The potential of baicalin to enhance neuroprotection and mitochondrial function in a human neuronal cell model.

Baicalin is a flavone glycoside derived from flowering plants belonging to the Scutellaria genus. Previous studies have reported baicalin's anti-inflammatory and neuroprotective properties in rodent models, indicating the potential of baicalin in neuropsychiatric disorders where alterations in numerous processes are observed. However, the extent of baicalin's therapeutic effects remains undetermined in a human cell model, more specifically, neuronal cells to mimic the brain environment in vitro. As a proof of concept, we treated C8-B4 cells (murine cell model) with three different doses of baicalin (0.1, 1 and 5 µM) and vehicle control (DMSO) for 24 h after liposaccharide-induced inflammation and measured the levels of TNF-α in the medium by ELISA. NT2-N cells (human neuronal-like cell model) underwent identical baicalin treatment, followed by RNA extraction, genome-wide mRNA expression profiles and gene set enrichment analysis (GSEA). We also performed neurite outgrowth assays and mitochondrial flux bioanalysis (Seahorse) in NT2-N cells. We found that in C8-B4 cells, baicalin at ≥ 1 µM exhibited anti-inflammatory effects, lowering TNF-α levels in the cell culture media. In NT2-N cells, baicalin positively affected neurite outgrowth and transcriptionally up-regulated genes in the tricarboxylic acid cycle and the glycolysis pathway. Similarly, Seahorse analysis showed increased oxygen consumption rate in baicalin-treated NT2-N cells, an indicator of enhanced mitochondrial function. Together, our findings have confirmed the neuroprotective and mitochondria enhancing effects of baicalin in human-neuronal like cells. Given the increased prominence of mitochondrial mechanisms in diverse neuropsychiatric disorders and the paucity of mitochondrial therapeutics, this suggests the potential therapeutic application of baicalin in human neuropsychiatric disorders where these processes are altered.

Network-based drug repurposing for schizophrenia.

Despite recent progress, the challenges in drug discovery for schizophrenia persist. However, computational drug repurposing has gained popularity as it leverages the wealth of expanding biomedical databases. Network analyses provide a comprehensive understanding of transcription factor (TF) regulatory effects through gene regulatory networks, which capture the interactions between TFs and target genes by integrating various lines of evidence. Using the PANDA algorithm, we examined the topological variances in TF-gene regulatory networks between individuals with schizophrenia and healthy controls. This algorithm incorporates binding motifs, protein interactions, and gene co-expression data. To identify these differences, we subtracted the edge weights of the healthy control network from those of the schizophrenia network. The resulting differential network was then analysed using the CLUEreg tool in the GRAND database. This tool employs differential network signatures to identify drugs that potentially target the gene signature associated with the disease. Our analysis utilised a large RNA-seq dataset comprising 532 post-mortem brain samples from the CommonMind project. We constructed co-expression gene regulatory networks for both schizophrenia cases and healthy control subjects, incorporating 15,831 genes and 413 overlapping TFs. Through drug repurposing, we identified 18 promising candidates for repurposing as potential treatments for schizophrenia. The analysis of TF-gene regulatory networks revealed that the TFs in schizophrenia predominantly regulate pathways associated with energy metabolism, immune response, cell adhesion, and thyroid hormone signalling. These pathways represent significant targets for therapeutic intervention. The identified drug repurposing candidates likely act through TF-targeted pathways. These promising candidates, particularly those with preclinical evidence such as rimonabant and kaempferol, warrant further investigation into their potential mechanisms of action and efficacy in alleviating the symptoms of schizophrenia.

Amyloid beta 42 alters cardiac metabolism and impairs cardiac function in male mice with obesity.

