Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence

Abstract

Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P ¼ 2 Â 10 À 8 and OR (95% CI) ¼ 0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.

A Review of Genome-Wide Association Studies of Stimulant and Opioid Use Disorders

“…Li et al [35] took an alternative approach relative to the aforementioned studies that focused on SNP associations. Rather than focusing on SNPs, Li et al [35] used genome-wide SNP data from genotyping microarrays to identify CNVs and investigated their association with OUD.…”

“…Rather than focusing on SNPs, Li et al [35] used genome-wide SNP data from genotyping microarrays to identify CNVs and investigated their association with OUD. CNVs or other types of structural variation in the genome might explain some of the heritability for complex trait risk [36].…”

“…The study by Li et al [35] included 5,152 subjects with genome-wide SNP array data (this sample overlaps partly with the sample used in the opioid study by Gelernter et al [29]). To identify CNVs, Li et al [35] used the raw intensity of GWAS array probes and the union of two CNV calling strategies, PennCNV [37] and QuantiSNP [38], and a third calling program, GNOSIS [39], was used to confirm CNVs identified by the first two programs. This approach ensured that there was a low false-positive discovery rate in the pool of CNVs that were used for association testing.…”

“…This approach ensured that there was a low false-positive discovery rate in the pool of CNVs that were used for association testing. Li et al [35] first observed that in EA and AA samples, OUD cases had fewer CNVs than the controls. In a genome-wide case versus control association analysis of common CNVs (frequency >1%), the most robust statistical support was for an intergenic region on 18q12.3.…”

“…Several additional regions of interest were identified in an analysis that focused on rare CNVs. Some of the CNVs of interest could potentially affect protein-coding genes that were previously reported to be associated with SUD, such as MAP3K4 with nicotine dependence [43], although as noted by Li et al [35], most CNVs mapped to regions not previously implicated in OUD or SUD risk, and their functions are unknown. This important line of research requires more attention.…”