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

M. L. Hamshere, E. K. Green, I. R. Jones, L. Jones, V. Moskvina, G. Kirov, D. Grozeva, I. Nikolov, D. Vukcevic, S. Caesar, K. Gordon-Smith, C. Fraser, E. Russell, G. Breen, D. St Clair, D. A. Collier, A. H. Young, I. N. Ferrier, A. Farmer, P. McGuffin & 4 others P. A. Holmans, M. J. Owen, M. C. O'Donovan, Nick Craddock*

*Corresponding author for this work

Research output: Contribution to journalArticle

73 Citations (Scopus)

Abstract

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 identity cases that are particularly helpful for biologicalgenetic 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 276122 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, GABRBI, 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.

Original languageEnglish
Pages (from-to)23-29
Number of pages7
JournalBritish Journal of Psychiatry
Volume195
Issue number1
DOIs
Publication statusPublished - 1 Jul 2009

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Bipolar Disorder
Psychotic Disorders
Single Nucleotide Polymorphism
Phenotype
Psychiatry
Research
Genome
Diagnostic and Statistical Manual of Mental Disorders
Sample Size
Genotype
Control Groups
Acids

ASJC Scopus subject areas

  • Psychiatry and Mental health

Cite this

Hamshere, M. L., Green, E. K., Jones, I. R., Jones, L., Moskvina, V., Kirov, G., ... Craddock, N. (2009). Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept. British Journal of Psychiatry, 195(1), 23-29. https://doi.org/10.1192/bjp.bp.108.061424

Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept. / 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.; St Clair, D.; Collier, D. A.; Young, A. H.; Ferrier, I. N.; Farmer, A.; McGuffin, P.; Holmans, P. A.; Owen, M. J.; O'Donovan, M. C.; Craddock, Nick.

In: British Journal of Psychiatry, Vol. 195, No. 1, 01.07.2009, p. 23-29.

Research output: Contribution to journalArticle

Hamshere, ML, Green, EK, Jones, IR, Jones, L, Moskvina, V, Kirov, G, Grozeva, D, Nikolov, I, Vukcevic, D, Caesar, S, Gordon-Smith, K, Fraser, C, Russell, E, Breen, G, St Clair, D, Collier, DA, Young, AH, Ferrier, IN, Farmer, A, McGuffin, P, Holmans, PA, Owen, MJ, O'Donovan, MC & Craddock, N 2009, 'Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept', British Journal of Psychiatry, vol. 195, no. 1, pp. 23-29. https://doi.org/10.1192/bjp.bp.108.061424
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. ; St Clair, D. ; Collier, D. A. ; Young, A. H. ; Ferrier, I. N. ; Farmer, A. ; McGuffin, P. ; Holmans, P. A. ; Owen, M. J. ; O'Donovan, M. C. ; Craddock, Nick. / Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept. In: British Journal of Psychiatry. 2009 ; Vol. 195, No. 1. pp. 23-29.
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abstract = "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 identity cases that are particularly helpful for biologicalgenetic 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 276122 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, GABRBI, 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.",
author = "Hamshere, {M. L.} and Green, {E. K.} and Jones, {I. R.} and L. Jones and V. Moskvina and G. Kirov and D. Grozeva and I. Nikolov and D. Vukcevic and S. Caesar and K. Gordon-Smith and C. Fraser and E. Russell and G. Breen and {St Clair}, D. and Collier, {D. A.} and Young, {A. H.} and Ferrier, {I. N.} and A. Farmer and P. McGuffin and Holmans, {P. A.} and Owen, {M. J.} and O'Donovan, {M. C.} and Nick Craddock",
note = "We are indebted to all individuals who have participated in our research. We thank MDF-The BiPolar Organization for the help of its staff and members. The members of the WTCCC are listed in the online supplement. We are grateful to WESC for use of computing resources.",
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T1 - Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept

AU - Hamshere, M. L.

AU - Green, E. K.

AU - Jones, I. R.

AU - Jones, L.

AU - Moskvina, V.

AU - Kirov, G.

AU - Grozeva, D.

AU - Nikolov, I.

AU - Vukcevic, D.

AU - Caesar, S.

AU - Gordon-Smith, K.

AU - Fraser, C.

AU - Russell, E.

AU - Breen, G.

AU - St Clair, D.

AU - Collier, D. A.

AU - Young, A. H.

AU - Ferrier, I. N.

AU - Farmer, A.

AU - McGuffin, P.

AU - Holmans, P. A.

AU - Owen, M. J.

AU - O'Donovan, M. C.

AU - Craddock, Nick

N1 - We are indebted to all individuals who have participated in our research. We thank MDF-The BiPolar Organization for the help of its staff and members. The members of the WTCCC are listed in the online supplement. We are grateful to WESC for use of computing resources.

PY - 2009/7/1

Y1 - 2009/7/1

N2 - 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 identity cases that are particularly helpful for biologicalgenetic 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 276122 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, GABRBI, 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.

AB - 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 identity cases that are particularly helpful for biologicalgenetic 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 276122 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, GABRBI, 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.

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