Peripheral inflammation levels associated with degree of advanced brain aging in schizophrenia

Ageing-related changes in the regulation of microglia and their interaction with neurons

Ageing is one of the most important risk factors for chronic health conditions, including neurodegenerative diseases. Inflammation is a feature of ageing, as well as a key pathophysiological mechanism for degenerative diseases. Microglia play multiple roles in the central nervous system; their states entail a complex assemblage of responses reflecting the multiplicity of functions they fulfil both under homeostatic basal conditions and in response to stimuli. Whereas glial cells can promote neuronal homeostasis and limit neurodegeneration, age-related inflammation (i.e. inflammaging) leads to the functional impairment of microglia and astrocytes, exacerbating their response to stimuli. Thus, microglia are key mediators for age-dependent changes of the nervous system, participating in the generation of a less supportive or even hostile environment for neurons. Whereas multiple changes of ageing microglia have been described, here we will focus on the neuron-microglia regulatory crosstalk through fractalkine (CX3CL1) and CD200, and the regulatory cytokine Transforming Growth Factor β1 (TGFβ1), which is involved in immunomodulation and neuroprotection. Ageing results in a dysregulated activation of microglia, affecting neuronal survival, and function. The apparent unresponsiveness of aged microglia to regulatory signals could reflect a restriction in the mechanisms underlying their homeostatic and reactive states. The spectrum of functions, required to respond to life-long needs for brain maintenance and in response to disease, would progressively narrow, preventing microglia from maintaining their protective functions. This article is part of the Special Issue on "Microglia".

Limited evidence of association between dysregulated immune marker levels and telomere length in severe mental disorders

OBJECTIVE

Accelerated ageing indexed by telomere attrition is suggested in schizophrenia spectrum- (SCZ) and bipolar disorders (BD). While inflammation may promote telomere shortening, few studies have investigated the association between telomere length (TL) and markers of immune activation and inflammation in severe mental disorders.

METHODS

Leucocyte TL defined as telomere template/amount of single-copy gene template (T/S ratio), was determined in participants with SCZ (N = 301) or BD (N = 211) and a healthy control group (HC, N = 378). TL was analysed with linear regressions for associations with levels of 12 immune markers linked to SCZ or BD. Adjustments were made for a broad range of potential confounding variables. TL was measured by quantitative polymerase chain reaction (qPCR) and the immune markers were measured by enzyme immunoassays.

RESULTS

A positive association between levels of soluble tumour necrosis factor receptor 1A (sTNF-R1) and TL in SCZ (β = 0.191, p = 0.012) was observed. Plasma levels of the other immune markers were not significantly associated with TL in the BD, SCZ or HC groups.

CONCLUSION

There was limited evidence of association between immune markers and TL in SCZ and BD. The results provide little support for involvement of immune dysregulation, as reflected by current systemic markers, in telomere attrition-related accelerated ageing in severe mental disorders.

Lithium, Inflammation and Neuroinflammation with Emphasis on Bipolar Disorder-A Narrative Review

This narrative review examines lithium's effects on immune function, inflammation and cell survival, particularly in bipolar disorder (BD) in in vitro studies, animal models and clinical studies. In vitro studies show that high lithium concentrations (5 mM, beyond the therapeutic window) reduce interleukin (IL)-1β production in monocytes and enhance T-lymphocyte resistance, suggesting a protective role against cell death. Lithium modulates oxidative stress in lipopolysaccharide (LPS)-activated macrophages by inhibiting nuclear factor (NF)-ƙB activity and reducing nitric oxide production. At therapeutically relevant levels, lithium increased both pro-inflammatory [interferon (INF)-γ, IL-8 and tumor necrosis factor (TNF)-α)] and anti-inflammatory (IL-10) cytokines on whole blood supernatant culture in healthy volunteers, influencing the balance of pro- and anti-inflammatory responses. Animal models reveal lithium's potential to alleviate inflammatory diseases by reducing pro-inflammatory cytokines and enhancing anti-inflammatory responses. It also induces selective macrophage death in atherosclerotic plaques without harming other cells. In primary rat cerebellum cultures (ex vivo), lithium prevents neuronal loss and inhibits astroglial growth, impacting astrocytes and microglia. Clinical studies show that lithium alters cytokine profiles and reduces neuroinflammatory markers in BD patients. Chronic treatment decreases IL-2, IL-6, IL-10 and IFN-γ secretion from peripheral blood leukocytes. Lithium response correlates with TNF-α levels, with poor responders showing higher TNF-α. Overall, these findings elucidate lithium's diverse mechanisms in modulating immune responses, reducing inflammation and promoting cell survival, with significant implications for managing BD and other inflammation-related conditions. Yet, to better understand the drug's impact in BD and other inflammatory/neuroinflammatory conditions, further research is warranted to appreciate lithium's therapeutic potential and its role in immune regulation.

