Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

Yanghui Chen; Yang Sun; Linlin Wang; Ke Xu; Dao Wen Wang

doi:10.1016/j.bja.2023.11.007

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

Br J Anaesth. 2024 Feb;132(2):372-382. doi: 10.1016/j.bja.2023.11.007. Epub 2023 Dec 15.

Authors

Yanghui Chen¹, Yang Sun¹, Linlin Wang¹, Ke Xu¹, Dao Wen Wang²

Affiliations

¹ Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR of China.
² Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR of China. Electronic address: dwwang@tjh.tjmu.edu.cn.

PMID: 38104003
DOI: 10.1016/j.bja.2023.11.007

Abstract

Background: Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

Methods: Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

Results: Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

Conclusions: We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

Keywords: Mendelian randomisation; biomarker; chronic pain; genetics; multisite chronic pain; therapeutic target.

MeSH terms

Apoferritins / genetics
Biological Specimen Banks
Biomarkers
Chronic Pain* / genetics
Diabetes Mellitus, Type 2*
Humans
Mendelian Randomization Analysis
Myocardial Infarction* / genetics
Polymorphism, Single Nucleotide
Risk Factors
UK Biobank

Substances

Apoferritins
Biomarkers