Interactions between genetic variants and environmental risk factors are associated with the severity of pelvic organ prolapse

Menopause. 2023 Jun 1;30(6):621-628. doi: 10.1097/GME.0000000000002182. Epub 2023 Apr 11.

Abstract

Objective: Both environmental and genetic risk factors contribute to pelvic organ prolapse (POP). No genome-wide study has investigated the gene-environment (G × E) interactions. In this study, we aim to identify single nucleotide polymorphisms (SNPs) that may interact with the potential environmental factors, maximum birth weight, and age in Chinese women.

Methods: We recruited 576 women for phase 1 and 264 women for phase 2 with stages III and IV prolapse from six geographic regions of China. Genomic DNAs from blood samples were genotyped using Affymetrix Axiom Genome-Wide CHB1 Array of 640,674 SNPs for phase 1 and Illumina Infinium Asian Screening Array of 743,722 SNPs for phase 2. Meta-analysis was used to combine the two results. Interactions of genetic variants with maximum birth weight and age on POP severity were identified.

Results: In phase 1, 502,283 SNPs in 523 women passed quality control and 450 women had complete POP-quantification measurements. In phase 2, 463,351 SNPs in 257 women passed quality control with complete POP-quantification measurements. Three SNPs rs76662748 ( WDR59 , Pmeta = 2.146 × 10 -8 ), rs149541061 ( 3p26.1 , Pmeta = 9.273 × 10 -9 ), and rs34503674 ( DOCK9 , Pmeta = 1.778 × 10 -9 ) respectively interacted with maximum birth weight, and two SNPs rs74065743 ( LINC01343 , Pmeta = 4.386 × 10 -8 ) and rs322376 ( NEURL1B - DUSP1 , Pmeta = 2.263 × 10 -8 ), respectively, interacted with age. The magnitude of disease severity associated with maximum birth weight and age differed according to genetic variants.

Conclusions: This study provided preliminary evidence that interactions between genetic variants and environmental risk factors are associated with POP severity, suggesting the potential use of combining epidemiologic exposure data with selected genotyping for risk assessment and patient stratification.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Birth Weight
  • China
  • Female
  • Genotype
  • Humans
  • Pelvic Organ Prolapse* / epidemiology
  • Pelvic Organ Prolapse* / genetics
  • Risk Factors