Body mass index and blood pressure in bipolar patients: Target cardiometabolic markers for clinical practice

Can mindful eating be a psycho-marker of obesity in bipolar disorder?

Introduction

Background and aim: obesity is a very important problem in individuals with bipolar disorder. The study was aimed to determine the prevalence of obesity in individuals with bipolar disorder and to evaluate the effects of factors affecting eating behavior such as mindful eating, impulsivity and eating disorders on the development of obesity in these individuals. Methods: this study is a cross-sectional study. A total of 109 individuals (52 female; 57 male) with bipolar disorder who were in a euthymic state at the time of the interview and underwent outpatient follow-up, treatment and monitorization, and 109 age- and sex-matched healthy individuals as the control group were included in the study. The Mindful Eating Questionnaire-30 (MEQ-30), Three-Factor Eating Questionnaire (TFEQ-21), Barratt Impulsiveness Scale 11-Short Form (BIS-11-SF), and Eating Attitude Test-26 (EAT-26) were used, and anthropometric measurements (height, bodyweight, etc.) were taken. Results: the obesity rate was 50.4 % among the cases and 24.8 % in the control group. Moreover, disinhibition (3.4 ± 0.93), emotional eating (3.5 ± 1.13), and mindfulness (2.6 ± 0.54) scores of individuals with BD were significantly lower than for healthy individuals (3.7 ± 0.82, 4.0 ± 0.93, 2.8 ± 0.55, respectively). The risk of obesity was 5.19 times higher in cases compared to the age- and gender-matched controls (OR = 5.19, 95 % CI (2.01-13.37), p = 0.001). The risk of obesity was 2.76 times higher in those with low mindful eating level (OR = 2.76, 95 % CI (1.07-5.47), p = 0.014) and 4.29 times higher in those using antipsyhotics/mood stabilizers (OR = 4.29, 95 % CI (1.12-12.24), p < 0.001). Conclusion: A comprehensive education program on mindful eating and healthy eating would be helpful in elucidating the mechanisms of the possible relationships between bipolar disorder-specific risk factors and mindful eating.

Prediction of medical admissions after psychiatric inpatient hospitalization in bipolar disorder: a retrospective cohort study

Objective

Bipolar Disorder (BD) is a severe mental illness associated with high rates of general medical comorbidity, reduced life expectancy, and premature mortality. Although BD has been associated with high medical hospitalization, the factors that contribute to this risk remain largely unexplored. We used baseline medical and psychiatric records to develop a supervised machine learning model to predict general medical admissions after discharge from psychiatric hospitalization.

Methods

In this retrospective three-year cohort study of 71 patients diagnosed with BD (mean age=52.19 years, females=56.33%), lasso regression models combining medical and psychiatric records, as well as those using them separately, were fitted and their predictive power was estimated using a leave-one-out cross-validation procedure.

Results

The proportion of medical admissions in patients with BD was higher compared with age- and sex-matched hospitalizations in the same region (25.4% vs. 8.48%). The lasso model fairly accurately predicted the outcome (area under the curve [AUC]=69.5%, 95%C.I.=55-84.1; sensitivity=61.1%, specificity=75.5%, balanced accuracy=68.3%). Notably, pre-existing cardiovascular, neurological, or osteomuscular diseases collectively accounted for more than 90% of the influence on the model. The accuracy of the model based on medical records was slightly inferior (AUC=68.7%, 95%C.I. = 54.6-82.9), while that of the model based on psychiatric records only was below chance (AUC=61.8%, 95%C.I.=46.2-77.4).

Conclusion

Our findings support the need to monitor medical comorbidities during clinical decision-making to tailor and implement effective preventive measures in people with BD. Further research with larger sample sizes and prospective cohorts is warranted to replicate these findings and validate the predictive model.

Cardiometabolic risk indicators in individuals with bipolar disorders: a replication study

OBJECTIVES

We recently conducted the first longitudinal study comparing cardiometabolic risk indicators (CMRIs) between a cohort of individuals with bipolar disorders (BDs) and controls from the general population. Here, we sought to validate the findings in that study using an independent case-control sample.

METHODS

We used data from the St. Göran project's Gothenburg cohort. The BDs group and the control group were examined at baseline and after a median of eight and seven years, respectively. Data collection occurred between March 2009 and June 2022. We used multiple imputation to handle missing data and linear mixed effects model to examine the annual change in CMRIs over the study period.

