Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Feb 14;9(1):89.
doi: 10.1038/s41398-019-0384-y.

Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism

Manav Kapoor  1 , Jen-Chyong Wang  2 , Sean P Farris  3 , Yunlong Liu  4 , Jeanette McClintick  4 , Ishaan Gupta  5 , Jacquelyn L Meyers  6 , Sarah Bertelsen  2 , Michael Chao  2 , John Nurnberger  4 , Jay Tischfield  7 , Oscar Harari  8 , Li Zeran  8 , Victor Hesselbrock  9 , Lance Bauer  9 , Towfique Raj  2 , Bernice Porjesz  6 , Arpana Agrawal  8 , Tatiana Foroud  4 , Howard J Edenberg  4 , R Dayne Mayfield  3 , Alison Goate  10
Affiliations

Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism

Manav Kapoor et al. Transl Psychiatry. .

Abstract

Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank's alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence.

PubMed Disclaimer

Conflict of interest statement

A.G. and J.-C.W. are listed as inventors on Issued U.S. Patent 8080,371, “Markers for Addiction” covering the use of certain variants in determining the diagnosis, prognosis, and treatment of addiction. The other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Top genes, pathways and networks from differential gene expression in DLFPC region from 68 alcoholics and 70 controls.
a Volcano plot showing top differentially expressed genes among cases and controls. b The genes passing FDR threshold of 20% were inputted to IPA for pathway enrichment analysis. The figure shows some of the top pathways identified by IPA. P values here are from right tail Fisher’s exact test. c Enrichment analysis of gene ontology “biological process” terms. Color depicts the qvalues with red being the strongest evidence of enrichment. d Network analysis on top genes (FDR < =20%) mapped to networks involved in the neurodegenerative disorders and organismal injuries. P value under the gene is the uncorrected p value for differential expression among alcoholics and controls. The nominally significant genes in the UKBB-alc and PGC-SUD GWAS are highlighted with purple border and blue annotation
Fig. 2
Fig. 2. Trait module correlations with P values for the top 5 modules.
WGCNA identified 27 modules, out of which 5 modules showed nominal- moderate statistical significance with any of 4 alcohol-related trait (AUDIT, alcohol consumption (gms/day), duration of drinking (years), DSM4 AD (classification). Thistle2 module also passed the multiple test correction (27 modules, 4 traits; 0.05/31 = 1.6 × 10−3)
Fig. 3
Fig. 3. Enrichment analysis of genes in thistle2 module that are differentially expressed in alcoholics and controls.
a More than 50% of genes in calcium signaling pathways were found to be downregulated in the thistle2 module. b Enrichment analysis for GO:BP terms showed downregulation of genes related to response to nicotine and postsynaptic potential. c Nearly 15 genes mapped to network related to amino-acid metabolism with many genes that were involved in G-protein coupled receptor signaling, calcium signaling and opioid signaling pathway. The nominally significant genes in the UKBB-alc and PGC-SUD GWAS are marked with red boundaries (ADCY5 P = 7.07 × 10−7 in UKBB-AC, ADCY7, P = 2.2 × 10−4 in UKBB-AC), IL12B, P = 1.1 × 10−2 in PGC-AD, PIK3C2G, P = 6.8 × 10−3 in UKBB-AC, PIK3R4, P = 3.4 × 10−2 in PGC-AD, CHRNA6 in UKBB-AC P = 7.60 × 10−3, CHRNA2 in PGC-AD P = 1.4 × 10−2, MN1 in PGC-AD P = 9.1 × 10−3 and HAPLN1 in UKBB-AC P = 1.9 × 10−2)
Fig. 4
Fig. 4. Enrichment analysis of brown4 module genes that were differentially expressed (FDR* < 0.05) among alcoholics and controls.
a Pathway analysis showed significant upregulation of genes related immune signaling and metabolism. b Enrichment analysis for GO:BP terms showed enrichment of genes related to inflamatory response. c The genes in the brown4 module mapped to network involved in infectious and respiratory diseases. The genes that were nominally significant in the UKBB-Alc and PGC-SUD GWAS are highlighted with red boundaries
See this image and copyright information in PMC

References

    1. Bell CC. DSM-IV: diagnostic and statistical manual of mental disorders. JAMA. 1994;272:828–829. doi: 10.1001/jama.1994.03520100096046. - DOI
    1. Sacks JJ, Gonzales KR, Bouchery EE, Tomedi LE, Brewer RD. 2010 National and State costs of excessive alcohol consumption. Am. J. Prev. Med. 2015;49:e73–e79. doi: 10.1016/j.amepre.2015.05.031. - DOI - PubMed
    1. Contet C. Gene expression under the influence: transcriptional profiling of ethanol in thebrain. Curr. Psychopharmacol. 2012;1:301–314. doi: 10.2174/2211556011201040301. - DOI - PMC - PubMed
    1. Alfonso-Loeches S, Guerri C. Molecular and behavioral aspects of the actions of alcohol on the adult and developing brain. Crit. Rev. Clin. Lab. Sci. 2011;48:19–47. doi: 10.3109/10408363.2011.580567. - DOI - PubMed
    1. Fan L, et al. Increased expression of mitochondrial genes in human alcoholic brain revealed by differential display. Alcohol. Clin. Exp. Res. 1999;23:408–413. doi: 10.1111/j.1530-0277.1999.tb04130.x. - DOI - PubMed

Publication types

MeSH terms