Human Genetics

, Volume 131, Issue 3, pp 373–391 | Cite as

Ion channels and schizophrenia: a gene set-based analytic approach to GWAS data for biological hypothesis testing

  • Kathleen AsklandEmail author
  • Cynthia Read
  • Chloe O’Connell
  • Jason H. Moore
Original Investigation


Schizophrenia is a complex genetic disorder. Gene set-based analytic (GSA) methods have been widely applied for exploratory analyses of large, high-throughput datasets, but less commonly employed for biological hypothesis testing. Our primary hypothesis is that variation in ion channel genes contribute to the genetic susceptibility to schizophrenia. We applied Exploratory Visual Analysis (EVA), one GSA application, to analyze European-American (EA) and African-American (AA) schizophrenia genome-wide association study datasets for statistical enrichment of ion channel gene sets, comparing GSA results derived under three SNP-to-gene mapping strategies: (1) GENIC; (2) 500-Kb; (3) 2.5-Mb and three complimentary SNP-to-gene statistical reduction methods: (1) minimum p value (pMIN); (2) a novel method, proportion of SNPs per Gene with p values below a pre-defined α-threshold (PROP); and (3) the truncated product method (TPM). In the EA analyses, ion channel gene set(s) were enriched under all mapping and statistical approaches. In the AA analysis, ion channel gene set(s) were significantly enriched under pMIN for all mapping strategies and under PROP for broader mapping strategies. Less extensive enrichment in the AA sample may reflect true ethnic differences in susceptibility, sampling or case ascertainment differences, or higher dimensionality relative to sample size of the AA data. More consistent findings under broader mapping strategies may reflect enhanced power due to increased SNP inclusion, enhanced capture of effects over extended haplotypes or significant contributions from regulatory regions. While extensive pMIN findings may reflect gene size bias, the extent and significance of PROP and TPM findings suggest that common variation at ion channel genes may capture some of the heritability of schizophrenia.


Schizophrenia Mapping Strategy Potassium Channel Activity Molecular Function Ontology Truncate Product Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The project described was supported by Award Number K08MH085810 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. The authors would like to thank Brady Tang, A.M., for his assistance with implementing the TPM algorithm. We would also like to thank Ben Greenberg, MD, PhD, for his editorial contributions.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Kathleen Askland
    • 1
    Email author
  • Cynthia Read
    • 1
  • Chloe O’Connell
    • 2
  • Jason H. Moore
    • 3
  1. 1.Department of Psychiatry and Human BehaviorButler Hospital, Brown UniversityProvidenceUSA
  2. 2.Brown UniversityProvidenceUSA
  3. 3.Departments of Genetics and Community and Family MedicineInstitute for Quantitative Biomedical Sciences, Dartmouth CollegeLebanonUSA

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