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Recent data provide strong support for a substantial common polygenic contribution (i.e. many alleles each of small effect) to genetic susceptibility for schizophrenia and overlapping susceptibility for bipolar disorder.
To test hypotheses about the relationship between schizophrenia and psychotic types of bipolar disorder.
Using a polygenic score analysis to test whether schizophrenia polygenic risk alleles, en masse, significantly discriminate between individuals with bipolar disorder with and without psychotic features. The primary sample included 1829 participants with bipolar disorder and the replication sample comprised 506 people with bipolar disorder.
The subset of participants with Research Diagnostic Criteria schizoaffective bipolar disorder (n = 277) were significantly discriminated from the remaining participants with bipolar disorder (n = 1552) in both the primary (P = 0.00059) and the replication data-sets (P = 0.0070). In contrast, those with psychotic bipolar disorder as a whole were not significantly different from those with non-psychotic bipolar disorder in either data-set.
Genetic susceptibility influences at least two major domains of psychopathological variation in the schizophrenia–bipolar disorder clinical spectrum: one that relates to expression of a ‘bipolar disorder-like’ phenotype and one that is associated with expression of ‘schizophrenia-like’ psychotic symptoms.
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
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 ×
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
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
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