The Role of Adiponectin in the Pathogenesis of Metabolic Disturbances in Patients With Schizophrenia

Effects of atypical antipsychotics on serum asprosin level and other metabolic parameters in patients with schizophrenia

BACKGROUND

In this cross-sectional study, we compared fasting serum asprosin levels and metabolic parameters between patients receiving one of three atypical antipsychotics (olanzapine, risperidone, or aripiprazole) and healthy subjects.

METHODS

The study population included 62 adult outpatients with schizophrenia and 22 healthy controls, matched for age and gender. Patients were in remission and had been on stable monotherapy with one of these atypical antipsychotics for over 6 months. Body Mass Index (BMI) and fasting serum levels of asprosin, glucose, HA1c, insulin, and lipid profile were compared across the investigated groups. Additionally, the number of participants meeting the insulin resistance criterion, defined as homeostasis model assessment for insulin resistance (HOMA-IR) >2.5, as well as the number of participants with elevated BMI levels (men >27 kg/m2, women >25 kg/m2) were compared among the groups.

RESULTS

We observed statistically significant differences in BMI and fasting serum levels of glucose, HA1c, insulin, triglyceride (TG), high-density lipoprotein cholesterol, and asprosin among patients receiving olanzapine or risperidone, as compared to those receiving aripiprazole and healthy subjects. Patients on aripiprazole exhibited values comparable to healthy subjects, whereas those on risperidone or olanzapine showed significantly higher values, with the highest observed in the olanzapine group. Additionally, the prevalence of participants meeting the insulin resistance criterion and those with elevated BMI was also greater in individuals receiving olanzapine or risperidone compared to those on aripiprazole and healthy subjects. Serum asprosin levels showed a significant positive correlation with BMI and several metabolic parameters, including HbA1c, fasting insulin, HOMA-IR, and TG. No significant differences were observed among the investigated groups in terms of serum levels of total cholesterol and low-density lipoprotein cholesterol.

CONCLUSIONS

Our cross-sectional study highlights the association between elevated asprosin levels, weight gain, and metabolic disorders in patients treated with olanzapine and risperidone. Given the bidirectional nature of the relationship between serum asprosin levels and these metabolic disturbances, further research is warranted to elucidate potential causative pathways.

High circulating MIF levels indicate the association with atypical antipsychotic-induced adverse metabolic effects

Atypical antipsychotics (AAPs) are primary medications for schizophrenia (SZ). However, their use is frequently associated with the development of adverse metabolic effects, and the mechanisms behind these negative effects remain inadequately elucidated. To investigate the role of macrophage migration inhibitory factor (MIF) in regulating antipsychotic-induced metabolic abnormalities, between 2017 and 2020, a cross-sectional study was conducted, involving 142 healthy individuals and 388 SZ patients undergoing treatment with either typical antipsychotic (TAP) or AAP medications. Symptoms of SZ patients were evaluated using the Positive and Negative Syndrome Scale (PANSS), and measurements of metabolic indices and plasma MIF levels were performed on all individuals. A significant increase in plasma MIF levels was observed in groups receiving five major AAP monotherapies in comparison to healthy controls (all p < 0.0001). There was no such increase shown in the group receiving TAP treatment (p > 0.05). Elevated plasma MIF levels displayed a notable correlation with insulin resistance (β = 0.024, p = 0.020), as well as with the levels of triglycerides (β = 0.019, p = 0.001) and total cholesterol (β = 0.012, p = 0.038) in the groups receiving AAPs. However, while the TAP group also displayed certain metabolic dysfunction compared to healthy controls, no significant association was evident with plasma MIF levels (all p > 0.05). In conclusion, plasma MIF levels exhibit a distinctive correlation with metabolic abnormalities triggered by AAPs. Hence, there is potential for further development of MIF as a distinctive marker for monitoring adverse metabolic effects induced by AAPs in clinical settings.

Schizophrenia and cardiometabolic abnormalities: A Mendelian randomization study

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect. Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis. Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10-8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods. Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001-0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002-0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis. Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.

Adiponectin and Stnfr2 peripheral levels are associated with cardiovascular risk in patients with schizophrenia

OBJECTIVES

To investigate the association between cytokine peripheral levels and the risk of cardiovascular disease in patients with schizophrenia and controls.

METHODS

A sample of 40 patients and 40 control subjects participated in the study. Psychiatric diagnosis was established following structured clinical assessment. The Framingham Score was used to assess cardiovascular risk (CVR). Serum levels of the cytokines IL-1β, IL-6, IL-8, IL-10, IL-12p70 and TNF-α were determined by cytometric bead array (CBA) technique, and the serum levels of IL-33, sST2, sTNFR1, sTNFR2, Leptin and Adiponectin by Enzyme-Linked Immunosorbent assay (ELISA).

