///2014 Abstract Details
2014 Abstract Details2019-07-18T14:34:47+00:00

Role of genetic factors for BMI in susceptibility to preeclampsia

Abstract Number: T-57
Abstract Type: Original Research

Manokanth Madapu M.B.B.S.1 ; Andrew Bjonnes M.Sc.2; Jacqueline M Lane Ph.D.3; Brian T Bateman M.D.4; Brendan Keating D. Phil.5; Richa Saxena Ph.D.6

Introduction: In the United States about 28% of women aged 20-39 are obese. Obesity and increased pre-pregnancy body mass index (BMI) increase adverse pregnancy outcomes. Preeclampsia (PE) affects 6-8% of pregnancies and is a leading cause of maternal and fetal morbidity and mortality. Compared to a BMI of 21, risk of PE doubles at a BMI of 26, triples at a BMI of 30 and increases further with severe obesity. Several large genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) that are associated with BMI. In contrast, despite its strong heritable component, there are no genetic variants that have been robustly associated with PE. In an effort to shed light on the genetic basis for PE and to better understand if obesity plays a causal role in PE, we sought to define the association between PE and SNPs implicated in obesity in pregnant patients of European ancestry.

Methods: The case-control study population comprised 516 PE patients and 1,097 controls, drawn from sample collections of European ancestry from 5 U.S. academic medical centers and a population-based study. Subjects were genotyped on a cardiovascular gene-centric SNP array containing ~2,000 loci selected based on prior genetic studies and on pathways expected to be important in cardiovascular disease. SNPs from 32 independent genome-wide significant BMI loci (P<5x10-8) were identified from a recent BMI GWAS comprising ~250,000 subjects; there were 15 independent SNPs with direct genotypes or proxies with r2>0.5 in HapMap CEU contained on our SNP array. These were analyzed for association with PE. Single-SNP genetic association testing was completed using logistic regression, assuming additive effects for each risk allele present, and included 10 principal components in the model to account for population structure. To assess the combined effect of BMI genetic factors in PE, a weighted genetic risk score (GRS) was constructed and evaluated for association with PE. Statistical significance for single variants was judged as a Bonferroni-corrected P<0.003 to account for multiple testing, while significance for the BMI GRS was judged as P<0.05 based on the single hypothesis.

Results: No BMI-associated SNPs were individually associated with increased risk of PE. In total 12/15 SNPs tested demonstrated a concordant direction of effect between PE and BMI, with the BMI-raising allele contributing to increased risk of PE (binomial P=0.014). The multi-SNP weighted GRS trended towards association with increased risk for PE (OR 1.29 (0.99-1.67) p = 0.057), while an unweighted GRS showed significant association (OR 1.06 (1.01-1.11) p = 0.021).

Conclusion: In sum, our results suggest that a GRS for BMI may predispose to risk of PE, but at present it is unknown if the risk is entirely mediated through BMI. These results require validation in larger studies with pre-pregnancy BMI on cases and controls.

SOAP 2014