Diagnosis and monitoring of bipolar disorder in general practice

Two hub genes of bipolar disorder, a bioinformatics study based on the GEO database

Bipolar disorder is a mood illness that affects many people. It has a high recurrence frequency and will cause significant damage to the patient's social function. At present, the pathogenesis of BD is not clear. The National Center for Biotechnology Information (NCBI) established and maintained the Gene Expression Omnibus (GEO) database, a gene expression database. For bioinformatics analysis, researchers can obtain expression data from the internet. At present, the samples of the dataset used in the research of BD are mostly from brain tissue, and the data containing blood samples are rarely used. GEO databases (GSE46416, GSE5388, and GSE5389) were used to retrieve public data, and utilizing the online tool GEO2R, differentially expressed genes (DEGs) were retrieved. The common DEGs between the samples of patients with BD and the samples of the normal population were screened by Venn diagrams. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to perform functional annotation and pathway enrichment analysis of DEGs. A protein-protein interaction network (PPI) was built to investigate hub genes on this basis. There were 117 up-regulated DEGs and 38 down-regulated DEGs discovered, with two hub genes [SRC, CDKN1A] among the up-regulated DEGs. These two hub genes were also highly enriched in the oxytocin signaling pathway, proteoglycans in cancer and bladder cancer, according to KEGG analysis. The results of the receiver operating characteristic curve (ROC) of SRC and CDKN1A in the three datasets strongly suggested that SRC and CDKN1A were potential diagnostic markers of BD. The results strongly suggest that SRC and CDKN1A are related to the pathogenesis of BD.

Mental health integrated care models in primary care and factors that contribute to their effective implementation: a scoping review

BACKGROUND

In the state of Victoria, Australia, the 111-day lockdown due to the COVID-19 pandemic exacerbated the population's prevailing state of poor mental health. Of the 87% of Australians who visit their GP annually, 71% of health problems they discussed related to psychological issues. This review had two objectives: (1) To describe models of mental health integrated care within primary care settings that demonstrated improved mental health outcomes that were transferable to Australian settings, and (2) To outline the factors that contributed to the effective implementation of these models into routine practice.

METHODS

A scoping review was undertaken to synthesise the evidence in order to inform practice, policymaking, and research. Data were obtained from PubMed, CINAHL and APA PsycINFO.

RESULTS

Key elements of effective mental health integrated care models in primary care are: Co-location of mental health and substance abuse services in the primary care setting, presence of licensed mental health clinicians, a case management approach to patient care, ongoing depression monitoring for up to 24 months and other miscellaneous elements. Key factors that contributed to the effective implementation of mental health integrated care in routine practice are the willingness to accept and promote system change, integrated physical and mental clinical records, the presence of a care manager, adequate staff training, a healthy organisational culture, regular supervision and support, a standardised workflow plan and care pathways that included clear role boundaries and the use of outcome measures. The need to develop sustainable funding mechanisms has also been emphasized.

CONCLUSION

Integrated mental health care models typically have a co-located mental health clinician who works closely with the GP and the rest of the primary care team. Implementing mental health integrated care models in Australia requires a 'whole of system' change. Lessons learned from the Mental Health Nurse Incentive Program could form the foundation on which this model is implemented in Australia.

Identification of Predictors of Mood Disorder Misdiagnosis and Subsequent Help-Seeking Behavior in Individuals With Depressive Symptoms: Gradient-Boosted Tree Machine Learning Approach

BACKGROUND

Misdiagnosis and delayed help-seeking cause significant burden for individuals with mood disorders such as major depressive disorder and bipolar disorder. Misdiagnosis can lead to inappropriate treatment, while delayed help-seeking can result in more severe symptoms, functional impairment, and poor treatment response. Such challenges are common in individuals with major depressive disorder and bipolar disorder due to the overlap of symptoms with other mental and physical health conditions, as well as, stigma and insufficient understanding of these disorders.

OBJECTIVE

In this study, we aimed to identify factors that may contribute to mood disorder misdiagnosis and delayed help-seeking.