There are epidemiological associations between obesity and type 2 diabetes, cardiovascular disease and Alzheimer's disease. The role of amyloid beta 42 (Aß42) in these diverse chronic diseases is obscure. Here we show that adipose tissue releases Aß42, which is increased from adipose tissue of male mice with obesity and is associated with higher plasma Aß42. Increasing circulating Aß42 levels in male mice without obesity has no effect on systemic glucose homeostasis but has obesity-like effects on the heart, including reduced cardiac glucose clearance and impaired cardiac function. The closely related Aß40 isoform does not have these same effects on the heart. Administration of an Aß-neutralising antibody prevents obesity-induced cardiac dysfunction and hypertrophy. Furthermore, Aß-neutralising antibody administration in established obesity prevents further deterioration of cardiac function. Multi-contrast transcriptomic analyses reveal that Aß42 impacts pathways of mitochondrial metabolism and exposure of cardiomyocytes to Aß42 inhibits mitochondrial complex I. These data reveal a role for systemic Aß42 in the development of cardiac disease in obesity and suggest that therapeutics designed for Alzheimer's disease could be effective in combating obesity-induced heart failure.

Use of gene regulatory network analysis to repurpose drugs to treat bipolar disorder.

BACKGROUND: Bipolar disorder (BD) presents significant challenges in drug discovery, necessitating alternative approaches. Drug repurposing, leveraging computational techniques and expanding biomedical data, holds promise for identifying novel treatment strategies. METHODS: This study utilized gene regulatory networks (GRNs) to identify significant regulatory changes in BD, using network-based signatures for drug repurposing. Employing the PANDA algorithm, we investigated the variations in transcription factor-GRNs between individuals with BD and unaffected individuals, incorporating binding motifs, protein interactions, and gene co-expression data. The differences in edge weights between BD and controls were then used as differential network signatures to identify drugs potentially targeting the disease-associated gene signature, employing the CLUEreg tool in the GRAND database. RESULTS: Using a large RNA-seq dataset of 216 post-mortem brain samples from the CommonMind consortium, we constructed GRNs based on co-expression for individuals with BD and unaffected controls, involving 15,271 genes and 405 TFs. Our analysis highlighted significant influences of these TFs on immune response, energy metabolism, cell signalling, and cell adhesion pathways in the disorder. By employing drug repurposing, we identified 10 promising candidates potentially repurposed as BD treatments. LIMITATIONS: Non-drug-naïve transcriptomics data, bulk analysis of BD samples, potential bias of GRNs towards well-studied genes. CONCLUSIONS: Further investigation into repurposing candidates, especially those with preclinical evidence supporting their efficacy, like kaempferol and pramocaine, is warranted to understand their mechanisms of action and effectiveness in treating BD. Additionally, novel targets such as PARP1 and A2b offer opportunities for future research on their relevance to the disorder.

Class IIa HDACs inhibit cell death pathways and protect muscle integrity in response to lipotoxicity.

Lipotoxicity, the accumulation of lipids in non-adipose tissues, alters the metabolic transcriptome and mitochondrial metabolism in skeletal muscle. The mechanisms involved remain poorly understood. Here we show that lipotoxicity increased histone deacetylase 4 (HDAC4) and histone deacetylase 5 (HDAC5), which reduced the expression of metabolic genes and oxidative metabolism in skeletal muscle, resulting in increased non-oxidative glucose metabolism. This metabolic reprogramming was also associated with impaired apoptosis and ferroptosis responses, and preserved muscle cell viability in response to lipotoxicity. Mechanistically, increased HDAC4 and 5 decreased acetylation of p53 at K120, a modification required for transcriptional activation of apoptosis. Redox drivers of ferroptosis derived from oxidative metabolism were also reduced. The relevance of this pathway was demonstrated by overexpression of loss-of-function HDAC4 and HDAC5 mutants in skeletal muscle of obese db/db mice, which enhanced oxidative metabolic capacity, increased apoptosis and ferroptosis and reduced muscle mass. This study identifies HDAC4 and HDAC5 as repressors of skeletal muscle oxidative metabolism, which is linked to inhibition of cell death pathways and preservation of muscle integrity in response to lipotoxicity.

Effects of antipsychotic drugs on energy metabolism.

