Association Between Primary Dysmenorrhea and Mental Health Traits: A Study Based on Multi-Phenotype Correlation Network and Mendelian Randomization Analysis in Female College Students

原发性痛经与心理健康特征的关联:一项基于多表型相关网络和孟德尔随机化分析的女大学生研究

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Abstract

Primary dysmenorrhea (PDM) is a common cyclic menstrual pain that significantly affects the quality of life for women. Several epidemiological studies have suggested a potential association between PDM and mental health traits, including stress, depression, and anxiety. However, there is a lack of systematic investigation into whether a causal relationship exists between PDM and mental health phenotypes compared to other physical phenotypes. In this study, we conducted a large-scale phenome study on a cohort of 7401 young female Chinese college students to explore the association between PDM and various physical and mental health phenotypes. Using a multi-phenotype correlation network model, we discovered that the correlation between the PDM phenotypes and mental health phenotypes was the most dominant among the complex inter-connections across different categories of phenotypes. Furthermore, employing a two-sample Mendelian randomization analysis, we systematically elucidated the genomic-level impact of PDM on the mental health traits of young women. Specifically, we identified an increased risk of depression and anxiety associated with PDM, potentially influenced by several Single-nucleotide polymorphism (SNP) variants such as ZMIZ1, DIO1, GRIK4 and RBFOX1. This study offers valuable insights into the genetic mechanism through which dysmenorrhea impacts mental health, which contributes to a better understanding of the comprehensive management of PDM and its associated psychological challenges. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43657-024-00213-6.

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