Julie Garnham

Clinical Features of Bipolar Disorder with and without Comorbid Diabetes Mellitus

Objective: Several papers have reported higher prevalence of diabetes mellitus (DM) type 2 in patients suffering from bipolar disorder (BD). The possible links between these 2 disorders include treatment, lifestyle, alterations in signal transduction, and possibly, a genetic link. To study this relation more closely, we investigated whether there are any differences in the clinical characteristics of BD patients with and without DM. Method: We compared the clinical data of 26 diabetic and 196 nondiabetic subjects from The Maritime Bipolar Registry. Subjects were aged 15 to 82 years, with psychiatric diagnoses of BD I (n = 151), BD II (n = 65), and BD not otherwise specified (n = 6). The registry included basic demographic data and details on the clinical course of bipolar illness, its treatment, and physical comorbidity. In a subsequent analysis using logistic regression, we examined the variables showing differences between groups, with diabetes as an outcome variable. Results: The prevalence of DM in our sample was 11.7% (n = 26). Diabetic patients were significantly older than nondiabetic patients (P < 0.001), had higher rates of rapid cycling (P = 0.02) and chronic course of BD (P = 0.006), scored lower on the Global Assessment of Functioning Scale (P = 0.01), were more often on disability for BD (P < 0.001), and had higher body mass index (P < 0.001) and increased frequency of hypertension (P = 0.003). Lifetime history of treatment with antipsychotics was not significantly associated with an elevated risk of diabetes (P = 0.16); however, the data showed a trend toward more frequent use of antipsychotic medication among diabetic subjects. Conclusions: Our findings suggest that the diagnosis of DM in BD patients is relevant for their prognosis and outcome.

Can body mass index help predict outcome in patients with bipolar disorder

OBJECTIVE Several studies have reported higher prevalence of obesity in patients suffering from bipolar disorder (BD). To study the relation of elevated body mass index (BMI) in patients with BD more closely, we investigated differences in sociodemographic, clinical, and medical characteristics with respect to BMI, with the hypothesis that BMI is related to prognosis and outcome. METHODS We measured the BMI of 276 subjects of a tertiary care sample from the Maritime Bipolar Registry. Subjects were 16 to 83 years old, with psychiatric diagnoses of bipolar I disorder (n = 186), bipolar II disorder (n = 85), and BD not otherwise specified (n = 5). The registry included basic demographic data and details of the clinical presentation. We first examined the variables showing a significant association with BMI; subsequently, we modeled the relationship between BMI and psychiatric outcome using structural equation analysis. RESULTS The prevalence of obesity in our sample was 39.1%. We found higher BMI in subjects with a chronic course (p < 0.001) and longer duration of illness (p = 0.02), lower scores on the Global Assessment of Functioning Scale (p = 0.02), and on disability (p = 0.002). Overweight patients had more frequent comorbid subthreshold social (p = 0.02) and generalized anxiety disorders (p = 0.05), diabetes mellitus type II (p < 0.001), and hypertension (p = 0.001). Subjects who achieved complete remission of symptoms on lithium showed significantly lower BMI (p = 0.01). CONCLUSIONS Our findings suggest that BMI is associated with the prognosis and outcome of BD. Whether this association is causal remains to be determined.

Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Objective The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the “Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder” scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. Materials and Methods Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (κ)] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. Results Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (κ = 0.66 and κ = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (ICC1 = 0.71 and ICC2 = 0.75, respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). Conclusions We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.

An admixture analysis of the age at index episodes in bipolar disorder

The interaction between polarity at onset (PAO) and age at onset (AAO) appears to be important for interpreting results of previous analyses of AAO in bipolar disorder (BD). Using an admixture analysis, we examined independently the distributions of age at first depressive and hypomanic/manic episodes in 379 BD I and II patients. Subsequently, we examined the association of PAO and AAO with specific clinical variables, using parametric and nonparametric analyses. Both depressive and manic onsets showed bimodal distributions. For depressive episodes, the means were: 18.5±4.1 (early onset) and 33.6±10.4 (late onset) years; and for manic episodes 18.9±3.3 (early onset) and 34.8±10.9 (late onset) years. For the overall AAO the best fit was for a mixture of three lognormal distributions (mean±S.D.): 15.5±2.0, 22.8±4.6, and 36.1±10.1years. Overall, an early onset was significantly associated with a chronic course of the disorder, a stronger family history of affective disorder, higher rates of rapid cycling, suicidal behavior, psychotic symptoms, and co-morbid anxiety disorders. Early onset depressive episodes were associated with higher rates of suicidal behavior and anxiety disorders, whereas early onset manic episodes were associated with psychotic symptoms and rapid cycling. Our results suggest the presence of a bimodal distribution of age at onset in BD according to the polarity of the index episode, and denote that an early onset BD, irrespective of polarity, may be a more serious subtype of the disorder.

