Impaired glucose metabolism moderates the course of illness in bipolar disorder

Type 2 diabetes mellitus is associated with manic morbidity in elderly patients with mood disorders

The association between mood disorders, especially bipolar disorder (BD), and metabolic disorders, is long known. However, to which extent metabolic disorders affect the course of mood disorders in late life is still open to inquiring. To assess the impact of type 2 diabetes mellitus (T2DM) on late-life mood disorders a retrospective chart review was performed. Elderly depressive patients (≥ 65 years) diagnosed with Major Depressive Disorder (N = 57) or BD (N = 43) and followed up for at least 18 months were included and subdivided according to the presence of T2DM comorbidity. Vascular encephalopathy (39.1% vs. 15.6%, P  = 0.021) and neurocognitive disorders (21.7% vs. 5.2%, P  = 0.028), were more frequently reported in patients with T2DM than in those without. Patients with T2DM showed a greater percentage of follow-up time in manic episodes (r = -0.23, P  = 0.020) and a higher rate of manic episode(s) during follow-up (21.7% vs. 5.2%, P  = 0.028) than those without. When restricting longitudinal analyses to patients with bipolar spectrum disorders, results were confirmed. In line with the well-known connection between BD and metabolic disorders, our data support an association between T2DM and unfavorable course of illness in the elderly with BD.

Associations of Circulating Biomarkers with Disease Risks: A Two-Sample Mendelian Randomization Study

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by four or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in four or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

Associations of Circulating Biomarkers with Disease Risks: a Two-Sample Mendelian Randomization Study

Background

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships.

Methods

Here we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR Egger. We use the MR-base resource (v0.5.6)1 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016)2-4 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan).

Results

We report novel causal relationships found by 4 or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in 4 or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction.

Conclusions

This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

Prevalence of insulin resistance and its associated factors in drug-naïve patients with bipolar disorder among Han Chinese population

BACKGROUND

Metabolic syndrome (Mets) is commonly seen in bipolar disorder (BD). As the key component and early biological index of Mets, insulin resistance (IR) among BD has received more and more attention. However, little is known about the prevalence of IR and its associated factors in drug-naïve patients with (BD), especially among Han Chinese population.

METHODS

A cross-sectional study was conducted on 125 drug-naïve patients with bipolar disorder (BD) and 85 healthy controls (HC). The Homeostatic Model Assessment of insulin resistance (HOMA-IR) was calculated, and IR was defined as HOMA-IR greater than the 75th percentile value for health controls (2.35). Clinical characteristics of BD were collected through semi-structural interview performed by a trained interviewer with background of psychiatric education.

RESULTS

Among the measured anthropocentric variables including BMI, waist circumference, abdomen circumference, hipline, and hip-waist ratio, waist circumference was found to be the most closely related to IR (0R = 1.070, 95%CI = 1.031-1.110, P < 0.001). Male was another factor that was associated with IR (OR = 2.281, 95%CI = 1.107-4.702, P = 0.025). After adjusted for gender and waist circumference, the risk of IR was significantly higher in bipolar disorder than in healthy controls (OR = 2.66, 95%CI = 1.364-5.214, P = 0.004). No significant association was found between IR and any of the observed physical and mental comorbidities, any characteristic of illness course including age onset, number of mixed episodes, types of current state, duration of current episode, duration of illness course, rapid cycling, number of mood episodes, and subgroup of BD. Hypersomnia was the only symptomatic feature that was significantly associated with IR (OR = 0.316, 95%CI = 0.124-0.803, P = 0.016).

CONCLUSIONS

Bipolar disorder increases two-to-three-fold risk of IR, both circumference and male are the risk factors of IR but hypersomnia act as a protective factor.

Ketogenic Diet Intervention on Metabolic and Psychiatric Health in Bipolar and Schizophrenia: A Pilot Trial

The ketogenic diet (KD, also known as metabolic therapy) has been successful in the treatment of obesity, type 2 diabetes, and epilepsy. More recently, this treatment has shown promise in the treatment of psychiatric illness. We conducted a 4-month pilot study to investigate the effects of a KD on individuals with schizophrenia or bipolar disorder with existing metabolic abnormalities. Twenty-three participants were enrolled in a single-arm trial. Results showcased improvements in metabolic health, with no participants meeting metabolic syndrome criteria by study conclusion. Adherent individuals experienced significant reduction in weight (12 %), BMI (12 %), waist circumference (13 %), and visceral adipose tissue (36 %). Observed biomarker enhancements in this population include a 27 % decrease in HOMA-IR, and a 25 % drop in triglyceride levels. In psychiatric measurements, participants with schizophrenia showed a 32 % reduction in Brief Psychiatric Rating Scale scores. Overall Clinical Global Impression (CGI) severity improved by an average of 31 %, and the proportion of participants that started with elevated symptomatology improved at least 1-point on CGI (79 %). Psychiatric outcomes across the cohort encompassed increased life satisfaction (17 %) and enhanced sleep quality (19 %). This pilot trial underscores the potential advantages of adjunctive ketogenic dietary treatment in individuals grappling with serious mental illness.

