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Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders

  • Dora Koller*
  • , Eleni Friligkou
  • , Brendan Stiltner
  • , Gita A. Pathak
  • , Solveig Løkhammer
  • , Daniel F. Levey
  • , Hang Zhou
  • , Alexander S. Hatoum
  • , Joseph D. Deak
  • , Rachel L. Kember
  • , Jorien L. Treur
  • , Henry R. Kranzler
  • , Emma C. Johnson
  • , Murray B. Stein
  • , Joel Gelernter
  • , Renato Polimanti*
  • *Corresponding author for this work
  • Yale University
  • Department of Veterans Affairs
  • University of Barcelona
  • University of Bergen
  • Washington University St. Louis
  • University of Pennsylvania
  • VA Medical Center
  • University of California at San Diego

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Individuals suffering from chronic pain develop substance use disorders (SUDs) more often than others. Understanding the shared genetic influences underlying the comorbidity between chronic pain and SUDs will lead to a greater understanding of their biology. Genome-wide association statistics were obtained from the UK Biobank for multisite chronic pain (MCP, Neffective = 387,649) and from the Million Veteran Program and the Psychiatric Genomics Consortium meta-analyses for alcohol use disorder (AUD, Neffective = 296,974), cannabis use disorder (CanUD, Neffective = 161,053), opioid use disorder (OUD, Neffective = 57,120), and problematic tobacco use (PTU, Neffective = 270,120). SNP-based heritability was estimated for each of the traits and genetic correlation (rg) analyses were performed to assess MCP-SUD pleiotropy. Bidirectional Mendelian Randomization analyses evaluated possible causal relationships. Finally, to identify and characterize individual loci, we performed a genome-wide pleiotropy analysis and a brain-wide analysis using imaging phenotypes available from the UK Biobank. MCP was positively genetically correlated with AUD (rg = 0.26, p = 7.55 × 10−18), CanUD (rg = 0.37, p = 8.21 × 10−37), OUD (rg = 0.20, p = 1.50 × 10−3), and PTU (rg = 0.29, p = 8.53 × 10−12). Although the MR analyses supported bi-directional relationships, MCP had larger effects on AUD (pain-exposure: beta = 0.18, p = 8.21 × 10−4; pain-outcome: beta = 0.07, p = 0.018), CanUD (pain-exposure: beta = 0.58, p = 2.70 × 10−6; pain-outcome: beta = 0.05, p = 0.014) and PTU (pain-exposure: beta = 0.43, p = 4.16 × 10−8; pain-outcome: beta = 0.09, p = 3.05 × 10−6) than the reverse. The genome-wide analysis identified two SNPs pleiotropic between MCP and all SUD investigated: IHO1 rs7652746 (ppleiotropy = 2.69 × 10−8), and CADM2 rs1248857 (ppleiotropy = 1.98 × 10−5). In the brain-wide analysis, rs7652746 was associated with multiple cerebellum and amygdala imaging phenotypes. When analyzing MCP pleiotropy with each SUD separately, we found 25, 22, and 4 pleiotropic variants for AUD, CanUD, and OUD, respectively. To our knowledge, this is the first large-scale study to provide evidence of potential causal relationships and shared genetic mechanisms underlying MCP-SUD comorbidity.
Original languageEnglish
Pages (from-to)2021-2030
Number of pages10
JournalMolecular psychiatry
Volume29
Issue number7
Early online date2024
DOIs
Publication statusPublished - Jul 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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