The potential shared role of inflammation in insulin resistance and schizophrenia: A bidirectional two-sample mendelian randomization study

Genetic predisposition and antipsychotic treatment effect on metabolic syndrome in schizophrenia: a ten-year follow-up study using the Estonian Biobank

Background

Schizophrenia (SCZ) patients exhibit 30% higher prevalence of metabolic syndrome (MetS) compared to the general population with its suboptimal management contributing to increased mortality. Large-scale studies providing real-world evidence of the underlying causes remain limited.

Methods

To address this gap, we used real-world health data from the Estonian Biobank, spanning a median follow-up of ten years, to investigate the impact of genetic predisposition and antipsychotic treatment on the development of MetS in SCZ patients. Specifically, we set out to characterize antipsychotic treatment patterns, genetic predisposition of MetS traits, MetS prognosis, and body mass index (BMI) trajectories, comparing SCZ cases (n = 677) to age- and sex-matched controls (n = 2708).

Findings

SCZ cases exhibited higher genetic predisposition to SCZ (OR = 1.75, 95% CI 1.58-1.94), but lower polygenic burden for increased BMI (OR = 0.88, 95% CI 0.88-0.96) and C-reactive protein (OR = 0.88, 95% CI 0.81-0.97) compared to controls. While SCZ cases showed worse prognosis of MetS (HR 1.95, 95% CI 1.54-2.46), higher antipsychotic adherence within the first treatment year was associated with reduced long-term MetS incidence. Linear mixed modelling, incorporating multiple BMI timepoints, underscored the significant contribution of both, antipsychotic medication, and genetic predisposition to higher BMI, driving the substantially upward trajectory of BMI in SCZ cases.

Interpretation

These findings contribute to refining clinical risk prediction and prevention strategies for MetS among SCZ patients and emphasize the significance of incorporating genetic information, long-term patient tracking, and employing diverse perspectives when analyzing real-world health data.

Funding

EU Horizon 2020, Swedish Research Council, Estonian Research Council, Estonian Ministry of Education and Research, University of Tartu.

Anhedonia as a potential transdiagnostic phenotype with immune-related changes in recent onset mental health disorders

BACKGROUND

Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes - reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in those with enduring illness, with few exploring inflammatory changes. We sought to identify an inflammatory signal and associated brain function underlying anhedonia among young people with recent onset psychosis (ROP) and recent onset depression (ROD).

METHOD

Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from N=108 (M age=26.2[SD 6.2]years; Female =50) participants with ROP (n=53) and ROD (n=55) from the EU-FP7-funded PRONIA study. Time-series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and functional connectivity model were developed to classify an anhedonic group, compared to a normal hedonic group.

RESULTS

A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic ROP/ROD groups with a balanced accuracy (BAC) of 63.9%, and an area under the curve (AUC) of 0.61. The functional connectivity model produced a BAC of 55.2% and an AUC of 0.57. Anhedonic group assignment was driven by higher levels of Interleukin-6, S100B, and Interleukin-1 receptor antagonist, and lower levels of Interferon gamma, in addition to connectivity within the precuneus and posterior cingulate.

CONCLUSION

We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Unraveling the genetic basis of the causal association between inflammatory cytokines and osteonecrosis

Background

Previous studies have reported that the occurrence and development of osteonecrosis is closely associated with immune-inflammatory responses. Mendelian randomization was performed to further assess the causal correlation between 41 inflammatory cytokines and osteonecrosis.

Methods

Two-sample Mendelian randomization utilized genetic variants for osteonecrosis from a large genome-wide association study (GWAS) with 606 cases and 209,575 controls of European ancestry. Another analysis included drug-induced osteonecrosis with 101 cases and 218,691 controls of European ancestry. Inflammatory cytokines were sourced from a GWAS abstract involving 8,293 healthy participants. The causal relationship between exposure and outcome was primarily explored using an inverse variance weighting approach. Multiple sensitivity analyses, including MR-Egger, weighted median, simple model, weighted model, and MR-PRESSO, were concurrently applied to bolster the final results.

Results

The results showed that bFGF, IL-2 and IL2-RA were clinically causally associated with the risk of osteonecrosis (OR=1.942, 95% CI=1.13-3.35, p=0.017; OR=0.688, 95% CI=0.50-0.94, p=0.021; OR=1.386, 95% CI=1.04-1.85, p = 0.026). there was a causal relationship between SCF and drug-related osteonecrosis (OR=3.356, 95% CI=1.09-10.30, p=0.034).

Conclusion

This pioneering Mendelian randomization study is the first to explore the causal link between osteonecrosis and 41 inflammatory cytokines. It conclusively establishes a causal association between osteonecrosis and bFGF, IL-2, and IL-2RA. These findings offer valuable insights into osteonecrosis pathogenesis, paving the way for effective clinical management. The study suggests bFGF, IL-2, and IL-2RA as potential therapeutic targets for osteonecrosis treatment.

Exploring the roles and potential therapeutic strategies of inflammation and metabolism in the pathogenesis of vitiligo: a mendelian randomization and bioinformatics-based investigation

Introduction

Vitiligo, a common autoimmune acquired pigmentary skin disorder, poses challenges due to its unclear pathogenesis. Evidence suggests inflammation and metabolism's pivotal roles in its onset and progression. This study aims to elucidate the causal relationships between vitiligo and inflammatory proteins, immune cells, and metabolites, exploring bidirectional associations and potential drug targets.

Methods

Mendelian Randomization (MR) analysis encompassed 4,907 plasma proteins, 91 inflammatory proteins, 731 immune cell features, and 1400 metabolites. Bioinformatics analysis included Protein-Protein Interaction (PPI) network construction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subnetwork discovery and hub protein identification utilized the Molecular Complex Detection (MCODE) plugin. Colocalization analysis and drug target exploration, including molecular docking validation, were performed.