Causal effects of diabetic retinopathy on depression, anxiety and bipolar disorder in the European population: a Mendelian randomization study

PURPOSE

To verify the causal effects of diabetic retinopathy (DR) on depression, anxiety and bipolar disorder (BD).

METHODS

Mendelian randomization (MR) analysis was performed to identify the causal relationships between DR and depression or anxiety or BD via using DR-related GWAS data (14,584 cases and 176,010 controls), depression-related GWAS data (59,851 cases and 113,154 controls), anxiety-related GWAS data (7016 cases and 14,745 controls) and BD-related GWAS data (41,917 cases and 371,549 controls). The inverse-variance weighted (IVW) model was adopted to estimate the causal relationship. The outcome was expressed as odds ratio (OR) with 95% confidence intervals (CI).

RESULTS

The MR analysis results presented that DR was causally associated with a significantly increased risk of BD in the European population (IVW, OR = 1.06, 95%CI [1.03, 1.08], P = 2.44 × 10-6), while DR was unable to causally influence the risk of depression (IVW, OR = 1.01, 95%CI [0.99, 1.04], P = 0.32) and anxiety (IVW, OR = 0.97, 95%CI [0.89, 1.06], P = 0.48) in the European population. Subgroup analysis based on BD identified DR causally increased the risk of bipolar I disorder (BD I) but not bipolar II disorder (BD II). Sensitivity analysis results did not show any pleiotropy and heterogeneity in both groups of analyses, indicating that the results were stable and reliable.

CONCLUSIONS

The results of the current MR analysis indicated a causal relationship between DR and BD in the European population, while there was no causal connection between DR and depression or anxiety. However, further research is needed to confirm these conclusions.

Insulin resistance in bipolar disorder: A systematic review of illness course and clinical correlates

BACKGROUND

Although insulin resistance (IR) and cardiometabolic syndrome are prevalent in patients with bipolar disorder (BD), only a few studies have attempted to precisely assess the degree and clinical impact of IR in BD.

METHODS

A comprehensive search was conducted from multiple research databases through May 2022, following a pre-defined protocol (PROSPERO: CRD42022359259). We extracted neuroimaging, cognition, illness course, and treatment response findings from individuals with BD with evidence of IR compared with euglycemic BD individuals.

RESULTS

Of 1436 identified articles, 10 reports fulfilling inclusion criteria were included (n = 1183). BD patients with IR displayed worse composite verbal memory scores and worse executive function and exhibited smaller hippocampal volumes along with prefrontal neurochemical alterations compared to euglycemic BD patients. Fixed-effect meta-analysis revealed that BD patients with impaired glucose metabolism (IGM) were more likely to develop a chronic and rapid cycling course when compared with euglycemic BD patients (k = 2, OR = 2.96, 95 % CI 1.69-5.17, OR = 2.88, 95 % CI 1.59-5.21, p < 0.001, respectively), with a trend for significantly lower Global Assessment of Functioning scores (k = 5, MD = -4, 95 % CI -8.23-0.23, p = 0.06). BD patients with IGM displayed a higher rate of poor response to mood stabilizers when compared with euglycemic BD patients (k = 2, OR = 6.74, 95 % CI 1.04-43.54, p = 0.04).

LIMITATIONS

Cross-sectional design and small sample sizes of studies included limit the generalizability of results.

CONCLUSION

IR is associated with worse clinical outcomes of BD and inadequate treatment response. Implementing strategies to prevent and treat IR in BD is crucial to improve the prognosis of such a difficult-to-treat population.

Association between impaired glucose metabolism and long-term prognosis at the time of diagnosis of depression: Impaired glucose metabolism as a promising biomarker proposed through a machine-learning approach

BACKGROUND

Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.

METHODS

Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model's performance. Kaplan-Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.

RESULTS

A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02-1.41, p = 0.027) at a 3-year follow-up.

CONCLUSIONS

We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.

