on a single platform with pipeline and analytic tool support; machine-readable with relevant clinical ontologies assigned; with user-friendly metadata and documentation; and future-ready processes for conversion of newly gathered data to AI/ML ready status. These steps will result in data ready for use in AI/ML analyses as well as traditional epidemiologic models and will enhance data accessibility to members of the research community, maximizing the potential scientific knowledge gain from the existing and future data contributed by the study.