Bobo, William V.

Background/Aims: Depressive disorders (DEP) are often comorbid with other chronic conditions. Bidirectional associations between DEP and these conditions are poorly understood. In this study, we aimed to identify chronic conditions with the greatest influence on the DEP diagnosis. Methods: A validated electronic health record-based algorithm was applied to identify DEP patients receiving primary care at Mayo Clinic between 2000 and 2013. Cases were identified on the basis of having > 2 DEP-related ICD-9 diagnosis codes, > 1 antidepressant prescription, and > 3 mentions of in- or outpatient clinical notes for DEP. Controls were matched on birth year (± 2 years), sex and outpatient clinic visits at the same year. We ascertained 26 chronic condition categories, as defined by Chronic Conditions Data Warehouse, using the 5 years of medical records prior to the DEP diagnosis. For each age group at diagnosis (60 years), gradient boosting machine models were applied to estimate relative influence (RI) of the chronic conditions on the DEP diagnosis. Results: A total of 11,219 DEP cases were identified (median age at DEP diagnosis 44 years, 34% male and 89% white). The proportion of subjects with at least one co-occurring condition increased with older age and was higher in DEP cases compared to controls (9.5% vs. 6.9% for subjects 60 years). For subjects aged ≤ 45 years, diabetes mellitus (RI=19.6%) was identified as the most influential condition contributing to the risk of DEP, followed by asthma (RI=11.6%) and rheumatoid arthritis (RI=11.0%). For subjects aged 46–60 years, the most influential condition was rheumatoid arthritis (RI=13.2%) followed by diabetes mellitus (RI=12.9%). For subjects older than 60 years, dementia (RI=10.7%) and rheumatoid arthritis (RI=10.2%) showed similar relative contribution to the risk of DEP. Discussion: Among nonelderly adults who received primary care at Mayo Clinic (2000–2013), diabetes mellitus and rheumatoid arthritis were the strongest risk predictors for a diagnosis of depression among 26 chronic conditions considered. Our results suggest that certain chronic conditions may play a role in exacerbating, precipitating or increasing longitudinal risk of medically significant depression.

ObjectivesWe tested the hypothesis that a common functional variant in brain‐derived neurotrophic factor (BDNF), Val66Met, which has been shown to be associated with increased body mass index (BMI) in schizophrenia (SCZ) and schizoaffective disorder (SAD), is also associated with antipsychotic‐induced weight gain in bipolar disorder (BPD). Association of Val66Met with other metabolic measures, including high‐ and low‐density cholesterol, triglycerides, total cholesterol, fasting blood glucose, and hemoglobin A1c, was also tested.MethodsThis was a 12‐month, prospective, randomized trial of two atypical antipsychotic drugs (APDs) with moderate (risperidone) or high (olanzapine) risk to cause weight gain. Subjects were diagnosed as having BPD (n = 90) and SCZ or SAD (n = 76).ResultsBMI was significantly greater in all diagnoses for Met66 allele carriers at six months (p = 0.01). Met66 carriers with BPD showed a greater increase in the triglycerides/high‐density (HDL) cholesterol ratio (p = 0.01), a key marker for metabolic syndrome related to insulin resistance, and log‐triglycerides (p = 0.04), after three or six months of treatment. Met66 carriers had the greatest increase in log‐triglycerides (p = 0.03) and triglycerides/HDL cholesterol ratio after three months of treatment with risperidone (p = 0.003), and the highest BMI at six months (p = 0.01).ConclusionsThe positive association of BNDF Val66Met with high BMI values replicates previous findings in patients with SCZ and indicates the BDNF Val66Met genotype as a potential risk factor for obesity and insulin resistance measures in patients with BPD receiving antipsychotics as well.