Schizophrenia (SCZ) is a complex neuropsychiatric disorder associated with altered bioenergetic pathways and mitochondrial dysfunction. Antipsychotic medications, both first and second-generation, are commonly prescribed to manage SCZ symptoms, but their direct impact on mitochondrial function remains poorly understood. In this study, we investigated the effects of commonly prescribed antipsychotics on bioenergetic pathways in cultured neurons. We examined the impact of risperidone, aripiprazole, amisulpride, and clozapine on gene expression, mitochondrial bioenergetic profile, and targeted metabolomics after 24-h treatment, using RNA-seq, Seahorse XF24 Flux Analyser, and gas chromatography-mass spectrometry (GC-MS), respectively. Risperidone treatment reduced the expression of genes involved in oxidative phosphorylation, the tricarboxylic acid cycle, and glycolysis pathways, and it showed a tendency to decrease basal mitochondrial respiration. Aripiprazole led to dose-dependent reductions in various mitochondrial function parameters without significantly affecting gene expression. Aripiprazole, amisulpride and clozapine treatment showed an effect on the tricarboxylic acid cycle metabolism, leading to more abundant metabolite levels. Antipsychotic drug effects on mitochondrial function in SCZ are multifaceted. While some drugs have greater effects on gene expression, others appear to exert their effects through enzymatic post-translational or allosteric modification of enzymatic activity. Understanding these effects is crucial for optimising treatment strategies for SCZ. Novel therapeutic interventions targeting energy metabolism by post-transcriptional pathways might be more effective as these can more directly and efficiently regulate energy production.

Metergoline Shares Properties with Atypical Antipsychotic Drugs Identified by Gene Expression Signature Screen.

Novel approaches are required to find new treatments for schizophrenia and other neuropsychiatric disorders. This study utilised a combination of in vitro transcriptomics and in silico analysis with the BROAD Institute's Connectivity Map to identify drugs that can be repurposed to treat psychiatric disorders. Human neuronal (NT2-N) cells were treated with a combination of atypical antipsychotic drugs commonly used to treat psychiatric disorders (such as schizophrenia, bipolar disorder, and major depressive disorder), and differential gene expression was analysed. Biological pathways with an increased gene expression included circadian rhythm and vascular endothelial growth factor signalling, while the adherens junction and cell cycle pathways were transcriptionally downregulated. The Connectivity Map (CMap) analysis screen highlighted drugs that affect global gene expression in a similar manner to these psychiatric disorder treatments, including several other antipsychotic drugs, confirming the utility of this approach. The CMap screen specifically identified metergoline, an ergot alkaloid currently used to treat seasonal affective disorder, as a drug of interest. In mice, metergoline dose-dependently reduced MK-801- or methamphetamine-induced locomotor hyperactivity confirming the potential of metergoline to treat positive symptoms of schizophrenia in an animal model. Metergoline had no effects on prepulse inhibition deficits induced by MK-801 or methamphetamine. Taken together, metergoline appears a promising drug for further studies to be repurposed as a treatment for schizophrenia and possibly other psychiatric disorders.

Impact of Mood Disorder History and Bone Health on Cognitive Function Among Men Without Dementia.

BACKGROUND: Poor cognitive function, a major disabling condition of older age, is often considered a prodromal feature of dementia. High mortality and the lack of a cure for dementia have necessitated a focus on the identification of potentially modifiable risk factors. Mental and physical health conditions such as mood disorders and bone loss have been previously linked with poor cognition individually although their combined effect remains largely unknown. OBJECTIVE: Considering the multifactorial nature of dementia pathology, we investigated whether mood disorders, bone health and their interaction are associated with cognitive function in a population-based sample of men. METHODS: Four hundred and forty-two male participants were drawn from the Geelong Osteoporosis Study. Cognitive function was assessed using the CogState Brief Battery, which measured cognitive performance across four domains and was used to compute overall cognitive function. Mood disorders and hip bone mineral density (BMD) were determined using a semi-structured clinical interview and dual-energy X-ray absorptiometry, respectively. RESULTS: Hip BMD (Bcoeff = 0.56, 95% CI: [0.07, 1.05], p = 0.025) but not mood disorder (Bcoeff = -0.50, 95% CI: [-0.20, 0.10], p = 0.529) was associated with overall cognitive function after accounting for potential confounders. Interaction effects were observed between the two exposures (Bcoeff = -1.37, 95% CI: [-2.49, -0.26], p = 0.016) suggesting that individuals without a mood disorder displayed better cognitive performance with increasing BMD, while those with a lifetime history of mood disorder displayed poorer cognitive function with increasing BMD. CONCLUSIONS: These findings highlight the importance of exploring interactions among potentially modifiable health conditions associated with cognitive function.

Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management.

Populations with common physical diseases - such as cardiovascular diseases, cancer and neurodegenerative disorders - experience substantially higher rates of major depressive disorder (MDD) than the general population. On the other hand, people living with MDD have a greater risk for many physical diseases. This high level of comorbidity is associated with worse outcomes, reduced adherence to treatment, increased mortality, and greater health care utilization and costs. Comorbidity can also result in a range of clinical challenges, such as a more complicated therapeutic alliance, issues pertaining to adaptive health behaviors, drug-drug interactions and adverse events induced by medications used for physical and mental disorders. Potential explanations for the high prevalence of the above comorbidity involve shared genetic and biological pathways. These latter include inflammation, the gut microbiome, mitochondrial function and energy metabolism, hypothalamic-pituitary-adrenal axis dysregulation, and brain structure and function. Furthermore, MDD and physical diseases have in common several antecedents related to social factors (e.g., socioeconomic status), lifestyle variables (e.g., physical activity, diet, sleep), and stressful live events (e.g., childhood trauma). Pharmacotherapies and psychotherapies are effective treatments for comorbid MDD, and the introduction of lifestyle interventions as well as collaborative care models and digital technologies provide promising strategies for improving management. This paper aims to provide a detailed overview of the epidemiology of the comorbidity of MDD and specific physical diseases, including prevalence and bidirectional risk; of shared biological pathways potentially implicated in the pathogenesis of MDD and common physical diseases; of socio-environmental factors that serve as both shared risk and protective factors; and of management of MDD and physical diseases, including prevention and treatment. We conclude with future directions and emerging research related to optimal care of people with comorbid MDD and physical diseases.

CaMKK2 as an emerging treatment target for bipolar disorder.

Current pharmacological treatments for bipolar disorder are inadequate and based on serendipitously discovered drugs often with limited efficacy, burdensome side-effects, and unclear mechanisms of action. Advances in drug development for the treatment of bipolar disorder remain incremental and have come largely from repurposing drugs used for other psychiatric conditions, a strategy that has failed to find truly revolutionary therapies, as it does not target the mood instability that characterises the condition. The lack of therapeutic innovation in the bipolar disorder field is largely due to a poor understanding of the underlying disease mechanisms and the consequent absence of validated drug targets. A compelling new treatment target is the Ca2+-calmodulin dependent protein kinase kinase-2 (CaMKK2) enzyme. CaMKK2 is highly enriched in brain neurons and regulates energy metabolism and neuronal processes that underpin higher order functions such as long-term memory, mood, and other affective functions. Loss-of-function polymorphisms and a rare missense mutation in human CAMKK2 are associated with bipolar disorder, and genetic deletion of Camkk2 in mice causes bipolar-like behaviours similar to those in patients. Furthermore, these behaviours are ameliorated by lithium, which increases CaMKK2 activity. In this review, we discuss multiple convergent lines of evidence that support targeting of CaMKK2 as a new treatment strategy for bipolar disorder.

A plasma protein signature associated with cognitive function in men without severe cognitive impairment.