Results

MR analysis identified 49 proteins, 39 immune cell features, and 59 metabolites causally related to vitiligo. Bioinformatics analysis revealed significant involvement in PPI, GO enrichment, and KEGG pathways. Subnetwork analysis identified six central proteins, with Interferon Regulatory Factor 3 (IRF3) exhibiting strong colocalization evidence. Molecular docking validated Piceatannol's binding to IRF3, indicating a stable interaction.

Conclusion

This study comprehensively elucidates inflammation, immune response, and metabolism's intricate involvement in vitiligo pathogenesis. Identified proteins and pathways offer potential therapeutic targets, with IRF3 emerging as a promising candidate. These findings deepen our understanding of vitiligo's etiology, informing future research and drug development endeavors.

A network of transcriptomic signatures identifies novel comorbidity mechanisms between schizophrenia and somatic disorders

The clinical burden of mental illness, in particular schizophrenia and bipolar disorder, are driven by frequent chronic courses and increased mortality, as well as the risk for comorbid conditions such as cardiovascular disease and type 2 diabetes. Evidence suggests an overlap of molecular pathways between psychotic disorders and somatic comorbidities. In this study, we developed a computational framework to perform comorbidity modeling via an improved integrative unsupervised machine learning approach based on multi-rank non-negative matrix factorization (mrNMF). Using this procedure, we extracted molecular signatures potentially explaining shared comorbidity mechanisms. For this, 27 case-control microarray transcriptomic datasets across multiple tissues were collected, covering three main categories of conditions including psychotic disorders, cardiovascular diseases and type II diabetes. We addressed the limitation of normal NMF for parameter selection by introducing multi-rank ensembled NMF to identify signatures under various hierarchical levels simultaneously. Analysis of comorbidity signature pairs was performed to identify several potential mechanisms involving activation of inflammatory response auxiliarily interconnecting angiogenesis, oxidative response and GABAergic neuro-action. Overall, we proposed a general cross-cohorts computing workflow for investigating the comorbid pattern across multiple symptoms, applied it to the real-data comorbidity study on schizophrenia, and further discussed the potential for future application of the approach.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Causal link between gut microbiome and schizophrenia: a Mendelian randomization study

OBJECTIVE

Some observational studies have shown that gut microbiome is significantly changed in patients with schizophrenia. We aim to identify the genetic causal link between gut microbiome and schizophrenia.

METHODS

A two-sample Mendelian randomization (MR) study was used to evaluate the causal link between gut microbiome and schizophrenia with 28 gut microbiome-associated genetic instrumental variants chosen from recent MR reports and the largest schizophrenia genome-wide association studies (8-Apr-22 release).

RESULTS

Inverse variance weighted method showed that genetically increased Bacteroidales_S24-7 (per SD) resulted in increased risk of schizophrenia (OR = 1.110, 95% CI: [1.012-1.217], P  = 0.027). Similarly, genetically increased Prevotellaceae promoted schizophrenia risk (OR = 1.124, 95% CI: [1.030-1.228], P  = 0.009). However, genetically increased Lachnospiraceae reduced schizophrenia risk (OR = 0.878, 95% CI: [0.785-0.983], P  = 0.023). In addition, schizophrenia risk was also suppressed by genetically increased Lactobacillaceae (OR = 0.878, 95% CI: [0.776-0.994], P  = 0.040) and Verrucomicrobiaceae (OR = 0.860, 95% CI: [0.749-0.987], P  = 0.032). Finally, we did not find any significant results in the causal association of other 23 gut microbiome with schizophrenia.

CONCLUSION

Our analysis suggests that genetically increased Bacteroidales_S24-7 and Prevotellaceae promotes schizophrenia risk, whereas genetically increased Lachnospiraceae, Lactobacillaceae, and Verrucomicrobiaceae reduces schizophrenia risk. Thus, regulation of the disturbed intestinal microbiota may represent a new therapeutic strategy for patients with schizophrenia.

Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio predict the prognosis in patients with type B aortic dissection receiving thoracic endovascular aortic repair

Background

The triglyceride-glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio are both reliable surrogate indicator of insulin resistance and have been shown to be valuable in predicting various cardiovascular diseases. However, few studies have explored its association with the prognosis of type B aortic dissection (TBAD) patients receiving thoracic endovascular aortic repair (TEVAR).

Methods

A total of 1,425 consecutive patients who underwent TEVAR were included. Data from 935 patients were analyzed in the study. The endpoint was defined as 30-day and 1-year aortic-related adverse events (ARAEs), all-cause mortality, and major adverse cardiovascular and cerebrovascular events (MACCEs).

Results

There were 935 patients included during a mean follow-up time of 2.8 years. After adjusting for multiple confounding factors, continuous TG/HDL-c [hazard ratio (HR) =1.07; 95% confidence interval (CI): 1.00-1.15; P=0.041] was independently associated with 1-year all-cause mortality. Both a high (Quintile 5: TG/HDL-c ratio ≥4.11) (HR =4.84; 95% CI: 1.55-15.13; P=0.007) and low TG/HDL-c ratio (Quintile 1: TG/HDL-c ratio <1.44) (HR =4.67; 95% CI: 1.46-14.94; P=0.001) were still independent risk factors for 1-year all-cause mortality.

Conclusions

Elevated baseline TG/HDL-c ratio and TG/HDL-c ≥4.11 were significantly related to a higher risk of 1-year all-cause mortality among TBAD patients undergoing TEVAR. At the same time, the low TG/HDL-c ratio was also independently associated with 1-year all-cause mortality. Special attention should be paid to TBAD patients with a higher or an overly low TG/HDL-c ratio.

Two-sample Mendelian randomization analysis of 91 circulating inflammatory protein levels and amyotrophic lateral sclerosis

Introduction

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with poorly understood pathophysiology. Recent studies have highlighted systemic inflammation, especially the role of circulating inflammatory proteins, in ALS.

Methods

This study investigates the potential causal link between these proteins and ALS. We employed a two-sample Mendelian Randomization(MR) approach, analyzing data from large-scale genome-wide association studies to explore the relationship between 91 circulating inflammatory proteins and ALS. This included various MR methods like MR Egger, weighted median, and inverse-variance weighted, complemented by sensitivity analyses for robust results.

