Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Circ Genom Precis Med. 2024 Feb 19;17(2):e004515. doi: 10.1161/CIRCGEN.123.004515

Sex Differences in the Association of Multi-Ethnic Genome-Wide Blood Pressure Polygenic Risk Score with Population-Level Systolic Blood Pressure Trajectories

Naman S Shetty 1, Akhil Pampana 1, Nirav Patel 1, Krishin Yerabolu 1, Gnyata Patel 2, Marguerite R Irvin 3, Pradeep Natarajan 4,5,6, Henry J Lin 7, Xiuqing Guo 7, Stephen S Rich 8, Jerome I Rotter 7, Peng Li 9, Garima Arora 1, Pankaj Arora 1,10
PMCID: PMC11021155  NIHMSID: NIHMS1965374  PMID: 38372177

Hypertension, a highly heritable trait and the primary modifiable risk factor for cardiovascular disease, affects nearly half of the US population.1, 2 Even though the prevalence of hypertension is higher in males, the age-associated increase in systolic blood pressure (SBP) is more rapid in females.3 Genetic determinants of BP may partly explain the observed sex-associated differences in the SBP trajectory. This study aimed to examine the contribution of the underlying genetic architecture to the sex-associated differences in population-level SBP trajectories in a pooled multi-ancestry US cohort.

Anonymized data publicly available on the NCBI Database of Genotypes and Phenotypes were used for this study. This study included individuals without prevalent cardiovascular disease from the Atherosclerosis Risk in Communities (ARIC) study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Multi-Ethnic Study of Atherosclerosis, Framingham Heart Study (Offspring and Gen3 cohorts), and Jackson Heart Study(JHS) who underwent whole-genome sequencing under the NHLBI TransOmics for Precision Medicine (TOPMed) program.1 The study designs have been described previously.1 Participants enrolled in both ARIC and JHS were included only as a part of ARIC. Ethical oversight was provided by the University of Alabama at Birmingham Institutional Review Board.

The sex-specific multi-ancestry SBP PRS, developed by Shetty et al. using the PRS-CS auto method, was used in this study.2 The male and female SBP-PRS included 1,115,603 and 1,115,521 variants, respectively.2 PLINK was used to calculate the SBP-PRS in the TOPMed cohorts. Based on the SBP-PRS, the cohort was stratified into low (<20th percentile), intermediate (20th-80th percentile), and high (>80th percentile) genetic risk of elevated SBP.

SBP measurements harmonized by the TOPMed BP Working Group were used in this study.4 SBP was corrected by adding 15 mmHg for individuals on antihypertensive medications.1

The non-linear relationship of SBP with age was modeled using restricted cubic splines with 3 knots. The regression models were adjusted for 1st 10 principal components of genetic ancestry, diabetes, smoking, total cholesterol, and BMI.3 The sex-associated difference in the population-level SBP trajectories was tested by comparing models with and without an interaction term(sex*cubic spline term for age) using the likelihood ratio test.3 Bootstrapping using 1000 samples was used to estimate the age and 95% confidence intervals at which the sex-specific population SBP trajectories crossed over. All analyses were conducted in the overall cohort and within each BP-PRS subgroup. R 4.0.2 (R Foundation, Vienna, Austria) was used for analyses.

Among 21,542 individuals in this study [median age: 54 (IQR: 47,64) years; 56.0% females; 35.8% non-White individuals], the non-linear association of SBP with age varied by sex (Pinteraction<0.001) and BP-PRS groups (Pinteraction:0.05). Across the entire population, younger females had lower SBP, but with advancing age, they showed a higher rate of SBP increase compared to males. The SBP in females surpassed that of males at 60.4 (95%CI: 60.3–60.6) years, after which the sex-associated differences in SBP became less pronounced. When categorized into BP-PRS groups, the trend of females exhibiting a greater age-related increase in SBP compared to males remained consistent (P<0.001 in low, intermediate, and high BP-PRS groups). As the genetic risk of SBP increased, the age at which females surpassed males in SBP gradually decreased. [low SBP-PRS:66.7 (95%CI: 66.4–67.0) years, intermediate SBP-PRS: 64.3 (95%CI: 64.1–64.6) years, high SBP-PRS: 55.8 (95%CI: 54.4–57.1) years; P<0.001] (Figure 1). In the high BP-PRS group, the sex-associated differences in population-level SBP trajectories were modest with females and males exhibiting similar SBP values in later life (Figure 1). Conversely, in the low BP-PRS group, the age-related increase in SBP was more pronounced in females than in males (Figure 1).

Figure 1:

Figure 1:

Open in a new tab

Study Design and Sex-Specific Population-Level Systolic Blood Pressure Trajectories in the Overall Population and Stratified by Systolic Blood Pressure Polygenic Risk Score. The figure on the left depicts the study design (Panel A). The figure on the right (Panel B) depicts the sex-specific population-level systolic blood pressure trajectories in the overall population and stratified by blood pressure polygenic risk score group. The non-linear relationship between age and systolic blood pressure was modeled using restricted cubic splines. Males and females have been depicted in blue and red, respectively. The dashed line represents the 95% confidence interval.

*Represents the age at which the systolic blood pressure in females surpasses the systolic blood pressure in males. The 95% confidence interval was estimated using bootstrapping. The age at which the systolic blood pressure in females surpassed that of males progressively decreased with increasing genetic risk of systolic blood pressure ( P<0.001).