BACKGROUND: A minimally invasive blood-based assessment of cognitive function could be a promising screening strategy to identify high-risk groups for the incidence of Alzheimer's disease. METHODS: The study included 448 cognitively unimpaired men (mean age 64.1 years) drawn from the Geelong Osteoporosis Study. A targeted mass spectrometry-based proteomic assay was performed to measure the abundance levels of 269 plasma proteins followed by linear regression analyses adjusted for age and APOE ε4 carrier status to identify the biomarkers related to overall cognitive function. Furthermore, two-way interactions were conducted to see whether Alzheimer's disease-linked genetic variants or health conditions modify the association between biomarkers and cognitive function. RESULTS: Ten plasma proteins showed an association with overall cognitive function. This association was modified by allelic variants in genes ABCA7, CLU, BDNF and MS4A6A that have been previously linked to Alzheimer's disease. Modifiable health conditions such as mood disorders and poor bone health, which are postulated to be risk factors for Alzheimer's disease, also impacted the relationship observed between protein marker levels and cognition. In addition to the univariate analyses, an 11-feature multianalyte model was created using the least absolute shrinkage and selection operator regression that identified 10 protein features and age associated with cognitive function. CONCLUSIONS: Overall, the present study revealed plasma protein candidates that may contribute to the development of a blood-based screening test for identifying early cognitive changes. This study also highlights the importance of considering other risk factors in elucidating the relationship between biomarkers and cognition, an area that remains largely unexplored.

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance.

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. 'Diversity Outbred in Australia (DOz)' is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle's contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.

Metabolic regulation to treat bipolar depression: mechanisms and targeting by trimetazidine.

Bipolar disorder's core feature is the pathological disturbances in mood, often accompanied by disrupted thinking and behavior. Its complex and heterogeneous etiology implies that a range of inherited and environmental factors are involved. This heterogeneity and poorly understood neurobiology pose significant challenges to existing drug development paradigms, resulting in scarce treatment options, especially for bipolar depression. Therefore, novel approaches are needed to discover new treatment options. In this review, we first highlight the main molecular mechanisms known to be associated with bipolar depression-mitochondrial dysfunction, inflammation and oxidative stress. We then examine the available literature for the effects of trimetazidine in said alterations. Trimetazidine was identified without a priori hypothesis using a gene-expression signature for the effects of a combination of drugs used to treat bipolar disorder and screening a library of off-patent drugs in cultured human neuronal-like cells. Trimetazidine is used to treat angina pectoris for its cytoprotective and metabolic effects (improved glucose utilization for energy production). The preclinical and clinical literature strongly support trimetazidine's potential to treat bipolar depression, having anti-inflammatory and antioxidant properties while normalizing mitochondrial function only when it is compromised. Further, trimetazidine's demonstrated safety and tolerability provide a strong rationale for clinical trials to test its efficacy to treat bipolar depression that could fast-track its repurposing to address such an unmet need as bipolar depression.

Use of a gene expression signature to identify trimetazidine for repurposing to treat bipolar depression.

OBJECTIVES: The aim of this study was to repurpose a drug for the treatment of bipolar depression. METHODS: A gene expression signature representing the overall transcriptomic effects of a cocktail of drugs widely prescribed to treat bipolar disorder was generated using human neuronal-like (NT2-N) cells. A compound library of 960 approved, off-patent drugs were then screened to identify those drugs that affect transcription most similar to the effects of the bipolar depression drug cocktail. For mechanistic studies, peripheral blood mononuclear cells were obtained from a healthy subject and reprogrammed into induced pluripotent stem cells, which were then differentiated into co-cultured neurons and astrocytes. Efficacy studies were conducted in two animal models of depressive-like behaviours (Flinders Sensitive Line rats and social isolation with chronic restraint stress rats). RESULTS: The screen identified trimetazidine as a potential drug for repurposing. Trimetazidine alters metabolic processes to increase ATP production, which is thought to be deficient in bipolar depression. We showed that trimetazidine increased mitochondrial respiration in cultured human neuronal-like cells. Transcriptomic analysis in induced pluripotent stem cell-derived neuron/astrocyte co-cultures suggested additional mechanisms of action via the focal adhesion and MAPK signalling pathways. In two different rodent models of depressive-like behaviours, trimetazidine exhibited antidepressant-like activity with reduced anhedonia and reduced immobility in the forced swim test. CONCLUSION: Collectively our data support the repurposing of trimetazidine for the treatment of bipolar depression.