Results

Significant associations were observed between levels of inflammatory proteins, including Adenosine Deaminase, Interleukin-17C, Oncostatin-M, Leukemia Inhibitory Factor Receptor, and Osteoprotegerin, and ALS risk. Consistencies were noted across different P-value thresholds. Bidirectional MR suggested that ALS risk might influence levels of certain inflammatory proteins.

Discussion

Our findings, via MR analysis, indicate a potential causal relationship between circulating inflammatory proteins and ALS. This sheds new light on ALS pathophysiology and suggests possible therapeutic targets. Further research is required to confirm these results and understand the specific roles of these proteins in ALS.

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

Genomic insights into the comorbidity between type 2 diabetes and schizophrenia

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa. Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify putative effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

The causal relationship between 25-hydroxyvitamin D and serum lipids levels: A bidirectional two-sample mendelian randomization study

Serum vitamin D levels were linked to lipid metabolism in observational studies, but the exact mechanism was unclear. Several studies have attempted to decipher the relationship between 25(OH)D and lipid levels. Conventional observational studies are vulnerable to confounding. Mendelian randomization (MR) analysis can better control for confounding factors and reverse causality, allowing for the inference of causal association. We, therefore, sought to use MR to investigate the possible causal relationship between 25(OH)D and blood lipid levels (HDL cholesterol, LDL cholesterol, triglycerides, and total cholesterol). A bidirectional two-sample Mendelian randomization (MR) was performed on data primarily from European ancestors. In addition, the potential causal effect of lipids on 25(OH)D was assessed by regressor-based multivariate magnetic resonance (MVMR). The single-nucleotide polymorphisms (SNPs) related to 25(OH)D were selected from a large-scale genome-wide association study (GWAS) database named IEU GWAS, and the SNPs associated with the four blood lipids were chosen from UK Biobank (UKB) lipid GWAS. When blood lipids were the outcome, the results of bidirectional two-sample MR demonstrated that 25(OH)D exhibited a negative causal association with TG, TC, and LDL-C: β = - 0.23, 95% CI = -0.28 to -0.19, P<0.001; β = - 0.16, 95% CI: - 0.30 to-0.03, P < 0.05; β = - 0.11, 95% CI: - 0.23 to 0, P < 0.05. There was no causal relationship between 25(OH)D and HDL-C (β = 0.05, 95% CI: - 0.11 to 0.20, P = 0.56). When setting blood lipids as exposure, TG and 25(OH)D, β = -0.13, 95% CI: - 0.15 to -0.10, P < 0.05; TC and 25(OH)D, β = -0.11, 95% CI: - 0.15 to -0.07, P < 0.05; HDL-C and 25(OH)D, β = 0.02, 95% CI: 0 to 0.03, P = 0.07; LDL-C and 25(OH)D, β = -0.08, 95% CI: - 0.11 to -0.05, P < 0.05). Our MVMR study also showed a significant relationship between genetically determined lipid traits and 25(OH)D levels (TG and 25(OH)D, P < 0.05; TC and 25(OH)D, P < 0.05). In all MR analyses, there was no horizontal pleiotropy (all P > 0.05), or statistical heterogeneity. The "Leave-one-out" sensitivity analysis confirmed the stability of our results. MR Studies have shown a bidirectional causal relationship between genetically-determined 25(OH)D levels and serum TG and TC levels. The findings have potential implications for etiological understanding and disease prevention.

Genetic proxies for antihypertensive drugs and mental disorders: Mendelian randomization study in European and East Asian populations

BACKGROUND

Mental disorders are among the top causes of disease burden worldwide. Existing evidence regarding the repurposing of antihypertensives for mental disorders treatment is conflicting and cannot establish causation.

METHODS

We used Mendelian randomization to assess the effects of angiotensin-converting-enzyme inhibitors (ACEIs), beta blockers (BBs), and calcium channel blockers (CCBs) on risk of bipolar disorder (BD), major depression disorder (MDD), and schizophrenia (SCZ). We used published genetic variants which are in antihypertensive drugs target genes and correspond to systolic blood pressure (SBP) in Europeans and East Asians, and applied them to summary statistics of BD (cases = 41,917; controls = 371,549 in Europeans), MDD (cases = 170,756; controls = 329,443 in Europeans and cases = 15,771; controls = 178,777 in East Asians), and SCZ (cases = 53,386; controls = 77,258 in Europeans and cases = 22,778; controls = 35,362 in East Asians) from the Psychiatric Genomics Consortium. We used inverse variance weighting with MR-Egger, weighted median, weighted mode, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier. We performed gene-specific analysis and utilized various methods to address potential pleiotropy.

RESULTS

After multiple testing correction, genetically proxied ACEIs were associated with an increased risk of SCZ in Europeans (odds ratio (OR) per 5 mmHg lower in SBP 2.10, 95% CI 1.54 to 2.87) and East Asians (OR per 5 mmHg lower in SBP 2.51, 95% CI 1.38 to 4.58). Genetically proxied BBs were not associated with any mental disorders in both populations. Genetically proxied CCBs showed no benefits on mental disorders.

CONCLUSIONS

Antihypertensive drugs have no protection for mental disorders but potential harm. Their long-term use among hypertensive patients with, or with high susceptibility to, psychiatric illness needs careful evaluation.

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.

