ArticleJournal of studies on alcohol and drugs2019
Characterization of DSM-IV Opioid Dependence Among Individuals of European Ancestry.
Article in Journal of studies on alcohol and drugs, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- The diet and benign paroxysmal positional vertigo (DaBC) study: protocol and baseline characteristics of a prospective cohort investigating dietary patterns and BPPV prognosis-the role of genetics and gut microbiota.Frontiers in nutrition · 2025Article
- Fentanyl-induced acute and conditioned behaviors in two inbred mouse lines: Potential role for Glyoxalase.Physiology & behavior · 2022Article
- Genomic and Personalized Medicine Approaches for Substance Use Disorders (SUDs) Looking at Genome-Wide Association Studies.Biomedicines · 2021Review
- Agreement between DSM-5 and DSM-IV measures of substance use disorders in a sample of adult substance users.Drug and alcohol dependence · 2021Article
- Genetic Vulnerability to Opioid Addiction.Cold Spring Harbor perspectives in medicine · 2021Review
- Multi-omic and multi-species meta-analyses of nicotine consumption.Translational psychiatry · 2021Article
- Genetic variation regulates opioid-induced respiratory depression in mice.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveThe 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).
methodStudy 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.
resultsAt 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).
conclusionsNearly 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.
Indexed as
Identifiers
31250797PMC6614928W2954701322What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.