Genome-wide association identifies candidate genes that influence the human electroencephalogram

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 107; no. 19; pp. 8695 - 8700
• Main Authors: Hodgkinson, Colin A, Enoch, Mary-Anne, Srivastava, Vibhuti, Cummins-Oman, Justine S, Ferrier, Cherisse, Iarikova, Polina, Sankararaman, Sriram, Yamini, Goli, Yuan, Qiaoping, Zhou, Zhifeng, Albaugh, Bernard, White, Kenneth V, Shen, Pei-Hong, Goldman, David
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 11.05.2010; National Acad Sciences
• Subjects: Admixtures; alcohol abuse; Alcohol related disorders; Alcoholism; Alcoholism - genetics; Alleles; anxiety; Bayesian analysis; Bayesian theory; Biological Sciences; Biological Transport; Biological variation; brain; Carrier Proteins - genetics; chromosomes; Chromosomes, Human, Pair 1 - genetics; Datasets; Electroencephalography; etiology; European Continental Ancestry Group - genetics; Gene Frequency - genetics; genes; Genes - genetics; Genetic diversity; Genetic loci; Genetic Loci - genetics; Genetic Markers; genetic variation; Genome-Wide Association Study; Genomics; Genotype & phenotype; Golgi Apparatus - metabolism; Heterogeneity; Humans; Medical genetics; Mental disorders; Phenotype; Phenotypes; Polymorphism, Single Nucleotide - genetics; Population genetics; probability; Reproducibility of Results; schizophrenia; transport proteins; United States; variance; Whites; United States

Complex psychiatric disorders are resistant to whole-genome analysis due to genetic and etiological heterogeneity. Variation in resting electroencephalogram (EEG) is associated with common, complex psychiatric diseases including alcoholism, schizophrenia, and anxiety disorders, although not diagnost...