METHODS

Participants with current depressive symptoms were recruited online and data were collected using an extensive digital mental health questionnaire, with the World Health Organization World Mental Health Composite International Diagnostic Interview delivered via telephone. A series of predictive gradient-boosted tree algorithms were trained and validated to identify the most important predictors of misdiagnosis and subsequent help-seeking in misdiagnosed individuals.

RESULTS

The analysis included data from 924 symptomatic individuals for predicting misdiagnosis and from a subset of 379 misdiagnosed participants who provided follow-up information when predicting help-seeking. Models achieved good predictive power, with area under the receiver operating characteristic curve of 0.75 and 0.71 for misdiagnosis and help-seeking, respectively. The most predictive features with respect to misdiagnosis were high severity of depressed mood, instability of self-image, the involvement of a psychiatrist in diagnosing depression, higher age at depression diagnosis, and reckless spending. Regarding help-seeking behavior, the strongest predictors included shorter time elapsed since last speaking to a general practitioner about mental health, sleep problems disrupting daily tasks, taking antidepressant medication, and being diagnosed with depression at younger ages.

CONCLUSIONS

This study provides a novel, machine learning-based approach to understand the interplay of factors that may contribute to the misdiagnosis and subsequent help-seeking in patients experiencing low mood. The present findings can inform the development of targeted interventions to improve early detection and appropriate treatment of individuals with mood disorders.

Bipolar Affective Disorder: A Case of Antidepressant-Induced Hypomania

Bipolar affective disorder (BAD) is found among 1-3% of the world's population and leads to a significant burden due to its chronicity. This report describes a case of antidepressant-induced BAD, presenting in the hypomanic phase. Diagnostic criteria in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were used for the diagnosis, after having performed investigations and excluding organic causes. The patient presented with typical features of altered mood, pressured speech, hyperactivity, and irritability. He was diagnosed according to the criteria available and managed promptly.

White Matter Microstructure in Individuals With and At Risk for Bipolar Disorder: Evidence for an Endophenotype From a Voxel-Based Meta-analysis

BACKGROUND

Aberrant white matter (WM) microstructure has been proposed as a mechanism underlying bipolar disorder (BD). Given the strong genetic underpinnings of both WM microstructure and BD, such WM aberrations may be not only a disease marker, but also an endophenotype of BD. If so, they should be observable in individuals at risk for BD (AR) (i.e., first-degree relatives). This meta-analysis integrates evidence on perturbed WM microstructure in individuals with or at risk for BD.

METHODS

A comprehensive search of literature published through April 2020 identified diffusion tensor imaging studies that used a voxel-based approach to compare fractional anisotropy (FA) and radial diffusivity between individuals with BD and/or AR individuals and healthy volunteers. Effect size comparison and conjunction analysis allowed identification of endophenotypes and disease markers of BD. Effects of age, sex, mood state, and psychotropic medication were explored using meta-regressions.

RESULTS

We included 57 studies in individuals with BD (N = 4631) and 10 in AR individuals (N = 753). Both individuals with and at risk for BD were associated with lower FA in the body and splenium of the corpus callosum. In the BD group, decreased FA and increased radial diffusivity comprised the entire corpus callosum, anterior thalamic radiation, fronto-orbito-polar tracts, and superior longitudinal fasciculus, and were influenced by age, sex, and mood state. Studies with higher proportions of individuals taking lithium or antipsychotics reported smaller FA reductions in BD.

CONCLUSIONS

Findings suggest that abnormalities in the body and splenium of the corpus callosum may be an endophenotype for BD, and they associate BD with WM tracts relevant for working memory performance, attention, and reward processing.

White matter microstructure in youth with and at risk for bipolar disorder

OBJECTIVES

Bipolar disorder (BD) and familial risk for BD have been associated with aberrant white matter (WM) microstructure in the corpus callosum and fronto-limbic pathways. These abnormalities might constitute trait or state marker and have been suggested to result from aberrant maturation and to relate to difficulties in emotion regulation.

