Insulin effects on core neurotransmitter pathways involved in schizophrenia neurobiology: a meta-analysis of preclinical studies. Implications for the treatment

Treatments for weight gain in schizophrenia

PURPOSE OF REVIEW

Obesity and related metabolic disorders are extremely common in psychiatric patients, particularly in those with schizophrenia. Elucidating this link's neurobiology may inform clinicians and researchers of rational therapeutic approaches necessary to optimize clinical outcomes.

RECENT FINDINGS

Current literature highlights the pivotal role of the inflammation-oxidative stress-insulin resistance loop in the pathophysiology of both metabolic and neuropsychiatric disorders. The concept of 'diabetophrenia' is put forward to highlight the overlapping neurobiological mechanisms underlying metabolic dysfunction and schizophrenia symptoms. Innovative treatments, including the combination of xanomeline with trospium and incretin-based medicines, demonstrate encouraging potential in addressing such complex health challenges.

SUMMARY

The nuanced dynamics of chronic inflammation and psychiatric symptomatology underscore the significance of addressing both metabolic and mental health factors in a cohesive fashion while considering unique psychosocial contexts, dietary preferences, and lifestyle choices. A multidisciplinary strategy is essential for incorporating counseling, dietary interventions, behavioral therapies, and pharmacotherapy into the management of schizophrenia. The ensuing enhanced collaboration among healthcare professionals may render obsolete the prevailing siloed conceptualizations of mental disorders, opening new vistas for generating synergistic insights into the mind-body systems and leading to improved health and quality of life for patients with schizophrenia and other psychiatric conditions.

Bioenergetic markers in cerebrospinal fluid in first-episode psychosis: Are they predictors of early antipsychotic response and 1-year outcomes?

Psychotic disorders involve complex pathophysiological mechanisms, and identification of biomarkers for treatment response remains a major challenge. We aimed to study whether routine cerebrospinal fluid (CSF) parameters measured at baseline predict poor early response at 2 weeks with optimal antipsychotic treatment doses in patients with first-episode psychosis (FEP). We also explored whether these parameters could predict changes in social functioning and psychopathology over a 1-year follow-up. Ninety-eight inpatients with FEP who had received less than 6 weeks of antipsychotic treatment were included in the study. A lumbar puncture was performed at the index admission to measure CSF parameters (glucose, total protein, and lactate dehydrogenase [LDH]). The Positive and Negative Syndrome Scale (PANSS) was administered. A poor early treatment response at week 2 was defined as a < 20 % reduction in the PANSS positive subscore of a consensus factor. Social functioning was assessed using the Personal and Social Performance Scale (PSP) at baseline and 2, 4, 6, 9, and 12 months. Statistical analyses explored the role of CSF biomarkers in early treatment response using logistic regression and long-term social functioning and psychopathology using mixed linear regression analyses. Eighteen patients with FEP (18.4 %) were nonresponders at week 2. The CSF LDH concentration was a predictor of early treatment nonresponse. Higher CSF LDH concentrations were associated with a reduced improvement in social functioning at month 2, and higher CSF glucose concentrations were associated with lower reductions in the PANSS total scores at all visits. These findings suggest that specific bioenergetic parameters in the CSF, such as LDH and glucose, may serve as prognostic biomarkers for early treatment response and 1-year social and psychopathological outcomes in patients with FEP.

Prevalence and Risk of Schizophrenia and Bipolar Disorder in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-analysis

Purpose of the Review

Schizophrenia and bipolar disorder are understood to have neuroinflammatory/neuro-immunological basis in their etiopathogenesis. There are few studies synthesizing the association of schizophrenia and bipolar disorder in type 1 diabetes mellitus (T1DM), a common immunological disorder.

Collection and Analysis of Data

We performed meta-analyses of studies assessing the prevalence and risk of schizophrenia and related disorders and bipolar disorder in individuals with T1DM. Fifteen studies consisting of a total sample of 9,768,028 (T1DM: 435,553; non-T1DM controls: 9,332,475) were included. Random-effects meta-analyses using the restricted maximum likelihood method for pooling logit transformed prevalence values and the Mantel-Haenszel test for pooling risk ratios were used. I 2 statistic and the rank correlation test for Funnel plots' asymmetry were used to assess heterogeneity and publication bias, respectively.

