© 2009 The Royal College of Psychiatrists
OPEN ACCESS ARTICLE
Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept
Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK
Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Department of Statistics, University of Oxford, UK
Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK
Department of Psychological Medicine, School of Medicine, Cardiff University, and Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK
Department of Psychological Medicine, School of Medicine, Cardiff University, UK
University of Aberdeen, Institute of Medical Sciences, Aberdeen, and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK
Department of Mental Health, University of Aberdeen, Royal Cornhill Hospital, Aberdeen, UK, and Psychiatric Laboratory, Department of Psychiatry, West China Hospital, Sichuan University, Sichuan, China
Division of Psychological Medicine and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK
School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK, and UBC Institute of Mental Health, Vancouver, British Columbia, Canada
School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK
Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK
Department of Psychological Medicine, School of Medicine, Cardiff University, UK.
Correspondence: Nick Craddock, Department of Psychological Medicine, School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK. Email: craddockn{at}cardiff.ac.uk
members’ names and affiliations are listed in the online supplement
Funding for recruitment and phenotype assessment has been provided by the Wellcome Trust (060620) and the Medical Research Council (G0000647). The genotype analyses were funded by the Wellcome Trust and undertaken within the context of the Wellcome Trust Case Control Consortium (WTCCC).
Background
Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological–genetic research.
Aims
To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case–control bipolar disorder sample.
Method
We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant at P<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type.
Results
The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42x10–7). Biological systems implicated included gamma amniobutyric acid (GABA)A receptors. Genes having at least one associated polymorphism at P<10–4 included B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and CDH12.
Conclusions
Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes.