Changes in leukocytes and CRP in different stages of major depression

Differences in Blood Leukocyte Subpopulations in Schizophrenia: A Systematic Review and Meta-Analysis

Importance

This study aims to provide robust evidence to support or challenge the immune hypothesis of schizophrenia.

Objective

To conduct a meta-analysis of reports on blood leukocyte subpopulations in schizophrenia vs healthy controls, examining disease- and treatment-related differences as well as potential confounders.

Data Sources

Systematic database search for English and non-English peer-reviewed articles in PubMed, Web of Science, Scopus, and Cochrane Library databases, with the last search in January 2024.

Study Selection

Cross-sectional, case-control, and longitudinal studies comparing leukocyte numbers in patients with schizophrenia and healthy controls. After duplicates were removed, 3691 studies were identified for screening.

Data Extraction and Synthesis

Data extraction and quality assessment were conducted following PRISMA and MOOSE guidelines. Data were independently extracted by 2 authors and pooled using random-effects models.

Main Outcomes and Measures

The planned primary outcomes were differences in leukocyte subpopulation counts between individuals with schizophrenia and healthy controls to increase our understanding of the immune system dysfunction in schizophrenia.

Results

Sixty-four relevant articles were identified (60 cross-sectional/case-control studies and 4 longitudinal studies) with data on leukocyte numbers from 26 349 individuals with schizophrenia and 16 379 healthy controls. Neutrophils (g = 0.69; 95% CI, 0.49 to 0.89; Bonferroni-adjusted P < .001; n = 40 951 [47 between-group comparisons]) and monocytes (g = 0.49; 95% CI, 0.24 to 0.75; Bonferroni-adjusted P < .001; n = 40 513 [44 between-group comparisons]) were higher in schizophrenia compared with control participants. Differences were greater in first-episode vs chronic schizophrenia and in patients who were not treated vs treated with antipsychotic medication. There were no significant differences in eosinophils (g = 0.02; 95% CI, -0.16 to 0.20; Bonferroni-adjusted P > .99; n = 3277 [18 between-group comparisons]), basophils (g = 0.14; 95% CI, -0.06 to 0.34; Bonferroni-adjusted P = .85; n = 2614 [13 between-group comparisons]), or lymphocytes (g = -0.08; 95% CI, -0.21 to 0.06; Bonferroni-adjusted P > .99; n = 41 693 [59 between-group comparisons]). Neutrophils decreased longitudinally (g = -0.30; 95% CI, -0.45 to -0.15; Bonferroni-adjusted P < .001; n = 896 [4 within-group comparisons]) and eosinophils increased longitudinally (g = 0.61; 95% CI, 0.52 to 0.71; Bonferroni-adjusted P < .001; n = 876 [3 within-group comparisons]) after successful treatment of acute psychosis.

Conclusions and Relevance

Our findings of increased blood neutrophils and monocytes support the immune hypothesis of schizophrenia, particularly highlighting the role of innate immune activation. As these effects were more pronounced in early disease stages and also reflected clinical improvement, they may pave the way for innovative treatment strategies based on immunological and inflammatory pathways and help revolutionize the treatment landscape for schizophrenia.

Exploring the mediating role of Charlson comorbidity index in the association between body mass index and depression in U.S. adults: NHANES 2007-2020

OBJECTIVE

The relationship among body mass index (BMI), Charlson comorbidity index (CCI), and depression forms a complex interplay that affects both physical and mental health. However, whether CCI mediates the association between BMI and depression remains unclear. In this study, we aimed to elucidate the mediating role of CCI in the relationship between BMI and depression.

METHODS

This study used data from the National Health and Nutrition Examination Survey, a program of the National Center for Health Statistics in the United States, including 23,639 participants from 2007 to 2020. Wilcoxon rank-sum and Rao-Scott adjusted chi-square tests were employed to compare characteristics between adults with and without depression. Weighted logistic regression and restricted cubic spline models were applied to investigate the pairwise associations among BMI, CCI, and depression. Mediation analysis was performed to assess whether CCI mediated the relationship between BMI and depression.