Insulin resistance disrupts white matter microstructure and amplitude of functional spontaneous activity in bipolar disorder

BACKGROUND

Bipolar disorder (BD) is linked to several structural and functional brain alterations. In addition, BD patients have a three-fold increased risk of developing insulin resistance, which is associated with neural changes and poorer BD outcomes. Therefore, we investigated the effects of insulin and two derived measures (insulin resistance and sensitivity) on white matter (WM) microstructure, resting-state (rs) functional connectivity (FC), and fractional amplitude of low-frequency fluctuation (fALFF).

METHODS

BD patients (n = 92) underwent DTI acquisition, and a subsample (n = 22) underwent rs-fMRI. Blood samples were collected to determine insulin and glucose levels. The Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) were computed. DTI data were analyzed via tract-based spatial statistics and threshold-free cluster enhancement. From rs-fMRI data, both ROI-to-ROI FC matrices and fALFF maps were extracted.

RESULTS

Insulin showed a widespread negative association with fractional anisotropy (FA) and a positive effect on radial diffusivity (RD) and mean diffusivity (MD). HOMA-IR exerted a significant effect on RD in the right superior longitudinal fasciculus, whereas QUICKI was positively associated with FA and negatively with RD and MD in the left superior longitudinal fasciculus, left anterior corona radiata, and forceps minor. fALFF was negatively modulated by insulin and HOMA-IR and positively associated with QUICKI in the precuneus. No significant results were found in the ROI-to-ROI analysis.

CONCLUSION

Our findings suggest that WM microstructure and functional alterations might underlie the effect of IR on BD pathophysiology, even if the causal mechanisms need to be further investigated.

Peripheral insulin sensitivity predicting cognitive function in euthymic bipolar disorder patients

OBJECTIVE

High prevalence of insulin resistance (IR) has been reported in bipolar disorder (BD) patients. Importantly, impaired insulin sensitivity could modulate the course and treatment outcome in BD. Here, we hypothesized that insulin sensitivity could be potentially associated with the neurocognitive trajectory in euthymic BD. We aimed to examine differences in insulin sensitivity and executive function between BD patients and controls.

METHODS

Sixty-two patients with BD receiving mood stabilizer treatment and 62 controls, matching age, sex, and body mass index, were recruited in this study. Insulin sensitivity was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR). The Wisconsin card-sorting test (WCST) was applied to test participants' ability to shift cognitive set. Group differences were measured and multivariate regression analysis was performed to examine relationships among factors.

RESULTS

The results indicated that the HOMA-IR (P = .048) value in the patients with BD were significantly higher than those in controls. With regards to executive function, the BD patients performed significantly poorer than the control subjects (P < .05). Moreover, the interaction effect between BD diagnosis and HOMA-IR value on the WCST-preservation errors was significant (P = .01), and post-hoc analyses showed that the cognitive abilities were worse in the BD patients with a higher IR than in the others groups.

CONCLUSION

Insulin sensitivity is associated with the neurocognitive performance in euthymic BD patients. Although the underlying mechanisms remain unclear, interventions to improve insulin sensitivity could potentially improve the functional outcome of BD.

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.

Biochemical and Endocrine Parameters for the Discrimination and Calibration of Bipolar Disorder or Major Depressive Disorder

OBJECTIVES

Conventional biochemical indexes may have predictive values in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

This study included 2,470 (BD/MDD = 1,333/1,137) hospitalized patients in Shanghai as training sets and 2,143 (BD/MDD = 955/1,188) in Hangzhou as test sets. A total of 35 clinical biochemical indexes were tested, including blood cells, immuno-inflammatory factors, liver enzymes, glycemic and lipid parameters, and thyroid and gonadal hormones. A stepwise analysis of a multivariable logistic regression was performed to build a predictive model to identify BD and MDD.

RESULTS

Most of these biochemical indexes showed significant differences between BD and MDD groups, such as white blood cell (WBC) in the hematopoietic system, uric acid (UA) in immuno-inflammatory factors, direct bilirubin (DBIL) in liver function, lactic dehydrogenase (LDH) in enzymes, and fasting blood glucose (FBG) and low-density lipoprotein (LDL) in glucolipid metabolism (p-values < 0.05). With these predictors for discrimination, we observed the area under the curve (AUC) of the predictive model to distinguish between BD and MDD to be 0.772 among men and 0.793 among women, with the largest AUC of 0.848 in the luteal phase of women. The χ² values of internal and external validation for male and female datasets were 2.651/10.264 and 10.873/6.822 (p-values < 0.05), respectively. The AUCs of the test sets were 0.696 for males and 0.707 for females.

