Cynthia V. Calkin

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.

The relationship between bipolar disorder and type 2 diabetes: More than just co-morbid disorders

Abstract Type 2 diabetes mellitus (T2DM) rates are three times higher in patients with bipolar disorder (BD), compared to the general population. This is a major contributing factor to the elevated risk of cardiovascular mortality, the leading cause of death in bipolar patients. There may be shared pathophysiology linking the two disorders, including hypothalamic-pituitary-adrenal and mitochondrial dysfunction, common genetic links, and epigenetic interactions. Life-style, phenomenology of bipolar symptoms, and adverse effects of pharmacotherapy may be contributing factors. Patients with BD and T2DM have a more severe course of illness and are more refractory to treatment. Control of their diabetes is poorer when compared to diabetics without BD, and an existing disparity in medical care may be partly responsible. Glucose abnormalities in bipolar patients need to be screened for and treated. Metformin appears to have the best benefit/risk ratio, and the dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 receptor agonists and analogues also appear promising, although these agents have not been specifically studied in populations with mood disorders. Physicians need to be aware of the increased risk for T2DM and cardiovascular disease in bipolar patients, and appropriate prevention, screening, case finding, and treatment is recommended.

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.

Type 2 diabetes mellitus: a potentially modifiable risk factor for neurochemical brain changes in bipolar disorders.

BACKGROUND Neuroimaging changes in bipolar disorder (BD) may be secondary to the presence of certain clinical factors. Type 2 diabetes mellitus (T2DM) damages the brain and frequently co-occurs with BD. Studying patients with both T2DM and BD could help identify preventable risk factors for neuroimaging changes in BD. METHODS We used 1.5T magnetic resonance spectroscopy to measure prefrontal N-acetylaspartate (NAA), which is mainly localized in neurons, and total creatine (tCr), an energy metabolite, in 19 BD patients with insulin resistance/glucose intolerance (BD + IR/GI), 14 BD subjects with T2DM (BD + T2DM), 15 euglycemic BD participants, and 11 euglycemic, nonpsychiatric control. RESULTS The levels of NAA and tCr were lowest among BD + T2DM, intermediate in the BD + IR/GI, and highest among the euglycemic BD and control subjects (F₃,₅₅ = 4.57, p = .006; F₃,₅₅ = 2.92, p = .04, respectively). Even the BD + IR/GI subjects had lower NAA than the euglycemic participants (t₄₃ = 2.13, p = .04). Total Cr was associated with NAA (β = .52, t₅₆ = 5.57, p = .000001). Both NAA and tCr correlated with Global Assessment of Functioning scores (r₄₆ = .28, p = .05; r₄₆ = .48, p = .0004, respectively). CONCLUSIONS T2DM, but also prediabetes, may be risk factors for prefrontal neurochemical alterations in BD. These changes were associated with poor psychosocial functioning and could indicate impaired energy metabolism. The findings emphasize the importance of improving diabetes care in BD and suggest potential options for treatment of neuroimaging alterations.

Insulin resistance, diabetes mellitus, and brain structure in bipolar disorders.

Type 2 diabetes mellitus (T2DM) damages the brain, especially the hippocampus, and frequently co-occurs with bipolar disorders (BD). Reduced hippocampal volumes are found only in some studies of BD subjects and may thus be secondary to the presence of certain clinical variables. Studying BD patients with abnormal glucose metabolism could help identify preventable risk factors for hippocampal atrophy in BD. We compared brain structure using optimized voxel-based morphometry of 1.5T MRI scans in 33 BD subjects with impaired glucose metabolism (19 with insulin resistance/glucose intolerance (IR/GI), 14 with T2DM), 15 euglycemic BD participants and 11 euglycemic, nonpsychiatric controls. The group of BD patients with IR, GI or T2DM had significantly smaller hippocampal volumes than the euglycemic BD participants (corrected p=0.02) or euglycemic, nonpsychiatric controls (corrected p=0.004). Already the BD subjects with IR/GI had smaller hippocampal volumes than euglycemic BD participants (t(32)=−3.15, p=0.004). Age was significantly more negatively associated with hippocampal volumes in BD subjects with IR/GI/T2DM than in the euglycemic BD participants (F(2, 44)=9.96, p=0.0003). The gray matter reductions in dysglycemic subjects extended to the cerebral cortex, including the insula. In conclusion, this is the first study demonstrating that T2DM or even prediabetes may be risk factors for smaller hippocampal and cortical volumes in BD. Abnormal glucose metabolism may accelerate the age-related decline in hippocampal volumes in BD. These findings raise the possibility that improving diabetes care among BD subjects and intervening already at the level of prediabetes could slow brain aging in BD.