RESULTS

Of the 23,639 participants, 2128 (9.0 %) had depression. Significant associations were observed between BMI and CCI; CCI and depression; and BMI and depression (P < 0.001). A U-shaped relationship between BMI and depression odds was identified, with the lowest odds at a BMI of 23 kg/m2. Mediation analysis revealed that CCI partially mediated the BMI-depression relationship, accounting for 19.5 % of the total effect.

CONCLUSIONS

The results suggest that CCI plays a mediating role in the association between BMI and depression, and that improved chronic disease management may be associated with lower odds of depression in high BMI populations.

Identifying behavior regulatory leverage over mental disorders transcriptomic network hubs toward lifestyle-dependent psychiatric drugs repurposing

BACKGROUND

There is a vast prevalence of mental disorders, but patient responses to psychiatric medication fluctuate. As food choices and daily habits play a fundamental role in this fluctuation, integrating machine learning with network medicine can provide valuable insights into disease systems and the regulatory leverage of lifestyle in mental health.

METHODS

This study analyzed coexpression network modules of MDD and PTSD blood transcriptomic profile using modularity optimization method, the first runner-up of Disease Module Identification DREAM challenge. The top disease genes of both MDD and PTSD modules were detected using random forest model. Afterward, the regulatory signature of two predominant habitual phenotypes, diet-induced obesity and smoking, were identified. These transcription/translation regulating factors (TRFs) signals were transduced toward the two disorders' disease genes. A bipartite network of drugs that target the TRFS together with PTSD or MDD hubs was constructed.

RESULTS

The research revealed one MDD hub, the CENPJ, which is known to influence intellectual ability. This observation paves the way for additional investigations into the potential of CENPJ as a novel target for MDD therapeutic agents development. Additionally, most of the predicted PTSD hubs were associated with multiple carcinomas, of which the most notable was SHCBP1. SHCBP1 is a known risk factor for glioma, suggesting the importance of continuous monitoring of patients with PTSD to mitigate potential cancer comorbidities. The signaling network illustrated that two PTSD and three MDD biomarkers were co-regulated by habitual phenotype TRFs. 6-Prenylnaringenin and Aflibercept were identified as potential candidates for targeting the MDD and PTSD hubs: ATP6V0A1 and PIGF. However, habitual phenotype TRFs have no leverage over ATP6V0A1 and PIGF.

CONCLUSION

Combining machine learning and network biology succeeded in revealing biomarkers for two notoriously spreading disorders, MDD and PTSD. This approach offers a non-invasive diagnostic pipeline and identifies potential drug targets that could be repurposed under further investigation. These findings contribute to our understanding of the complex interplay between mental disorders, daily habits, and psychiatric interventions, thereby facilitating more targeted and personalized treatment strategies.

Dissecting biological heterogeneity in major depressive disorder based on neuroimaging subtypes with multi-omics data

The heterogeneity of Major Depressive Disorder (MDD) has been increasingly recognized, challenging traditional symptom-based diagnostics and the development of mechanism-targeted therapies. This study aims to identify neuroimaging-based MDD subtypes and dissect their predominant biological characteristics using multi-omics data. A total of 807 participants were included in this study, comprising 327 individuals with MDD and 480 healthy controls (HC). The amplitude of low-frequency fluctuations (ALFF), a functional neuroimaging feature, was extracted for each participant and used to identify MDD subtypes through machine learning clustering. Multi-omics data, including profiles of genetic, epigenetics, metabolomics, and pro-inflammatory cytokines, were obtained. Comparative analyses of multi-omics data were conducted between each MDD subtype and HC to explore the molecular underpinnings involved in each subtype. We identified three neuroimaging-based MDD subtypes, each characterized by unique ALFF pattern alterations compared to HC. Multi-omics analysis showed a strong genetic predisposition for Subtype 1, primarily enriched in neuronal development and synaptic regulation pathways. This subtype also exhibited the most severe depressive symptoms and cognitive decline compared to the other subtypes. Subtype 2 is characterized by immuno-inflammation dysregulation, supported by elevated IL-1 beta levels, altered epigenetic inflammatory measures, and differential metabolites correlated with IL-1 beta levels. No significant biological markers were identified for Subtype 3. Our results identify neuroimaging-based MDD subtypes and delineate the distinct biological features of each subtype. This provides a proof of concept for mechanism-targeted therapy in MDD, highlighting the importance of personalized treatment approaches based on neurobiological and molecular profiles.

