The genetics of bipolar disorder with obesity and type 2 diabetes

Cardiovascular disease and bipolar disorder: A review of pathophysiology and treatment implications

OBJECTIVE

Despite the well-established increased risk of cardiovascular mortality in individuals with bipolar disorder (BD), prevention and treatment of cardiovascular risk factors and diseases have been largely overlooked in this population. This manuscript reviews the pathophysiological basis of the connection between BD and cardiovascular diseases, highlighting their shared mechanisms, reciprocal interactions, and relevant prevention and treatment strategies.

METHODS

For this narrative review, a search was carried out on PubMed using the keywords bipolar disorder, cardiovascular diseases, and cardiovascular risk factors.

RESULTS

The increased frequency of cardiovascular morbidity in BD can be attributed to overlapping biological and psychosocial mechanisms. These mechanisms are complex and involve both direct effects of BD and indirect effects mediated by lifestyle and pharmacological factors. Cardiovascular diseases also significantly exacerbate the clinical course of BD and increase morbidity and healthcare costs; thus, their effective management can improve psychiatric outcomes and vice versa. However, patients with BD frequently encounter healthcare barriers.

CONCLUSION

Awareness initiatives and research on integrated care are needed to determine the best strategies for improving cardiovascular and psychiatric outcomes in individuals with BD.

Gain of bipolar disorder-related lncRNA AP1AR-DT in mice induces depressive and anxiety-like behaviors by reducing Negr1-mediated excitatory synaptic transmission

BACKGROUND

Bipolar disorder is a complex polygenic disorder that is characterized by recurrent episodes of depression and mania, the heterogeneity of which is likely complicated by epigenetic modifications that remain to be elucidated.

METHODS

We performed transcriptomic analysis of peripheral blood RNA from monozygotic (MZ) twins discordant for bipolar disorder to identify disease-associated differentially expressed long noncoding RNAs (DE-lncRNAs), which were further validated in the PsychENCODE brain RNA-seq dataset. We then performed behavioral tests, electrophysiological assays, chromatin immunoprecipitation, and PCR to investigate the function of DE-lncRNAs in the mouse and cell models. Statistical analyses were performed using GraphPad Prism 9.0 or SPSS.

RESULTS

We identified a bipolar disorder-associated upregulated long non-coding RNA (lncRNA), AP1AR-DT. We observed that overexpression of AP1AR-DT in the mouse medial prefrontal cortex (mPFC) resulted in a reduction of both the total spine density and the spontaneous excitatory postsynaptic current (sEPSC) frequency of mPFC neurons as well as depressive and anxiety-like behaviors. A combination of the results of brain transcriptome analysis of AP1AR-DT overexpressing mice brains with the known genes associated with bipolar disorder revealed that NEGR1, which encodes neuronal growth regulator 1, is one of the AP1AR-DT targets and is reduced in vivo upon gain of AP1AR-DT in mice. We further demonstrated that overexpression of recombinant Negr1 in the mPFC neurons of AP1AR-DTOE mice ameliorates depressive and anxiety-like behaviors and normalizes the reduced excitatory synaptic transmission induced by the gain of AP1AR-DT. We finally identified that AP1AR-DT reduces NEGR1 expression by competing for the transcriptional activator NRF1 in the overlapping binding site of the NEGR1 promoter region.

CONCLUSIONS

The epigenetic and pathophysiological mechanism linking AP1AR-DT to the modulation of depressive and anxiety-like behaviors and excitatory synaptic function provides etiological implications for bipolar disorder.

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.

Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data

Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.

Bipolar disorder: Diagnosis, treatment and future directions

Bipolar disorder is a relatively common mental illness, characterised by recurrent episodes of mania (or hypomania) and major depression, and associated with a significant burden of morbidity and premature mortality. Physicians across all specialities are likely to encounter individuals with the condition within their clinical practice. This short review provides an up-to-date overview of the clinical features, epidemiology, pathophysiology, evidence-based management, prognosis and future directions for treatment and research in bipolar disorder. Aspects of cross-specialty relevance are highlighted, including the physical health burden associated with the condition, and the side effects and safety considerations of medication regimes used in bipolar disorder.