Alteration patterns of peripheral concentrations of cytokines and associated inflammatory proteins in acute and chronic stages of schizophrenia: a systematic review and network meta-analysis.

BACKGROUND: Immune system dysfunction is considered to play an aetiological role in schizophrenia spectrum disorders, with substantial alterations in the concentrations of specific peripheral inflammatory proteins, such as cytokines. However, there are inconsistencies in the literature over which inflammatory proteins are altered throughout the course of illness. Through conducting a systematic review and network meta-analysis, this study aimed to investigate the patterns of alteration that peripheral inflammatory proteins undergo in both acute and chronic stages of schizophrenia spectrum disorders, relative to a healthy control population. METHODS: In this systematic review and meta-analysis, we searched PubMed, PsycINFO, EMBASE, CINAHL, and the Cochrane Central Register of Controlled Trials from inception to March 31, 2022, for published studies reporting peripheral inflammatory protein concentrations in cases of people with schizophrenia-spectrum disorders and healthy controls. Inclusion criteria were: (1) observational or experimental design; (2) a population consisting of adults diagnosed with schizophrenia-spectrum disorders with a specified indicator of acute or chronic stage of illness; (3) a comparable healthy control population without mental illness; (4) a study outcome measuring the peripheral protein concentration of a cytokine, associated inflammatory marker, or C-reactive protein. We excluded studies that did not measure cytokine proteins or associated biomarkers in blood. Mean and SDs of inflammatory marker concentrations were extracted directly from full-text publshed articles; articles that did not report data as results or supplementary results were excluded (ie, authors were not contacted) and grey literature and unpublished studies were not sought. Pairwise and network meta-analyses were done to measure the standardised mean difference in peripheral protein concentrations between three groups: individuals with acute schizophrenia-spectrum disorder, individuals with chronic schizophrenia-spectrum disorder, and healthy controls. This protocol was registered on PROSPERO, CRD42022320305. FINDINGS: Of 13 617 records identified in the database searches, 4492 duplicates were removed, 9125 were screened for eligibility, 8560 were excluded after title and abstract screening, and three were excluded due to limited access to the full-text article. 324 full-text articles were then excluded due to inappropriate outcomes, mixed or undefined schizophrenia cohorts, or duplicate study populations, five were removed due to concerns over data integrity, and 215 studies were included in the meta-analysis. 24 921 participants were included, with 13 952 adult cases of schizophrenia-spectrum disorder and 10 969 adult healthy controls (descriptive data for the entire cohort were not available for age, numbers of males and females, and ethnicity). Concentration of interleukin (IL)-1ß, IL-1 receptor antagonist (IL-1RA), soluble interleukin-2 receptor (sIL-2R), IL-6, IL-8, IL-10, tumour necrosis factor (TNF)-α, and C-reactive protein were consistently elevated in both individuals with acute schizophrenia-spectrum disorder and chronic schizophrenia-spectrum disorder, relative to healthy controls. IL-2 and interferon (IFN)-γ were significantly elevated in acute schizophrenia-spectrum disorder, while IL-4, IL-12, and IFN-γ were significantly decreased in chronic schizophrenia-spectrum disorder. Sensitivity and meta-regression analyses revealed that study quality and a majority of the evaluated methodological, demographic, and diagnostic factors had no significant impact on the observed results for most of the inflammatory markers. Specific exceptions to this included: methodological factors of assay source (for IL-2 and IL-8), assay validity (for IL-1ß), and study quality (for transforming growth factor-ß1); demographic factors of age (for IFN-γ, IL-4, and IL-12), sex (for IFN-γ and IL-12), smoking (for IL-4), and BMI (for IL-4); and diagnostic factors including diagnostic composition of schizophrenia-spectrum cohort (for IL-1ß IL-2, IL-6, and TNF-α), antipsychotic-free cases (for IL-4 and IL-1RA), illness duration (for IL-4), symptom severity (for IL-4), and subgroup composition (for IL-4). INTERPRETATION: Results suggest that people with schizophrenia-spectrum disorders have a baseline level of inflammatory protein alteration throughout the illness, as reflected by consistently elevated pro-inflammatory proteins, hypothesised here as trait markers (eg, IL-6), while those with acute psychotic illness might have superimposed immune activity with increased concentrations of hypothesised state markers (eg, IFN-γ). Further research is required to determine whether these peripheral alterations are reflected within the central nervous system. This research facilitates an entry point in understanding how clinically relevant inflammatory biomarkers might one day be useful to the diagnosis and prognostication of schizophrenia-spectrum disorders. FUNDING: None.