Revealing the Causal Relationship Between Differential White Blood Cell Counts and Depression: A Bidirectional Two-Sample Mendelian Randomization Study

Background: The link between white blood cells (WBC) and depression has been studied, but the causal relationship remains unclear. This study aimed to elucidate the potential bidirectional causal links between six specific WBC count features and depression using a two-sample Mendelian randomization (MR) analysis, leveraging summary statistics from genome-wide association studies (GWAS). Method: The dataset on depression (N = 406,986) was sourced from the FinnGen database, while the dataset on WBC (N = 563,085) was obtained from a combined dataset of Blood Cell Consortium (BCX) and UK Biobank. The MR analyses employed include inverse variance weighted (IVW), MR-Egger, weighted median, contamination mixture method (conmix), and constrained maximum likelihood-based Mendelian randomization (cML-MA). A threshold p < 0.05 after false discovery rate (FDR) correction was set as the criterion for causality based on IVW. Results: Reverse MR analysis indicated a causal relationship where depression leads to an increase in overall WBC count (IVW beta = 0.031, p = 0.015, p FDR = 0.044) and specifically in basophil count (IVW beta = 0.038, p = 0.006, p FDR = 0.038), with a marginally significant impact on lymphocyte count (beta = 0.029, p = 0.036, p FDR = 0.071). Furthermore, forward MR analysis suggested a potential role of monocyte count in decreasing depression risk (p = 0.028), though this association did not retain statistical significance after FDR correction. Conclusion: These findings suggest that depression may causally influence the immune system by elevating overall WBC and basophil counts, with a marginally significant increase in lymphocyte levels. Conversely, higher monocyte count might confer some protection against depression, albeit with less statistial certainty. This study provides novel insights into the complex interplay between depression and immune function.

The immunological perspective of major depressive disorder: unveiling the interactions between central and peripheral immune mechanisms

Major depressive disorder is a prevalent mental disorder, yet its pathogenesis remains poorly understood. Accumulating evidence implicates dysregulated immune mechanisms as key contributors to depressive disorders. This review elucidates the complex interplay between peripheral and central immune components underlying depressive disorder pathology. Peripherally, systemic inflammation, gut immune dysregulation, and immune dysfunction in organs including gut, liver, spleen and adipose tissue influence brain function through neural and molecular pathways. Within the central nervous system, aberrant microglial and astrocytes activation, cytokine imbalances, and compromised blood-brain barrier integrity propagate neuroinflammation, disrupting neurotransmission, impairing neuroplasticity, and promoting neuronal injury. The crosstalk between peripheral and central immunity creates a vicious cycle exacerbating depressive neuropathology. Unraveling these multifaceted immune-mediated mechanisms provides insights into major depressive disorder's pathogenic basis and potential biomarkers and targets. Modulating both peripheral and central immune responses represent a promising multidimensional therapeutic strategy.

Association of Neutrophil-Percentage-To-Albumin Ratio(NPAR) with depression symptoms in U.S. adults: a NHANES study from 2011 to 2018

BACKGROUND

Inflammation is crucial in the development of depression. This study aims to examine the potential association between the Neutrophil-Percentage-to-Albumin Ratio(NPAR) and depression symptoms.

METHODS

This study adopted a cross-sectional design, involving patients with depression symptoms and those without depression symptoms with comprehensive NPAR data originated from the National Health and Nutrition Examination Survey(NHANES) spanning 2011 to 2018. The research utilized weighted multivariate logistic regression models and multivariate linear regression to investigate the linear relationship between NPAR levels and depression symptoms and its severity scores. The characterization of nonlinear relationships was accomplished by employing fitted smoothing curves. Furthermore, subgroup analyses and interaction assessments were conducted to offer additional insights.