Chronotype and Cardiometabolic Parameters in Patients with Bipolar Disorder: Preliminary Findings

Cardiometabolic alterations are very common in bipolar disorder (BD). The aim of this study was to investigate the relationship between chronotype and cardiometabolic parameters in patients with a primary diagnosis of BD. This study is an observational clinical investigation including 170 subjects consecutively admitted to the Psychiatric Inpatient Unit of the IRCCS Ospedale Policlinico San Martino (Genoa, Italy), recruited over a period of 48 months. A psychometric tool assessing chronotype was administered and blood tests were performed. Furthermore, the atherogenic coefficient ((total cholesterol-HDL cholesterol)/HDL cholesterol), and Castelli risk index-I (total cholesterol/HDL cholesterol) and -II (LDL cholesterol/HDL cholesterol) were calculated. Patients with BD and an eveningness chronotype showed a higher body mass index, total and low-density lipotrotein cholesterol compared to patients with BD and an intermediate or morning chronotype. Furthermore, the Atherogenic Coefficient and Castelli Risk-Index I-II were found to be higher in bipolar patients with an evening chronotype. The role of chronotype in the development of obesity and cardiovascular risk is, therefore, a relationship worth being investigated, especially in the context of BD, to ameliorate the clinical and therapeutic approach, aiming at increasing the quality of life and reducing the mortality.

Structural and functional features of treatment-resistant depression: A systematic review and exploratory coordinate-based meta-analysis of neuroimaging studies

OBJECTIVES

A third of people suffering from major depressive disorder do not experience a significant improvement in their symptoms even after adequate treatment with two different antidepressant medications. This common condition, termed treatment-resistant depression (TRD), severely affects the quality of life of millions of people worldwide, causing long-lasting interpersonal problems and social costs. Given its epidemiological and clinical relevance and the little consensus on whether the neurobiological underpinnings of TRD differ from treatment-sensitive depression (TSD), we sought to highlight the convergent morphometric and functional neuroimaging correlates of TRD.

METHODS

We systematically reviewed the published literature on structural and resting-state functional neuroimaging of TRD compared to TSD and healthy controls (HC) and performed exploratory coordinate-based meta-analyses (CBMA) of significant results separately for each modality and multimodally ("all-effects"). CBMAs were also performed for each direction and combining both directions of group contrasts.

RESULTS

Out of the initial 1929 studies, only eight involving 555 participants (189 patients with TRD, 156 with TSD, and 210 HC) were included. In all-effects CBMA, precentral/superior frontal gyrus showed a significant difference between TRD and HC. Functional and structural imaging meta-analyses did not yield statistically significant results. A marginally significant cluster of altered intrinsic activity was found between TRD and HC in the cerebellum/pons.

CONCLUSIONS

Frontal, cerebellar, and brainstem functions can be involved in the pathophysiology of TRD. However, the design and heterogeneity of the (scarce) published literature hinder the generalizability of the findings.

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.

Brain gyrification in bipolar disorder: a systematic review of neuroimaging studies

Bipolar disorder (BD) is a severe mental illness with a strong genetic component. Genetic variations have been involved in the risk of this disorder, including those mediating brain function and neurodevelopment. Early neurodevelopment and neuroprogression processes could be reflected in brain gyrification patterns and help optimize the prediction and diagnosis of such disorders that is often delayed. Previous neuroimaging studies using this measure in patients with bipolar disorder revealed controversial results. This systematic review aimed to summarize available neuroimaging investigations on gyrification in BD compared to healthy controls (HC) and/or other psychiatric groups. Fourteen studies including 733 patients with BD, 585 patients with schizophrenia (SCZ), 90 with schizoaffective disorder (SZA), and 1380 healthy subjects were identified. Overall, a heterogeneous pattern of gyrification emerged between patients with BD and HC. Interestingly, increased gyrification or no differences were also observed in patients with BD compared to those with the schizophrenia-spectrum disorders. Furthermore, relatives of patients with BD showed lower or no differences in gyrification compared to healthy subjects without a family history of affective illness. Differences in the design and in methodological approaches could have contributed to the heterogeneity of the findings. The current review supports an altered brain gyrification pattern that underlies the pathophysiology of BD spanning large anatomical and functional neural networks, associated with altered cognitive functioning, difficulties in processing and affective regulation, and clinical symptoms. Longitudinal studies are needed to test different bipolar phenotypes and pharmacological effects on gyrification.