Treatment of bipolar disorder: New perspectives

Treatment of bipolar disorder (BD) has traditionally focused on alleviation of acute symptoms and prevention of future recurrences. Current treatment guide-lines advocate more or less similar treatment algorithms for all patients. Such approach largely ignores the clinical, genetic, and pathophysiological heterogeneity of BD, which makes certain patients more (or less) likely to respond to specific treatments. Variables such as family history, comorbidity, course of illness, quality and duration of previous remissions, physical and medical comorbidity, and side-effects may help in selecting the most effective treatment for an individual patient, yet their value is not recognized by current algorithms. As well, polymorphisms of specific genes may prove useful in predicting treatment outcome and/or understanding the pharmacological mechanisms of mood stabilization. Novel molecular targets have recently emerged from studies of mechanisms of action of available mood stabilizers. They include inhibitors of protein kinase C, inhibitors of glycogen synthase kinase, or medications modulating glutamatergic neurotransmission. As well, treatment targets are moving beyond acute symptoms and prevention of mood episodes. Cognitive deficits, persistence of residual symptoms, and increased mortality of BD are recognized as important for outcome of BD, yet are not always adequately addressed by traditional treatments.

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.

Repeated Erythromycin/codeine-induced Psychotic Mania

BackgroundMania is generally associated with bipolar disorder; however, it can be iatrogenic. For instance, antibiotics and corticosteroids can cause manic symptoms. Case ReportHere, we present a case of a young man who had symptoms of psychotic mania after administration of erythromycin and acetaminophen with codeine on 2 separate occasions, with rapid resolution of each episode. ConclusionsAdverse events of psychotic mania have been rarely reported with erythromycin and acetaminophen with codeine, despite these being commonly prescribed medications. Clinicians should be aware that these drugs may be an iatrogenic cause of psychiatric disturbances and that these adverse events are more likely to occur during their concomitant use.

Insulin resistance in bipolar disorder: relevance to routine clinical care

Bipolar disorder (BD) is associated with significant morbidity. Patients are symptomatic for almost one-half of their lives and experience significant disability (1). Many patients go on to have a more progressive form of BD with greater illness burden. These patients have a more chronic course, are refractory to treatment and have poorer outcomes. They require intensive and prolonged care due to lack of remission in an illness that for others is episodic. Obesity, type II diabetes (T2D), and now insulin resistance (IR) have been found to be associated with this more severe form of BD. Together, they contribute significantly to comorbid cardiovascular disease (CVD), the leading cause of death in BD (2). The key difference between IR and the other risk factors is that it does not show up on routine laboratory testing—one has to go looking for it. In a cross-sectional study of 121 patients who were not acutely unwell with bipolar I or bipolar II disorder at the time of study, we found very high rates of IR (32% of patients had IR, 22% had T2D, and only 46% were euglycemic). We made a new diagnosis of T2D in 39% of those with T2D (8% of the total sample), highlighting the high rates of undiagnosed T2D in BD, and none of the patients had been previously diagnosed with IR. Together, this represents 40% of all patients in our sample who had a previously unidentified metabolic disturbance; one that may be affecting clinical outcome. Patients with BD and either T2D or IR had three times higher odds of a chronic course compared to euglycemic patients [50% and 49% versus 27%, respectively; odds ratio (OR) = 3.07, p = 0.007], three times higher odds of rapid cycling (39% and 40% versus 18%, respectively; OR = 3.13, p = 0.012), and were more likely to be refractory to lithium treatment (37% and 37% versus 3%, respectively; OR = 8.40, p < 0.0001), even after controlling for antipsychotic exposure and body mass index (BMI) (3). Of note, patients with IR had equally poor psychiatric outcomes as those with T2D. Our findings suggest that IR may be a factor in the progression of BD to a more advanced stage of disease, even before T2D manifests. This is important, as patients are not screened for IR by either their family physician or their psychiatrist, even when their BD fails to remit. Association does not imply causation, however, and our results do not allow us to determine the direction of a possible causal relationship between IR/T2D and poor outcome in BD. For that, we need prospective studies examining the relationship between IR, glycemic control and outcome in BD. It is not surprising that we find an association between IR and poor outcomes in BD. In our earlier cross-sectional studies we found that patients with BD and T2D had higher rates of rapid cycling, a more chronic course of illness, poorer functioning and greater disability. They had greater medical comorbidity (higher rates of obesity and hypertension) (4). Patients with BD and elevated BMI also had a more chronic course, with longer duration of illness, more anxiety, poorer functioning, greater disability and higher rates of T2D and hypertension (5). We have studied response to lithium (the principal treatment for BD) in relation to BMI. We found that those