RESULTS

This study involved a total of 10,829 participants, and the prevalence of depression among them was found to be 15.08%. The multiple logistic regression analysis revealed a statistically significant positive association between the continuum of NPAR and depression symptoms[OR:1.03, 95% CI: (1.00, 1.05)], as well as depression severity scores[β: 0.08, 95% CI: (0.04,0.11)]. Stratifying NPAR into quartiles, we found that higher NPAR associated with increased odds of depression symptoms. Furthermore, in subgroup analysis, there were no significant differences in the relationship between NPAR levels and depression symptoms or its severity scores within populations with or without diabetes and cardiovascular diseases. Additionally, the use of a two-stage linear regression model uncovered a non-linear relationship between NPAR and depression symptoms.

CONCLUSIONS

Our research indicates that NPAR levels were associated with depression symptoms. To corroborate our findings, larger prospective studies are warranted to elucidate nonlinear associations in greater detail.

The Role of Inflammation in Depression and Beyond: A Primer for Clinicians

PURPOSE OF REVIEW

We evaluate available evidence for the role of inflammation in depression. We reappraise literature involving systemic inflammation, neuroinflammation and neurotransmission and their association with depression. We review the connection between depression, autoimmunity and infectious diseases. We revise anti-inflammatory treatments used in depression.

RECENT FINDINGS

Peripheral inflammatory markers are present in a subset of patients with depression and can alter common neurotransmitters in this population but there is no clear causality between depression and systemic inflammation. Infectious conditions and autoimmune illnesses do not have a clear correlation with depression. Certain medications have positive evidence as adjunctive treatments in depression but studies are heterogenic, hence they are sparsely used in clinical settings. The current evidence does not fully support inflammation, infections or autoimmunity as possible etiologies of depression. The available studies have numerous confounders that obscure the findings. Anti-inflammatory agents may have potential for treatment of depression, but further research is needed to clarify their usefulness in routine clinical practice.

SCG2 mediates blood-brain barrier dysfunction and schizophrenia-like behaviors after traumatic brain injury

Traumatic brain injury (TBI), which is characterized by acute neurological dysfunction, is also one of the most widely recognized environmental risk factors for various neurological and psychiatric disorders. However, the role of TBI in neurological perturbation and the mechanisms underlying these disorders remain unknown. We evaluated transcriptional changes in cells of the frontal cortex after TBI by exploiting single-cell RNA sequencing (scRNA-Seq). We adopted the gene expression omnibus and scRNA-Seq to identify the mediation by secretogranin II (SCG2) of TBI-induced schizophrenia. Astrocytes are a principal source of SCG2 in the frontal cortex after TBI. Our analysis indicated that SCG2-triggered disruption of the blood-brain barrier (BBB) via the CypA-MMP-9 signaling pathway. Furthermore, astrocytic SCG2 knockout in the frontal cortex reduced BBB damage, mitigated inflammation, and inhibited schizophrenia after TBI. In conclusion, we identified the SCG2-CypA-MMP-9 signaling pathway in reactive astrocytes as a key switch in the protection of the BBB and provided a novel therapeutic avenue for treating psychiatric disorders after TBI.

Association between neutrophil-to-lymphocyte ratio and length of hospital stay in an acute psychiatric hospital: A cross-sectional study

Aim

The available evidence for predicting length of stay in acute psychiatric hospitals includes demographics, diagnosis, and treatment variables. This study aimed to evaluate the association between neutrophil-to-lymphocyte ratio (NLR) and length of hospital stay in an acute psychiatric hospital.

Methods

A total of 116 patients who were admitted to an acute psychiatric ward at Urawa Neuropsychiatric Sanatorium (Saitama, Japan) from August 2022 to December 2022 were eligible for this study. Laboratory data of lymphocytes and neutrophils were assessed on the first day of admission and NLR was calculated based on the data. Participants were categorized into two groups, high NLR and low NLR, which were set as predictor variables, as well as using NLR as a continuous variable. Multiple linear regression was performed to determine the association between NLR and length of hospital stay, adjusting for confounding factors.

Results

A total of 90 participants were included in this study. The association of NLR as a continuous variable and length of hospital stay was not significant. When we categorized participants into high- and low-NLR groups, the association was significant even after adjusting by covariates (p < 0.05).

