Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior

Molecular Psychiatry volume 26, pages 5040–5052 (2021)Cite this article

Subjects

Abstract

Aberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3–7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12–30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3–5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p < 2 × 10-9). Converging data provide support for the role of genetic variants on chromosome 18q23 in regulating neural connectivity and alcohol use behavior, potentially via dysregulated myelination. While findings were less robust, genome-wide associations were also observed with rs151174000 and parieto-frontal low theta coherence, rs14429078 and parieto-occipital interhemispheric high theta coherence, and rs116445911 with centro-parietal low theta coherence. These novel genetic findings highlight the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Manhattan plot displaying genome-wide meta-analysis association results for interhemispheric low theta coherence (P3-O1–P4-O2).
Fig. 2: Increased posterior corpus callosum volume was observed among a subset of COGA’s rs12954372 A-allele carriers.

Similar content being viewed by others

References

  1. Filbey FM. The American Journal of Drug and Alcohol Abuse An introduction to “The addiction connectome: brain connectivity in drug and alcohol addiction”. Am J Drug Alcohol Abus. 2013;39:341–2.

    Google Scholar 

  2. Uhlhaas PJ, Singer W. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron. 2006;52:155–68.

    CAS  PubMed  Google Scholar 

  3. Nunez PL, Srinivasan R, Westdorp AF, Wijesinghe RS, Tucker DM, Silberstein RB, et al. EEG coherency: I: statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. Electroencephalogr Clin Neurophysiol. 1997;103:499–515.

    CAS  PubMed  Google Scholar 

  4. Srinivasan R, Winter WR, Ding J, Nunez PL. EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics. J Neurosci Methods. 2007;166:41–52.

    PubMed  PubMed Central  Google Scholar 

  5. Chorlian DB, Tang Y, Rangaswamy M, O’Connor S, Rohrbaugh J, Taylor R, et al. Heritability of EEG coherence in a large sib-pair population. Biol Psychol. 2007;75:260–6.

    PubMed  PubMed Central  Google Scholar 

  6. Porjesz B, Rangaswamy M, Kamarajan C, Jones KA, Padmanabhapillai A, Begleiter H. The utility of neurophysiological markers in the study of alcoholism. Clin Neurophysiol. 2005;116:993–1018.

    PubMed  Google Scholar 

  7. Meyers JL, Zhang J, Wang JC, Su J, Kuo SI, Kapoor M, et al. An endophenotype approach to the genetics of alcohol dependence: a genome wide association study of fast beta EEG in families of African ancestry. Mol Psychiatry. 2017. https://doi.org/10.1038/mp.2016.239.

  8. Porjesz B, Rangaswamy M. Neurophysiological endophenotypes, CNS disinhibition, and risk for alcohol dependence and related disorders. Sci World J. 2007;7:131–41.

    Google Scholar 

  9. Rangaswamy M, Porjesz B. Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: a review of human brain oscillations as effective endophenotypes. Brain Res. 2008;1235:153–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Edenberg HJ, Dick DM, Xuei X, Tian H, Almasy L, Bauer LO, et al. Variations in GABRA2, encoding the α2 subunit of the GABAA receptor, are associated with alcohol dependence and with brain oscillations. Am J Hum Genet. 2004;74:705–14.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Malone SM, McGue M, Iacono WG. What can time-frequency and phase coherence measures tell us about the genetic basis of P3 amplitude? Int J Psychophysiol. 2017;115:40–56.

    PubMed  Google Scholar 

  12. Iacono WG, Malone SM, Vaidyanathan U, Vrieze SI. Genome-wide scans of genetic variants for psychophysiological endophenotypes: a methodological overview. Psychophysiology. 2014;51:1207–24.

    PubMed  PubMed Central  Google Scholar 

  13. Vrieze SI, Malone SM, Pankratz N, Vaidyanathan U, Miller MB, Kang HM, et al. Genetic associations of nonsynonymous exonic variants with psychophysiological endophenotypes. Psychophysiology. 2014;51:1300–8.