Results

Pooled (transformed-back-transformed) prevalence for schizophrenia and related psychotic disorders was 0.37% (95%CI: 0.19-0.73), and for bipolar disorder it was 0.39% (95%CI: 0.05-2.99) (together: 0.38% (95%CI: 0.2-0.71)] in T1DM. The prevalence models showed significant heterogeneity but were statistically significant, had low publication bias, and survived sensitivity analysis. The pooled risk ratio for schizophrenia and related disorders together with bipolar disorder was 1.80 (95%CI: 0.64-5.03), and for schizophrenia and related disorders alone it was 1.19 (95%CI: 0.46-3.11), indicating higher rates of these disorders in T1DM. The pooled risk ratios were not statistically significant and did not survive sensitivity analysis. Trial sequential analysis suggested the need for more studies to confirm increased risk.

Conclusion

With available studies, we could not provide convincing evidence for the hypothesis that the prevalence and risk of schizophrenia and related disorders and bipolar disorder are significantly greater in individuals with T1DM.

IUPHAR review: Drug repurposing in Schizophrenia - An updated review of clinical trials

There is an urgent need for mechanistically novel and more efficacious treatments for schizophrenia, especially those targeting negative and cognitive symptoms with a more favorable side-effect profile. Drug repurposing-the process of identifying new therapeutic uses for already approved compounds-offers a promising approach to overcoming the lengthy, costly, and high-risk process of traditional CNS drug discovery. This review aims to update our previous findings on the clinical drug repurposing pipeline in schizophrenia. We examined studies conducted between 2018 and 2024, identifying 61 trials evaluating 40 unique repurposed drug candidates. These encompassed a broad range of pharmacological mechanisms, including immunomodulation, cognitive enhancement, and hormonal, metabolic, and neurotransmitter modulation. A notable development is the combination of the muscarinic modulators xanomeline, a compound with antipsychotic properties, and trospium, included to mitigate peripheral side effects, now approved by the FDA as the first antipsychotic drug in decades with a fundamentally novel mechanism of action. Moving beyond the traditional dopaminergic paradigm of schizophrenia, such findings highlight opportunities to improve treatment-resistant symptoms and alleviate adverse effects. Overall, the evolving drug repurposing landscape illustrates a significant shift in the rationale for schizophrenia drug development, highlighting the potential of in silico strategies, biomarker-based patient stratification, and personalized treatments that align with underlying pathophysiological processes.

Addressing brain metabolic connectivity in treatment-resistant schizophrenia: a novel graph theory-driven application of 18F-FDG-PET with antipsychotic dose correction

Few studies using Positron Emission Tomography with 18F-fluorodeoxyglucose (18F-FDG-PET) have examined the neurobiological basis of antipsychotic resistance in schizophrenia, primarily focusing on metabolic activity, with none investigating connectivity patterns. Here, we aimed to explore differential patterns of glucose metabolism between patients and controls (CTRL) through a graph theory-based approach and network comparison tests. PET scans with 18F-FDG were obtained by 70 subjects, 26 with treatment-resistant schizophrenia (TRS), 28 patients responsive to antipsychotics (nTRS), and 16 CTRL. Relative brain glucose metabolism maps were processed in the automated anatomical labeling (AAL)-Merged atlas template. Inter-subject connectivity matrices were derived using Gaussian Graphical Models and group networks were compared through permutation testing. A logistic model based on machine-learning was employed to estimate the association between the metabolic signals of brain regions and treatment resistance. To account for the potential influence of antipsychotic medication, we incorporated chlorpromazine equivalents as a covariate in the network analysis during partial correlation calculations. Additionally, the machine-learning analysis employed medication dose-stratified folds. Global reduced connectivity was detected in the nTRS (p-value = 0.008) and TRS groups (p-value = 0.001) compared to CTRL, with prominent alterations localized in the frontal lobe, Default Mode Network, and dorsal dopamine pathway. Disruptions in frontotemporal and striatal-cortical connectivity were detected in TRS but not nTRS patients. After adjusting for antipsychotic doses, alterations in the anterior cingulate, frontal and temporal gyri, hippocampus, and precuneus also emerged. The machine-learning approach demonstrated an accuracy ranging from 0.72 to 0.8 in detecting the TRS condition.