Conclusion

Categorized NLR was positively associated with the length of hospital stay in patients admitted to an acute psychiatric hospital. Categorized NLR may predict the length of hospital stay for patients who are admitted to an acute psychiatric hospital.

The relationship between inflammatory markers, clinical characteristics, and cognitive performance in drug-naïve patients with schizophrenia

Increasing evidence implicates that inflammatory factors do play a crucial role in the pathophysiology of schizophrenia. However, the association between inflammatory markers and different symptom dimensions and cognitive function of schizophrenia remains unclear. A total of 140 drug-naïve patients with schizophrenia and 69 healthy controls matched for age and gender were enrolled. Peripheral blood plasma concentrations of S-100 calcium-binding protein B (S100B), neutrophil gelatinase-associated lipocalin (NGAL), and interferon-γ (IFN-γ) were detected by enzyme-linked immunosorbent assay (ELISA). Psychotic symptoms were measured using the Positive and Negative Syndrome Scale (PANSS), and cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Compared with healthy controls, patients with schizophrenia had significantly worse cognitive function and lower levels of NGAL and IFN-γ (P < 0.001). In schizophrenia, plasma NGAL and IFN-γ levels negatively correlated with positive symptom scores (all P < 0.05). There was a positive correlation between plasma levels of NGAL and IFN-γ with visual learning, neurocognition, and MCCB total score (all P < 0.05). We found that NGAL levels (β = 0.352, t = 5.553, 95% CI 0.228-0.477, P < 0.001) and negative symptoms subscale scores (β = - 0.321, OR = 0.725, 95% CI 648-0.811, P < 0.001) were independently associated with the MCCB total score. Further, binary logistic regression analysis indicated that the concentrations of NGAL (β = - 0.246, OR = 0.782, 95% CI 0.651-0.939, P = 0.008) were independently associated with the diagnosis of schizophrenia. There was a positive correlation between NGAL and IFN-γ levels and MCCB total score in schizophrenia. NGAL level was an independent protective factor for cognitive function and an independent risk factor for the diagnosis of schizophrenia.

Analyzing the Prevalence of Depression and Its Influencing Factors in Elderly Patients With Obstructive Sleep Apnea: A Machine Learning Approach

Objective: Depressive symptoms are prevalent and detrimental in elderly patients with obstructive sleep apnea (OSA). Understanding the factors influencing these symptoms is crucial. This study aims to use machine learning algorithms to identify the contributing factors in this population. Method: The National Health and Nutrition Examination Survey database provided the data for this study. The study includes elderly patients who are eligible for diagnostic evaluation for OSA. Logistic regression was used to screen their influencing factors, and random forest (RF), extreme gradient boosting (XGB), artificial neural network (ANN), and support vector machine (SVM) were utilized to 4 algorithms were used to construct depressive symptoms classification models, and the best model performance was selected for feature importance ranking. Influential factors included demographics (age, gender, education, etc.), chronic disease status (diabetes, hypertension, etc.), and laboratory findings (white blood cells, C-reactive protein, cholesterol, etc.). Result: Ultimately, we chose 1538 elderly OSA patients for the study, out of which 528 (34.4%) suffered from depressive symptoms. Logistic regression initially identified 17 influencing factors and then constructed classification models based on those 17 using RF, XGB, ANN, and SVM. We selected the best-performing SVM model [area under the curve (AUC) = 0.746] based on the AUC values of 0.73, 0.735, 0.742, and 0.746 for the 4 models. We ranked the variables in order of importance: General health status, sleep disorders, gender, frequency of urinary incontinence, liver disease, physical activity limitations, education, moisture, eosinophils, erythrocyte distribution width, and hearing loss. Conclusion: Elderly OSA patients experience a high incidence of depressive symptoms, influenced by various objective and subjective factors. The situation is troubling, and healthcare institutions and policymakers must prioritize their mental health. We should implement targeted initiatives to improve the mental health of high-risk groups in multiple dimensions.