Minocycline as Treatment for Psychiatric and Neurological Conditions: A Systematic Review and Meta-Analysis.

Minocycline has anti-inflammatory, antioxidant, and anti-apoptotic properties that explain the renewed interest in its use as an adjunctive treatment for psychiatric and neurological conditions. Following the completion of several new clinical trials using minocycline, we proposed an up-to-date systematic review and meta-analysis of the data available. The PICO (patient/population, intervention, comparison and outcomes) framework was used to search 5 databases aiming to identify randomized controlled trials that used minocycline as an adjunctive treatment for psychiatric and neurological conditions. Search results, data extraction, and risk of bias were performed by two independent authors for each publication. Quantitative meta-analysis was performed using RevMan software. Literature search and review resulted in 32 studies being included in this review: 10 in schizophrenia, 3 studies in depression, and 7 in stroke, with the benefit of minocycline being used in some of the core symptoms evaluated; 2 in bipolar disorder and 2 in substance use, without demonstrating a benefit for using minocycline; 1 in obsessive-compulsive disorder, 2 in brain and spinal injuries, 2 in amyotrophic lateral sclerosis, 1 in Alzheimer's disease, 1 in multiple systems atrophy, and 1 in pain, with mixes results. For most of the conditions included in this review the data is still limited and difficult to interpret, warranting more well-designed and powered studies. On the other hand, the studies available for schizophrenia seem to suggest an overall benefit favoring the use of minocycline as an adjunctive treatment.

Adjunctive minocycline for major depressive disorder: A sub-study exploring peripheral immune-inflammatory markers and associated treatment response.

Background: Adjunctive minocycline shows promise in treating affective and psychotic disorders; however, the therapeutic mechanism remains unclear. Identifying relevant biomarkers may enhance the efficacy of novel adjunctive treatment candidates. We thus investigated the peripheral immune-inflammatory profile in a randomized controlled trial (RCT) of minocycline in major depressive disorder (MDD). Methods: This sub-study investigated serum samples from a RCT evaluating minocycline (200 mg/day, 12 weeks) in addition to treatment as usual for MDD (ACTRN12612000283875). Of the original sample (N = 71), serum assays were conducted in 47 participants (placebo n = 24; minocycline n = 23) targeting an array of 46 immune-inflammatory analytes including cytokines, chemokines, and acute-phase reactants. General estimating equations (GEE) were used to assess whether analyte concentration at baseline (effect modification) and change in analytes (change association) influenced change in Montgomery-Åsberg Depression Rating Scale (MADRS) score over time. The Benjamini-Hochberg approach was applied when adjusting for false discovery rates (FDR). Results: GEE models revealed several interaction effects. After adjusting for FDR several change association-models survived correction. However, no such models remained significant for effect modification. Three-way group × time × marker interactions were significant for complement C3 (B = -10.46, 95%CI [-16.832, -4.095], q = 0.019) and IL-1Ra (B = -9.008, 95%CI [-15.26, -2.751], q = 0.036). Two-way group × biomarker interactions were significant for ICAM-1/CD54 (B = -0.387, 95%CI [-0.513, -0.26], q < 0.001) and IL-8/CXCL8 (B = -4.586, 95%CI [-7.698, -1.475], q = 0.036) indicating that increases in the serum concentration of these analytes were associated with an improvement in MADRS scores in the minocycline group (compared with placebo). Conclusions: Change in complement C3, IL-1Ra, IL-8/CXCL8, and ICAM-1 may be associated with greater change in depressive scores following adjunctive minocycline treatment in MDD. Further investigations are needed to assess the utility of these biomarkers.

