Colin A. Hodgkinsona,1, Mary-Anne Enocha, Vibhuti Srivastavaa, Justine S. Cummins-Omana, Cherisse Ferriera, Polina Iarikovaa, Sriram Sankararamanb, Goli Yaminia, Qiaoping Yuana, Zhifeng Zhoua, Bernard Albaughc, Kenneth V. Whitea, Pei-Hong Shena, and David Goldmana aLaboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, Rockville, MD 20852; bComputer Science Department, University of California, Berkeley, CA 94720; and cCenter for Human Behavior Studies, Weatherford, OK 73096 Edited* by Raymond L. White, University of California, Emeryville, CA, and approved March 31, 2010 (received for review July 23, 2009) 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 diagnostic for any of them. EEG traits for an individual are stable, variable between individuals, and moderately to highly heritable. Such intermediate phenotypes appear to be closer to underlying molecular processes than are clinical symptoms, and represent an alternative approach for the identification of genetic variation that underlies complex psychiat- ric disorders. We performed a whole-genome association study on alpha (α), beta (β), and theta (θ) EEG power in a Native American cohort of 322 individuals to take advantage of the genetic and en- vironmental homogeneity of this population isolate. We identified three genes (SGIP1, ST6GALNAC3, and UGDH) with nominal associ- ation to variability of θ or α power. SGIP1 was estimated to account for 8.8% of variance in θ power, and this association was replicated in US Caucasians, where it accounted for 3.5% of the variance. Bayesian analysis of prior probability of association based upon earlier linkage to chromosome 1 and enrichment for vesicle-related transport proteins indicates that the association of SGIP1 with θ power is genuine. We also found association of SGIP1 with alcohol- ism, an effect that may be mediated via the same brain mechanisms accessed by θ EEG, and which also provides validation of the use of EEG as an endophenotype for alcoholism. alcoholism | electroencephalogram | endophenotype | genetics | whole-genome association Genetic studies of behavior and psychiatric disorders are ham- pered by etiologic heterogeneity of these complex phenotypes. Addiction vulnerability arises from both internalizing (emotional) and externalizing (dyscontrol) behavioral dimensions (1), and both of these broad aspects of behavior are strongly influenced by early life trauma and other gene/environment interactions (2). Etiologic heterogeneity dilutes power to detect genetic effects, and is a reason for failures to detect and replicate genome-wide associations (GWAS) in complex disorders. Increasing sample size does not remove underlying heterogeneity and can introduce additional confounds. In neuropsychiatry, these considerations have led to the use of intermediate phenotypes (or endophenotypes) that are her- itable, relevant to disease, and have good measurement properties and assay variation more closely related to gene function (3) as surrogates to probe the underlying biology of complex disorders. Risk genes for schizophrenia have recently been identified using quantitative variables derived from functional magnetic resonance imagingincomparativelysmallcohorts(4).Therefore,animportant strategy to increase power for GWAS of psychiatric disorders might be the use of endophenotypes. The resting electroencephalogram (EEG) is a safely and in- expensively obtained phenotype relevant to normal behavioral variation and to psychiatric disease. The EEG recorded at the scalp is the sum of postsynaptic currents of synchronously depo- larized, radially oriented pyramidal cells in the cerebral cortex, and reflects rhythmic electrical activity of the brain. EEG patterns dynamically and quantitatively index cortical activation, cognitive function, and state of consciousness. EEG traits were among the original intermediate phenotypes in neuropsychiatry, having been first recorded in humans in 1924 by Hans Berger, who documented the α rhythm, seen maximally during states of relaxation with eyes closed, and supplanted by faster β waves during mental activity. EEG can be used clinically for the evaluation and differential di- agnosis of epilepsy and sleep disorders, differentiation of en- cephalopathy from catatonia, assessment of depth of anesthesia, prognosis in coma, and determination of brain death (5, 6). EEG also has moderate predictive value for personality variation and psychiatric disease including depression (7), bipolar disorder (8), attention-deficit/hyperactivity disorder (9), and obsessive-com- pulsive disorder (10). Increased β power is associated with both alcoholism and family history of alcoholism (11, 12), θ power is altered in alcoholics (13–15), and reduced α power has been as- sociated with a family history of alcoholism and with alcoholism with comorbid anxiety disorders (16, 17). However, the EEG is not clinically useful for diagnosis of any specific psychiatric disorder. The stability and heritability of the EEG make it suitable for genetic analysis. Under standardized conditions the resting EEG is a stable trait in healthy adults, with high test-retest correlations [e.g., 0.7 even at >10 months (18)]. The marked interindividual variability in the resting EEG spectral band power is largely genetically determined and heritability of EEG spectral power is uniformly high for all wave forms (19, 20). We have performed GWAS in a sample of Plains American Indians, in which α (8–13 Hz), β (13–30 Hz), and θ (3–8 Hz) EEG spectral power are moderately heritable with high test-retest cor- relations over 2 years (15). Notably, this sample represents a population isolate evidencing a small but, as it turned out, useful degree of European admixture, and is genetically distinct from other Native American populations. In this dataset, common fa- milial traits such as alcoholism and other psychiatric disorders do not themselves generate statistical signals approaching genome- wide significance. However, we were able to identify a set of genes and possible pathways that affect α and θ EEG wave forms that are relevant to some of these same complex behavioral traits. Two of the gene associations were replicated in a US Caucasian dataset. Results Genome-Wide Significant Loci for Resting EEG Power. Five separate genomic regions, three for θ power [Fig. 1A, all on chromosome Author contributions: C.A.H., M.-A.E., and D.G. designed research; C.A.H., M.-A.E., J.S.C.-O., C.F., P.I., Z.Z., B.A., and K.V.W. performed research; S.S. contributed new reagents/analytic tools; C.A.H., M.-A.E., V.S., J.S.C.-O., C.F., P.I., G.Y., Q.Y., Z.Z., P.-H.S., and D.G. analyzed data; and C.A.H., M.-A.E., V.S., and D.G. wrote the paper. The authors declare no conflict of interest. *This Direct Submission article had a prearranged editor. 1To whom correspondence should be addressed. E-mail:
[email protected]. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.0908134107/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.0908134107 PNAS | May 11, 2010 | vol. 107 | no. 19 | 8695–8700 GENETICS