Peripheral inflammation and trajectories of depressive symptomology after ischemic stroke: A prospective cohort study

BACKGROUND

Understanding the association of peripheral inflammation and post-stroke depressive symptomology (PSDS) might provide further insights into the complex etiological mechanism of organic depression. However, studies focusing on the longitudinal patterns of PSDS were limited and it remained unclear whether peripheral inflammation influences the occurrence and development of PSDS.

METHODS

A total of 427 prospectively enrolled and followed ischemic stroke patients were included in the analytical sample. Depressive symptomology was assessed on four occasions during 1 year after ischemic stroke. Peripheral inflammatory proteins on admission and repeated measures of peripheral immune markers in three stages were collected. Latent class growth analysis (LCGA) was employed to delineate group-based trajectories of peripheral immune markers and PSDS. Multinomial regression was performed to investigate the association of peripheral inflammation with PSDS trajectories.

RESULTS

Four distinct trajectories of PSDS were identified: stable-low (n = 237, 55.5 %), high-remitting (n = 120, 28.1 %), late-onset (n = 44, 10.3 %), and high-persistent (n = 26, 6.1 %) PSDS trajectories. The elevation of peripheral fibrinogen on admission increased the risk of high-persistent PSDS in patients with early high PSDS. Additionally, chronic elevation of innate immune levels might not only increase the risk of high-persistent PSDS in patients with early high PSDS but also increase the risk of late-onset PSDS in patients without early high PSDS. The elevation of adaptive immune levels in the convalescence of ischemic stroke may contribute to the remission of early high PSDS.

CONCLUSIONS

Peripheral immunity could influence the development of PSDS, and this influence might have temporal heterogeneity. These results might provide vital clues for the inflammation hypothesis of PSD.

Repetitive Administration of Low-Dose Lipopolysaccharide Improves Repeated Social Defeat Stress-Induced Behavioral Abnormalities and Aberrant Immune Response

Repetitive exposure of innate immune cells to a subthreshold dosage of endotoxin components may modulate inflammatory responses. However, the regulatory mechanisms in the interactions between the central nervous system (CNS) and the immune system remain unclear. This study aimed to investigate the effects of lipopolysaccharide (LPS) preconditioning in repeated social defeat stress (RSDS)-induced abnormal immune responses and behavioral impairments. This study aimed to elucidate the mechanisms that underlie the protective effects of repeated administration of a subthreshold dose LPS on behavioral impairments using the RSDS paradigm. LPS preconditioning improved abnormal behaviors in RSDS-defeated mice, accompanied by decreased monoamine oxidases and increased glucocorticoid receptor expression in the hippocampus. In addition, pre-treated with LPS significantly decreased the recruited peripheral myeloid cells (CD11b+CD45hi), mainly circulating inflammatory monocytes (CD11b+CD45hiLy6ChiCCR2+) into the brain in response to RSDS challenge. Importantly, we found that LPS preconditioning exerts its protective properties by regulating lipocalin-2 (LCN2) expression in microglia, which subsequently induces expressions of chemokine CCL2 and pro-inflammatory cytokine. Subsequently, LPS-preconditioning lessened the resident microglia population (CD11b+CD45intCCL2+) in the brains of the RSDS-defeated mice. Moreover, RSDS-associated expressions of leukocytes (CD11b+CD45+CCR2+) and neutrophils (CD11b+CD45+Ly6G+) in the bone marrow, spleen, and blood were also attenuated by LPS-preconditioning. In particular, LPS preconditioning also promoted the expression of endogenous antioxidants and anti-inflammatory proteins in the hippocampus. Our results demonstrate that LPS preconditioning ameliorates lipocalin 2-associated microglial activation and aberrant immune response and promotes the expression of endogenous antioxidants and anti-inflammatory protein, thereby maintaining the homeostasis of pro-inflammation/anti-inflammation in both the brain and immune system, ultimately protecting the mice from RSDS-induced aberrant immune response and behavioral changes.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we performed an exploratory study of the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. Overall, we observed relatively weak associations (p < 1 × 10-4) with BP phenotypes within immune-related genes. Network and functional enrichment analyses of the top findings from the association analyses of Li response variables showed an overrepresentation of pathways participating in cell adhesion and intercellular communication. These appeared to converge on the well-known Li-induced inhibition of GSK-3β. Association analyses of age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation suggested modest contributions of genes such as RTN4, XKR4, NRXN1, NRG1/3 and GRK5 to disease characteristics. PGS analyses returned weak associations (p < 0.05) between inflammation markers and the studied BP phenotypes. Our results suggest a modest relationship between immunity and clinical features in BP. More research is needed to assess the potential therapeutic relevance.