    PubMed  PubMed Central  Google Scholar 

  14. Kang SJ, Rangaswamy M, Manz N, Wang J-C, Wetherill L, Hinrichs T, et al. Family-based genome-wide association study of frontal θ oscillations identifies potassium channel gene KCNJ6. Genes Brain Behav. 2012;11:712–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Smit DJA, Wright MJ, Meyers JL, Martin NG, Ho YYW, Malone SM, et al. Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity. Hum Brain Mapp. 2018;39:4183–95.

    PubMed  PubMed Central  Google Scholar 

  16. Porjesz B, Almasy L, Edenberg HJ, Wang K, Chorlian DB, Foroud T, et al. Linkage disequilibrium between the beta frequency of the human EEG and a GABAA receptor gene locus. Proc Natl Acad Sci USA. 2002;99:3729–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Whedon M, Perry NB, Calkins SD, Bell MA. Changes in frontal EEG coherence across infancy predict cognitive abilities at age 3: The mediating role of attentional control. Dev Psychol. 2016;52:1341–52.

    PubMed  PubMed Central  Google Scholar 

  18. Segalowitz SJ, Santesso DL, Jetha MK. Electrophysiological changes during adolescence: a review. Brain Cogn. 2010;72:86–100.

    PubMed  Google Scholar 

  19. Chorlian DB, Rangaswamy M, Porjesz B. EEG coherence: topography and frequency structure. Exp Brain Res. 2009;198:59–83.

    PubMed  Google Scholar 

  20. Duffy FH, Mcanulty GB, Albert MS. Effects of age upon interhemispheric EEG coherence in normal adults. Neurobiol Aging. 1996;17:587–99.

    CAS  PubMed  Google Scholar 

  21. Rangaswamy M, Porjesz B. Understanding alcohol use disorders with neuroelectrophysiology. Handb Clin Neurol. 2014;125:383–414.

    PubMed  PubMed Central  Google Scholar 

  22. Cardenas VA, Price M, Fein G. EEG coherence related to fMRI resting state synchrony in long-term abstinent alcoholics. NeuroImage Clin. 2018;17:481–90.

    PubMed  Google Scholar 

  23. Fein G, Di Sclafani V, Cardenas VA, Goldmann H, Tolou-Shams M, Meyerhoff DJ. Cortical gray matter loss in treatment-naïve alcohol dependent individuals. Alcohol Clin Exp Res. 2002;26:558–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Jernigan TL, Butters N, DiTraglia G, Schafer K, Smith T, Irwin M, et al. Reduced cerebral grey matter observed in alcoholics using magnetic resonance imaging. Alcohol Clin Exp Res. 1991;15:418–27.

    CAS  PubMed  Google Scholar 

  25. Hommer DW, Momenan R, Kaiser E, Rawlings RR. Evidence for a gender-related effect of alcoholism on brain volumes. Am J Psychiatry. 2001;158:198–204.

    CAS  PubMed  Google Scholar 

  26. Pfefferbaum A, Lim KO, Zipursky RB, Mathalon DH, Rosenbloom MJ, Lane B, et al. Brain gray and white matter volume loss accelerates with aging in chronic alcoholics: a quantitative MRI study. Alcohol Clin Exp Res. 1992;16:1078–89.

    CAS  PubMed  Google Scholar 

  27. Pfefferbaum A, Lim KO, Desmond JE, Sullivan EV. Thinning of the corpus callosum in older alcoholic men: a magnetic resonance imaging study. Alcohol Clin Exp Res. 1996;20:752–7.

    CAS  PubMed  Google Scholar 

  28. Pfefferbaum A, Sullivan EV. Microstructural but not macrostructural disruption of white matter in women with chronic alcoholism. Neuroimage. 2002;15:708–18.

    PubMed  Google Scholar 

  29. Pitel A-L, Chanraud S, Sullivan EV, Pfefferbaum A. Callosal microstructural abnormalities in Alzheimer’s disease and alcoholism: same phenotype, different mechanisms. Psychiatry Res Neuroimaging. 2010;184:49–56.

