Kember, Rachel L

ABSTRACT Amidst the opioid crisis, understanding the genetic basis of opioid use disorder (OUD) is crucial for identifying biological mechanisms and intervention points. However, genome‐wide association studies (GWASs) have been hampered by inadequate sample sizes and often the use of control populations not assessed for prior opioid exposure. Because opioid exposure is a prerequisite for the development of OUD, consideration of exposure history in controls is important. Electronic health record data (EHR) paired with genomic information allow a broader sampling of patients with OUD and exposed controls. We leveraged data across two healthcare systems to evaluate the impact of using controls not screened for opioid exposure (‘generic’) versus minimally opioid‐exposed control (‘exposed’). First, at the phenotypic level, we conducted phenome‐wide association studies (PheWAS) to compare the medical comorbidity profiles of OUD cases when using generic versus exposed controls. While PheWAS results for OUD‐related comorbidities were more pronounced when using the generic group, 83% of the disease associations were overlapping and of similar effect sizes. Second, at the genetic level, we conducted GWAS (cases vs. generic; cases vs. exposed) and assessed differences in genetic correlations and degrees of phenotypic misclassification. Genetic results were concordant across control groups based on heritability (generic: 0.16 ± 0.07 vs. 0.10 ± 0.07), associations with the coding OPRM1 variant rs1799971 ( p generic = 8.83E‐03 vs. p exposed = 1.83E‐02) and genetic correlations with prior OUD GWAS ( r g‐generic = 0.83 ± 0.26 vs. r g‐exposed = 0.78 ± 0.27). Although GWASs were limited by sample size ( N generic = 6269, N exposed = 6365), compared to an independent OUD GWAS ( N = 425 944), the dilution value for the two GWAS was not different from 1, suggesting no major impact of phenotypic misclassification. This study represents the first effort to enhance OUD genetic research through optimization of control definitions using EHR data. Generic controls ascertained within the US health systems, where exposure to prescription opioids is high, offer a practical alternative for genetic studies of OUD.

Abstract Background In two 12‐week, randomized, placebo‐controlled trials (RCTs) in individuals with alcohol use disorder (AUD), topiramate significantly reduced heavy drinking days (HDDs), and alcohol‐related problems. In a secondary analysis of those findings, we examined four broad measures of genetic risk—polygenic scores (PGS)—of problematic alcohol use (PAU), drinks per week (DPW), and time to relapse to any drinking (TR) and heavy drinking (THR) as moderators of topiramate's effect on HDDs and alcohol‐related problems. Methods We analyzed data from 285 individuals with AUD (65.6% male) of European‐like ancestry, who were treated with either topiramate (49.1%) or placebo (50.9%). All patients underwent genome‐wide array genotyping, and PGS were calculated using summary statistics from genome‐wide association studies of PAU, DPW, and TR and THR (two time‐to‐event outcomes among patients treated in AUD pharmacotherapy trials). We hypothesized an interaction effect in which greater genetic risk—particularly for PAU—would be associated with a greater therapeutic response to topiramate than placebo. Results As shown previously, topiramate significantly reduced both HDDs (odds ratio [OR] = 0.50, p < 0.001) and Short Index of Problems (SIP) scores ( b = −3.04, p < 0.001) more than placebo. There were nonsignificant associations of higher PGS with more HDDs (OR = 1.17, 95% CI = 0.98–1.41, p = 0.091) and a greater reduction in HDDs in the topiramate group (OR = 0.80, 95% CI = 0.62–1.03, p = 0.089). There were also significant interaction effects with treatment on SIP score by PGS for PAU ( b = −1.64, SE = 0.78, p = 0.033), TR ( b = −2.16, SE = 0.72, p = 0.003), and TRH ( b = −2.17, SE = 0.72, p = 0.003). Conclusions These findings provide proof of principle for the use of alcohol‐related PGS as moderators of the effects of topiramate for treating AUD. Larger RCTs of topiramate are needed to provide adequate statistical power to validate this pharmacogenetic approach to precision AUD treatment.