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Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Little is known about the impact of insulin resistance on bipolar
To examine the relationships between insulin resistance, type 2 diabetes
and clinical course and treatment outcomes in bipolar disorder.
We measured fasting glucose and insulin in 121 adults with bipolar
disorder. We diagnosed type 2 diabetes and determined insulin resistance.
The National Institute of Mental Health Life Chart was used to record the
course of bipolar disorder and the Alda scale to establish response to
prophylactic lithium treatment.
Patients with bipolar disorder and type 2 diabetes or insulin resistance
had three times higher odds of a chronic course of bipolar disorder
compared with euglycaemic patients (50% and 48.7% respectively
v. 27.3%, odds ratio (OR) = 3.07, P
= 0.007), three times higher odds of rapid cycling (38.5% and 39.5%
respectively v. 18.2%, OR = 3.13, P =
0.012) and were more likely to be refractory to lithium treatment (36.8%
and 36.7% respectively v. 3.2%, OR = 8.40,
P<0.0001). All associations remained significant
after controlling for antipsychotic exposure and body mass index in
Comorbid insulin resistance may be an important factor in resistance to
treatment in bipolar disorder.
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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