White Matter Abnormalities in Late Onset First Episode Mania: A Diffusion Tensor Imaging Study

Cognition and gut microbiota in schizophrenia spectrum and mood disorders: A systematic review

FRILEUX, M., BOLTRI M. and al. Cognition and Gut microbiota in schizophrenia spectrum and mood disorders: a Systematic Review. NEUROSCI BIOBEHAV REV (1) 2024 Schizophrenia spectrum disorders and major mood disorders are associated with cognitive impairments. Recent studies suggest a link between gut microbiota composition and cognitive functioning. Here, we review the relationship between gut microbiota and cognition in these disorders. To do this, we conducted a systematic review, searching Cochrane Central Register of Controlled Trials, EBSCOhost, Embase, Pubmed, Scopus, and Web of Science. Studies were included if they investigated the relationship between gut microbiota composition and cognitive function through neuropsychological assessments in patients with bipolar, depressive, schizophrenia spectrum, and other psychotic disorders. Ten studies were identified. Findings underscore a link between gut dysbiosis and cognitive impairment. This relationship identified specific taxa (Haemophilus, Bacteroides, and Alistipes) as potential contributors to bolstered cognitive performance. Conversely, Candida albicans, Toxoplasma gondii, Streptococcus and Deinococcus were associated with diminished performance on cognitive assessments. Prebiotics and probiotics interventions were associated with cognitive enhancements, particularly executive functions. These results emphasize the role of gut microbiota in cognition, prompting further exploration of the underlying mechanisms paving the way toward precision psychiatry.

The emerging neuroimmune hypothesis of bipolar disorder: An updated overview of neuroimmune and microglial findings

Bipolar disorder (BD) is a severe and multifactorial disease, with onset usually in young adulthood, which follows a progressive course throughout life. Replicated epidemiological studies have suggested inflammatory mechanisms and neuroimmune risk factors as primary contributors to the onset and development of BD. While not all patients display overt markers of inflammation, significant evidence suggests that aberrant immune signaling contributes to all stages of the disease and seems to be mood phase dependent, likely explaining the heterogeneity of findings observed in this population. As the brain's immune cells, microglia orchestrate the brain's immune response and play a critical role in maintaining the brain's health across the lifespan. Microglia are also highly sensitive to environmental changes and respond to physiological and pathological events by adapting their functions, structure, and molecular expression. Recently, it has been highlighted that instead of a single population of cells, microglia comprise a heterogeneous community with specialized states adjusted according to the local molecular cues and intercellular interactions. Early evidence has highlighted the contribution of microglia to BD neuropathology, notably for severe outcomes, such as suicidality. However, the roles and diversity of microglial states in this disease are still largely undermined. This review brings an updated overview of current literature on the contribution of neuroimmune risk factors for the onset and progression of BD, the most prominent neuroimmune abnormalities (including biomarker, neuroimaging, ex vivo studies) and the most recent findings of microglial involvement in BD neuropathology. Combining these different shreds of evidence, we aim to propose a unifying hypothesis for BD pathophysiology centered on neuroimmune abnormalities and microglia. Also, we highlight the urgent need to apply novel multi-system biology approaches to characterize the diversity of microglial states and functions involved in this enigmatic disorder, which can open bright perspectives for novel biomarkers and therapeutic discoveries.

Gray matter biomarkers for major depressive disorder and manic disorder using logistic regression

The study investigates morphometric changes using surface-based measures and logistic regression in Major depressive-disorder (MDD) and Manic-disorder patients as compared to controls. MDD (n = 21) and manic (n = 20) subjects were recruited from psychiatric clinics, along with 19 healthy-controls from local population, after structured and semi-structured clinical interview (DSM-IV, brief Psychotic-Rating Scale (BPRS), Young Mania Rating Scale (YMRS), Hamilton depression rating scale (HDRS), cognitive function by postgraduate Institute Battery of Brain Dysfunction (PGIBBD)). Using 3D T1-weighted images, gray matter (GM) cortical thickness and GM-based morphometric signatures (using logistic regression) were compared among MDD, manic disorder and controls using analysis of covariance (ANCOVA). No significant difference was found between the MDD and manic disorder patients. When compared to controls, cortical thinning was observed in bilateral rostral middle frontal gyrus and parsopercularis, right lateral occipital cortex, right lingual gyrus in MDD; and bilateral rostral middle frontal and superior frontal gyrus, right middle temporal gyrus, left supramarginal and left precentral gyrus in Manic disorders. Logistic regression analysis exhibited GM cortical thinning in the bilateral parsopercularis, right lateral occipital cortex and lingual gyrus in MDD; and bilateral rostral middle, superior frontal gyri, right middle temporal gyrus in Manic with a sensitivity and specificity of 85.7 % and 94.7 % and 90.0 % and 94.7 %, respectively in comparison with controls. Both groups exhibited GM loss in bilateral rostral middle frontal gyrus brain regions compared to controls. Multivariate analysis revealed common changes in GM in MDD and manic disorders associated with mood temperament, but differences when compared to controls.