Brain predicted age in chronic pelvic pain: a study by the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network

ABSTRACT

The effect of chronic pain on brain-predicted age is unclear. We performed secondary analyses of a large cross-sectional and 3-year longitudinal data set from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network to test the hypothesis that chronic pelvic pain accelerates brain aging and brain aging rate. Brain-predicted ages of 492 chronic pelvic pain patients and 72 controls were determined from T1-weighted MRI scans and used to calculate the brain-predicted age gap estimation (brainAGE; brain-predicted - chronological age). Separate regression models determined whether the presence of chronic pelvic pain could explain brainAGE and brain aging rate when accounting for covariates. We performed secondary analyses to understand whether brainAGE was associated with factors that subtype chronic pelvic pain patients (inflammation, widespread pain, and psychological comorbidities). We found a significant association between chronic pelvic pain and brainAGE that differed by sex. Women with chronic pelvic pain had higher brainAGE than female controls, whereas men with chronic pelvic pain exhibited lower brainAGE than male controls on average-however, the effect was not statistically significant in men or women when considered independently. Secondary analyses demonstrated preliminary evidence of an association between inflammatory load and brainAGE. Further studies of brainAGE and inflammatory load are warranted.

Microglia-neuron interactions in schizophrenia

Multiple lines of evidence implicate increased neuroinflammation mediated by glial cells to play a key role in neurodevelopmental disorders such as schizophrenia. Microglia, which are the primary innate immune cells of the brain, are crucial for the refinement of the synaptic circuitry during early brain development by synaptic pruning and the regulation of synaptic plasticity during adulthood. Schizophrenia risk factors as genetics or environmental influences may further be linked to increased activation of microglia, an increase of pro-inflammatory cytokine levels and activation of the inflammasome resulting in an overall elevated neuroinflammatory state in patients. Synaptic loss, one of the central pathological hallmarks of schizophrenia, is believed to be due to excess removal of synapses by activated microglia, primarily affecting glutamatergic neurons. Therefore, it is crucial to investigate microglia-neuron interactions, which has been done by multiple studies focusing on post-mortem brain tissues, brain imaging, animal models and patient iPSC-derived 2D culture systems. In this review, we summarize the major findings in patients and in vivo and in vitro models in the context of neuron-microglia interactions in schizophrenia and secondly discuss the potential of anti-inflammatory treatments for the alleviation of positive, negative, and cognitive symptoms.

Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset

Accelerated brain aging (ABA) intricately links with age-associated neurodegenerative and neuropsychiatric diseases, emphasizing the critical need for a nuanced exploration of heterogeneous ABA patterns. This investigation leveraged data from the UK Biobank (UKB) for a comprehensive analysis, utilizing structural magnetic resonance imaging (sMRI), diffusion magnetic resonance imaging (dMRI), and resting-state functional magnetic resonance imaging (rsfMRI) from 31,621 participants. Pre-processing employed tools from the FMRIB Software Library (FSL, version 5.0.10), FreeSurfer, DTIFIT, and MELODIC, seamlessly integrated into the UKB imaging processing pipeline. The Lasso algorithm was employed for brain-age prediction, utilizing derived phenotypes obtained from brain imaging data. Subpopulations of accelerated brain aging (ABA) and resilient brain aging (RBA) were delineated based on the error between actual age and predicted brain age. The ABA subgroup comprised 1949 subjects (experimental group), while the RBA subgroup comprised 3203 subjects (control group). Semi-supervised heterogeneity through discriminant analysis (HYDRA) refined and characterized the ABA subgroups based on distinctive neuroimaging features. HYDRA systematically stratified ABA subjects into three subtypes: SubGroup 2 exhibited extensive gray-matter atrophy, distinctive white-matter patterns, and unique connectivity features, displaying lower cognitive performance; SubGroup 3 demonstrated minimal atrophy, superior cognitive performance, and higher physical activity; and SubGroup 1 occupied an intermediate position. This investigation underscores pronounced structural and functional heterogeneity in ABA, revealing three subtypes and paving the way for personalized neuroprotective treatments for age-related neurological, neuropsychiatric, and neurodegenerative diseases.

