Exploratory factor analysis of shared and specific genetic associations in depression and anxiety

Chun'e Li; Shiqiang Cheng; Yujing Chen; Yumeng Jia; Yan Wen; Huijie Zhang; Chuyu Pan; Jingxi Zhang; Zhen Zhang; Xuena Yang; Peilin Meng; Yao Yao; Feng Zhang

doi:10.1016/j.pnpbp.2023.110781

Exploratory factor analysis of shared and specific genetic associations in depression and anxiety

Prog Neuropsychopharmacol Biol Psychiatry. 2023 Aug 30:126:110781. doi: 10.1016/j.pnpbp.2023.110781. Epub 2023 May 9.

Authors

Chun'e Li¹, Shiqiang Cheng¹, Yujing Chen¹, Yumeng Jia¹, Yan Wen¹, Huijie Zhang¹, Chuyu Pan¹, Jingxi Zhang¹, Zhen Zhang¹, Xuena Yang¹, Peilin Meng¹, Yao Yao¹, Feng Zhang²

Affiliations

¹ Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, PR China.
² Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, PR China. Electronic address: fzhxjtu@mail.xjtu.edu.cn.

PMID: 37164147
DOI: 10.1016/j.pnpbp.2023.110781

Abstract

Background: Previous genetic studies of anxiety and depression were mostly based on independent phenotypes. This study aims to investigate the shared and specific genetic structure between anxiety and depression.

Method: To identify the underlying factors of Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and their combined scale (joint scale), we employed exploratory factor analysis (EFA) using the eigenvalue of parallel analysis. Subsequently, we conducted a genome-wide association study (GWAS) for these factors. In addition, we utilized LD Score Regression (LDSC) to determine the genetic correlations between the identified factors and four common mental disorders, three sleep phenotypes, and other traits that have been previously linked to anxiety and depression.

Results: The EFA uncovered two factors for the GAD-7 scale, namely nervousness and disturbance, two factors for the PHQ-9 scale, namely negative affect and sleep/appetite disturbance, and four factors for the joint scale, specifically nervousness, anhedonia, sleep/appetite disturbance, and fidget. We identified two genome-wide significant genomic loci, with overlap across GAD-7 factor 1 and joint scale factor 1: rs148579586 (P_GAD-7 = 1.365 × 10^-09, P_{Joint scale} = 1.434 × 10^-09) and rs201074060 (P_GAD-7 = 3.672 × 10^-09, P_{Joint scale} = 3.824 × 10^-09). Genetic correlations in factors ranged from 0.722 to 1.000 (all p < 1.786 × 10^-03) with 27 of 28 correlations being significantly smaller than one. The genetic correlations with external phenotypes showed small variation across the eight factors.

Conclusion: Unidimensional structures can provide more precise scores, which can aid in identifying the shared and specific genetic associations between anxiety and depression. This is a crucial step in characterizing the genetic structure of these conditions and their co-occurrence.

Keywords: Exploratory factor analysis; Generalized anxiety disorder-7; Genome-wide association analysis; Patient health questionnaire-9.

MeSH terms

Anxiety / genetics
Anxiety Disorders / genetics
Depression* / genetics
Factor Analysis, Statistical
Genome-Wide Association Study
Humans
Sleep Wake Disorders*