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 in | British journal of psychiatry Vol. 195; no. 1; pp. 23 - 29 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Cambridge, UK
Cambridge University Press
01.07.2009
RCP Royal College Of Psychiatrists |
Subjects | |
Online Access | Get full text |
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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. |
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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 |
AuthorAffiliation_xml | – name: University of Aberdeen, Institute of Medical Sciences, Aberdeen, and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK – name: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – name: Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK – name: Department of Psychological Medicine, School of Medicine, Cardiff University, and Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK – name: Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK – name: Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK – name: School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK, and UBC Institute of Mental Health, Vancouver, British Columbia, Canada – name: Division of Psychological Medicine and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, UK – name: Department of Statistics, University of Oxford, UK – name: School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK – name: members’ names and affiliations are listed in the online supplement – name: 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 |
Author_xml | – sequence: 1 givenname: M. L. surname: Hamshere fullname: Hamshere, M. L. organization: Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 2 givenname: E. K. surname: Green fullname: Green, E. K. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 3 givenname: I. R. surname: Jones fullname: Jones, I. R. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 4 givenname: L. surname: Jones fullname: Jones, L. organization: Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK – sequence: 5 givenname: V. surname: Moskvina fullname: Moskvina, V. organization: Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 6 givenname: G. surname: Kirov fullname: Kirov, G. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 7 givenname: D. surname: Grozeva fullname: Grozeva, D. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 8 givenname: I. surname: Nikolov fullname: Nikolov, I. organization: Biostatistics and Bioinformatics Unit and Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 9 givenname: D. surname: Vukcevic fullname: Vukcevic, D. organization: Department of Statistics, University of Oxford, UK – sequence: 10 givenname: S. surname: Caesar fullname: Caesar, S. organization: Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK – sequence: 11 givenname: K. surname: Gordon-Smith fullname: Gordon-Smith, K. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, and Department of Psychiatry, University of Birmingham, National Centre for Mental Health, Birmingham, UK – sequence: 12 givenname: C. surname: Fraser fullname: Fraser, C. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 13 givenname: E. surname: Russell fullname: Russell, E. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 14 givenname: G. surname: Breen fullname: Breen, G. organization: University of Aberdeen, Institute of Medical Sciences, Aberdeen, and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK – sequence: 15 givenname: D. St surname: Clair fullname: Clair, D. St organization: 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 – sequence: 16 givenname: D. A. surname: Collier fullname: Collier, D. A. organization: Division of Psychological Medicine and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK – sequence: 17 givenname: A. H. surname: Young fullname: Young, A. H. organization: School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK, and UBC Institute of Mental Health, Vancouver, British Columbia, Canada – sequence: 18 givenname: I. N. surname: Ferrier fullname: Ferrier, I. N. organization: School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK – sequence: 19 givenname: A. surname: Farmer fullname: Farmer, A. organization: Division of Psychological Medicine and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK – sequence: 20 givenname: P. surname: McGuffin fullname: McGuffin, P. organization: Division of Psychological Medicine and Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK – sequence: 21 givenname: P. A. surname: Holmans fullname: Holmans, P. A. organization: School of Neurology, Neurobiology and Psychiatry, Royal Victoria Infirmary, Newcastle upon Tyne, UK – sequence: 22 givenname: M. J. surname: Owen fullname: Owen, M. J. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 23 givenname: M. C. surname: O'Donovan fullname: O'Donovan, M. C. organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK – sequence: 24 givenname: N. surname: Craddock fullname: Craddock, N. email: craddockn@cardiff.ac.uk organization: Department of Psychological Medicine, School of Medicine, Cardiff University, UK |
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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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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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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 |
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