CONCLUSION

Discrimination and calibration were satisfactory, with fair-to-good diagnostic accuracy and external calibration capability in the final prediction models. Female patients may have a higher differentiability with a conventional biochemical index than male patients.

TRIAL REGISTRATION

ICTRP NCT03949218. Registered on 20 November 2018. Retrospectively registered. https://www.clinicaltrials.gov/ct2/show/NCT03949218?id=NCT03949218&rank=1.

Investigating the association between diabetes and mental health: A train-and-test approach

Diabetes is a chronic health condition that affects how the body turns food into energy. Research has demonstrated a relationship between diabetes and various mental health issues, which include psychiatric disorders and other problems that are specific for people living with diabetes. Although previous studies have shed light on the associations between diabetes and various types of mental health issues with a focus on depression and anxiety, much less is known about how diabetes is associated with other dimensions of mental health such as social dysfunction and anhedonia and loss of confidence in a large nationally representative survey from the United Kingdom. The aim of the current study is to replicate the factor structure of the GHQ-12 and investigate how diabetes is related to general mental health and dimensions of mental health. By adopting a train-and-test approach to data from the UKHLS including 2,255 diabetes patients and 14,585 age and sex-matched participants who indicated that they were not clinically diagnosed with diabetes, the current study found that hypotheses are well-supported by the results.

Does metabolic syndrome or its component factors alter the course of bipolar disorder? A systematic review

Metabolic syndrome (MetS) and its component factors, obesity, hypertension, dyslipidaemia and insulin resistance, have shown a bidirectional relationship with the prevalence and severity of bipolar disorder (BD). A systematic search of electronic databases (Pubmed, PsycINFO, clinicaltrials.gov) was conducted to explore and integrate current evidence about the role of MetS and its component factors with clinical outcomes of BD. Thirty-four articles met the inclusion criteria. Studies were grouped by the metabolic factors assessed, which included MetS, obesity and body mass index (BMI), dyslipidaemia, impaired glucose metabolism (IGM), diabetes mellitus and hypertension. They were then classified according to outcomes such as course of episodes, rapid cycling, suicidal behavior, treatment response, and global and cognitive functioning. Although current evidence remains controversial in most aspects of clinical outcomes, metabolic risk factors could alter the course of BD, with worse global functioning, poorer treatment response and a chronic course of illness, as well as enhancing rapid cycling. Further research is needed to elucidate the role of each risk factor in the mentioned outcomes.

The Role of Mitochondria in Mood Disorders: From Physiology to Pathophysiology and to Treatment

Mitochondria are cellular organelles involved in several biological processes, especially in energy production. Several studies have found a relationship between mitochondrial dysfunction and mood disorders, such as major depressive disorder and bipolar disorder. Impairments in energy production are found in these disorders together with higher levels of oxidative stress. Recently, many agents capable of enhancing antioxidant defenses or mitochondrial functioning have been studied for the treatment of mood disorders as adjuvant therapy to current pharmacological treatments. A better knowledge of mitochondrial physiology and pathophysiology might allow the identification of new therapeutic targets and the development and study of novel effective therapies to treat these specific mitochondrial impairments. This could be especially beneficial for treatment-resistant patients. In this article, we provide a focused narrative review of the currently available evidence supporting the involvement of mitochondrial dysfunction in mood disorders, the effects of current therapies on mitochondrial functions, and novel targeted therapies acting on mitochondrial pathways that might be useful for the treatment of mood disorders.

Insulin resistance takes center stage: a new paradigm in the progression of bipolar disorder

