Empowering Women: How a Healthy Lifestyle Lowers Cardiovascular Risk in Those Genetically Prone to Pregnancy-Related Hypertension – Nature Communications

Ethics Approval

This study followed ethical regulations for research involving people and met the standards of the Declaration of Helsinki. The UK Biobank (UKBB) study got approval from the National Research Ethics Committee on June 17, 2011, with an extension on May 10, 2016. The use of genetic data and biospecimens within the Penn Medicine Biobank (PMBB) study was approved by the University of Pennsylvania’s ethics board. Participants gave written consent for their samples and data to be used for research. All data was handled according to privacy regulations, and no extra ethical approval was needed for this analysis because we used already approved datasets. This research also complied with the STROBE guidelines for reporting observational studies.

Study Population

The UK Biobank is a comprehensive observational study that enrolled over 500,000 adults across the UK from 2006 to 2010. Participants, aged 40 to 69, provided detailed information about their demographics, lifestyle, physical measurements, and biological samples. For our study, we focused on women of European descent who had given birth at least once and had genetic data available.

The PMBB study recruited participants from outpatient settings without specific selection criteria. Individuals provided access to their electronic health records and contributed genetic data. We extracted comprehensive health information, including diagnoses and lab results, until July 2020.

Hypertensive Disorders of Pregnancy

In the UKBB, women reported their reproductive history, including details about pregnancies and conditions like gestational hypertension and preeclampsia. These were identified based on self-reported data or specific ICD codes from healthcare records. The same approach was used for identifying hypertensive disorders within the PMBB.

We assessed the risk of hypertensive disorders during pregnancy (HDP) using a polygenic risk score (PRS), taking into account factors like age at first pregnancy and existing health conditions that increase the risk for HDP, such as hypertension or diabetes. These were determined through self-reports or relevant ICD codes prior to their first live birth.

Cardiovascular Outcomes

To study the link between cardiovascular disease and HDP, we excluded individuals with congenital heart disease. We focused on newly diagnosed atherosclerotic cardiovascular disease (ASCVD), which includes conditions like heart attacks and strokes, ensuring that only participants without prior cardiovascular issues were analyzed.

Variables

Participants in the UKBB shared information about their health, demographics, and lifestyle habits through questionnaires and interviews. Factors like smoking status, obesity, physical activity, and diet were considered key components of their lifestyle. Obesity was defined as having a BMI of 30 or higher. We categorized lifestyle behaviors into three groups: unfavorable, intermediate, and favorable.

Metabolic health was assessed based on five criteria, allowing us to classify participants as ideal, intermediate, or poor in terms of metabolic health.

Genotype Data Quality Control

We ensured the quality of genetic data using standard genotyping practices and imputation methods. In the UKBB, over 800,000 SNPs were analyzed. Out of these, 164,500 female participants were deemed eligible for genetic analysis after quality control. In the PMBB, 43,623 samples were genotyped, leading to a focus on 982 parous women of European ancestry and 1,019 of African ancestry for replication analysis.

Polygenic Risk Score

The HDP-PRS was based on data from a large-scale genetic study, combining information from thousands of cases and controls. The scores were calculated using Bayesian methods to assess the genetic risk of developing hypertensive disorders.

Statistical Analysis

We analyzed demographic and health data using various statistical tests to compare groups. A multivariate logistic regression model helped us evaluate the association between HDP and HDP-PRS, adjusting for factors like age, BMI, and smoking status. We also looked at new-onset cardiovascular outcomes using Cox regression analysis.

For replication, we examined how maintaining a healthy lifestyle impacted different genetic risk groups, using the PMBB cohort for our analysis. Statistical significance was defined as a p-value of less than 0.05, with analyses conducted using R software and PLINK.

Reporting Summary

For additional details about the research design, please refer to the Nature Portfolio Reporting Summary linked to this article.