Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence

Shaunna L. Clark, Joseph L. McClay, Daniel E. Adkins, Gaurav Kumar, Karolina A. Aberg, Srilaxmi Nerella, Linying Xie, Ann L. Collins, James J. Crowley, Corey R. Quackenbush, Christopher E. Hilliard, Andrey A. Shabalin, Scott I. Vrieze, Roseann E. Peterson, William E. Copeland, Judy L. Silberg, Matt McGue, Hermine Maes, William G. Iacono, Patrick F. Sullivan & 2 others Elizabeth J. Costello, Edwin J. van den Oord

Research output: Contribution to journalArticle

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Abstract

Background: Previous genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies. Methods: We employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate. Results: No single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (p = 1.47 × 10−5; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10−5; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family. Conclusions: To our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD.

LanguageEnglish (US)
Pages711-718
Number of pages8
JournalAlcoholism: Clinical and Experimental Research
Volume41
Issue number4
DOIs
StatePublished - Jan 1 2017

Fingerprint

High-Throughput Nucleotide Sequencing
Alcoholism
Genes
Alcohols
Alcohol Dehydrogenase
Aldehyde Dehydrogenase
Purinergic P1 Receptors
Nucleic Acid Regulatory Sequences
Opioid Receptors
G-Protein-Coupled Receptors
Gene Library
Reward
Metabolism

Keywords

  • Alcohol Dependence
  • Aldehyde Dehydrogenase
  • Genetics
  • Next-Generation Sequencing
  • Serotonin
  • SNP

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Toxicology
  • Psychiatry and Mental health

Cite this

Clark, S. L., McClay, J. L., Adkins, D. E., Kumar, G., Aberg, K. A., Nerella, S., ... van den Oord, E. J. (2017). Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. Alcoholism: Clinical and Experimental Research, 41(4), 711-718. DOI: 10.1111/acer.13352

Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. / Clark, Shaunna L.; McClay, Joseph L.; Adkins, Daniel E.; Kumar, Gaurav; Aberg, Karolina A.; Nerella, Srilaxmi; Xie, Linying; Collins, Ann L.; Crowley, James J.; Quackenbush, Corey R.; Hilliard, Christopher E.; Shabalin, Andrey A.; Vrieze, Scott I.; Peterson, Roseann E.; Copeland, William E.; Silberg, Judy L.; McGue, Matt; Maes, Hermine; Iacono, William G.; Sullivan, Patrick F.; Costello, Elizabeth J.; van den Oord, Edwin J.

In: Alcoholism: Clinical and Experimental Research, Vol. 41, No. 4, 01.01.2017, p. 711-718.

Research output: Contribution to journalArticle

Clark, SL, McClay, JL, Adkins, DE, Kumar, G, Aberg, KA, Nerella, S, Xie, L, Collins, AL, Crowley, JJ, Quackenbush, CR, Hilliard, CE, Shabalin, AA, Vrieze, SI, Peterson, RE, Copeland, WE, Silberg, JL, McGue, M, Maes, H, Iacono, WG, Sullivan, PF, Costello, EJ & van den Oord, EJ 2017, 'Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence' Alcoholism: Clinical and Experimental Research, vol. 41, no. 4, pp. 711-718. DOI: 10.1111/acer.13352
Clark SL, McClay JL, Adkins DE, Kumar G, Aberg KA, Nerella S et al. Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. Alcoholism: Clinical and Experimental Research. 2017 Jan 1;41(4):711-718. Available from, DOI: 10.1111/acer.13352
Clark, Shaunna L. ; McClay, Joseph L. ; Adkins, Daniel E. ; Kumar, Gaurav ; Aberg, Karolina A. ; Nerella, Srilaxmi ; Xie, Linying ; Collins, Ann L. ; Crowley, James J. ; Quackenbush, Corey R. ; Hilliard, Christopher E. ; Shabalin, Andrey A. ; Vrieze, Scott I. ; Peterson, Roseann E. ; Copeland, William E. ; Silberg, Judy L. ; McGue, Matt ; Maes, Hermine ; Iacono, William G. ; Sullivan, Patrick F. ; Costello, Elizabeth J. ; van den Oord, Edwin J./ Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. In: Alcoholism: Clinical and Experimental Research. 2017 ; Vol. 41, No. 4. pp. 711-718
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