Bipolar Disorder (BD) is a major psychiatric illness affecting up to 5% of the population. BD can progress over time to a chronic "neuroprogressive" course with cognitive and functional impairment. Currently, there are no validated predictors indicating which patients will develop a neuroprogressive course and there are no specific treatments. This review presents data supporting a novel hypothesis on the mechanisms underlying bipolar neuroprogression. Insulin resistance (IR) is present in 52% of BD patients and is associated with chronic course, treatment nonresponse, adverse brain changes and cognitive impairment. Further, bipolar morbidity increases 12-fold following the onset of IR indicating that IR may modify disease progression. I review evidence that IR is a testable and treatable modifying factor in neuroprogression and that reversing IR may be an efficient (and perhaps the only) means of obtaining remission in some patients. I draw a parallel with Helicobacter pylori in peptic ulcer disease (a novel mechanism that brought together two previously unrelated phenomena that uncovered a new treatment approach). This model of bipolar progression combines shared dysregulated mechanisms between IR and BD, allowing for early screening, case finding, and monitoring for neuroprogression, with the potential for intervention that could prevent advanced bipolar illness. KEY MESSAGES Neuroprogression in bipolar disorder is defined by a more severe form of illness and poor outcome. Currently, there are no validated predictors of neuroprogression, which could help inform treatment and improve prognosis. Insulin resistance is present in more than half of all bipolar patients and is associated with a chronic course of illness, lack of response to mood stabilizing treatment, cognitive impairment and poor functional outcomes. Insulin resistance may modify the course of bipolar disorder and promote neuroprogression. Insulin resistance may be a testable and potentially modifiable risk factor for neuroprogression in bipolar disorder.

Attenuated inflammatory response of monocyte-derived macrophage from patients with BD: a preliminary report

BACKGROUND

Innate immune system dysfunction has been recognized as an important element in the pathophysiology of bipolar disorder (BD). We aimed to investigate whether there are differences in the response of macrophages derived from patients in the early stages and late stages of BD and healthy subjects.

METHODS

Human monocytes purified from peripheral blood mononuclear cells (PBMCs) of patients with BD type I (n = 18)-further classified into early- and late stage BD patients according to their functioning- and from healthy individuals (n = 10) were differentiated into macrophages in vitro. Monocyte-derived macrophages (M) were exposed to IFNγ plus LPS-M(IFNγ + LPS)- or IL-4-M(IL-4)-to induce their polarization into the classical (also called M1) or alternative (also called M2) activation phenotypes, respectively; or either Mψ were not exposed to any stimuli characterizing the resting state (denominated M0). In vitro secretion of cytokines, such as IL-1β, IL-6, IL-10, and TNF-α, was used as an index of macrophage activity.

RESULTS

M(IFNγ + LPS) from late-stage BD patients produced less amount of IL-1β, IL-6, and IL-10 when compared to early-stage BD patients and healthy controls. Following alternative activation, M(IL-4) derived from late-stage patients secreted less IL-6 compared to the other groups. TNFα was less secreted by all macrophage phenotypes derived from late-stage patients when compared to healthy controls only (p < 0.005). Mψ from late-stage patients exhibited lower production of IL-1β and IL-10 compared to macrophages from healthy subjects and early-stage patients respectively. Interestingly, cytokines secretion from M(IFNγ + LPS), M(IL-4) and Mψ were similar between early-stage patients and healthy controls.

CONCLUSION

Our results suggest a progressive dysfunction in the response of peripheral innate immune cells of BD patients in the late stages of the illness. This failure in the regulation of the immune system function may be implicated in the multisystemic progression of BD.

Metabolic profile in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives

Objective

The prevalence of metabolic syndrome and insulin resistance is twice as high in patients with bipolar disorder compared with the general population, and possibly associated with a disabling illness trajectory of bipolar disorder, an increased risk of cardiovascular disease and premature death. Despite these detrimental effects, the prevalence of metabolic syndrome and insulin resistance in patients newly diagnosed with bipolar disorder and their unaffected first-degree relatives is largely unknown.

Methods

In a cross-sectional study of 206 patients with newly diagnosed bipolar disorder, 50 of their unaffected first-degree relatives and 109 healthy age- and sex-matched individuals, we compared the prevalence of metabolic syndrome and insulin resistance (HOMA-IR). In patients with bipolar disorder, we further investigated illness and medication variables associated with the metabolic syndrome and insulin resistance.

Results

Higher rates of metabolic syndrome (odds ratio = 3.529, 95% CI 1.378–9.041, P = 0.009) and levels of insulin resistance (B = 1.203, 95% CI 1.059–1.367, P = 0.005) were found in patients newly diagnosed with bipolar disorder, but not in their unaffected first-degree relatives compared with matched healthy individuals (data adjusted for sex and age). Most patients with bipolar disorder (94.7%) were diagnosed within the preceding 2 years, and the average illness duration, defined as time from first mood episode, was 10 years.

Conclusion

Our findings of elevated prevalence of metabolic syndrome and insulin resistance in patients with newly diagnosed bipolar disorder highlight the importance of screening for these conditions at an early stage to employ adequate and early care reducing the risk of cardiovascular disease and premature death.

