Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept

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 rese...

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Published inBritish journal of psychiatry Vol. 195; no. 1; pp. 23 - 29
Main Authors Hamshere, M. L., Green, E. K., Jones, I. R., Jones, L., Moskvina, V., Kirov, G., Grozeva, D., Nikolov, I., Vukcevic, D., Caesar, S., Gordon-Smith, K., Fraser, C., Russell, E., Breen, G., Clair, D. St, Collier, D. A., Young, A. H., Ferrier, I. N., Farmer, A., McGuffin, P., Holmans, P. A., Owen, M. J., O'Donovan, M. C., Craddock, N.
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.07.2009
RCP
Royal College Of Psychiatrists
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Abstract 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. 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. 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. 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 = 2.42 x 10(-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. 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.
AbstractList 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 = 2.42×10 –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.
BACKGROUNDPsychiatric 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. AIMSTo 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. METHODWe 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. RESULTSThe 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 = 2.42 x 10(-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. CONCLUSIONSOur 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.
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. Adapted from the source document.
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. 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. 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. 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 = 2.42 x 10(-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. 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.
Author Farmer, A.
Russell, E.
Grozeva, D.
Green, E. K.
Moskvina, V.
Nikolov, I.
Breen, G.
Vukcevic, D.
Ferrier, I. N.
O'Donovan, M. C.
Caesar, S.
Clair, D. St
Owen, M. J.
Fraser, C.
Collier, D. A.
Jones, I. R.
Craddock, N.
Holmans, P. A.
Hamshere, M. L.
Jones, L.
Young, A. H.
Gordon-Smith, K.
McGuffin, P.
Kirov, G.
AuthorAffiliation Biostatistics and Bioinformatics Unit and 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
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
Department of Statistics, University of Oxford, 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 Mental Health, University of Aberdeen, Royal Cornhill Hospital, Aberdeen, UK, and Psychiatric Laboratory, Department of Psychiatry, West China Ho
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/19567891$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright Copyright © Royal College of Psychiatrists, 2009
Royal College of Psychiatrists 2009
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DocumentTitleAlternate Genetic Support for Broadly Defined Bipolar Schizoaffective Disorder
Hamshere et al
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  publication-title: Nature
– ident: S0007125000007315_ref28
  doi: 10.1038/sj.mp.4001348
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Snippet Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to...
Background: Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would...
BACKGROUNDPsychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be...
Background Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be...
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StartPage 23
SubjectTerms Adolescent
Adult
Aged
Aged, 80 and over
Bipolar affective disorder
Bipolar Disorder - diagnosis
Bipolar Disorder - genetics
Case-Control Studies
Female
Genes
Genome-Wide Association Study
Genotype
Humans
Male
Middle Aged
Phenotypes
Polymorphism, Single Nucleotide - genetics
Psychiatric Status Rating Scales
Psychotic Disorders - diagnosis
Psychotic Disorders - genetics
Schizoaffective disorder
Serotonin Plasma Membrane Transport Proteins - genetics
Signals
Young Adult
Title Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept
URI https://www.cambridge.org/core/product/identifier/S0007125000007315/type/journal_article
http://bjp.rcpsych.org/cgi/content/abstract/195/1/23
https://www.ncbi.nlm.nih.gov/pubmed/19567891
https://search.proquest.com/docview/57305150
https://search.proquest.com/docview/733362345
https://pubmed.ncbi.nlm.nih.gov/PMC2802523
Volume 195
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