    Google Scholar 

  30. Clarke T-K, Adams MJ, Davies G, Howard DM, Hall LS, Padmanabhan S, et al. Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N = 112 117). Mol Psychiatry. 2017;22:1376–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Walters RK, Polimanti R, Johnson EC, McClintick JN, Adams MJ, Adkins AE, et al. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci. 2018;21:1656–69.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Chorlian DB, Rangaswamy M, Manz N, Meyers JL, Kang SJ, Kamarajan C, et al. Genetic correlates of the development of theta event related oscillations in adolescents and young adults. Int J Psychophysiol. 2017;115:24–39.

    PubMed  Google Scholar 

  33. Bucholz KK, Cadoret R, Cloninger CR, Dinwiddie SH, Hesselbrock VM, Nurnberger JI, et al. A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol. 1994;55:149–58.

    CAS  PubMed  Google Scholar 

  34. Travis F. Temporal and spatial characteristics of meditation EEG. Psychol Trauma Theory, Res Pract Policy. 2019. https://doi.org/10.1037/tra0000488.

  35. Ahnaou A, Huysmans H, Jacobs T, Drinkenburg WHIM. Cortical EEG oscillations and network connectivity as efficacy indices for assessing drugs with cognition enhancing potential. Neuropharmacology. 2014;86:362–77.

    CAS  PubMed  Google Scholar 

  36. Passynkova N, Neubauer H, Scheich H. Spatial organization of EEG coherence during listening to consonant and dissonant chords. Neurosci Lett. 2007;412:6–11.

    CAS  PubMed  Google Scholar 

  37. Cook IA, O’Hara R, Uijtdehaage SH, Mandelkern M, Leuchter AF. Assessing the accuracy of topographic EEG mapping for determining local brain function. Electroencephalogr Clin Neurophysiol. 1998;107:408–14.

    CAS  PubMed  Google Scholar 

  38. Wang J-C, Foroud T, Hinrichs AL, Le NXH, Bertelsen S, Budde JP, et al. A genome-wide association study of alcohol-dependence symptom counts in extended pedigrees identifies C15orf53. Mol Psychiatry. 2013;18:1218–24.

    CAS  PubMed  Google Scholar 

  39. Baurley JW, Edlund CK, Pardamean CI, Conti DV, Bergen AW. Smokescreen: a targeted genotyping array for addiction research. BMC Genomics. 2016;17:145.

    PubMed  PubMed Central  Google Scholar 

  40. Delaneau O, Howie B, Cox AJ, Zagury J-F, Marchini J. Haplotype estimation using sequencing reads. Am J Hum Genet. 2013;93:687–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Wetherill L, Agrawal A, Kapoor M, Bertelsen S, Bierut LJ, Brooks A, et al. Association of substance dependence phenotypes in the COGA sample. Addict Biol. 2015;20:617–27.

    CAS  PubMed  Google Scholar 

  43. Turley P, Walters RK, Maghzian O, Okbay A, Lee JJ, Fontana MA, et al. Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat Genet. 2018;50:229–37.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190–1.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015;11:e1004219.

    PubMed  PubMed Central  Google Scholar 

  48. Carithers LJ, Moore HM. The Genotype-Tissue Expression (GTEx) project. Biopreserv Biobank. 2015. https://doi.org/10.1038/ng.2653.

  49. Martin JS, Xu Z, Reiner AP, Mohlke KL, Sullivan P, Ren B, et al. HUGIn: Hi-C unifying genomic interrogator. Bioinformatics. 2017;33:3793–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Schmitt AD, Hu M, Jung I, Xu Z, Qiu Y, Tan CL, et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 2016;17:2042–59.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Pandey AK, Ardekani BA, Kamarajan C, Zhang J, Chorlian DB, Byrne KN-H, et al. Lower prefrontal and hippocampal volume and diffusion tensor imaging differences reflect structural and functional abnormalities in abstinent individuals with alcohol use disorder. Alcohol Clin Exp Res. 2018. https://doi.org/10.1111/acer.13854. 17 August 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Wang Z. Direct assessment of multiple testing correction in case-control association studies with related individuals. Genet Epidemiol. 2011;35:70–9.

    PubMed  Google Scholar 

  53. Fanous AH, Zhou B, Aggen SH, Bergen SE, Amdur RL, Duan J, et al. Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms. Am J Psychiatry. 2012;169:1309–17.

    PubMed  PubMed Central  Google Scholar 

  54. Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533:539–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Vorstman JAS, Parr JR, Moreno-De-Luca D, Anney RJL, Nurnberger JI Jr, Hallmayer JF. Autism genetics: opportunities and challenges for clinical translation. Nat Rev Genet. 2017;18:362–76.

    CAS  PubMed  Google Scholar 

  56. Farris SP, Arasappan D, Hunicke-Smith S, Harris RA, Mayfield RD. Transcriptome organization for chronic alcohol abuse in human brain. Mol Psychiatry. 2015;20:1438–47.

    CAS  PubMed  Google Scholar 

  57. Zuo L, Tan Y, Wang Z, Wang K-S, Zhang X, Chen X, et al. Long noncoding RNAs in psychiatric disorders. Psychiatr Genet. 2016;26:109–16.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Sartor GC, St. Laurent G, Wahlestedt C. The emerging role of non-coding RNAs in drug addiction. Front Genet. 2012;3.

  59. Spadaro PA, Flavell CR, Widagdo J, Ratnu VS, Troup M, Ragan C, et al. Long noncoding RNA-directed epigenetic regulation of gene expression is associated with anxiety-like behavior in mice. Biol Psychiatry. 2015;78:848–59.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Chen J, Bacanu S-A, Yu H, Zhao Z, Jia P, Kendler KS, et al. Genetic relationship between schizophrenia and nicotine dependence. Sci Rep. 2016;6:25671.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Warrington NM, Shevroja E, Hemani G, Hysi PG, Jiang Y, Auton A, et al. Genome-wide association study identifies nine novel loci for 2D:4D finger ratio, a putative retrospective biomarker of testosterone exposure in utero. Hum Mol Genet. 2018;27:2025–38.

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Chen H, Sun J, Jiang H, Wang X, Wu L, Wu W, et al. Inferring alcoholism SNPs and regulatory chemical compounds based on ensemble bayesian network. Comb Chem High Throughput Screen. 2017;20:107–15.

    CAS  PubMed  Google Scholar 

  63. Eeles R, Goh C, Castro E, Bancroft E, Guy M, Olama AAAl, et al. The genetic epidemiology of prostate cancer and its clinical implications. Nat Rev Urol. 2014;11:18–31.

    CAS  PubMed  Google Scholar 

  64. Pottier C, Zhou X, Perkerson RB, Baker M, Jenkins GD, Serie DJ, et al. Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study. Lancet Neurol. 2018;17:548–58.

    PubMed  PubMed Central  Google Scholar 

  65. Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47:979–86.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Kanai M, Akiyama M, Takahashi A, Matoba N, Momozawa Y, Ikeda M, et al. Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. Nat Genet. 2018;50:390–400.

    CAS  PubMed  Google Scholar 

  67. Poggi G, Boretius S, Möbius W, Moschny N, Baudewig J, Ruhwedel T, et al. Cortical network dysfunction caused by a subtle defect of myelination. Glia. 2016;64:2025–40.

    PubMed  PubMed Central  Google Scholar 

  68. Li Z, Chen J, Yu H, He L, Xu Y, Zhang D, et al. Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia. Nat Genet. 2017;49:1576–83.

    CAS  PubMed  Google Scholar 

  69. Kam JWY, Bolbecker AR, O’Donnell BF, Hetrick WP, Brenner CA. Resting state EEG power and coherence abnormalities in bipolar disorder and schizophrenia. J Psychiatr Res. 2013;47:1893–901.

    PubMed  PubMed Central  Google Scholar 

  70. Peterson RE, Kuchenbaecker K, Walters RK, Chen C-Y, Popejoy AB, Periyasamy S, et al. Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. Cell. 2019;179:589–603.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Khramtsova EA, Davis LK, Stranger BE. The role of sex in the genomics of human complex traits. Nat Rev Genet. 2019;20:173–90.