Impaired Glucose Metabolism in Bipolar Patients: The Role of Psychiatrists in Its Detection and Management

Bipolar patients have a higher risk of type 2 diabetes and obesity, which are associated with cardiovascular diseases as the leading cause of death in this group. Additionally, there is growing evidence that impaired glucose metabolism in bipolar patients is associated with rapid cycling, poor response to mood stabilizers and chronic course of illness. The aim of the study was to assess the prevalence of type 2 diabetes and other types of impaired glucose metabolism in bipolar patients along with an evaluation of the Fasting Triglycerides and Glucose Index (TyG) as a method of the insulin sensitivity assessment. The analysis of fasting glycemia, insulinemia and lipid profile in euthymic bipolar patients was performed, and the Homeostasis model assessment for insulin resistance (HOMA-IR) and TyG were computed. Type 2 diabetes was observed in 9% and insulin resistance with HOMA-IR in 48% of patients. The TyG and HOMA-IR indices were correlated (p < 0.0001), the TyG index value of 4.7 had the highest sensitivity and specificity for insulin resistance detection. The usefulness of TyG in the recognition of insulin resistance in bipolar patients was suggested. The significant role of psychiatrists in the detection and management of impaired glucose metabolism in bipolar patients was presented.

Laparoscopic radical cystectomy with pelvic re-peritonealization: the technique and initial clinical outcomes

Background

Delayed bowel function recovery and postoperative ileus are relatively serious complications of laparoscopic radical cystectomy (LRC). Our study aimed to determine whether performing pelvic re-peritonealization reduces the incidence of these complications.

Methods

Clinical data of 78 patients who had undergone LRC with pelvic re-peritonealization from August 2015 to December 2017 were retrospectively collected and compared with those of 92 patients who had undergone LRC alone between January 2013 and July 2015 in our institution. Differences in duration of surgery, estimated blood loss, time to recovery of bowel function, the complications of intestinal and blood vessel injury, and incidence of postoperative ileus between the two groups were analyzed.

Results

Baseline characteristics such as age, sex and BMI were balanced between the two groups. There were no significant differences in duration of surgery (P = 0.072), estimated blood loss (P = 0.717), or incidence of intestinal obstruction (P = 0.225) between the two groups. Interestingly, patients who had undergone pelvic re-peritonealization recovered bowel function more rapidly than those had not (2.79 d vs. 3.72 d, P = 0.001). Additionally, hospitalization stay was significantly shorter for patients with re-peritonealization than for those without (5.46 d vs. 6.68 d, P = 0.029).

Conclusions

Compared with LRC alone, LRC with pelvic re-peritonealization as described in the present study had comparable perioperative complications, but was associated with more rapid gastrointestinal recovery and shorter hospitalization stay.

Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach

OBJECTIVE

Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity.

METHOD

A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States. Machine learning algorithms were used on clinical and biological variables to enhance characterization of patients.

RESULTS

After adjustment, patients with emotional hyper-reactivity (n = 306) had significantly higher levels of systolic and diastolic blood pressure (P < 1.0 × 10^-8 ), high-sensitivity C-reactive protein (P < 1.0 × 10^-8 ), fasting glucose (P < 2.23 × 10^-6 ), glycated hemoglobin (P = 0.0008) and suicide attempts (P = 1.4 × 10^-8 ). Using models of combined clinical and biological factors for distinguishing BD patients with and without emotional hyper-reactivity, the strongest predictors were: systolic and diastolic blood pressure, fasting glucose, C-reactive protein and number of suicide attempts. This predictive model identified patients with emotional hyper-reactivity with 84.9% accuracy.

CONCLUSION

The assessment of emotional hyper-reactivity in remitted BD patients is clinically relevant, particularly for identifying those at higher risk of cardiometabolic dysfunction, chronic inflammation, and suicide.

Course of bipolar illness worsens after onset of insulin resistance

Cross-sectional studies indicate that comorbid insulin resistance (IR) and type 2 diabetes are associated with a more severe course of bipolar disorder (BD); however, this relationship has not previously been assessed longitudinally. To address this, we reviewed health records of a case series of six patients with BD and comorbid IR. Severity and length of affective episodes (both mania and depression) over the lifetime were recorded using the Affective Morbidity Index; these data were obtained from ongoing prospective follow-up and from detailed retrospective chart reviews. All six patients with a previously episodic, relapsing-remitting course of illness experienced a worsening of morbidity after the onset of laboratory-demonstrated IR. These results suggest that IR may be a potential testable, modifiable factor in the progression of BD from a treatment responsive (episodic) to a non-responsive (chronic) course of illness.

Obesity and frontal-striatal brain structures in offspring of individuals with bipolar disorder: Results from the global mood and brain science initiative

OBJECTIVES

To compare frontal-striatal brain volumes between offspring of individuals with bipolar disorder (BD) and healthy controls; to investigate the associations of body mass index (BMI) and age with brain volumes; and to assess the moderating effects of BMI and age on the relationship between risk status and structural brain differences.

METHODS

We cross-sectionally assessed structural regional and global brain volumes using magnetic resonance imaging and BMI among 53 BD offspring subjects, stratified by risk status, and 23 non-BD offspring controls (aged 8-28 years). Analyses of variance and covariance and linear regression analyses were conducted to investigate the associations between BMI and measures of brain volume, as well as the interaction effects between age, BMI, and risk status on brain volumes.

RESULTS

After adjusting for age, sex, and intracranial volume, higher BD risk status was associated with lower bilateral cerebellar cortical and right pars orbitalis volumes. Higher BMI was significantly associated with greater brain volumes in frontal and subcortical structures. A significant interaction effect between BMI and risk status was observed in right middle frontal volume. The moderating effect of BMI on brain volume was most robustly observed among subjects aged 14-19 years and less robustly observed among those aged 20-28 years; BMI and brain volumes were negatively correlated among subjects aged 8-13 years.

CONCLUSIONS

Alterations in brain structures in individuals at risk for BD may be moderated by BMI. Obesity among individuals with a family history of BD may confer additional risk, particularly in mid-adolescence.

BDNF and BMI effects on brain structures of bipolar offspring: results from the global mood and brain science initiative

OBJECTIVE

To compare brain-derived neurotrophic factor (BDNF) levels between offspring of individuals with bipolar disorders (BD) and healthy controls (HCs) and investigate the effects of BDNF levels and body mass index (BMI) on brain structures.

METHOD

Sixty-seven bipolar offspring and 45 HCs were included (ages 8-28). Structural images were acquired using 3.0 Tesla magnetic resonance imaging. Serum BDNF levels were measured using enzyme-linked immunosorbent assay. Multivariate and univariate analyses of covariance were conducted.

RESULTS

Significantly higher BDNF levels were observed among bipolar offspring, relative to HCs (P > 0.025). Offspring status moderated the association between BDNF and BMI (F₁ =4.636, P = 0.034). After adjustment for relevant covariates, there was a trend for a significant interaction of group and BDNF on neuroimaging parameters (Wilks'λ F_56,94 =1.463, P = 0.052), with significant effects on cerebellar white matter and superior and middle frontal regions. Brain volume and BDNF were positively correlated among HCs and negatively correlated among bipolar offspring. Interactions between BDNF and BMI on brain volumes were non-significant among HCs (Wilks'λ F_28,2 =2.229, P = 0.357), but significant among bipolar offspring (Wilks'λ F_28,12 =2.899, P = 0.028).

CONCLUSION

Offspring status and BMI moderate the association between BDNF levels and brain structures among bipolar offspring, underscoring BDNF regulation and overweight/obesity as key moderators of BD pathogenesis.

FGF21 Is Associated with Metabolic Effects and Treatment Response in Depressed Bipolar II Disorder Patients Treated with Valproate

BACKGROUND

Patients with bipolar disorder are at high risk of metabolic disturbance after mood stabilizer treatment. However, the mediators linking the two conditions remain unknown. In this study, we investigated whether fibroblast growth factor-21 (FGF21) was associated with metabolic effects and treatment response in depressed bipolar disorder patients.

METHODS

We recruited 78 community-dwelling controls and 137 bipolar disorder patients; the latter were interviewed using the Chinese Version of the Modified Schedule of Affective Disorder and Schizophrenia-Life Time. Upon study entry, the bipolar disorder patients were all in a major depressive status, with 17-item Hamilton Depression Rating Scale (HDRS) scores >15. They received valproate (500-1000 mg daily) for 12 weeks, and fluoxetine 20 mg daily was permitted to treat depressive symptoms. Fasting plasma level of FGF21, lipid profiles, and body weight were collected at baseline and after 12 weeks of treatment.

RESULTS

At baseline, the demographic characteristics, FGF21 level, and metabolic indices did not differ significantly between the controls and bipolar disorder patients. After 12 weeks of treatment, the FGF21 level (167.7±122.0 to 207.1±162.3 pg/mL, P=.001), body weight and waist circumference had increased significantly (P<.001 and P=.028, respectively). Moreover, the change in FGF21 level was significantly correlated with the changes in HDRS score (r=0.393, P=.002), total cholesterol (r=-0.344, P=.008), and low-density lipoprotein (r=-0.347, P=.007).

CONCLUSIONS

The central and peripheral mediating effects of FGF21 on bipolar disorder depression treatment might be opposite. High peripheral FGF21 levels might link regulation of metabolic effect and resistance to treatment in bipolar disorder.

Body mass index associates with white matter microstructure in bipolar depression

OBJECTIVES

Obesity has been reported in over 60% of bipolar disorder (BD) patients. It worsens the severity of illness, and influences cognition and functional outcomes. White matter (WM) abnormalities are one of the most consistently reported findings in neuroimaging studies of BD. We hypothesized that body mass index (BMI) could correlate with WM integrity in bipolar patients.

METHODS

We evaluated BMI in a sample of 164 depressed patients affected by BD. We performed whole-brain tract-based spatial statistics with threshold-free cluster enhancement for the diffusion tensor imaging (DTI) measures of WM integrity: fractional anisotropy; axial, radial, and mean diffusivity.

RESULTS

We observed that BMI was associated with DTI measures of WM integrity in several fiber tracts: anterior corona radiata, anterior thalamic radiation, inferior fronto-occipital fasciculus and corpus callosum.

CONCLUSIONS

The association of BMI in key WM tracts that are crucial to mood regulation and neurocognitive functioning suggests that BMI might contribute to the pathophysiology of BD through a detrimental action on structural connectivity in critical cortico-limbic networks.

Adverse effects of obesity on cognitive functions in individuals at ultra high risk for bipolar disorder: Results from the global mood and brain science initiative

BACKGROUND

The burden of illness associated with bipolar disorder (BD) warrants early pre-emption/prevention. Prediction models limited to psychiatric phenomenology have insufficient predictive power. Herein, we aimed to evaluate whether the presence of overweight/obesity is associated with greater cognitive decline in individuals at high risk (HR) or ultra high risk (UHR) for BD.

METHODS

We conducted a retrospective analysis to investigate the moderational role of body mass index (BMI) on measures of cognitive function. Subjects between the ages of 8 and 28 years with a positive family history of BD were compared to age-matched controls with a negative family history of BD. Subjects with at least one biological parent with bipolar I/II disorder were further stratified into UHR or HR status by the presence or absence, respectively, of subthreshold hypomanic, major depressive, attenuated psychotic, and/or attention-deficit/hyperactivity disorder symptoms.

RESULTS

A total of 36 individuals at HR for BD, 33 individuals at UHR for BD, and 48 age-matched controls were included in the analysis. Higher BMI was significantly associated with lower performance on measures of processing speed (i.e. Brief Assessment of Cognition in Schizophrenia-symbol coding: r=-.186, P=.047) and attention/vigilance (i.e. Continuous Performance Test-Identical Pairs: r=-.257, P=.006). There were trends for negative correlations between BMI and measures of working memory (i.e. Wechsler Memory Scale-III Spatial Span: r=-0.177, P=.059) and overall cognitive function (i.e. Measurement and Treatment Research to Improve Cognition in Schizophrenia composite score: r=-.157, P=.097). Negative associations between BMI and cognitive performance were significantly stronger in the UHR group than in the HR group, when compared to controls.

CONCLUSIONS

Individuals at varying degrees of risk for BD exhibit greater cognitive impairment as a function of co-existing overweight/obesity. Prediction models for BD may be substantively informed by including information related to overweight/obesity and, perhaps, other general medical conditions that share pathology with BD. Our findings herein, as well as the salutary effects of bariatric surgery on measures of cognitive function in obese populations, provide the rationale for hypothesizing that mitigating excess weight in individuals at elevated risk for BD may forestall or prevent declaration of illness.

Update on bipolar disorder biomarker candidates

INTRODUCTION

Bipolar disorder is a chronic and disabling mood disorder with a complex pathophysiological basis. A significant percentage of patients do not receive correct diagnosis which directly influences therapeutic response, rendering recovery troublesome. There is a long-standing need for proper non-clinically based tools for diagnosis, treatment selection and follow-up of such patients. Areas covered: In the past decade, the scientific community has shown a great interest in biomarker development. Here, we highlight the different potential biomarkers and we discuss their feasibility and their possible clinical relevance. Expert commentary: To date, despite the major ongoing trials and consortia with promising future perspectives, no reliable biomarker of bipolar disorder has been fully defined.