Genome-wide association analysis of opioid use disorder: A novel approach using clinical data

Drug Alcohol Depend. 2020 Dec 1:217:108276. doi: 10.1016/j.drugalcdep.2020.108276. Epub 2020 Sep 15.

Abstract

Background: Opioid use disorder (OUD) represents a large and pervasive global public health challenge. Previous genetic studies have demonstrated the significant heritability of OUD and identified several single-nucleotide polymorphisms (SNPs) associated with its prevalence.

Methods: In this paper, we conducted a genome-wide association analysis on opioid use disorder that leveraged genetic and clinical data contained in a biobank of 21,310 patients of European ancestry. We identified 1039 cases of opioid use disorder based on diagnostic codes from nearly 16 million encounters in electronic health records (EHRs).

Results: We discovered one novel OUD-associated locus on chromosome 4 that was significant at a genome-wide threshold (p = 2.40 × 10-8). Heritability analysis suggested that common SNPs explained 0.06 (se 0.02, p = 0.0065) of the phenotypic variation in OUD. When we restricted controls to those with previous opioid prescriptions, we were able to further strengthen the original signal and discovered another significant locus on chromosome 16. Pair-wise genetic correlation analysis yielded strong positive correlations between OUD and two other major substance use disorders, alcohol and nicotine, with the strongest correlation between nicotine and opioid use disorder (genetic correlation 0.65, se = 0.19, p = 0.00048), suggesting a significant shared genetic component across different substance disorders.

Conclusions: This pragmatic, clinically-focused approach may supplement more traditional methods to facilitate identification of new genetic underpinnings of OUD and related disorders.

Keywords: Addiction; Clinical biobank; Clinical phenotype; Electronic health record; Genome-wide association analysis; Opioid use disorder.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Data Analysis*
  • Electronic Health Records*
  • Female
  • Genome-Wide Association Study / methods*
  • Humans
  • Male
  • Middle Aged
  • Opioid-Related Disorders / diagnosis
  • Opioid-Related Disorders / epidemiology*
  • Opioid-Related Disorders / genetics*
  • Polymorphism, Single Nucleotide / genetics*