Genomic insights into the comorbidity between type 2 diabetes and schizophrenia

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa. Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify high-confidence effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

Association of Single Nucleotide Polymorphisms of Cytokine Genes with Depression, Schizophrenia and Bipolar Disorder

Immune gene variants are known to be associated with the risk of psychiatric disorders, their clinical manifestations, and their response to therapy. This narrative review summarizes the current literature over the past decade on the association of polymorphic variants of cytokine genes with risk, severity, and response to treatment for severe mental disorders such as bipolar disorder, depression, and schizophrenia. A search of literature in databases was carried out using keywords related to depressive disorder, bipolar disorder, schizophrenia, inflammation, and cytokines. Gene lists were extracted from publications to identify common genes and pathways for these mental disorders. Associations between polymorphic variants of the IL1B, IL6, and TNFA genes were the most replicated and relevant in depression. Polymorphic variants of the IL1B, IL6, IL6R, IL10, IL17A, and TNFA genes have been associated with schizophrenia. Bipolar disorder has mainly been associated with polymorphic variants of the IL1B gene. Interestingly, the IL6R gene polymorphism (rs2228145) was associated with all three diseases. Some cytokine genes have also been associated with clinical presentation and response to pharmacotherapy. There is also evidence that some specific polymorphic variants may affect the expression of cytokine genes. Thus, the data from this review indicate a link between neuroinflammation and severe mental disorders.

Associations of Insomnia With Insulin Resistance Traits: A Cross-sectional and Mendelian Randomization Study

CONTEXT

Insomnia is associated with insulin resistance (IR) in observational studies; however, whether insomnia is causally associated with IR remains unestablished.

OBJECTIVE

This study aims to estimate the causal associations of insomnia with IR and its related traits.

METHODS

In primary analyses, multivariable regression (MVR) and 1-sample Mendelian randomization (1SMR) analyses were performed to estimate the associations of insomnia with IR (triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol [TG/HDL-C] ratio) and its related traits (glucose level, TG, and HDL-C) in the UK Biobank. Thereafter, 2-sample MR (2SMR) analyses were used to validate the findings from primary analyses. Finally, the potential mediating effects of IR on the pathway of insomnia giving rise to type 2 diabetes (T2D) were examined using a 2-step MR design.

RESULTS

Across the MVR, 1SMR, and their sensitivity analyses, we found consistent evidence suggesting that more frequent insomnia symptoms were significantly associated with higher values of triglyceride-glucose index (MVR, β = 0.024, P < 2.00E-16; 1SMR, β = 0.343, P < 2.00E-16), TG/HDL-C ratio (MVR, β = 0.016, P = 1.75E-13; 1SMR, β = 0.445, P < 2.00E-16), and TG level (MVR, β = 0.019 log mg/dL, P < 2.00E-16, 1SMR: β = 0.289 log mg/dL, P < 2.00E-16) after Bonferroni adjustment. Similar evidence was obtained by using 2SMR, and mediation analysis suggested that about one-quarter (25.21%) of the association between insomnia symptoms and T2D was mediated by IR.

CONCLUSIONS

This study provides robust evidence supporting that more frequent insomnia symptoms are associated with IR and its related traits across different angles. These findings indicate that insomnia symptoms can be served as a promising target to improve IR and prevent subsequent T2D.

Socioenvironmental Adversity and Adolescent Psychotic Experiences: Exploring Potential Mechanisms in a UK Longitudinal Cohort

BACKGROUND AND HYPOTHESIS

Children exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association.

STUDY DESIGN

Data were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences.

STUDY RESULTS

Higher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses.

CONCLUSIONS

Cognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Variability of glucose, insulin, and lipid disturbances in first-episode psychosis: a meta-analysis

BACKGROUND

First-episode psychosis (FEP) is associated with metabolic alterations. However, it is not known if there is heterogeneity in these alterations beyond what might be expected due to normal individual differences, indicative of subgroups of patients at greater vulnerability to metabolic dysregulation.

METHODS

We employed meta-analysis of variance, indexed using the coefficient of variation ratio (CVR), to compare variability of the following metabolic parameters in antipsychotic naïve FEP and controls: fasting glucose, glucose post-oral glucose tolerance test (OGTT), fasting insulin, insulin resistance, haemoglobin A1c (HbA1c), total-cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol, and triglycerides. Standardised mean difference in metabolic parameters between groups was also calculated; meta-regression analyses examined physiological/demographic/psychopathological moderators of metabolic change.

RESULTS

Twenty-eight studies were analysed (1716 patients, 1893 controls). Variability of fasting glucose [CVR = 1.32; 95% confidence interval (CI) 1.12-1.55; p = 0.001], glucose post-OGTT (CVR = 1.43; 95% CI 1.10-1.87; p = 0.008), fasting insulin (CVR = 1.31; 95% CI 1.09-1.58; p = 0.01), insulin resistance (CVR = 1.34; 95% CI 1.12-1.60; p = 0.001), HbA1c (CVR = 1.18; 95% CI 1.06-1.27; p < 0.0001), total-cholesterol (CVR = 1.15; 95% CI 1.01-1.31; p = 0.03), LDL-cholesterol (CVR = 1.28; 95% CI 1.09-1.50; p = 0.002), and HDL-cholesterol (CVR = 1.15; 95% CI 1.00-1.31; p < 0.05), but not triglycerides, was greater in patients than controls. Mean glucose, glucose post-OGTT, fasting insulin, insulin resistance, and triglycerides were greater in patients; mean total-cholesterol and HDL-cholesterol were reduced in patients. Increased symptom severity and female sex were associated with worse metabolic outcomes.

CONCLUSIONS

Patients with FEP present with greater variability in metabolic parameters relative to controls, consistent with a subgroup of patients with more severe metabolic changes compared to others. Understanding determinants of metabolic variability could help identify patients at-risk of developing metabolic syndrome. Female sex and severe psychopathology are associated with poorer metabolic outcomes, with implications for metabolic monitoring in clinical practice.

The association between schizophrenia and white blood cells count: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Positive associations between the risk of schizophrenia and the level of white blood cells (WBC) count have been suggested by observational studies. However, the causality of this association is still unclear.