    CAS  PubMed  Google Scholar 

  72. Meyers JL, Chorlian DB, Johnson EC, Pandey AK, Kamarajan C, Salvatore JE, et al. Association of polygenic liability for alcohol dependence and EEG connectivity in adolescence and young adulthood. Brain Sci. 2019;9:280.

    PubMed Central  Google Scholar 

  73. Cousminer DL, Stergiakouli E, Berry DJ, Ang W, Groen-Blokhuis MM, Körner A, et al. Genome-wide association study of sexual maturation in males and females highlights a role for body mass and menarche loci in male puberty. Hum Mol Genet. 2014;23:4452–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  74. CONVERGE consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature. 2015;523:588–91.

    PubMed Central  Google Scholar 

  75. Barry RJ, Clarke AR, McCarthy R, Selikowitz M, Johnstone SJ, Hsu C-I, et al. Age and gender effects in EEG coherence: II. Boys with attention deficit/hyperactivity disorder. Clin Neurophysiol. 2005;116:977–84.

    PubMed  Google Scholar 

  76. Barry RJ, Clarke AR, McCarthy R, Selikowitz M. Age and gender effects in EEG coherence: III. Girls with attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2006;117:243–51.

    PubMed  Google Scholar 

  77. Marosi E, Harmony T, Becker J, Bernal J, Reyes A, Rodriguez M, et al. Sex differences in EEG coherence in normal children. Int J Neurosci. 1993;72:115–21.

    CAS  PubMed  Google Scholar 

  78. Costin BN, Miles MF. Molecular and neurologic responses to chronic alcohol use. Handb Clin Neurol. 2014;125:157–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Pfefferbaum A, Adalsteinsson E, Sullivan EV. Supratentorial profile of white matter microstructural integrity in recovering alcoholic men and women. Biol Psychiatry. 2006;59:364–72.

    PubMed  Google Scholar 

  80. McQueeny T, Schweinsburg BC, Schweinsburg AD, Jacobus J, Bava S, Frank LR, et al. Altered white matter integrity in adolescent binge drinkers. Alcohol Clin Exp Res. 2009;33:1278–85.

    PubMed  PubMed Central  Google Scholar 

  81. Tozakidou M, Stippich C, Fischmann A. Teaching neuroimages: radiologic findings in Marchiafava-Bignami disease. Neurology. 2011;77:e67.

    PubMed  Google Scholar 

  82. Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, Toga AW. Mapping cortical change across the human life span. Nat Neurosci. 2003;6:309–15.

    CAS  PubMed  Google Scholar 

  83. Sowell ER, Delis D, Stiles J, Jernigan TL. Improved memory functioning and frontal lobe maturation between childhood and adolescence: a structural MRI study. J Int Neuropsychol Soc. 2001;7:312–22.

    CAS  PubMed  Google Scholar 

  84. Sowell ER, Thompson PM, Toga AW. Mapping changes in the human cortex throughout the span of life. Neurosci. 2004;10:372–92.

    Google Scholar 

  85. Alfonso-Loeches S, Pascual M, Guerri C. Gender differences in alcohol-induced neurotoxicity and brain damage. Toxicology. 2013;311:27–34.

    CAS  PubMed  Google Scholar 

  86. Welch KA, Carson A, Lawrie SM. Brain structure in adolescents and young adults with alcohol problems: systematic review of imaging studies. Alcohol Alcohol. 2013;48:433–44.