Relevance of diet in schizophrenia: a review focusing on prenatal nutritional deficiency, obesity, oxidative stress and inflammation

Background/Objectives

Schizophrenia is a complex mental disorder influenced by genetic and environmental factors, including dietary habits. Oxidative stress and inflammation play a crucial role in the pathophysiology of schizophrenia. Emerging research suggests that diet may affect schizophrenia through different biological mechanisms beyond oxidative stress and inflammation. In particular, epigenetic changes may alter the expression of genes related to neurodevelopment and neurotransmitter systems, while neuroplasticity plays a crucial role in brain adaptation and resilience to psychiatric disorders.

Methods

The literature search included the main available databases (Science Direct, PubMed and Google Scholar), considering the English language, and our screening was performed based on several words such as "schizophrenia", "diet", "nutrients", "obesity", "oxidative stress", "inflammation", "antioxidants" and "prenatal nutritional deficiency". The review focused specifically on studies examining the relevance of diet in schizophrenia, as well as prenatal nutritional deficiency, obesity, oxidative stress, and inflammation associated with this disorder.

Results

Following a review of the literature, it was found that nutritional deficiencies, including lack of omega-3 fatty acids, vitamins D, and B, during the prenatal and postnatal periods can have a negative impact on neurodevelopment and increase the risk of schizophrenia. Patients with schizophrenia have imbalances in antioxidant enzymes, such as glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT), and reduced levels of antioxidants (vitamin E, vitamin C). These biochemical changes lead to an increase in markers of oxidative stress, including malondialdehyde (MDA). In addition, cytokine-mediated inflammation, microglial activation, and intestinal dysbiosis are associated with the onset of schizophrenia and the severity of schizophrenia symptoms. Currently, there is no universally accepted dietary regimen for control. However, various diets and nutritional methods are being researched and applied to alleviate the symptoms of schizophrenia and improve the overall health of patients, including the Mediterranean diet, the ketogenic diet, the gluten-free diet, and the DASH (Dietary Approaches to Stop Hypertension) diet.

Conclusion

A healthy diet, rich in anti-inflammatory nutrients and antioxidants, may help manage schizophrenia by reducing oxidative stress, preventing complications, and improving quality of life. Omega-3 fatty acids, vitamin D, and B vitamins are particularly important for brain development and function. In this review, we aim to analyze the literature on the influence of diet on schizophrenia, focusing on the role of prenatal nutritional deficiencies, obesity, oxidative stress, and inflammation.

Sex-Differential Markers of Psychiatric Risk and Treatment Response Based on Premature Aging of Functional Brain Network Dynamics and Peripheral Physiology

BACKGROUND

Aging is a multilevel process of gradual decline that predicts morbidity and mortality. Independent investigations have implicated senescence of brain and peripheral physiology in psychiatric risk, but it is unclear whether these effects stem from unique or shared mechanisms.

METHODS

To address this question, we analyzed clinical, blood chemistry, and resting-state functional neuroimaging data in a healthy aging cohort (n = 427; ages 36-100 years) and 2 disorder-specific samples including patients with early psychosis (100 patients, 16-35 years) and major depressive disorder (MDD) (104 patients, 20-76 years).

RESULTS

We identified sex-dependent coupling between blood chemistry markers of metabolic senescence (i.e., homeostatic dysregulation), functional brain network aging, and psychiatric risk. In females, premature aging of frontoparietal and somatomotor networks was linked to greater homeostatic dysregulation. It also predicted the severity and treatment resistance of mood symptoms (depression/anxiety [all 3 samples], anhedonia [MDD]) and social withdrawal/behavioral inhibition (avoidant personality disorder [healthy aging], negative symptoms [early psychosis]). In males, premature aging of the default mode, cingulo-opercular, and visual networks was linked to reduced homeostatic dysregulation and predicted the severity and treatment resistance of symptoms relevant to hostility/aggression (antisocial personality disorder [healthy aging], mania/positive symptoms [early psychosis]), impaired thought processes (early psychosis, MDD), and somatic problems (healthy aging, MDD).