To what extent does white matter map to cognition in bipolar disorder? A systematic review of the evidence

Cognitive impairment is a prominent feature of bipolar disorder (BD), however the neural substrates underpinning it remain unclear. Several studies have explored white matter as a correlate of cognitive functioning in BD cohorts, but mixed results and varied methodologies from one to another make inferences about this relationship difficult to draw. Here we sought to systematically synthesise the findings of these studies to more clearly explicate the nature and extent of relationships between white matter and cognition in BD and determine best practice methodologies and areas for future research in this area. Using PRISMA guidelines, we identified and systematically reviewed 37 relevant studies, all of which were cross-sectional by design. There was substantial methodological heterogeneity and variability in the clinical presentations of BD cohorts encapsulated within the studies we reviewed, which complicated our synthesis of the findings. Nonetheless, there was some evidence that cognition is related to both white matter macrostructure and microstructure in people with BD. In particular, multiple microstructural studies consistently reported that higher fractional anisotropy, both globally and in the corpus callosum, associated with better complex attention skills and executive functioning. However, several reports did not identify any associations at all, and in general, associations between WM and cognition tended to only be evident in studies utilising larger samples and post-hoc selection of WM regions of interest. Further research with increased statistical power and standardised methods are required moving forward.

White matter characteristics in the early and late stages of bipolar disorder: A diffusion tensor imaging study

BACKGROUND

Bipolar disorder (BD) is characterized by recurrent mood episodes that may progress over time. Staging models may be used to follow the long-term course of BD. BD is associated with microstructural changes in white matter (WM). This study aims to compare the WM integrity within patients groups who are in different stages of BD and healthy controls and investigate whether WM integrity changes may be a biomarker that can be used in the clinical staging of BD.

METHODS

The study sample included euthymic 54 patients diagnosed with BD according to Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) and 27 healthy volunteers. Early-stage patients (n = 26) were determined as patients who have not had any mood episodes after the first manic episode, and late-stage patients (n = 28) determined as patients with recurrent mood episodes. MRI was performed using a 1.5 Tesla MR system and DTI sequences were acquired.

RESULTS

Region of interest (ROI) analyses showed that late-stage patients had significantly reduced fractional anisotropy (FA) in the right sagittal stratum and genu of the corpus callosum compared with healthy controls and early-stage patients. Regression models show that corpus callosum genu and right sagittal stratum FA values are predictive for the late-stage patient group.

LIMITATIONS

There are some limitations of the ROI method. The cross-sectional design is another limitation of this study.

CONCLUSIONS

WM integrity of corpus callosum genu and right sagittal stratum may be a biomarker for clinical staging of BD. Identifying stage-specific biomarkers may help us predict the neuroprogressive course of BD. Longitudinal studies would be required to detect stage-specific biomarkers.

Identifying neurocognitive heterogeneity in Older Adults with Bipolar Disorder: a cluster analysis

BACKGROUND

Cognitive profiles of BD patients show a demonstrated heterogeneity among young and middle-aged patients, but this issue has not yet deeply explored in Older Adults with bipolar disorder (OABD). The aim of the present study was to analyze cognitive variability in a sample of OABD.

METHODS

A total of 138 OABD patients and 73 healthy controls were included in this study. A comprehensive neuropsychological assessment was administered. We performed a k-means cluster analysis method based on the neurocognitive performance to detect heterogeneous subgroups. Demographic, clinical, cognitive and functional variables were compared. Finally, univariate logistic regressions were conducted to detect variables associated with the severity of the cognitive impairment.

RESULTS

We identified three distinct clusters based on the severity of cognitive impairment: (1) a preserved group (n = 58; 42%) with similar cognitive performance to HC, (2) a group showing mild cognitive deficits in all cognitive domains (n = 64; 46%) and, finally, (3) a group exhibiting severe cognitive impairment (n = 16; 12%). Older age, late onset, higher number of psychiatric admissions and lower psychosocial functioning were associated with the greatest cognitive impairment. Lower age, more years of education and higher estimated IQ were associated with a preserve cognitive functioning.

LIMITATIONS

The small sample size of the severely impaired group.

CONCLUSIONS

Cognitive heterogeneity remains at late-life bipolar disorder. Demographic and specific illness factors are related to cognitive dysfunction. Detecting distinct cognitive subgroups may have significant clinical implications for tailoring specific intervention strategies adapted to the level of the impairment and also to prevent cognitive decline.