METHODS

We used a group of bidirectional two-sample Mendelian randomization (MR) analyses to estimate the causal relationship between schizophrenia and WBC count traits (i.e., WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count). The threshold of FDR-adjusted P < 0.05 was considered as showing potential evidence of a causal effect. Instrument variables were included based on the genome-wide significance threshold (P < 5 × 10^- 8) and linkage disequilibrium (LD) clumping (r² < 0.01). In total, 81, 95, 85, 87, 76, and 83 schizophrenia-related single nucleotide polymorphisms (SNPs) were used as genetic instruments from Psychiatric Genomics Consortium for six WBC count traits, respectively. And in reverse MR analysis, 458, 206, 408, 468, 473, and 390 variants extracted from six WBC count traits were utilized as genetic instruments, which were obtained from a recent large-scale Genome-Wide Association Study (GWAS).

RESULTS

Genetically predicted schizophrenia was positively associated with the level of WBC count [odds ratio (OR) 1.017, 95% confidence interval (CI) 1.008-1.026; P = 7.53 × 10^- 4], basophil count (OR 1.014, 95%CI 1.005-1.022; P = 0.002), eosinophil count (OR 1.021, 95%CI 1.011-1.031; P = 2.77 × 10^- 4), monocyte count (OR 1.018, 95%CI 1.009-1.027; P = 4.60 × 10^- 4), lymphocyte count (OR 1.021, 95%CI 1.012-1.030; P = 4.51 × 10^- 5), and neutrophil count (OR 1.013, 95%CI 1.005-1.022; P = 0.004). WBC count traits are not associated with the risk of schizophrenia in our reverse MR results.

CONCLUSION

Schizophrenia is associated with elevated levels of WBC count (i.e., higher WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count).

Genetically predicted circulating levels of cytokines and the risk of osteoarthritis: A mendelian randomization study

Background: The association between inflammatory cytokines and osteoarthritis (OA) has been reported in several observational studies, but the causal relationship between these two remains unknown. Hence, we performed this two-sample Mendelian randomization (MR) to confirm the causal relationship between circulating levels of inflammatory factors and osteoarthritis risk.

Method: We used genetic variants associated with cytokine circulation levels from a meta-analysis of genome-wide association studies (GWASs) in 8,293 Finns as instrumental variables and obtained OA data from the United Kingdom Biobank, including a total of 345,169 subjects of European ancestry (66,031 diagnosed OA cases and 279,138 controls). Inverse variance weighting (IVW), MR-Egger, Wald Ratio, weighted median, and MR multiplicity residual sums with outliers (MR-PRESSO) were used.

Result: We found a causal relationship between circulating levels of macrophage inflammatory protein-1beta (MIP-1β) and risk of OA (OR = 0.998, 95% CI = 0.996–0.999p = 9.61 × 10−5); tumour necrosis factor beta (TNF-β) was also causally associated with risk of OA (OR = 0.996,95%CI = 0.994–0.999, p = 0.002); finally we found a suggestive association between C-C motif chemokine ligand 5(CCL5, also called Rantes) and OA risk (OR = 1.013, 95%CI = 1.002–1.024,p = 0.016).

Conclusion: Our findings offer promising leads for the development of new therapeutic targets in the treatment of osteoarthritis. By identifying the role of inflammatory cytokines in this debilitating condition through a genetic epidemiological approach, our study contributes to a better understanding of the underlying disease mechanisms. These insights may ultimately pave the way for more effective treatments that improve patient outcomes.

Psychiatric disorders and Type 2 diabetes mellitus: A bidirectional Mendelian randomization

BACKGROUND

Extensive observational evidence put forward the association between psychiatric disorders and type 2 diabetes mellitus (T2DM). However, causal relationships between these two diseases required further research. Thus, we evaluated the bidirection casual effect between five psychiatric disorders and T2DM using two-sample mendelian randomization (MR).

METHODS

By selecting single nucleotide polymorphisms associated with T2DM and five psychiatric disorders (attention-deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), schizophrenia, anxiety disorder and panic disorder), a bidirectional two-sample MR was applied to evaluate causality between these diseases. The inverse-variance weighted (IVW) method was used as the primary analysing approach for estimating possible causal effects. MR-Egger and weighted median were also conducted to verify the results. The funnel plot, Cochran's Q test and MR-Egger intercept test were used for sensitivity analyses. In addition, potential mediators were investigated by risk factor analyses.

RESULTS

Genetic susceptibilities of ADHD and MDD would increase the risk of T2DM (ADHD: OR = 1.14, 95%CI 1.08-1.20; p = 5.7 × 10 - 6 ; MDD: OR = 1.22, 95%CI 1.09-1.36; p = 0.0004 ). In addition, genetic predisposition to T2DM was also associated with ADHD (OR = 1.09, 95%CI 1.04-1.14; p = 0.0004). Several risk factors of T2DM were implicated in the above causal associations, including smoking, high body mass index, waist-to-hip ratio and elevated serum triglycerides.

CONCLUSION

Our studies indicated a causal effect of ADHD and MDD on increasing the risk of T2DM, which was potentially mediated by smoking and obesity-related phenotypes. Meanwhile, we found a causal effect of T2DM on ADHD. Thus, prevention strategies for T2DM should also include mental health and vice versa.

MicroRNA schizophrenia: Etiology, biomarkers and therapeutic targets

The three sets of symptoms associated with schizophrenia-positive, negative, and cognitive-are burdensome and have serious effects on public health, which affects up to 1% of the population. It is now commonly believed that in addition to the traditional dopaminergic mesolimbic pathway, the etiology of schizophrenia also includes neuronal networks, such as glutamate, GABA, serotonin, BDNF, oxidative stress, inflammation and the immune system. Small noncoding RNA molecules called microRNAs (miRNAs) have come to light as possible participants in the pathophysiology of schizophrenia in recent years by having an impact on these systems. These small RNAs regulate the stability and translation of hundreds of target transcripts, which has an impact on the entire gene network. There may be improved approaches to treat and diagnose schizophrenia if it is understood how these changes in miRNAs alter the critical related signaling pathways that drive the development and progression of the illness.

Genetically predicted blood pressure, antihypertensive drugs and risk of heart failure: a Mendelian randomization study

BACKGROUND

Elevated blood pressure (BP) was associated with higher risk of heart failure, but the relationship between BP-lowering via antihypertensive drugs and diminution of heart failure was inconclusive. This study aimed to estimate the causal association of BP with heart failure, and explore the effects of BP-lowering through different antihypertensive drug classes on heart failure risk using Mendelian randomization analysis with genetic variants as instrument variables.