CONCLUSIONS

Our findings identify sexually dimorphic relationships between brain dynamics, peripheral physiology, and risk for psychiatric illness, suggesting that the specificity of putative risk biomarkers and precision therapeutics may be improved by considering sex and other relevant personal characteristics.

Codes between Poles: Linking Transcriptomic Insights into the Neurobiology of Bipolar Disorder

Bipolar disorder (BPD) is a serious psychiatric condition that is characterized by the frequent shifting of mood patterns, ranging from manic to depressive episodes. Although there are already treatment strategies that aim at regulating the manifestations of this disorder, its etiology remains unclear and continues to be a question of interest within the scientific community. The development of RNA sequencing techniques has provided newer and better approaches to studying disorders at the transcriptomic level. Hence, using RNA-seq data, we employed intramodular connectivity analysis and network pharmacology assessment of disease-associated variants to elucidate the biological pathways underlying the complex nature of BPD. This study was intended to characterize the expression profiles obtained from three regions in the brain, which are the nucleus accumbens (nAcc), the anterior cingulate cortex (AnCg), and the dorsolateral prefrontal cortex (DLPFC), provide insights into the specific roles of these regions in the onset of the disorder, and present potential targets for drug design and development. The nAcc was found to be highly associated with genes responsible for the deregulated transcription of neurotransmitters, while the DLPFC was greatly correlated with genes involved in the impairment of components crucial in neurotransmission. The AnCg did show association with some of the expressions, but the relationship was not as strong as the other two regions. Furthermore, disease-associated variants or single nucleotide polymorphisms (SNPs) were identified among the significant genes in BPD, which suggests the genetic interrelatedness of such a disorder and other mental illnesses. DRD2, GFRA2, and DCBLD1 were the genes with disease-associated variants expressed in the nAcc; ST8SIA2 and ADAMTS16 were the genes with disease-associated variants expressed in the AnCg; and FOXO3, ITGA9, CUBN, PLCB4, and RORB were the genes with disease-associated variants expressed in the DLPFC. Aside from unraveling the molecular and cellular mechanisms behind the expression of BPD, this investigation was envisioned to propose a new research pipeline in studying the transcriptome of psychiatric disorders to support and improve existing studies.

The cross-sectional association between dietary total, animal, and plant-based protein intake and the prevalence and severity of depressive symptoms in Dutch adults with type 2 diabetes: The Hoorn Diabetes Care System cohort

OBJECTIVE

This study aimed to investigate cross-sectional associations of total, animal, and plant-based protein intake and depressive symptoms in Dutch adults with type 2 diabetes (T2D).

METHODS

We included 1137 individuals with T2D (aged 68.6 ± 9.0) from the Hoorn Diabetes Care System cohort. Energy-adjusted protein intake was assessed using a validated Food Frequency Questionnaire. The nine-item Patient Health Questionnaire (PHQ-9) was used to assess the prevalence of depressive symptoms (PHQ-9 ≥ 10 and/or anti-depressant use) and the severity of depressive symptoms (continuous PHQ-9 score). Associations between total, animal, and plant-based protein (quartiles) with depressive symptoms were assessed using multiple logistic and linear regression.

RESULTS

Highest intake of total, animal, and plant-based protein was not associated with the prevalence of depressive symptoms, compared to lowest intake (e.g., total protein, ORQ4vsQ1:0.75, 95%CI 0.42;1.32). For the severity of depressive symptoms, highest total protein intake was significantly associated with lower PHQ-9 scores (ORQ4vsQ1:0.87, 95%CI 0.75;1.00), compared to lowest intake. Animal protein was not associated with the severity of depressive symptoms (β ∼ 1), while the association for plant-based protein was marginally non-significant (βQ4vsQ1:0.88, 95%CI 0.76;1.02).