    CAS  PubMed  Google Scholar 

  87. Liu M, Jiang Y, Wedow R, Li Y, Brazel DM, Chen F, et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet. 2019;51:237–44.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Sokhadze TM, Cannon RL, Trudeau DL. EEG biofeedback as a treatment for substance use disorders: review, rating of efficacy, and recommendations for further research. Appl Psychophysiol Biofeedback. 2008;33:1–28.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This research is supported by U10AA008401 (BP), K01DA037914 (JLM), K01AA024152 (JES), K02DA32573 (AA), and K02AA018755 (DMD). The Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators B. Porjesz, V. Hesselbrock, T. Foroud; Scientific Director, A. Agrawal; Translational Director, D. Dick, includes eleven different centers: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, T. Foroud, J. Nurnberger Jr., Y. Liu); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz, J. Meyers, C. Kamarajan, A. Pandey); Washington University in St. Louis (L. Bierut, J. Rice, K. Bucholz, A. Agrawal); University of California at San Diego (M. Schuckit); Rutgers University (J. Tischfield, A. Brooks, R. Hart); The Children’s Hospital of Philadelphia, University of Pennsylvania (L. Almasy); Virginia Commonwealth University (D. Dick, J. Salvatore); Icahn School of Medicine at Mount Sinai (A. Goate, M. Kapoor, P. Slesinger); and Howard University (D. Scott). Other COGA collaborators include: L. Bauer (University of Connecticut); L. Wetherill, X. Xuei, D. Lai, S. O’Connor, M. Plawecki, S. Lourens (Indiana University); L. Acion (University of Iowa); G. Chan (University of Iowa; University of Connecticut); D.B. Chorlian, J. Zhang, S. Kinreich, G. Pandey (SUNY Downstate); M. Chao (Icahn School of Medicine at Mount Sinai); A. Anokhin, V. McCutcheon, S. Saccone (Washington University); F. Aliev, P. Barr (Virginia Commonwealth University); H. Chin and A. Parsian are the NIAAA Staff Collaborators.We continue to be inspired by our memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, P. Michael Conneally, Raymond Crowe, and Wendy Reich, for their critical contributions. We also thank Tim Bernard Bigdeli for his assistance with this manuscript. This national collaborative study is supported by NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA).

Author information

Authors and Affiliations

  1. Department of Psychiatry and the Henri Begleiter Neurodynamics Laboratory, State University of New York Downstate Medical Center, Brooklyn, NY, 11203, USA

    Jacquelyn L. Meyers, Jian Zhang, David B. Chorlian, Ashwini K. Pandey, Chella Kamarajan, Sivan Kinreich & Bernice Porjesz

  2. Departments of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA

    Jen-Chyong Wang, Michael Chao, Manav Kapoor, Sarah Bertelsen & Alison Goate

  3. Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA

    Jen-Chyong Wang, Manav Kapoor, Sarah Bertelsen & Alison Goate

  4. Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA

    Leah Wetherill, Dongbing Lai, Jeanette McClintick, Tatiana Foroud & Howard J. Edenberg

  5. Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, 06030, USA

    Grace Chan, Lance Bauer & Victor Hesselbrock

  6. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA

    Jeanette McClintick & Howard J. Edenberg

  7. Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, IA, 52242, USA

    Samuel Kuperman & John Kramer

  8. Department of Psychology and the Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA

    Jessica E. Salvatore & Danielle M. Dick

  9. Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA

    Arpana Agrawal

  10. Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA

    Alison Goate

Authors
  1. Jacquelyn L. Meyers
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David B. Chorlian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ashwini K. Pandey
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chella Kamarajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jen-Chyong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Leah Wetherill
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Dongbing Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Michael Chao
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Grace Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Sivan Kinreich
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Manav Kapoor
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Sarah Bertelsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Jeanette McClintick
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Lance Bauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Victor Hesselbrock
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Samuel Kuperman
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. John Kramer
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Jessica E. Salvatore
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Danielle M. Dick
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Arpana Agrawal
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Tatiana Foroud
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Howard J. Edenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Alison Goate
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Bernice Porjesz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jacquelyn L. Meyers.

Ethics declarations

Conflict of interest

Unrelated to this work, coauthor AA received peer-reviewed funding, travel and an honorarium from ABMRF (end 12/2012) which receives support from the brewing industry. We have no other conflicts of interest to disclose.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Meyers, J.L., Zhang, J., Chorlian, D.B. et al. A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior. Mol Psychiatry 26, 5040–5052 (2021). https://doi.org/10.1038/s41380-020-0777-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-020-0777-6

This article is cited by

Search

Advanced search

Quick links