Leslie A Brick1, Lauren Micalizzi2, Valerie S Knopik3, Rohan H C Palmer4. 1. Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, Rhode Island. 2. Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, School of Public Health, Brown University, Providence, Rhode Island. 3. Department of Human Development and Family Studies, Purdue University, West Lafayette, Indiana. 4. Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, Georgia.
Abstract
OBJECTIVE: The opioid epidemic in the United States has led to unprecedented increases in morbidity and mortality, posing a serious public health crisis. Although twin and family studies, as well as genome-wide association studies (GWAS), all identify significant genetic factors contributing to opioid dependence, no studies to date have estimated marker-based heritability estimates of opioid dependence. The goal of the current study was to use a large, genetically imputed, case/control sample of 4,064 participants (after quality control and imputation) with genome-wide data to estimate the unbiased heritability tagged by single nucleotide polymorphisms (SNPs). METHOD: Study data were part of the Genome-wide Study of Heroin Dependence obtained via the Database for Genotypes and Phenotypes (dbGaP). Genomic-Relatedness-Matrix Restricted Maximum Likelihood with adjustment for minor allele frequency (MAF) and linkage disequilibrium (LD; GREML-LDMS) was used to determine the variation in opioid dependence attributable to common SNPs from imputed data. Mixed linear models were used in an exploratory GWAS to assess effects of single SNPs. RESULTS: At least 45% of the variance in opioid dependence according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, was attributable to common SNPs, after stratifying to account for differences in MAF and LD across the genome. Most of the genetic variance was tagged by SNPs in the 1%-9% MAF range and in low LD with other SNPs in the region. Two markers in LOC101927293 survived multiple-testing correction (i.e., q value < .05). CONCLUSIONS: Nearly half of the variation in opioid dependence can be attributed to common SNPs. Most of this variation is due to rare variants in low LD with other markers in the region.
OBJECTIVE: The opioid epidemic in the United States has led to unprecedented increases in morbidity and mortality, posing a serious public health crisis. Although twin and family studies, as well as genome-wide association studies (GWAS), all identify significant genetic factors contributing to opioid dependence, no studies to date have estimated marker-based heritability estimates of opioid dependence. The goal of the current study was to use a large, genetically imputed, case/control sample of 4,064 participants (after quality control and imputation) with genome-wide data to estimate the unbiased heritability tagged by single nucleotide polymorphisms (SNPs). METHOD: Study data were part of the Genome-wide Study of Heroin Dependence obtained via the Database for Genotypes and Phenotypes (dbGaP). Genomic-Relatedness-Matrix Restricted Maximum Likelihood with adjustment for minor allele frequency (MAF) and linkage disequilibrium (LD; GREML-LDMS) was used to determine the variation in opioid dependence attributable to common SNPs from imputed data. Mixed linear models were used in an exploratory GWAS to assess effects of single SNPs. RESULTS: At least 45% of the variance in opioid dependence according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, was attributable to common SNPs, after stratifying to account for differences in MAF and LD across the genome. Most of the genetic variance was tagged by SNPs in the 1%-9% MAF range and in low LD with other SNPs in the region. Two markers in LOC101927293 survived multiple-testing correction (i.e., q value < .05). CONCLUSIONS: Nearly half of the variation in opioid dependence can be attributed to common SNPs. Most of this variation is due to rare variants in low LD with other markers in the region.
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