CONCLUSION

In individuals with T2D, higher total protein intake was associated with reduced severity of depressive symptoms, but not with the prevalence of depressive symptoms. Further prospective research with a larger sample size is needed to confirm these associations.

Intestinal mycobiota dysbiosis associated inflammation activation in chronic schizophrenia

The microbiome-gut-brain axis is related to schizophrenia (SCZ). The role of intestinal mycobiota in SCZ has been under investigated. We present a half-year follow-up study involving 109 chronic SCZ patients and 77 healthy controls. Intestinal mycobiota was tested by internal transcribed spacer (ITS). Untargeted liquid chromatography-mass spectrometry (LC-MS) was used to measure fecal metabolites. Symptom severity was assessed using the Positive and Negative Syndrome Scale. Enterotype analysis showed that Candida-type patients exhibited severer positive symptoms and depression factors than Saccharomyces-type patients. Candida and its top species and operational taxonomic units (OTUs) were positively correlated with depression factors (all p=0.001). Fecal metabolites analysis showed that upregulated metabolites were associated with chronic inflammation (NF-κB pathway and T helper cell differentiation), downregulated metabolites were associated with glutamate metabolism, serotonergic and dopaminergic synapse. Procrustes analysis revealed significant correlation between intestinal mycobiota and fecal metabolites (M2=0.937, p<0.001). Metabolic module analysis showed that the top module, MEturquoise (associated with Th1 and Th2 cell differentiation), was negatively correlated with SCZ (r=-0.783, p<0.0001), positively correlated with Candida, Aspergillus, Trichosporon and Talaromyces (decreased in SCZ) and negatively correlated with Saccharomyces (increased in SCZ). We also found impairments of intestinal barrier in SCZ, characterized by increased in blood D-lactate (mucosa impairment marker) and decreased in blood mucin 2 (mucosal barrier protective protein). Serum levels of TNF-α was increased and showed stable high levels during treatment. This study suggests that mycobiota dysbiosis-related chronic inflammation and an impaired intestinal mucosal barrier are associated with chronic SCZ.

Insulin resistance as the molecular link between diabetes and Alzheimer's disease

Diabetes mellitus (DM) and Alzheimer's disease (AD) are two major health concerns that have seen a rising prevalence worldwide. Recent studies have indicated a possible link between DM and an increased risk of developing AD. Insulin, while primarily known for its role in regulating blood sugar, also plays a vital role in protecting brain functions. Insulin resistance (IR), especially prevalent in type 2 diabetes, is believed to play a significant role in AD's development. When insulin signalling becomes dysfunctional, it can negatively affect various brain functions, making individuals more susceptible to AD's defining features, such as the buildup of beta-amyloid plaques and tau protein tangles. Emerging research suggests that addressing insulin-related issues might help reduce or even reverse the brain changes linked to AD. This review aims to explore the rela-tionship between DM and AD, with a focus on the role of IR. It also explores the molecular mechanisms by which IR might lead to brain changes and assesses current treatments that target IR. Understanding IR's role in the connection between DM and AD offers new possibilities for treatments and highlights the importance of continued research in this interdisciplinary field.

[Nutrition, metabolism, brain and mental health]

This review article explores the intricate relationship between nutrition, metabolism, brain function and mental health. It highlights two key complementary models: the energy balance model and the more comprehensive carbohydrate-insulin model, to understand the development of obesity and metabolic dysfunctions. It particularly focuses on the role of dopamine in dietary regulation and insulin in the brain, both of which are crucial in the pathogenesis of neurodegenerative and stress-associated mental disorders. Additionally, the significance of sleep and dietary habits, such as medically assisted calorie restriction for mental health and the concept of "brain food" are described. These findings emphasize the importance of nutritional medicine in psychiatry and psychotherapy and the consideration of metabolic states for the prevention and treatment of mental and neurodegenerative diseases.

Cognitive dysfunction in schizophrenia patients caused by down-regulation of γ-aminobutyric acid receptor subunits

BACKGROUND

The expression pattern of gamma aminobutyric acid (GABA) receptor subunits are commonly altered in patients with schizophrenia, which may lead to nerve excitation/inhibition problems, affecting cognition, emotion, and behavior.