Insulin resistance and outcome in bipolar disorder

BACKGROUND Little is known about the impact of insulin resistance on bipolar disorder. AIMS To examine the relationships between insulin resistance, type 2 diabetes and clinical course and treatment outcomes in bipolar disorder. METHOD 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. RESULTS 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 sensitivity analyses. CONCLUSIONS Comorbid insulin resistance may be an important factor in resistance to treatment in bipolar disorder.

Cross-prevalence of migraine and bipolar disorder

OBJECTIVE In two related studies, we explored the prevalence of migraine and its associated clinical characteristics in patients with bipolar disorder (BD) as well as psychiatric morbidity in patients treated for migraine. METHOD The first study included 323 subjects with BD type I (BD I) or BD type II (BD II), diagnosed using the Schedule for Affective Disorders and Schizophrenia, Lifetime version (SADS-L) format, or the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID). Migraine history was assessed by means of a structured questionnaire. In a second sample of 102 migraine patients, we investigated current and lifetime psychiatric morbidity using the SADS-L. Statistical analyses were conducted using nonparametric analysis and log-linear models. RESULTS A total of 24.5% of BD patients had comorbid migraine; those with BD II had a higher prevalence (34.8%) compared to BD I (19.1%) (p < 0.005). BD patients with comorbid migraine had significantly higher rates of suicidal behaviour, social phobia, panic disorder, generalized anxiety disorder, and obsessive-compulsive disorder (all p < 0.05). In the sample of migraine patients, 34.3% had a current psychiatric diagnosis, and 73.5% had a lifetime psychiatric diagnosis. The prevalence of BD I was 4.9%, and 7.8% for BD II. DISCUSSION Migraine is prevalent within the BD population, particularly among BD II subjects. It is associated with an increased risk of suicidal behaviour and comorbid anxiety disorders. Conversely, migraine sufferers have high rates of current and lifetime psychopathology. A greater understanding of this comorbidity may contribute to our knowledge of the underlying mechanisms of BD.

Rapid cycling bipolar disorders in primary and tertiary care treated patients

OBJECTIVE Rapid cycling (RC) affects 13-30% of bipolar patients. Most of the data regarding RC have been obtained in tertiary care research centers. Generalizability of these findings to primary care populations is thus questionable. We examined clinical and demographic factors associated with RC in both primary and tertiary care treated populations. METHOD Clinical data were obtained by interview from 240 bipolar I disorder (BDI) or bipolar II disorder (BDII) community-treated patients and by chart reviews from 119 bipolar patients treated at an outpatient clinic of a teaching hospital. RESULTS Lifetime history of rapid cycling was present in 33.3% and 26.9% of patients from the primary and tertiary care samples, respectively. Among community-treated patients, lifetime history of RC was significantly associated with history of suicidal behavior and higher body mass index. There was a trend for association between RC and BDII, psychiatric comorbidity, diabetes mellitus, as well as lower age of onset of mania/hypomania. In the tertiary care treated sample there was a trend for association between lifetime history of RC and suicidal behavior. Tertiary versus primary care treated subjects with lifetime history of RC demonstrated markedly lower response to mood stabilizers. CONCLUSIONS Lifetime history of RC is highly prevalent in both primary and tertiary settings. Even primary care treated subjects with lifetime history of RC seem to suffer from a more complicated and less treatment-responsive variant of bipolar disorder. Our findings further suggest relatively good generalizability of data from tertiary to primary care settings.

Nonlinear dynamics of mood regulation in bipolar disorder

We sought to study the underlying dynamic processes involved in mood regulation in subjects with bipolar disorder and healthy control subjects using time‐series analysis and to then analyze the relation between anxiety and mood using cross‐correlation techniques.

Internet use by patients with bipolar disorder:results from an international multisite survey

There is considerable international interest in online education of patients with bipolar disorder, yet little understanding of how patients use the Internet and other sources to seek information. 1171 patients with a diagnosis of bipolar disorder in 17 countries completed a paper-based, anonymous survey. 81% of the patients used the Internet, a percentage similar to the general public. Older age, less education, and challenges in country telecommunications infrastructure and demographics decreased the odds of using the Internet. About 78% of the Internet users looked online for information on bipolar disorder or 63% of the total sample. More years of education in relation to the country mean, and feeling very confident about managing life decreased the odds of seeking information on bipolar disorder online, while having attended support groups increased the odds. Patients who looked online for information on bipolar disorder consulted medical professionals plus a mean of 2.3 other information sources such as books, physician handouts, and others with bipolar disorder. Patients not using the Internet consulted medical professionals plus a mean of 1.6 other information sources. The percentage of patients with bipolar disorder who use the Internet is about the same as the general public. Other information sources remain important.

Early-onset and very-early-onset bipolar disorder: distinct or similar clinical conditions?

This study aimed to examine differences in the clinical presentation of very‐early‐onset (VEO) and early‐onset (EO) bipolar disorder (BD) not fully explored previously.