METHODS

Genetic variants associated with BP were derived from UK Biobank ( n  = 317 754) and the genome-wide association study (GWAS) meta-analysis of UK Biobank and International Consortium of Blood Pressure ( n  = 757 601). Heart failure summary association data were contributed by HERMES Consortium (47 309 heart failure cases and 930 014 controls). Inverse variance weighted (IVW) was performed to estimate causality between exposure and outcome, and weighted median was utilized as sensitivity analysis, and Mendelian randomization-Egger regression was used to identify pleiotropy of instrument variables. Multivariable Mendelian randomization (MVMR) was applied to control for the confounders.

RESULTS

Genetically predicted SBP and DBP were associated with heart failure [SBP: odds ratio (OR) = 1.355, 95% confidence interval (CI) 1.201-1.529; DBP: OR = 1.348, 95% CI 1.213-1.498] in UK Biobank. Likewise, in the GWAS meta-analysis of UK Biobank and International Consortium of Blood Pressure, the causal associations were observed between SBP, DBP and heart failure (SBP: OR = 1.237, 95% CI 1.188-1.289; DBP: OR = 1.337, 95% CI 1.245-1.437). Genetically determined β-blockers and calcium channel blockers (CCBs) were associated with lower risk of heart failure (β-blockers: OR = 0.617, 95% CI 0.453-0.839; CCBs: OR = 0.730, 95% CI 0.625-0.851). No association was found between angiotensin receptor blockers (ARBs) and heart failure (OR = 1.593, 95% CI 0.647-3.924). When adjusted for smoking, alcohol, physical activity, fruit and vegetable intake, the results were stable.

CONCLUSION

Our study indicates causal associations between SBP, DBP, and heart failure, and suggests the preventive effects of heart failure by BP-lowering using β-blockers and CCBs.

Applications of Mendelian randomization in psychiatry: a comprehensive systematic review

Psychiatric diseases exact a heavy socioeconomic toll, and it is particularly difficult to identify their risk factors and causative mechanisms due to their multifactorial nature, the limited physiopathological insight, the many confounding factors, and the potential reverse causality between the risk factors and psychiatric diseases. These characteristics make Mendelian randomization (MR) a precious tool for studying these disorders. MR is an analytical method that employs genetic variants linked to a certain risk factor, to assess if an observational association between that risk factor and a health outcome is compatible with a causal relationship. We report the first systematic review of all existing applications and findings of MR in psychiatric disorders, aiming at facilitating the identification of risk factors that may be common to different psychiatric diseases, and paving the way to transdiagnostic MR studies in psychiatry, which are currently lacking. We searched Web of Knowledge, Scopus, and Pubmed databases (until 3 May 2022) for articles on MR in psychiatry. The protocol was preregistered in PROSPERO (CRD42021285647). We included methodological details and results from 50 articles, mainly on schizophrenia, major depression, autism spectrum disorders, and bipolar disorder. While this review shows how MR can offer unique opportunities for unraveling causal links in risk factors and etiological elements of specific psychiatric diseases and transdiagnostically, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

The triglycerides-glucose index and the triglycerides to high-density lipoprotein cholesterol ratio are both effective predictors of in-hospital death in non-diabetic patients with AMI

Background

The triglycerides-glucose index (TyG) and the triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) are simple indicators for assessing insulin resistance in epidemiological studies. We aimed to clarify the relationship between indicators of insulin resistance and prognosis in non-diabetic acute myocardial infarction (AMI) patients.

Methods

A total of 1,648 AMI patients without diabetes were enrolled from the Department of Cardiology, Zhongda Hospital, between 2012.03 and 2018.12. The medical history, laboratory and imaging data of patients were collected through the medical record system, and all-cause death events were recorded. Pearson analysis was used to study the correlation among different variables. Logistic regression analysis was used to analyze the predictive effect of TyG and TG/HDL-C in in-hospital death of AMI patients.

Results

1. In AMI group, the TyG index was significantly increased in death groups compared to no-death groups (P = 0.025). TG/HDL-C was not significantly increased in the death group of AMI patients (P = 0.588). The patients were respectively divided into Q1-Q4 groups and T1-T4 groups according to the quartiles of TyG and TG/HDL-C. The trends of in-hospital mortality in the Q4 group of TyG and T4 group of TG/HDL-C were higher than in other groups, although these differences were not significant. 2. Pearson correlation analysis showed that TyG was positively correlated with lipid-related markers, including ApoB (r = 0.248, P < 0.001), total cholesterol (TC) (r = 0.270, P < 0.001), low-density lipoprotein cholesterol (LDL-C) (r = 0.238, P < 0.001). Spearman analysis showed that TG/HDL-C was also positively associated with TC (r = 0.107, P < 0.001), ApoB (r = 0.180, P < 0.001) and LDL-C (r = 0.164, P < 0.001). 3. Logistic regression analysis showed that TyG (OR = 3.106, 95% CI [2.122-4.547], P < 0.001) and TG/HDL-C (OR = 1.167, 95% CI [1.062-1.282], P = 0.001) were both important factors to predict the in-hospital death of AMI patients without diabetes.

Conclusions

TyG index and TG/HDL-C, as emerged simple markers of insulin resistance, were both important predictors of in-hospital death in AMI patients without diabetes.

Precision-medicine findings from the FACE-SZ cohort to develop motivation-enhancing programs in real-world schizophrenia

BACKGROUND

In people with schizophrenia, major areas of everyday life are impaired, including independent living, productive activities, social relationships and overall quality of life. Enhanced understanding of factors that hinder real-life functioning is vital for treatments to translate into more positive outcomes.

AIM

The goal of the present study was to identify factors associated with motivation deficits in real-life schizophrenia, and to assess its contribution to impaired functioning and quality of life.