AIM

To explore GABA receptor expression and its relationship with schizophrenia and to provide insights into more effective treatments.

METHODS

This case-control study enrolled 126 patients with schizophrenia treated at our hospital and 126 healthy volunteers who underwent physical examinations at our hospital during the same period. The expression levels of the GABA receptor subunits were detected using 1H-magnetic resonance spectroscopy. The recognized cognitive battery tool, the MATRICS Consensus Cognitive Battery, was used to evaluate the scores for various dimensions of cognitive function. The correlation between GABA receptor subunit downregulation and schizophrenia was also analyzed.

RESULTS

Significant differences in GABA receptor subunit levels were found between the case and control groups (P < 0.05). A significant difference was also found between the case and control groups in terms of cognitive function measures, including attention/alertness and learning ability (P < 0.05). Specifically, as the expression levels of GABRA1 (α1 subunit gene), GABRB2 (β2 subunit gene), GABRD (δ subunit), and GABRE (ε subunit) decreased, the severity of the patients' condition increased gradually, indicating a positive correlation between the downregulation of these 4 receptor subunits and schizophrenia (P < 0.05). However, the expression levels of GABRA5 (α5 subunit gene) and GABRA6 (α6 subunit gene) showed no significant correlation with schizophrenia (P > 0.05).

CONCLUSION

Downregulation of the GABA receptor subunits is positively correlated with schizophrenia. In other words, when GABA receptor subunits are downregulated in patients, cognitive impairment becomes more severe.

Non-Pharmacological Interventions for Type 2 Diabetes in People Living with Severe Mental Illness: Results of a Systematic Review and Meta-Analysis

BACKGROUND

People with serious mental illnesses (SMIs) such as schizophrenia and bipolar disorder die up to 30 years younger than individuals in the general population. Premature mortality among this population is often due to medical comorbidities, such as type 2 diabetes (T2D). Being a disease directly related to diet, adverse lifestyle choices, and side effects of psychotropic medication, an effective approach to T2D treatment and management could be non-pharmacological interventions. This systematic review and meta-analysis (1) summarise the current evidence base for non-pharmacological interventions (NPI) for diabetes management in people living with SMI and (2) evaluate the effect of these interventions on diverse health outcomes for people with SMI and comorbid diabetes.

METHODS

Six databases were searched to identify relevant studies: PubMed (MEDLINE), PsycINFO, Embase, Scopus, CINAHL, and Web of Science. Studies were included if they reported on non-pharmacological interventions targeted at the management of T2D in people living with SMI. To be eligible, studies had to further involve a control group or report multiple time points of data in the same study population. Whenever there were enough interventions reporting data on the same outcome, we also performed a meta-analysis.

RESULTS

Of 1867 records identified, 14 studies were included in the systematic review and 6 were also eligible for meta-analysis. The results showed that there was a reduction, although not significant, in glycated haemoglobin (HbA1c) in the NPI group compared with the control, with a mean difference of -0.14 (95% CI, -0.42, 0.14, p = 0.33). Furthermore, NPI did not significantly reduce fasting blood glucose in these participants, with a mean difference of -17.70 (95% CI, -53.77, 18.37, p = 0.34). However, the meta-analysis showed a significant reduction in psychiatric symptoms: BPRS score, -3.66 (95% CI, -6.8, -0.47, p = 0.02) and MADRS score, -2.63 (95% CI, -5.24, -0.02, p = 0.05). NPI also showed a significant reduction in the level of total cholesterol compared with the control, with a mean difference of -26.10 (95% CI, -46.54, -5.66, p = 0.01), and in low-density lipoprotein (LDL) cholesterol compared with control, with a standardised mean difference of -0.47 (95% CI, -0.90, -0.04, p = 0.03). NPI did not appear to have significant effect (p > 0.05) on body mass index (BMI), health-related quality of life (HRQL), triglycerides, and high-density lipoprotein cholesterol compared with control.

CONCLUSIONS

This systematic review and meta-analysis demonstrated that NPI significantly (p < 0.05) reduced psychiatric symptoms, levels of total cholesterol, and LDL cholesterol in people with type 2 diabetes and SMI. While non-pharmacological interventions also reduced HbA1c, triglyceride, and BMI levels and improved quality of life in these people, the effects were not significant (p > 0.05).