Objective: This study examines characteristics of individuals with bipolar disorder who sought psychotherapy versus those who did not. Methods: Bipolar CHOICE was an 11-site comparative effectiveness study of lithium versus quetiapine in symptomatic outpatients ( N = 482) with bipolar disorder. At baseline, participants’ psychotherapy use within the past 3 months, mood, functioning, and overall health were assessed. Logistic regressions were used to test whether psychotherapy users and non-users differed on various demographic and clinical variables at baseline. Mixed-effects regression was used to determine whether psychotherapy groups differed on response to treatment over the 6-month study. Kaplan-Meier plots and log-rank tests were employed to test whether there were any differences in time to recovery (CGI-BP ≤ 2 for at least 8 weeks) between the groups. Results: Thirty one percent of participants reported using psychotherapy services. Psychotherapy users reported greater medication side effect burden than non-users and were more likely to have moderate to high suicide risk and at least one anxiety disorder. Participants not utilizing medications or psychotherapy had greater mania symptom severity, were younger, and less educated than medication only users. Medication only users were more likely to be married than the other participants. Conclusions: These data suggest that a minority of individuals with bipolar disorder attend psychotherapy services, and those that do have greater illness burden.

ObjectivesIndividuals with bipolar disorder have high rates of other medical comorbidity, which is associated with higher mortality rates and worse course of illness. The present study examined common predictors of medical comorbidity.MethodsThe Clinical and Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study (Bipolar CHOICE) enrolled 482 participants with bipolar I or bipolar II disorder in a six‐month, randomized comparative effectiveness trial. Baseline assessments included current and lifetime DSM‐IV‐TR diagnoses, demographic information, psychiatric and medical history, severity of psychiatric symptoms, level of functioning, and a fasting blood draw. Medical comorbidities were categorized into two groups: cardiometabolic (e.g., diabetes, hyperlipidemia, and metabolic syndrome) and non‐cardiovascular (e.g., seizures, asthma, and cancer). Additionally, we looked at comorbid substance use (e.g., smoking and drug dependence).ResultsWe found that 96.3% of participants had at least one other medical comorbidity. Older age predicted a greater likelihood of having a cardiometabolic condition. Early age of onset of bipolar symptoms was associated with a lower chance of having a cardiometabolic condition, but a greater chance of having other types of medical comorbidity. Additional predictors of other medical comorbidities in bipolar disorder included more time spent depressed, less time spent manic/hypomanic, and longer duration of illness. Medications associated with weight gain were associated with low high‐density lipoprotein and abnormal triglycerides.ConclusionsThere appears to be a substantial medical burden associated with bipolar disorder, highlighting the need for collaborative care among psychiatric and general medical providers to address both psychiatric and other medical needs concomitantly in this group of patients.

ObjectiveTo review the evidence on and estimate the risk of myocardial infarction and stroke in bipolar disorder.MethodA systematic search using MEDLINE, EMBASE, PsycINFO, Web of Science, Scopus, Cochrane Database of Systematic Reviews, and bibliographies (1946 – May, 2013) was conducted. Case‐control and cohort studies of bipolar disorder patients age 15 or older with myocardial infarction or stroke as outcomes were included. Two independent reviewers extracted data and assessed quality. Estimates of effect were summarized using random‐effects meta‐analysis.ResultsFive cohort studies including 13 115 911 participants (27 092 bipolar) were included. Due to the use of registers, different statistical methods, and inconsistent adjustment for confounders, there was significant methodological heterogeneity among studies. The exploratory meta‐analysis yielded no evidence for a significant increase in the risk of myocardial infarction: [relative risk (RR): 1.09, 95% CI 0.96–1.24, P = 0.20; I2 = 6%]. While there was evidence of significant study heterogeneity, the risk of stroke in bipolar disorder was significantly increased (RR 1.74, 95% CI 1.29–2.35; P = 0.0003; I2 = 83%).ConclusionThere may be a differential risk of myocardial infarction and stroke in patients with bipolar disorder. Confidence in these pooled estimates was limited by the small number of studies, significant heterogeneity and dissimilar methodological features.