METHODS

Based on previous literature and clinical experience, several factors were selected and grouped into factors potentially explaining motivation deficits. Some of these variables were never investigated before in relationship with motivation deficits.

RESULTS

In 561 patients with schizophrenia of the national FACE-SZ cohort living in the community, 235 (41.9%) reported severe motivation deficits. These deficits were found to be significantly associated with impaired socially useful activities, psychological and physical quality of life (in almost all domains), alcohol use disorder (aOR = 2.141, p = 0.021), severe nicotine dependence (aOR = 2.906, p < 0.001) independently of age and sex. No significant association was found for body mass index, metabolic syndrome or physical activity level. In the second model, we identified the following modifiable factors associated with motivation deficits: history of suicide attempt (aOR = 2.297, p = 0.001), positive symptoms (aOR = 1.052, p = 0.006), current major depressive episode (aOR = 2.627, p < 0.001), sleep disorders (aOR = 1.474, p = 0.024) and lower medication adherence (aOR = 0.836, p = 0.001) independently of gender, current alcohol use disorder, second-generation antipsychotics and akathisia. No significant association was found for negative symptoms, childhood trauma and inflammation. These results were maintained after removing patients with schizoaffective disorders or those with major depressive disorder.

INTERPRETATION

Motivation deficits are frequent and remain persistent unmet need in real-world schizophrenia that should be addressed in future guidelines. Based on our results, literature and clinical experience, we recommend to address in priority major depression, sleep, suicide, positive symptoms (when present and as early as possible) and medication adherence to improve motivation deficits of schizophrenia.

Exploring Lead loci shared between schizophrenia and Cardiometabolic traits

Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

Influencing factors of obesity in community patients with deficit schizophrenia: a cross-sectional study

Background

Obesity is very common in patients with schizophrenia. We aimed to evaluate the influencing factors of obesity in community patients with deficit schizophrenia, to provide implication for schizophrenia management in community.

Methods

We selected patients with deficit schizophrenia who lived in 10 communities in our city from March 1 to June 30, 2021. The characteristics of included schizophrenia patients were evaluated and analyzed. Pearson correlation analysis was conducted to evaluate the obesity and related characteristics. Logistic regression analyses were conducted to assess the risk factors of obesity in patients with schizophrenia.

Results

A total of 284 patients with schizophrenia were included, the incidence of obesity in patients with schizophrenia was 56.70%. gender (r = 0.619), waist circumference (r = 0.644), BMI (r = 0.891), diabetes (r = 0.698), FG (r = 0.582), triglyceride (r = 0.618), HDL-C (r = −0.644), LDL-C (r = 0.583), apolipoprotein B (r = 0.595), and PANSS score (r = 0.813) were all correlated with the obesity in patients with schizophrenia (all p < 0.05). Logistic regression analysis indicated that female (OR 2.129, 95% CI 1.615–3.022), waist circumference ≥ 90 cm (OR 3.814, 95% CI 2.778 ~ 4.312), diabetes (OR 2.856, 95% CI 1.905 ~ 3.448), FG ≥ 88 mg/dL (OR 1.551, 95% CI 1.284 ~ 2.183), triglyceride ≥ 160 mg/dL (OR 1.804, 95% CI 1.236–2.845), HDL-C ≤ 0.8 mmol/L (OR 2.032, 95% CI 1.614–3.079), LDL-C ≥ 2.0 mmol/L (OR 1.926, 95% CI 1.442–2.041) and apolipoprotein B ≥ 0.70 g/L (OR 2.119, 95% CI 1.658–2.873) were the risk factors of obesity in patients with schizophrenia (all p < 0.05).

Conclusions

The obesity rate of patients with deficit schizophrenia in the community is high, and there are many associated risk factors. Early intervention targeted on those risk factors are warranted to reduce the obesity in schizophrenia patients.

Childhood immuno-metabolic markers and risk of depression and psychosis in adulthood: A prospective birth cohort study

BACKGROUND

Metabolic and inflammatory disorders commonly co-occur with depression and psychosis, with emerging evidence implicating immuno-metabolic dysfunction in their aetiology. Previous studies have reported metabolic dysfunction and inflammation in adults with depression and psychosis. However, longitudinal studies testing the direction of association, and the effects of different dimensions of early-life immuno-metabolic dysfunction on adult psychopathology are limited.

METHODS

Using data from 3258 birth cohort participants we examined longitudinal associations of three metabolic hormones (leptin, adiponectin, insulin) at age 9 with risks for depression- and psychosis-spectrum outcomes at age 24. In addition, using nine immuno-metabolic biomarkers (leptin, adiponectin, insulin, interleukin-6, C-Reactive protein, low density lipoprotein, high density lipoprotein, triglycerides, and BMI), we constructed an exploratory bifactor model showing a general immuno-metabolic factor and three specific factors (adiposity, inflammation, and insulin resistance), which were also used as exposures.

RESULTS

Childhood leptin was associated with adult depressive episode (adjusted odds ratio (aOR)= 1.31; 95% CI, 1.02-1.71) and negative symptoms (aOR=1.15; 95% CI, 1.07-1.24), but not positive psychotic symptoms. The general immuno-metabolic factor was associated with atypical depressive symptoms (aOR=1.07; 95% CI, 1.01-1.14) and psychotic experiences (aOR=1.21; 95% CI, 1.02-1.44). The adiposity factor was associated with negative symptoms (aOR=1.07; 95% CI 1.02-1.12). Point estimates tended to be larger in women, though 95% credible intervals overlapped with those for men. In women, the inflammatory factor was associated with depressive episodes (aOR=1.27; 95% CI, 1.03-1.57).

CONCLUSIONS

While general immuno-metabolic dysfunction in childhood may contribute to risks for both psychotic and depressive symptoms in adulthood, childhood adiposity and inflammation appear to be particularly linked to affective (depressive and negative), but not positive psychotic symptoms.