METHODS

To determine whether WM alterations represent a trait, disease or resilience marker, we compared youth at risk for BD (n = 36 first-degree relatives, REL) to youth with BD (n = 36) and healthy volunteers (n = 36, HV) using diffusion tensor imaging.

RESULTS

Individuals with BD and REL did not differ from each other in WM microstructure and, compared to HV, showed similar aberrations in the superior corona radiata (SCR)/corticospinal tract (CST) and the body of the corpus callosum. WM microstructure of the anterior CC showed reduced age-related in-creases in BD compared to REL and HV. Further, individuals with BD and REL showed in-creased difficulties in emotion regulation, which were associated with the microstructure of the anterior thalamic radiation.

DISCUSSION

Alterations in the SCR/CST and the body of the corpus callosum appear to represent a trait marker of BD, whereas changes in other WM tracts seem to be a disease state marker. Our findings also support the role of aberrant developmental trajectories of WM microstructure in the risk architecture of BD, although longitudinal studies are needed to confirm this association. Finally, our findings show the relevance of WM microstructure for difficulties in emotion regulation-a core characteristic of BD.

Abnormal Degree Centrality Associated With Cognitive Dysfunctions in Early Bipolar Disorder

Delayed diagnosis of bipolar disorder (BD) is common. However, diagnostic validity may be enhanced using reliable neurobiological markers for BD. Degree centrality (DC) is one such potential marker that enables researchers to visualize neuronal network abnormalities in the early stages of some neuropsychiatric disorders. In the present study, we measured resting-state DC abnormalities and cognitive deficits in order to identify early neurobiological markers for BD. We recruited 23 patients with BD who had recently experienced manic episodes (duration of illness <2 years) and 46 matched healthy controls. Our findings indicated that patients with BD exhibited DC abnormalities in frontal areas, temporal areas, the right postcentral gyrus, and the posterior lobe of the cerebellum. Moreover, correlation analysis revealed that psychomotor speed indicators were associated with DC in the superior temporal and inferior temporal gyri, while attention indicators were associated with DC in the inferior temporal gyrus, in patients with early BD. Our findings suggest that DC abnormalities in neural emotion regulation circuits are present in patients with early BD, and that correlations between attention/psychomotor speed deficits and temporal DC abnormalities may represent early markers of BD.

Phase II Randomised Controlled Trial of a patient decision-aid website to improve treatment decision-making for young adults with bipolar II disorder: A feasibility study protocol

BACKGROUND/AIMS

This paper describes the protocol for a feasibility study for a parallel Phase II randomised control trial (RCT) aiming to evaluate a novel decision-aid website (e-DA) to support young adults with bipolar II disorder (BPII), and their families.

MATERIAL AND METHODS

The e-DA was developed according to the International Patient Decision-Aid Standards (IPDAS). Participants will be 40 young adults (18-30 years) referred to a specialist outpatient clinical facility, who have a confirmed clinical diagnosis of BPII. Participants will be randomised (1:1) to receive access to the clinic's online factsheets/website with (Intervention) or without (Control) the e-DA. A series of validated and purpose-designed questionnaires will be administered at baseline (T0), immediately post-decision (T1), and 3 months post-decision (T2). Questionnaires assess key decision-making constructs related to decision-making quality, including: decisional conflict, subjective and objective treatment knowledge, values-based informed choice, concordance between preferred/actual decision-making involvement, preparation for decision-making, and decisional regret. Self-report symptom severity and anxiety will ascertain the safety of e-DA use. The focus of analyses will be to assess effect sizes, in order to guide a future RCT.

DISCUSSION

This feasibility study will evaluate a world first, evidence-based online decision-support resource, a DA website, for young adults with BPII and their families who are deciding on treatment options for relapse prevention. Findings will determine the e-DA's feasibility in RCT procedures (i.e., outpatient clinical setting) and provide estimates of effect sizes on outcomes related to improving treatment decision-making and patient outcomes in a sample of potential end-users, compared to usual care.

TRIAL REGISTRATION

This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12617000840381.