Understanding the Biological Relationship between Migraine and Depression

Migraine is a highly prevalent neurological disorder. Among the risk factors identified, psychiatric comorbidities, such as depression, seem to play an important role in its onset and clinical course. Patients with migraine are 2.5 times more likely to develop a depressive disorder; this risk becomes even higher in patients suffering from chronic migraine or migraine with aura. This relationship is bidirectional, since depression also predicts an earlier/worse onset of migraine, increasing the risk of migraine chronicity and, consequently, requiring a higher healthcare expenditure compared to migraine alone. All these data suggest that migraine and depression may share overlapping biological mechanisms. Herein, this review explores this topic in further detail: firstly, by introducing the common epidemiological and risk factors for this comorbidity; secondly, by focusing on providing the cumulative evidence of common biological aspects, with a particular emphasis on the serotoninergic system, neuropeptides such as calcitonin-gene-related peptide (CGRP), pituitary adenylate cyclase-activating polypeptide (PACAP), substance P, neuropeptide Y and orexins, sexual hormones, and the immune system; lastly, by remarking on the future challenges required to elucidate the etiopathological mechanisms of migraine and depression and providing updated information regarding new key targets for the pharmacological treatment of these clinical entities.

Systemic inflammatory biomarkers in Schizophrenia are changed by ECT administration and related to the treatment efficacy

Immune inflammation has long been implicated in the pathogenesis of schizophrenia. Despite as a rapid and effective physical therapy, the role of immune inflammation in electroconvulsive therapy (ECT) for schizophrenia remains elusive. The neutrophils to lymphocytes (NLR), platelets to monocytes (PLR) and monocytes to lymphocytes (MLR) are inexpensive and accessible biomarkers of systemic inflammation. In this study, 70 schizophrenia patients and 70 age- and sex-matched healthy controls were recruited. The systemic inflammatory biomarkers were measured before and after ECT. Our results indicated schizophrenia had significantly higher peripheral NLR, PLR and MLR compared to health controls at baseline, while lymphocytes did not differ. After 6 ECT, the psychiatric symptoms were significantly improved, as demonstrated by the Positive and Negative Syndrome Scale (PANSS). However, there was a decline in cognitive function scores, as indicated by the Mini-Mental State Examination (MMSE). Notably, the neutrophils and NLR were significantly reduced following ECT. Although lymphocytes remained unchanged following ECT, responders had significantly higher lymphocytes compared to non-responders. Moreover, the linear regression analyses revealed that higher lymphocytes served as a predictor of larger improvement in positive symptom following ECT. Overall, our findings further highlighted the presence of systemic inflammation in schizophrenia patients, and that ECT may exert a therapeutic effect in part by attenuating systemic inflammation. Further research may therefore lead to new treatment strategies for schizophrenia targeting the immune system.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Peripheral immunity and risk of incident brain disorders: a prospective cohort study of 161,968 participants

Whether peripheral immunity prospectively influences brain health remains controversial. This study aims to investigate the longitudinal associations between peripheral immunity markers with incident brain disorders. A total of 161,968 eligible participants from the UK Biobank were included. We investigated the linear and non-linear effects of peripheral immunity markers including differential leukocytes counts, their derived ratios and C-reactive protein (CRP) on the risk of dementia, Parkinson's disease (PD), stroke, schizophrenia, bipolar affective disorder (BPAD), major depressive disorder (MDD) and anxiety, using Cox proportional hazard models and restricted cubic spline models. Linear regression models were used to explore potential mechanisms driven by brain structures. During a median follow-up of 9.66 years, 16,241 participants developed brain disorders. Individuals with elevated innate immunity markers including neutrophils, monocytes, platelets, neutrophil-to-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII) had an increased risk of brain disorders. Among these markers, neutrophils exhibited the most significant correlation with risk of dementia (hazard ratio 1.08, 95% confidence interval 1.04-1.12), stroke (HR 1.06, 95% CI 1.03-1.09), MDD (HR 1.13, 95% CI 1.10-1.16) and anxiety (HR 1.07, 95% CI 1.04-1.10). Subgroup analysis revealed age-specific and sex-specific associations between innate immunity markers with risk of dementia and MDD. Neuroimaging analysis highlighted the associations between peripheral immunity markers and alterations in multiple cortical, subcortical regions and white matter tracts, typically implicated in dementia and psychiatric disorders. These findings support the hypothesis that neuroinflammation is important to the etiology of various brain disorders, offering new insights into their potential therapeutic approaches.