Neuroinflammation in Late-Onset Schizophrenia: Viewing from the Standpoint of the Microglia Hypothesis

Schizophrenia develops mainly in adolescence, but late-onset schizophrenia (LOS) is not uncommon. According to the international consensus, schizophrenia which develops over 40 years old is called LOS and psychosis which develops over 60 years old is called very late-onset schizophrenia-like psychosis (VLOS). Compared to early-onset schizophrenia (EOS) that develops before the age of 40 years, LOS and VLOS are reported to be more common in women, and there are clinically clear differences such as less involvement of genetic factors than EOS. This review outlines the abnormalities of the neuroimmune system in the pathophysiology of LOS, especially focusing on the role of microglia.

Evidence for Shared Genetic Aetiology Between Schizophrenia, Cardiometabolic, and Inflammation-Related Traits: Genetic Correlation and Colocalization Analyses

BACKGROUND

Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology.

METHODS

We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology.

RESULTS

We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (r_g = -0.07; 95% C.I., -0.03,0.12; P = .002) and BMI (r_g = -0.09; 95% C.I., -0.06, -0.12; P = 1.83 × 10^-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways.

CONCLUSIONS

LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.

Association of higher plasma leptin levels with HOMA-IR index, high sensitivity C-reactive protein and glycolipid metabolism in patients with chronic schizophrenia: A multi-center cross-sectional study

BACKGROUND

Previous research has revealed that plasma leptin levels were closely related to glycolipid metabolism in schizophrenic patients. Insulin resistance (IR) and high sensitivity C-reactive protein (hs-CRP) were involved in glucolipid metabolism disorders. This study explored the correlation between plasma higher leptin levels, homeostasis model assessment of insulin resistance (HOMA-IR) index, hs-CRP and glycolipid metabolism in patients with chronic schizophrenia (CS).

METHODS

322 subjects were enrolled, and the psychopathological symptoms of each patient were assessed by a 30-item Positive and Negative Syndrome Scale (PANSS_-30). Patients' plasma leptin levels were measured by enzyme-linked immunosorbent assay (ELISA). Fasting blood glucose (FBG) levels were determined by oxidase method. Insulin levels were tested by electrochemiluminescence, and hs-CRP levels were tested by immunoturbidimetry. IBM SPSS 22.0 was used for data analysis.

RESULTS

Compared to the lower leptin group, patients in the higher leptin group had significantly higher body mass index (BMI), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), insulin, HOMA-IR and hs-CRP levels; and lower negative factor scores, cognitive factor scores, and PANSS total scores (P < 0.05). Plasma leptin levels in CS patients were positively correlated with BMI, TC, TG, LDL-C, insulin, HOMA-IR and hs-CRP levels, and were negatively correlated with gender (male = 1, Female = 2), positive factor scores, negative factor scores, cognitive factor scores and PANSS total scores. Multiple linear regression analysis revealed that gender, BMI, positive factor scores, PANSS total scores, FBG, LDL-C, insulin, HOMA-IR and hs-CRP levels were independent influencing factors of leptin levels in CS patients (P < 0.05).

CONCLUSION

Gender, BMI, positive factor scores, PANSS total scores, FBG, LDL-C, insulin, HOMA-IR and hs-CRP levels were independent influencing factors of plasma leptin levels in CS patients. Plasma leptin, HOMA-IR and hs-CRP levels should be measured regularly in CS patients to prevent or treat the disorders of glucose and lipid metabolism comorbidity with schizophrenia patients in clinical diagnosis and treatment.

Prenatal and Childhood Immuno-Metabolic Risk Factors for Adult Depression and Psychosis

Depression and psychosis have a developmental component to their origin. Epidemiologic evidence, which we synthesize in this nonsystematic review, suggests that early-life infection, inflammation, and metabolic alterations could play a role in the etiology of these psychiatric disorders. The risk of depression and psychosis is associated with prenatal maternal and childhood infections, which could be mediated by impaired neurodevelopment. Evidence suggests linear dose-response associations between elevated concentrations of circulating inflammatory markers in childhood, particularly the inflammatory cytokine interleukin 6, and the risk for depression and psychosis subsequently in early adulthood. Childhood inflammatory markers are also associated with persistence of depressive symptoms subsequently in adolescence and early adulthood. Developmental trajectories reflecting persistently high insulin levels during childhood and adolescence are associated with a higher risk of psychosis in adulthood, whereas increased adiposity during and after puberty is associated with the risk of depression. Together, these findings suggest that higher levels of infection, inflammation, and metabolic alterations commonly seen in people with depression and psychosis could be a cause for, rather than simply a consequence of, these disorders. Therefore, early-life immuno-metabolic alterations, as well as factors influencing these alterations such as adversity or maltreatment, could represent targets for prevention of these psychiatric disorders. Inflammation could also be an important treatment target for depression and psychosis. The field requires further research to examine sensitive periods when exposure to such immuno-metabolic alterations is most harmful. Interventional studies are also needed to test the potential usefulness of targeting early-life immuno-metabolic alterations for preventing adult depression and psychosis.

COVID-19 in People With Schizophrenia: Potential Mechanisms Linking Schizophrenia to Poor Prognosis

As the global burden of mortality from COVID-19 continues to rise, an understanding of who is most at risk of adverse outcomes is of paramount importance. Pre-existing cardiometabolic, renal and respiratory diseases as well as old age are well-established risk factors associated with disease severity and mortality among patients with COVID-19. However, mounting evidence also indicates an increased susceptibility to, and risk of adverse outcomes from COVID-19 in people with schizophrenia, independent of age and comorbidity. Therefore, elucidating the underlying pathophysiological mechanisms which may increase the risk of poor outcomes in people with schizophrenia is of crucial importance. Here, we provide a narrative on the current understanding of COVID-19 in patients with schizophrenia and propose potential mechanisms which may link schizophrenia with an increased susceptibility to, and greater risk of adverse outcomes from COVID-19. Given the existing knowledge gaps, robust clinical and biological studies are required to further our understanding of some of these underlying mechanisms, so that effective prevention and treatment strategies for COVID-19 in patients with schizophrenia can be developed.