Citations

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 Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a life-time risk of 1 in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry GWAS in ALS including 29,612 ALS patients and 122,656 controls which identified 15 risk loci in ALS. When combined with 8,953 whole-genome sequenced individuals (6,538 ALS patients, 2,415 controls) and the largest cortex-derived eQTL dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, repeat expansions or regulatory effects. ALS associated risk loci were shared with multiple traits within the neurodegenerative spectrum, but with distinct enrichment patterns across brain regions and cell-types. Of the environmental and life-style risk factors obtained from literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. All ALS associated signals combined reveal a role for perturbations in vesicle mediated transport and autophagy, and provide evidence for cell-autonomous disease initiation in glutamatergic neurons.