Review of Major Social Determinants of Health in Schizophrenia-Spectrum Psychotic Disorders: III. Biology

BACKGROUND

Social determinants of health (SDoHs) are nonmedical factors that significantly impact health and longevity. We found no published reviews on the biology of SDoHs in schizophrenia-spectrum psychotic disorders (SSPD).

STUDY DESIGN

We present an overview of pathophysiological mechanisms and neurobiological processes plausibly involved in the effects of major SDoHs on clinical outcomes in SSPD.

STUDY RESULTS

This review of the biology of SDoHs focuses on early-life adversities, poverty, social disconnection, discrimination including racism, migration, disadvantaged neighborhoods, and food insecurity. These factors interact with psychological and biological factors to increase the risk and worsen the course and prognosis of schizophrenia. Published studies on the topic are limited by cross-sectional design, variable clinical and biomarker assessments, heterogeneous methods, and a lack of control for confounding variables. Drawing on preclinical and clinical studies, we propose a biological framework to consider the likely pathogenesis. Putative systemic pathophysiological processes include epigenetics, allostatic load, accelerated aging with inflammation (inflammaging), and the microbiome. These processes affect neural structures, brain function, neurochemistry, and neuroplasticity, impacting the development of psychosis, quality of life, cognitive impairment, physical comorbidities, and premature mortality. Our model provides a framework for research that could lead to developing specific strategies for prevention and treatment of the risk factors and biological processes, thereby improving the quality of life and increasing the longevity of people with SSPD.

CONCLUSIONS

Biology of SDoHs in SSPD is an exciting area of research that points to innovative multidisciplinary team science for improving the course and prognosis of these serious psychiatric disorders.

Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study

Although many studies on brain-age prediction in patients with schizophrenia have been reported recently, none has predicted brain age based on different neuroimaging modalities and different brain regions in these patients. Here, we constructed brain-age prediction models with multimodal MRI and examined the deviations of aging trajectories in different brain regions of participants with schizophrenia recruited from multiple centers. The data of 230 healthy controls (HCs) were used for model training. Next, we investigated the differences in brain age gaps between participants with schizophrenia and HCs from two independent cohorts. A Gaussian process regression algorithm with fivefold cross-validation was used to train 90, 90, and 48 models for gray matter (GM), functional connectivity (FC), and fractional anisotropy (FA) maps in the training dataset, respectively. The brain age gaps in different brain regions for all participants were calculated, and the differences in brain age gaps between the two groups were examined. Our results showed that most GM regions in participants with schizophrenia in both cohorts exhibited accelerated aging, particularly in the frontal lobe, temporal lobe, and insula. The parts of the white matter tracts, including the cerebrum and cerebellum, indicated deviations in aging trajectories in participants with schizophrenia. However, no accelerated brain aging was noted in the FC maps. The accelerated aging in 22 GM regions and 10 white matter tracts in schizophrenia potentially exacerbates with disease progression. In individuals with schizophrenia, different brain regions demonstrate dynamic deviations of brain aging trajectories. Our findings provided more insights into schizophrenia neuropathology.

Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia

Brain-age prediction is a novel approach to assessing deviated brain aging trajectories in different diseases. However, most studies have used an average brain age gap (BAG) of individuals with schizophrenia of different illness durations for comparison with healthy participants. Therefore, this study investigated whether declined brain structures as reflected by BAGs may be present in schizophrenia in terms of brain volume, cortical thickness, and fractional anisotropy across different illness durations. We used brain volume, cortical thickness, and fractional anisotropy as features to train three models from the training dataset. Three models were applied to predict brain ages in the hold-out test and schizophrenia datasets and calculate BAGs. We divided the schizophrenia dataset into multiple groups based on the illness duration using a sliding time window approach for ANCOVA analysis. The brain volume and cortical thickness models revealed that, in comparison with healthy controls, individuals with schizophrenia had larger BAGs across different illness durations, whereas the BAG in terms of fractional anisotropy did not differ from that of healthy controls after disease onset. Moreover, the BAG at the initial stage of schizophrenia was the largest in the cortical thickness model. In contrast, the BAG from approximately two decades after disease onset was the largest in the brain volume model. Our findings suggest that schizophrenia differentially affects the decline of different brain structures during the disease course. Moreover, different trends of decline in thickness and volume-based measures suggest a differential decline in dimensions of brain structure throughout the course of schizophrenia.