TY - JOUR
T1 - A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation
AU - Bramon, Elvira
AU - Pirinen, Matti
AU - Strange, Amy
AU - Lin, Kuang
AU - Freeman, Colin
AU - Bellenguez, Céline
AU - Su, Zhan
AU - Band, Gavin
AU - Pearson, Richard
AU - Vukcevic, Damjan
AU - Langford, Cordelia
AU - Deloukas, Panos
AU - Hunt, Sarah
AU - Gray, Emma
AU - Dronov, Serge
AU - Potter, Simon C.
AU - Tashakkori-Ghanbaria, Avazeh
AU - Edkins, Sarah
AU - Bumpstead, Suzannah J.
AU - Arranz, Maria J.
AU - Bakker, Steven
AU - Bender, Stephan
AU - Bruggeman, Richard
AU - Cahn, Wiepke
AU - Chandler, David
AU - Collier, David A.
AU - Crespo-Facorro, Benedicto
AU - Dazzan, Paola
AU - de Haan, Lieuwe
AU - Di Forti, Marta
AU - Dragović, Milan
AU - Giegling, Ina
AU - Hall, Jeremy
AU - Iyegbe, Conrad
AU - Jablensky, Assen
AU - Kahn, René S.
AU - Kalaydjieva, Luba
AU - Kravariti, Eugenia
AU - Lawrie, Stephen
AU - Linszen, Don H.
AU - Mata, Ignacio
AU - McDonald, Colm
AU - McIntosh, Andrew
AU - Myin-Germeys, Inez
AU - Ophoff, Roel A.
AU - Pariante, Carmine M.
AU - Paunio, Tiina
AU - Picchioni, Marco
AU - Ripke, Stephan
AU - Van Os, Jim
PY - 2014/3/1
Y1 - 2014/3/1
N2 - 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 × 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 meta-analysis 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.
AB - 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 × 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 meta-analysis 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.
KW - Bipolar disorder
KW - genome-wide association
KW - meta-analysis
KW - polygenic score analysis
KW - psychosis
KW - schizophrenia
UR - http://www.scopus.com/inward/record.url?scp=84893814574&partnerID=8YFLogxK
U2 - 10.1016/j.biopsych.2013.03.033
DO - 10.1016/j.biopsych.2013.03.033
M3 - Article
C2 - 23871474
AN - SCOPUS:84893814574
SN - 0006-3223
VL - 75
SP - 386
EP - 397
JO - Biological Psychiatry
JF - Biological Psychiatry
IS - 5
ER -