A preliminary composite of blood-based biomarkers to distinguish major depressive disorder and bipolar disorder in adolescents and adults

BACKGROUND

Since diagnosis of mood disorder heavily depends on signs and symptoms, emerging researches have been studying biomarkers with the attempt to improve diagnostic accuracy, but none of the findings have been broadly accepted. The purpose of the present study was to construct a preliminary diagnostic model to distinguish major depressive disorder (MDD) and bipolar disorder (BD) using potential commonly tested blood biomarkers.

METHODS

Information of 721 inpatients with an ICD-10 diagnosis of MDD or BD were collected from the electronic medical record system. Variables in the nomogram were selected by best subset selection method after a prior univariable screening, and then constructed using logistic regression with inclusion of the psychotropic medication use. The discrimination, calibration and internal validation of the nomogram were evaluated by the receiver operating characteristic curve (ROC), the calibration curve, cross validation and subset validation method.

RESULTS

The nomogram consisted of five variables, including age, eosinophil count, plasma concentrations of prolactin, total cholesterol, and low-density lipoprotein cholesterol. The model could discriminate between MDD and BD with an area under the ROC curve (AUC) of 0.858, with a sensitivity of 0.716 and a specificity of 0.890.

CONCLUSION

The comprehensive nomogram constructed by the present study can be convenient to distinguish MDD and BD since the incorporating variables were common indicators in clinical practice. It could help avoid misdiagnoses and improve prognosis of the patients.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

Identification of mitophagy-related biomarkers and immune infiltration in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a life-threatening and debilitating mental health condition. Mitophagy, a form of selective autophagy that eliminates dysfunctional mitochondria, is associated with depression. However, studies on the relationship between mitophagy-related genes (MRGs) and MDD are scarce. This study aimed to identify potential mitophagy-related biomarkers for MDD and characterize the underlying molecular mechanisms.

METHODS

The gene expression profiles of 144 MDD samples and 72 normal controls were retrieved from the Gene Expression Omnibus database, and the MRGs were extracted from the GeneCards database. Consensus clustering was used to determine MDD clusters. Immune cell infiltration was evaluated using CIBERSORT. Functional enrichment analyses were performed to determine the biological significance of mitophagy-related differentially expressed genes (MR-DEGs). Weighted gene co-expression network analysis, along with a network of protein-protein interactions (PPI), was used to identify key modules and hub genes. Based on the least absolute shrinkage and selection operator analysis and univariate Cox regression analysis, a diagnostic model was constructed and evaluated using receiver operating characteristic curves and validated with training data and external validation data. We reclassified MDD into two molecular subtypes according to biomarkers and evaluated their expression levels.

RESULTS

In total, 315 MDD-related MR-DEGs were identified. Functional enrichment analyses revealed that MR-DEGs were mainly enriched in mitophagy-related biological processes and multiple neurodegenerative disease pathways. Two distinct clusters with diverse immune infiltration characteristics were identified in the 144 MDD samples. MATR3, ACTL6A, FUS, BIRC2, and RIPK1 have been identified as potential biomarkers of MDD. All biomarkers showed varying degrees of correlation with immune cells. In addition, two molecular subtypes with distinct mitophagy gene signatures were identified.

CONCLUSIONS

We identified a novel five-MRG gene signature that has excellent diagnostic performance and identified an association between MRGs and the immune microenvironment in MDD.