P-values presented in the panel indicate the sex-associated difference in the population-level SBP trajectories and were calculated using the likelihood ratio test comparing models with and without an interaction term(sex*cubic spline term for age).

This study of >21,000 multi-ancestry individuals demonstrated that the age-related increase in SBP was higher in females compared with males across the BP-PRS groups. As the genetic risk of SBP increases, there appears to be a trend where females achieve a similar SBP level to males at a younger age. This observation suggests a gradual reduction in the age at which this convergence in SBP between females and males occurs. These findings indicate that the underlying genetic architecture may play a role in the population-level differences in SBP trajectories between sexes.

Notably, this study evaluated the sex-associated differences in the genetic risk of elevated SBP contributed by autosomes. These sex-based autosomal differences could be attributed to the variation in the transcription of mRNA by sex.5 A prior study has shown that the rate at which SBP increases is higher in females compared with males.3 This study adds to the literature by demonstrating that the genetic determinants of SBP may play a role in the sex-associated differences in population-level SBP trajectories.

Study limitations include population-level SBP trajectories instead of individual-level, potential underestimation of antihypertensive effects due to the use of the correction factor for SBP, and variability among different antihypertensive medications. Additionally, the analysis lacks data on hypertensive disorders of pregnancy and menopause status in females. Lastly, the sphygmomanometers varied across the cohorts which introduced heterogeneity in measurement. However, this study used TOPMed harmonized data that accounts for these differences.

In summary, this study demonstrated that the population-level SBP trajectories may vary by the genetic risk of SBP and sex. Further studies are required to assess sex-specific strategies for hypertension treatment and sex-specific responses to pharmacotherapy.

Sources of Funding:

Dr. Pankaj Arora is supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health (NIH) awards (R01HL160982, R01HL163852, R01HL163081, and K23HL146887). Dr. Nirav Patel is supported by the National Institutes of Health grant T32HL007457. The Multi-Ethnic Study of Atherosclerosis (MESA) projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491, and R01HL105756. The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutes can be found at http://www.mesa-nhlbi.org.

Disclosures:

Dr. Pankaj Arora reports grant support from Merck Sharp & Dohme LLC and Bristol-Myers Squibb and consulting income from Bristol-Myers Squibb, which are all unrelated to this work. Pradeep Natarajan reports grant support from Amgen, Apple, AstraZeneca, and Boston Scientific; consulting income from Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Genentech, and Novartis; and spousal employment at Vertex, which are all unrelated to the current work. None of the other authors had any conflicts of interest or financial disclosures to declare.

Nonstandard Abbreviations and Acronyms

ARIC

Atherosclerosis Risk in Communities

SBP PRS

Systolic Blood Pressure Polygenic Risk Score

JHS

Jackson Heart Study

References:

  • 1.Parcha V, Pampana A, Shetty NS, Irvin MR, Natarajan P, Lin HJ, Guo X, Rich SS, Rotter JI, Li P, Oparil S, Arora G and Arora P. Association of a Multi-Ancestry Genome-Wide Blood Pressure Polygenic Risk Score with Adverse Cardiovascular Events. Circ Genom Precis Med. 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Shetty NS, Pampana A, Patel N, Li P, Yerabolu K, Gaonkar M, Arora G and Arora P. Sex Differences in the Association of Genome-Wide Systolic Blood Pressure Polygenic Risk Score With Hypertension. Circ Genom Precis Med. 2023:e004259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Ji H, Kim A, Ebinger JE, Niiranen TJ, Claggett BL, Bairey Merz CN and Cheng S. Sex Differences in Blood Pressure Trajectories Over the Life Course. JAMA Cardiol. 2020;5:19–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Stilp AM, Emery LS, Broome JG, Buth EJ, Khan AT, Laurie CA, Wang FF, Wong Q, Chen D, D’Augustine CM, Heard-Costa NL, Hohensee CR, Johnson WC, Juarez LD, Liu J, Mutalik KM, Raffield LM, Wiggins KL, de Vries PS, Kelly TN, Kooperberg C, Natarajan P, Peloso GM, Peyser PA, Reiner AP, Arnett DK, Aslibekyan S, Barnes KC, Bielak LF, Bis JC, Cade BE, Chen MH, Correa A, Cupples LA, de Andrade M, Ellinor PT, Fornage M, Franceschini N, Gan W, Ganesh SK, Graffelman J, Grove ML, Guo X, Hawley NL, Hsu WL, Jackson RD, Jaquish CE, Johnson AD, Kardia SLR, Kelly S, Lee J, Mathias RA, McGarvey ST, Mitchell BD, Montasser ME, Morrison AC, North KE, Nouraie SM, Oelsner EC, Pankratz N, Rich SS, Rotter JI, Smith JA, Taylor KD, Vasan RS, Weeks DE, Weiss ST, Wilson CG, Yanek LR, Psaty BM, Heckbert SR and Laurie CC. A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program. Am J Epidemiol. 2021;190:1977–1992. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Ellegren H and Parsch J. The evolution of sex-biased genes and sex-biased gene expression. Nat Rev Genet. 2007;8:689–98. [DOI] [PubMed] [Google Scholar]

RESOURCES