Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction

Kember, Rachel L.; Vickers-Smith, Rachel; Xu, Heng; Toikumo, Sylvanus; Niarchou, Maria; Zhou, Hang; Hartwell, Emily E.; Crist, Richard C.; Rentsch, Christopher T; Davis, Lea K.; Justice, Amy C.; Sanchez‐Roige, Sandra; Kampman, Kyle M.; Kranzler, Henry R.

doi:10.1038/s41593-022-01160-z

Cited by 56 publications

(71 citation statements)

References 88 publications

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“…PPP6C was recently associated with opioid addiction in EA individuals according to gene-based and eQTL analyses [46]. This finding was replicated in a GWAS on opioid use disorder conducted among MVP participants [47].…”

Section: Resultsmentioning

confidence: 82%

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Cheng

Dao

Zhou

et al. 2022

Preprint

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Smoking behaviors and alcohol use disorder (AUD), moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to comorbid smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N=318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 18 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants onSIX3, NCAM1, and nearDRD2. Functional annotation of the MTAG variants highlighted biologically important regions onZBTB20, DRD2, PPP6C, andGCKRthat contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly comorbid phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

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Section: Resultsmentioning

confidence: 82%

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Cheng

Dao

Zhou

et al. 2022

Preprint

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“…We used such an approach to demonstrate polygenic effects on the age of onset of substance-related traits and the progression from regular substance use to substance-related problems and dependence. To do this, we used summary statistics from large GWAS of AUD, 20 OUD, 21 and SMK 22 to calculate PRS in a sample of deeply phenotyped individuals either with alcohol and drug use disorders or who were screened controls. We also compared these effects by population group and by sex within population groups.…”

Section: Discussionmentioning

confidence: 99%

“…PRS were calculated for AUD, 20 OUD, 21 and SMK 22 using Polygenic Risk Scores– Continuous Shrinkage software (PRS-CS) 27 and the 1000 Genomes Project phase 3 AFR and EUR samples for estimates of linkage disequilibrium. Global shrinkage parameters were obtained from each set of summary statistics by the PRS-CS package and effective sample sizes were used to calculate the final PRS.…”

Section: Methodsmentioning

confidence: 99%

“…We used GWAS summary statistics for alcohol use disorder (AUD), 20 opioid use disorder (OUD), 21 and smoking trajectories (SMK) 22 as discovery samples for calculating PRS in the Yale-Penn sample. The three discovery samples are described in detail in Supplemental Methods.…”

Section: Discovery Samplesmentioning

confidence: 99%

“…Genotype data were filtered for individual call rates and excessive heterozygosity using PLINK v1.9 and were imputed using the Michigan Imputation Server 25 and the Haplotype Reference Consortium Panel. 26 PRS were calculated for AUD, 20 OUD, 21 and SMK 22 using Polygenic Risk Scores-Continuous Shrinkage software (PRS-CS) 27 and the 1000 Genomes Project phase 3 AFR and EUR samples for estimates of linkage disequilibrium. Global shrinkage parameters were obtained from each set of summary statistics by the PRS-CS package and effective sample sizes were used to calculate the final PRS.…”

Section: Genotyping Imputation and Polygenic Risk Scoresmentioning

confidence: 99%

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Polygenic Risk for Substance-Related Traits Predicts Substance Use Onset and Progression: Sex and Population Group Differences

Kranzler

Feinn

et al. 2022

Preprint

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Background: Charting the clinical course of substance use disorders (SUDs) to identify etiologic contributors to milestone onset and progression could inform intervention efforts. Methods: We calculated polygenic risk scores (PRS) in 5,692 European-ancestry individuals (EUR) (56.2% male) and 4,918 African-ancestry (AFR) individuals (54.9% male) using genome-wide association studies (GWAS) of alcohol use disorder (AUD), opioid use disorder (OUD), and smoking trajectory (SMK). Using Cox regression, we examined the association of polygenic risk with age of first substance use, regular use, reported problems, and dependence diagnosis and with progression from regular use to onset of problems and dependence. Results: EUR and males reported earlier onset and shorter progression times than AFR and females, respectively. Among EUR, higher AUD PRS predicted earlier onset and more rapid progression to alcohol-related milestones (p<0.0001) and although a stronger moderator of problem onset among females (p=0.0165), it was more predictive of the progression to problems among males (p=0.0054). OUD and SMK PRS in EUR also predicted earlier onset of the respective milestones (p=0.0002). Among AFR, where power is lower, AUD PRS predicted age of regular alcohol use (p=0.039) and dependence (p=0.001) and progression from regular use to diagnosis (p=0.045), while SMK PRS predicted earlier age of initiation (p=0.036). Conclusions: Genetic risk for SUDs predicts milestones and symptom progression in EUR and, to a lesser extent, among AFR. Larger, diverse discovery GWAS and target samples are needed to enhance the power of PRS to personalize interventions for individuals at genetic risk of serious substance-related outcomes.

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Predicting Heterogeneity in Patient Response to Morphine Treatment for Neonatal Opioid Withdrawal Syndrome

Smolyak

Humphries

Parikh

et al. 2023

Clin Pharma and Therapeutics

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Infants with neonatal opioid withdrawal syndrome commonly receive morphine treatment to manage their withdrawal signs. However, the effectiveness of this pharmacotherapy in managing the infants' withdrawal signs vary widely. We sought to understand how information available early in infant monitoring can anticipate this treatment response, focusing on early modified Finnegan Neonatal Abstinence Scoring System (FNASS) scores, polygenic risk for opioid dependence (polygenic risk score (PRS)), and drug exposure. Using k‐means clustering, we divided the 213 infants in our cohort into 3 groups based on their FNASS scores in the 12 hours before and after the initiation of pharmacotherapy. We found that these groups were pairwise significantly different for risk factors, including methadone exposure, and for in‐hospital outcomes, including total morphine received, length of stay, and highest FNASS score. Whereas PRS was not predictive of receipt of treatment, PRS was pairwise significantly different between a subset of the groups. Using tree‐based machine learning methods, we then constructed network graphs of the relationships among these groups, FNASS scores, PRS, drug exposures, and in‐hospital outcomes. The resulting networks also showed meaningful connection between early FNASS scores and PRS, as well as between both of those and later in‐hospital outcomes. These analyses present clinicians with the opportunity to better anticipate infant withdrawal progression and prepare accordingly, whether with expedited morphine treatment or non‐pharmacotherapeutic alternative treatments.

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Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction

Cited by 56 publications

References 88 publications

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Polygenic Risk for Substance-Related Traits Predicts Substance Use Onset and Progression: Sex and Population Group Differences

Predicting Heterogeneity in Patient Response to Morphine Treatment for Neonatal Opioid Withdrawal Syndrome

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