RESULTS

The baseline cohort included 407 individuals with BDs (mean age 40 years, 63% women) and 56 controls (mean age 43 years, 54% women). Of those, 63 persons with BDs and 42 controls participated at follow-up. At baseline, individuals with BDs had significantly higher mean values of body mass index (β = 0.14, p = 0.003) than controls. Over the study period, the difference in average annual change between the patient and the control group indicated an increase in patients relative to controls in waist-to-hip ratio (0.004 unit/year, p = 0.01), diastolic (0.6 mm Hg/year, p = 0.048), and systolic (0.8 mm Hg/year, p = 0.02) blood pressure.

CONCLUSIONS

This study replicated the main findings from our previous study and showed that central obesity and measures of blood pressure worsened over a relatively short time in individuals with BDs relative to controls. It is vital for clinicians to monitor CMRIs in persons with BDs and to be proactive in preventing cardiometabolic diseases in this high-risk group.

The bi-directional association between bipolar disorder and obesity: Evidence from Meta and bioinformatics analysis

BACKGROUND

The globally high prevalence of both obesity and bipolar disorder makes the bidirectional relationship between the two disorders a pivotal phenomenon; hence, a meta-analysis to synopsize their co-occurrence is indispensable. Psychotropic-induced obesity has been reported to be an important factor linking bipolar disorder and obesity. Nonetheless, the molecular signature of this connection is perplexing.

METHODS

Here, we leverage both meta-analysis and bioinformatics analysis to provide a conspectus and deduce the molecular signature of obesity in bipolar disease patients following psychotropic treatment. Searches were performed on a diverse collection of databases through June 25, 2020. The Newcastle-Ottawa Scale was used to rate the quality of the studies. Analysis of OR, 95% CI, and tests of homogeneity were carried out with STATA software. For the bioinformatics analysis, the LIMMA package which is incorporated into the Gene Expression Omnibus database was used.

RESULTS

Our search yielded 138 studies, of which 18 fitted our inclusion criteria. Individuals who are obese have an increased risk of developing bipolar disorder (pooled adjusted OR = 1.32, 95% CI = 1.01-1.62). In a manner analogous to this, the pooled adjusted odds ratio reveals that patients with bipolar disorder have an increased chance of obesity (OR = 1.68, 95% CI = 1.35-2). To deduce the molecular signature of obesity in bipolar disorder patients following psychotropic treatment, three data sets from the Gene Expression Omnibus database (GSE5392, GSE87610, and GSE35977) were integrated and the genes obtained were validated by a cohort of known single nucleotide polymorphism of obesity via direct overlap. Results indicate genes that are activated after psychotropic treatment. Some of these genes are CYBB, C3, OLR1, CX3CR1, C3AR1, CD53, AIF1, LY86, BDNF, ALOX5AP, CXCL10, and the preponderance falls under mesodermal and PI3K-Akt signaling pathway. The ROC analysis reveals a strong discriminating value between the two groups (UBAP2L AUC = 0.806, p = 1.1e-04, NOVA2 AUC = 0.73, p = 6.7e-03).

CONCLUSION

Our study shows unequivocal evidence of a bi-directional association between bipolar disorder and obesity, but more crucially, it provides a snapshot of the molecular signature of obesity in bipolar patients as a result of psychotropic medication.

Time effect on cardiometabolic risk indicators in patients with bipolar disorder: a longitudinal case-control study

Individuals with bipolar disorder are at increased risk for cardiovascular diseases. Most studies have described increases in cardiometabolic risk indicators (CMRIs) using clinical cut-off values. Further, there are no longitudinal studies on CMRIs. We aimed to investigate continuous measures of CMRIs in individuals with bipolar disorder and controls using both cross-sectional and longitudinal data. We used data from the Swedish St. Göran Bipolar project. Study individuals were examined at baseline and after a median of 6 and 7 years for the control and patient group, respectively. Data were collected December 2005-December 2020. The cohort included 281 individuals with bipolar disorder (mean age 39 years, 59% women) and 114 controls (mean age 38 years, 55% women). Of those, 155 patients and 74 controls also provided follow-up data. At baseline, individuals with bipolar disorder had significantly higher mean values of waist-to-hip ratio (WHR) (β = 0.142, p = 0.001), body mass index (β = 0.150, p = 0.006), plasma triacylglycerol (TAG) (β = 0.218, p < 0.001), total/plasma high-density lipoprotein-cholesterol (TChol/HDL-C) ratio (β = 0.103, p = 0.03), TAG/HDL-C ratio (β = 0.151, p = 0.006), and non-HDL-C (β = 0.168, p = 0.001) than controls. Most CMRIs remained higher in the patient group at follow-up. The difference between patients and controls increased over time for WHR (0.005 unit/year, p < 0.001), and systolic (1.1 mm Hg/year, p = 0.002) and diastolic (0.8 mm Hg/year, p < 0.001) blood pressure. Individuals with bipolar disorder displayed persistently higher levels of nearly all included CMRIs. Over time, a subset of CMRIs worsened in patients relative to controls. This suggests that active measures to counter cardiovascular risk in persons with bipolar disorder should be considered.

