Genetic Risk Factors for Opioid Use Disorder Identified

Overview: A new large-scale genome-wide study has identified 18 new genetic risk factors for opioid use disorders, bringing the number of OUD-associated genes from 1-19.

Source: Yalea

A new human genomics study led by Yale scientists has identified genetic risk factors for opioid use disorder (OUD) and related substance use disorders according to a new large-scale genome-wide association study, increasing the number of known risk genes from 1 to 19.

This work comes at a time when opioid-related overdoses have reached an all-time high in the United States and continue to rise around the world. The findings, published in Molecular Psychiatry, addressing an urgent need, as genetic discovery for OUD has been limited in recent years. Genetic discovery leads to a better understanding of biology.

Senior author Joel Gelernter, MD, Foundations Fund professor of psychiatry and professor of genetics and neuroscience at Yale, said not much is known about specific genetic factors that influence the risk of OUD.

In this study, researchers worked to advance the understanding of OUD genetics by completing a meta-analysis for OUD — that is, pooling data from many different studies — and then by genetic information from other related use disorders. of resources for more gene-finding capacity.

Researchers examined genetic data from more than 600,000 participants of European and African genetic ancestry, more information than previous studies on OLD risk variation.

The scientists identified genetic variation in 19 genes that was associated with OUD risk; OPRM1 and FURIN were two genes identified in the analysis of OUD alone, with many more genes identified in the analysis containing information from OUD, along with cannabis use disorder and alcohol use disorder.

“OPRM1 is a gene that encodes mu opioid receptors in the brain, making it an excellent genetic opportunity for OUD – previous work showed that variation in this gene influences OUD risk. Our challenge was to go beyond OPRM1”, says Gelernter.

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This work comes at a time when opioid-related overdoses have reached an all-time high in the United States and continue to rise around the world. Image is in the public domain

“Our effort produced as much genome-wide data as possible. We wanted to collect as many datasets and samples as possible,” said Joseph D. Deak, Ph.D., postdoctoral fellow in the Yale Department of Psychiatry Division of Human Genetics and lead author of the paper. .

“We believe our findings have identified genetic risk specific to OLD, as well as genetic risk that is more broadly shared with other types of substance use disorders. That is consistent with previous studies showing specific genetic effects for certain drugs, along with shared genetic liability for substance use disorders in general.”

The findings also reveal genetic links between the development of OLD and related conditions such as chronic pain, the inability to work due to illness or disability, and other psychiatric outcomes such as anxiety, depression and PTSD.

“These genetic findings are consistent with common features often seen in the clinical presentation of individuals diagnosed with OLD. We found that genetic overlap,” Deak said.

We know that there are many factors that influence the risk of substance use disorders, such as OLD. These results are not to say that someone with these specific genetic risk factors should or should not be given opioids to control pain or anything; this work does not support that conclusion, but it could help clarify some unanswered questions as we continue to expand on these findings in hopes of addressing public health concerns related to opioids.

About this news about genetics and addiction research

Author: Christopher Gardner
Source: Yalea
Contact: Christopher Gardner – Yalea
Image: The image is in the public domain

Original research: Open access.
“Genome-wide association study in individuals of European and African descent and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci” by Joseph D. Deak et al. Molecular Psychiatry


Genome-wide association study in individuals of European and African descent and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci

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Despite the high toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD have so far revealed few susceptibility loci.

We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) descent, optimizing genetic information by performing MTAG (Multi-trait analysis or GWAS) with genetically correlated substance use disorders. (SUDs).

Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU and Yale-Penn 3, resulting in a total N = 639,063 (Ncases= 20,686;Neffective= 77,026) on ancestry. OUD cases were defined as having a lifelong OUD diagnosis and controls as someone not known to meet the OUD criteria. We estimate SNP heritability (h2SNP ) and genetic correlations (rg ).

Based on genetic correlation, we performed MTAG on OLD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3.

The EUR meta-analysis identified three genome-wide significant (GWS; p 5×10−8) lead SNPs – one on FURIN (rs11372849; p= 9.54 × 10−10) and two OPRM1variants (rs1799971, p= 4.92 × 10−09; rs79704991, p= 1.11 × 10−08; r2= 0.02). Rs1799971 (p = 4.91 × 10−08) and another OPRM1variant (rs9478500; p= 1.95 × 10−08; r2= 0.03) were identified in the cross-ancestry meta-analysis. estimated h2SNPwas 12.75%, with a strong rgwith CanUD (rg= 0.82; p= 1.14 × 10−47) and AUD (rg= 0.77; p= 6.36 × 10−78).

The OUD-MTAG resulted in a GWAS Nequivalent= 128,748 and 18 independent GWS loci, some mapped to genes or gene regions previously associated with psychiatric or addiction phenotypes.

The OUD-MTAG PRS accounted for 3.81% of the OUD variance (beta = 0.61; se = 0.066; p= 2.00 × 10−16) compared to 2.41% (beta = 0.45; se = 0.058; p= 2.90 × 10−13) declared by the OLD PRS. The present study identified associations with OUD variants in OPRM1simple variant associations with FURINand 18 GWS associations in the OUD-MTAG.

The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared by SUDs.

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