Sally Hyde

Bipolar disorder and polymorphisms in the dysbindin gene (DTNBP1)

BACKGROUND Several studies support the dysbindin (dystrobrevin binding protein 1) gene (DTNBP1) as a susceptibility gene for schizophrenia. We previously reported that variation at a specific 3-locus haplotype influences susceptibility to schizophrenia in a large United Kingdom (UK) Caucasian case-control sample. METHODS Using similar methodology to our schizophrenia study, we have investigated this same 3-locus haplotype in a large, well-characterized bipolar sample (726 Caucasian UK DSM-IV bipolar I patients; 1407 ethnically matched controls). RESULTS No significant differences were found in the distribution of the 3-locus haplotype in the full sample. Within the subset of bipolar I cases with predominantly psychotic episodes of mood disturbance (n = 133) we found nominally significant support for association at this haploptype (p < .042) and at SNP rs2619538 (p = .003), with a pattern of findings similar to that in our schizophrenia sample. This finding was not significant after correction for multiple testing. CONCLUSIONS Our data suggest that variation at the polymorphisms examined does not make a major contribution to susceptibility to bipolar disorder in general. They are consistent with the possibility that DTNBP1 influences susceptibility to a subset of bipolar disorder cases with psychosis. However, our subset sample is small and the hypothesis requires testing in independent, adequately powered samples.

Clinical differences between bipolar and unipolar depression

It is commonly -- but wrongly -- assumed that there are no important differences between the clinical presentations of major depressive disorder and bipolar depression. Here we compare clinical course variables and depressive symptom profiles in a large sample of individuals with major depressive disorder (n=593) and bipolar disorder (n=443). Clinical characteristics associated with a bipolar course included the presence of psychosis, diurnal mood variation and hypersomnia during depressive episodes, and a greater number of shorter depressive episodes. Such features should alert a clinician to a possible bipolar course. This is important because optimal management is not the same for bipolar and unipolar depression.

Age-at-onset in bipolar-I disorder: Mixture analysis of 1369 cases identifies three distinct clinical sub-groups

BACKGROUND To assess whether bipolar disorder type I segregates into three clinically distinct sub-groups defined by age-at-onset. METHODS Clinical data were available on 1369 individuals with DSM-IV bipolar I disorder. Mixture analysis was performed on the age-at-onset (AAO) data to determine whether they were composed of more than one normal distribution. Individuals were allocated to groups according to the results of the mixture analysis. Categorical logistic regression was then used to investigate relationships between AAO and nine clinical characteristics. RESULTS The distribution of AAOs in our sample comprised a mixture of three normal distributions with means of 18.7 (SD=3.7), 28.3 (SD=5.5) and 43.3 (SD=9.1) years, with relative proportions of 0.47, 0.39 and 0.14 respectively. Individuals were allocated into three groups dependent on their AAO: < or = 22; 25-37; and > or = 40 years, producing a sample of 1225 individuals (144 with borderline values were excluded). Eight out of the nine clinical characteristics showed evidence for a statistical association with AAO group. LIMITATIONS Systematic and non-systematic recruitment of participants. Some data relied on retrospective recall. CONCLUSIONS Our results provide further robust evidence to suggest that the AAO distribution of individuals affected with bipolar disorder is composed of three normal distributions. Substantial clinical heterogeneity between the three AAO groups may reflect genetic heterogeneity within bipolar I disorder. Future genetic studies should consider AAO grouping as potential sub-phenotypes.

Polarity at illness onset in bipolar I disorder and clinical course of illness

OBJECTIVES Studies have suggested that episode polarity at illness onset in bipolar disorder may be predictive of some aspects of lifetime clinical characteristics. We here examine this possibility in a large, well-characterized sample of patients with bipolar I disorder. METHODS We assessed polarity at onset in patients with bipolar I disorder (N = 553) recruited as part of our ongoing studies of affective disorders. Lifetime clinical characteristics of illness were compared in patients who had a depressive episode at first illness onset (n = 343) and patients who had a manic episode at first illness onset (n = 210). RESULTS Several lifetime clinical features differed between patients according to the polarity of their onset episode of illness. A logistic regression analysis showed that the lifetime clinical features significantly associated with a depressive episode at illness onset in our sample were: an earlier age at illness onset; a predominantly depressive polarity during the lifetime; more frequent and more severe depressive episodes; and less prominent lifetime psychotic features. CONCLUSIONS Knowledge of pole of onset may help the clinician in providing prognostic information and management advice to an individual with bipolar disorder.

Clinical characteristics of unipolar disorder and bipolar disorder according to the lifetime presence of recurrent panic attacks

OBJECTIVES The frequent comorbidity of panic and affective disorders has been described in previous studies. However, it is not clear how panic disorder comorbidity in unipolar disorder and bipolar disorder is related to illness course. METHODS We compared lifetime clinical characteristics of illness and items of symptomatology in samples of individuals with bipolar I disorder (n = 290) and unipolar disorder (n = 335) according to the lifetime presence of recurrent panic attacks. RESULTS We found significant differences in clinical course of illness characteristics that were shared across the unipolar and bipolar samples according to the lifetime presence of panic attacks. We also found a number of differences according to the presence of panic attacks that may be specific to the diagnostic group. CONCLUSIONS Distinguishing patients who have mood disorder diagnoses, especially bipolar I disorder, according to the lifetime presence of panic attacks may not only be of use in clinical practice, but may also be informative for aetiological research, such as molecular genetic studies.