The genetics of bipolar disorder with obesity and type 2 diabetes

BACKGROUND

Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.

METHODS

We searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.

RESULTS

The first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk.

LIMITATIONS

The narrative nature of this review.

CONCLUSIONS

Findings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related heterogeneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phenotypes, test gene-environmental interactions and add population diversity.

Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: A systematic review and meta-analysis

OBJECTIVES

The study herein aimed to assess the prevalence of type 2 diabetes mellitus (T2DM), impaired fasting glucose (IFG), as well as general and abdominal obesity in patients with bipolar disorder (BD). We also compared the prevalence of T2DM and general obesity in patients with BD with age- and gender-matched healthy controls.

METHODS

A systematic search of Embase, Medline, PubMed, and APA PsycArticles was conducted from inception to June 2021 without language restrictions. Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS) modified for case-control studies.

RESULTS

A total of forty-nine studies were included in this analysis. The pooled prevalence of T2DM was 9.6% (95% CI, 7.3-12.2%). Patients with BD had a nearly 1.6 times greater risk of developing T2DM compared to their age- and gender-matched controls (RR=1.57, 95% CI 1.36-1.81, p<0.001). In the present analysis, IFG is defined as a fasting plasma glucose (FPG) ≥ 100 mg/dL (FPG≥100) with a prevalence of 22.4% (95% CI, 16.7-28.7%), or as an FPG equal to or greater than 110 mg/d (FPG≥110) with a prevalence of 14.8% (95% CI, 10.8-19.3%). The prevalence of general obesity (BMI≥30 kg/m²) was 29.0% (95% CI, 22.8-35.6%); the risk of obesity was almost twice the rate reported in patients with BD compared to controls (RR=1.67, 95% CI 1.32-2.12, p<0.001). We also observed that more than half of the BD participants had abdominal obesity (i.e., prevalence of 51.1%; 95% CI, 45.0-57.3%).

LIMITATIONS

A significant degree of heterogeneity was detected. Sources of heterogeneity included differences in study designs, inclusion criteria, measurement tools, and data analysis methods.

CONCLUSION

Bipolar disorder is associated with a higher prevalence of T2DM, IFG, general obesity, and abdominal obesity. Type 2 diabetes mellitus and obesity are significantly more prevalent in patients with BD than in their age- and gender-matched controls.

STUDY REGISTRATION

CRD42021258431.

Revisiting the bipolar disorder with migraine phenotype: Clinical features and comorbidity

INTRODUCTION

To evaluate the prevalence and clinical correlates of lifetime migraine among patients with bipolar disorder (BD).

METHODS

In a cross-sectional study, we evaluated 721 adults with BD from the Mayo Clinic Bipolar Disorder Biobank and compared clinical correlates of those with and without a lifetime history of migraine. A structured clinical interview (DSM-IV) and a clinician-assessed questionnaire were utilized to establish a BD diagnosis, lifetime history of migraine, and clinical correlates.

RESULTS

Two hundred and seven (29%) BD patients had a lifetime history of migraine. BD patients with migraine were younger and more likely to be female as compared to those without migraine (p values <0.01). In a multivariate logistic regression model, younger age (OR=0.98, p<0.01), female sex (OR=2.02, p<0.01), higher shape/weight concern (OR=1.04, p=0.02), greater anxiety disorder comorbidities (OR=1.24, p<0.01), and evening chronotype (OR=1.65, p=0.03) were associated with migraine. In separate regression models for each general medical comorbidity (controlled for age, sex, and site), migraines were significantly associated with fibromyalgia (OR=3.17, p<0.01), psoriasis (OR=2.65, p=0.03), and asthma (OR=2.0, p<0.01). Participants with migraine were receiving ADHD medication (OR=1.53, p=0.05) or compounds associated with weight loss (OR=1.53, p=0.02) at higher rates compared to those without migraine.

LIMITATIONS

Study design precludes determination of causality. Migraine subtypes and features were not assessed.

CONCLUSIONS

Migraine prevalence is high in BD and is associated with a more severe clinical burden that includes increased comorbidity with pain and inflammatory conditions. Further study of the BD-migraine phenotype may provide insight into common underlying neurobiological mechanisms.