Identification of reversible and druggable pathways to improve beta-cell function and survival in Type 2 diabetes.

Targeting ß-cell failure could prevent, delay or even partially reverse Type 2 diabetes. However, development of such drugs is limited as the molecular pathogenesis is complex and incompletely understood. Further, while ß-cell failure can be modeled experimentally, only some of the molecular changes will be pathogenic. Therefore, we used a novel approach to identify molecular pathways that are not only changed in a diabetes-like state but also are reversible and can be targeted by drugs. INS1E cells were cultured in high glucose (HG, 20 mM) for 72 h or HG for an initial 24 h followed by drug addition (exendin-4, metformin and sodium salicylate) for the remaining 48 h. RNAseq (Illumina TruSeq), gene set enrichment analysis (GSEA) and pathway analysis (using Broad Institute, Reactome, KEGG and Biocarta platforms) were used to identify changes in molecular pathways. HG decreased function and increased apoptosis in INS1E cells with drugs partially reversing these effects. HG resulted in upregulation of 109 pathways while drug treatment downregulated 44 pathways with 21 pathways in common. Interestingly, while hyperglycemia extensively upregulated metabolic pathways, they were not altered with drug treatment, rather pathways involved in the cell cycle featured more heavily. GSEA for hyperglycemia identified many known pathways validating the applicability of our cell model to human disease. However, only a fraction of these pathways were downregulated with drug treatment, highlighting the importance of considering druggable pathways. Overall, this provides a powerful approach and resource for identifying appropriate targets for the development of ß-cell drugs.

Metformin is Protective Against the Development of Mood Disorders.

INTRODUCTION: Mood disorders are a major cause of disability, and current treatment options are inadequate for reducing the burden on a global scale. The aim of this project was to identify drugs suitable for repurposing to treat mood disorders. METHODS: This mixed-method study utilized gene expression signature technology and pharmacoepidemiology to investigate drugs that may be suitable for repurposing to treat mood disorders. RESULTS: The transcriptional effects of a combination of drugs commonly used to treat mood disorders included regulation of the steroid and terpenoid backbone biosynthesis pathways, suggesting a mechanism involving cholesterol biosynthesis, and effects on the thyroid hormone signaling pathway. Connectivity Map analysis highlighted metformin, an FDA-approved treatment for type 2 diabetes, as a drug having global transcriptional effects similar to the mood disorder drug combination investigated. In a retrospective cohort study, we found evidence that metformin is protective against the onset of mood disorders. DISCUSSION: These results provide proof-of-principle of combining gene expression signature technology with pharmacoepidemiology to identify potential novel drugs for treating mood disorders. Importantly, metformin may have utility in the treatment of mood disorders, warranting future randomized controlled trials to test its efficacy.

The role of metformin as a treatment for neuropsychiatric illness.

Advances in psychopharmacology have been significantly slower to evolve than in other disciplines of medicine and therefore investigation into novel therapeutic approaches is required. Additionally, concurrent metabolic conditions are prevalent among people with mental disorders. Metformin is a widely used hypoglycaemic agent that is now being studied for use beyond diabetes management. Evidence is emerging that metformin has multiple effects on diverse neurobiological pathways and consequently may be repurposed for treating mental illness. Metformin may have beneficial neuroimmunological, neuroplastic, neuro-oxidative and neuro-nitrosative effects across a range of psychiatric and neurodegenerative illnesses. Mechanisms include glucose lowering effects and effects on AMP-activated protein kinase (AMPK) signalling, however the best evidence for clinical benefit is through the glucose lowering effects, with other mechanisms less supported by the current evidence base. This narrative review aims to draw together the existing evidence for use of metformin as a psychopharmaceutical and present the role of metformin in the context of physical and psychiatric ill health, including metabolic, endocrinological and cancer domains. It not only has therapeutic potential in medical comorbidity but may have potential in core illness domains.