Gene expression analysis reveals diabetes-related gene signatures

BACKGROUND

Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction.

METHODS

A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network.

RESULTS

Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets.

CONCLUSIONS

This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.

Psychotropic Drug-Related Weight Gain and Its Treatment

Psychotropic drug-related weight gain (PDWG) is a common occurrence and is highly associated with non-initiation, discontinuation, and dissatisfaction with psychiatric drugs. Moreover, PDWG intersects with the elevated risk for obesity and associated morbidity that has been amply reported in the psychiatric population. Evidence indicates that differential liability for PDWG exists for antipsychotics, antidepressants, and anticonvulsants. During the past two decades, agents within these classes have become available with significantly lower or no liability for PDWG and as such should be prioritized. Although lithium is associated with weight gain, the overall extent of weight gain is significantly lower than previously estimated. The benefit of lifestyle and behavioral modification for obesity and/or PDWG in psychiatric populations is established, with effectiveness similar to that in the general population. Metformin is the most studied pharmacological treatment in the prevention and treatment of PDWG, and promising data are emerging for glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., liraglutide, exenatide, semaglutide). Most pharmacologic antidotes for PDWG are supported with low-confidence data (e.g., topiramate, histamine-2 receptor antagonists). Future vistas for pharmacologic treatment for PDWG include large, adequately controlled studies with GLP-1 receptor agonists and possibly GLP-1/glucose-dependent insulinotropic polypeptide co-agonists (e.g., tirzepatide) as well as specific dietary modifications.

Insulin Resistance/Diabetes and Schizophrenia: Potential Shared Genetic Factors and Implications for Better Management of Patients with Schizophrenia

Schizophrenia is a complex psychotic disorder with co-occurring conditions, including insulin resistance and type 2 diabetes (T2D). It is well established that T2D and its precursors (i.e., insulin resistance) are more prevalent in patients with schizophrenia who are treated with antipsychotics, as well as in antipsychotic-naïve patients experiencing their first episode of psychosis, compared with the general population. However, the mechanism(s) underlying the increased susceptibility, shared genetics, and possible cause-effect relationship between schizophrenia and T2D remain largely unknown. The objective of this narrative review was to synthesize important studies, including Mendelian randomization (MR) analyses that have integrated genome-wide association studies (GWAS), as well as results from in vitro models, in vivo models, and observational studies of patients with schizophrenia. Both GWAS and MR studies have found that schizophrenia and T2D/insulin resistance share genetic risk factors, and this may mediate a connection between peripheral or brain insulin resistance and T2D with cognition impairment and an increased risk of developing prediabetes and T2D in schizophrenia. Moreover, accumulating evidence supports a causal role for insulin resistance in schizophrenia and emphasizes the importance of a genetic basis for susceptibility to T2D in patients with schizophrenia before they receive psychotic treatment. The present findings and observations may have clinical implications for the development of better strategies to treat patients with schizophrenia, with both pharmacological (i.e., samidorphan, empagliflozin) and/or nonpharmacological (i.e., lifestyle changes) approaches. Additionally, this review may benefit the design of future studies by physicians and clinical investigators.

Restoring autophagic function: a case for type 2 diabetes mellitus drug repurposing in Parkinson's disease

Parkinson's disease (PD) is a predominantly idiopathic pathological condition characterized by protein aggregation phenomena, whose main component is alpha-synuclein. Although the main risk factor is ageing, numerous evidence points to the role of type 2 diabetes mellitus (T2DM) as an etiological factor. Systemic alterations classically associated with T2DM like insulin resistance and hyperglycemia modify biological processes such as autophagy and mitochondrial homeostasis. High glucose levels also compromise protein stability through the formation of advanced glycation end products, promoting protein aggregation processes. The ability of antidiabetic drugs to act on pathways impaired in both T2DM and PD suggests that they may represent a useful tool to counteract the neurodegeneration process. Several clinical studies now in advanced stages are looking for confirmation in this regard.