A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

Elvira Bramon, Matti Pirinen, Amy Strange, Kuang Lin, Colin Freeman, Celine Bellenguez, Zhan Su, Gavin Band, Richard Pearson, Damjan Vukcevic, Cordelia Langford, Panos Deloukas, Sarah Hunt, Emma Gray, Serge Dronov, Simon C. Potter, Avazeh Tashakkori-Ghanbaria, Sarah Edkins, Suzannah J. Bumpstead, Maria J. ArranzSteven Bakker, Stephan Bender, Richard Bruggeman, Wiepke Cahn, David Chandler, David A. Collier, Benedicto Crespo-Facorro, Paola Dazzan, Lieuwe de Haan, Marta di Forti, Milan Dragovic, Ina Giegling, Jeremy Hall, Conrad Iyegbe, Assen Jablensky, Rene S. Kahn, Luba Kalaydjieva, Eugenia Kravariti, Stephen Lawrie, Don H. Lins-Zen, Ignacio Mata, Colm McDonald, Andrew McIntosh, Inez Myin-Germeys, Roel A. Ophoff, Carmine M. Pariante, Tiina Paunio, Marco Picchioni, Jessika Sussmann, Heather Whalley, Psychiat Genomics Consortium, Psychosis Endophenotypes Int Conso, Wellcome Trust Case-Control Consor

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories.

Methods: 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls).

Results: No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p.003). A polygenic score analysis found that the Psychiatric GWAS Consortium's panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 x 10(-14)) and explained approximately 2% of the phenotypic variance.

Conclusions: Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through metaanalysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.

Original languageEnglish
Pages (from-to)386-397
Number of pages12
JournalBiological Psychiatry
Volume75
Issue number5
DOIs
Publication statusPublished - 1 Mar 2014

Keywords

  • Bipolar disorder
  • genome-wide association
  • meta-analysis
  • polygenic score analysis
  • psychosis
  • schizophrenia
  • BIPOLAR-DISORDER
  • PSYCHIATRIC-DISORDERS
  • COMMON VARIANTS
  • GENETIC RISK
  • SUSCEPTIBILITY LOCUS
  • GENERAL-POPULATION
  • CONFERRING RISK
  • WINNERS CURSE
  • HAN CHINESE
  • FOLLOW-UP

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