RESULTS

Patients with schizophrenia showed greater frequency of moderate CVR when compared with controls (p = 0.14). In addition, patients showed higher levels of sTNFR2 and Adiponectin compared to controls (p = 0.007 and p < 0.001, respectively). Adiponectin and sTNFR2 were associated with CVR only in patients (p = 0.0002 and p = 0.033, respectively). In multivariate analysis controlling for socio-demographic and clinical confounders, illness duration (r = 0.492; p < 0.002) and sTNFR2 (r = 0.665; p < 0.004) were independent predictors of CVR.

CONCLUSION

Our results reinforce the concept that patients with schizophrenia are at greater risk to develop cardiovascular diseases, and suggest that the associated chronic low-grade inflammation might play a role in this process.

Metabolic disturbances associated with antipsychotic drug treatment in patients with schizophrenia: State-of-the-art and future perspectives

Metabolic disturbances and obesity are major cardiovascular risk factors in patients with schizophrenia, resulting in a higher mortality rate and shorter life expectancy compared with those in the general population. Although schizophrenia and metabolic disturbances may share certain genetic or pathobiological risks, antipsychotics, particularly those of second generation, may further increase the risk of weight gain and metabolic disturbances in patients with schizophrenia. This review included articles on weight gain and metabolic disturbances related to antipsychotics and their mechanisms, monitoring guidelines, and interventions. Nearly all antipsychotics are associated with weight gain, but the degree of the weight gain varies considerably. Although certain neurotransmitter receptor-binding affinities and hormones are correlated with weight gain and specific metabolic abnormalities, the precise mechanisms underlying antipsychotic-induced weight gain and metabolic disturbances remain unclear. Emerging evidence indicates the role of genetic polymorphisms associated with antipsychotic-induced weight gain and antipsychotic-induced metabolic disturbances. Although many guidelines for screening and monitoring antipsychotic-induced metabolic disturbances have been developed, they are not routinely implemented in clinical care. Numerous studies have also investigated strategies for managing antipsychotic-induced metabolic disturbances. Thus, patients and their caregivers must be educated and motivated to pursue a healthier life through smoking cessation and dietary and physical activity programs. If lifestyle intervention fails, switching to another antipsychotic drug with a lower metabolic risk or adding adjunctive medication to mitigate weight gain should be considered. Antipsychotic medications are essential for schizophrenia treatment, hence clinicians should monitor and manage the resulting weight gain and metabolic disturbances.

Cytokine Level Changes in Schizophrenia Patients with and without Metabolic Syndrome Treated with Atypical Antipsychotics

The present study aims at comparing the change in cytokine levels in schizophrenia patients treated with atypical antipsychotics, with or without metabolic syndrome (MetS). The study included 101 patients with schizophrenia, 38 with and 63 without MetS, who received risperidone, quetiapine, olanzapine or aripiprazole for six weeks. We analyzed the concentration of 21 cytokines in the serum patients. The treatment with atypical antipsychotics changed some proinflammatory cytokine levels. It led to increased IFN-α2 (p = 0.010), IL-1α (p = 0.024) and IL-7 (p = 0.017) levels in patients with MetS, whereas the same treatment led to decreased levels of IFN-γ (p = 0.011), IL-1β (p = 0.035), IL-12р40 (p = 0.011), IL-17A (p = 0.031), IL-6 (p = 0.043) and TNF-α (p = 0.012) in individuals without MetS. Our results demonstrated the effects of atypical antipsychotics on the immune–inflammatory parameters, depending on the metabolic disturbances in schizophrenia patients.

Examining the Causal Inference of Leptin and Soluble Plasma Leptin Receptor Levels on Schizophrenia: A Mendelian Randomization Study

Background: Observational studies that have supported the role of the leptin level in schizophrenia (SCZ) risk are conflicting. Therefore, we performed a two-sample Mendelian randomization (MR) analysis to investigate whether the circulating leptin and soluble plasma leptin receptor (sOB-R) levels play a causal role in SCZ risk. Methods: We first selected five independent single-nucleotide polymorphisms (SNPs) associated with the circulating leptin level and three independent SNPs associated with the sOB-R level from two genome-wide association studies (GWASs) of European individuals. Then, we extracted their associations with SCZ using a large-scale GWAS that consisted of 40,675 patients with SCZ and 64,643 controls of European ancestry. We performed an MR analysis using the inverse variance-weighted (IVW) method to examine the causal effect of leptin on SCZ risk. Moreover, we performed sensitivity analyses to verify our MR results using the weighted median and MR-Egger methods. Results: According to the IVW method, genetically predicted circulating leptin levels were not associated with SCZ risk (OR = 1.98, for per 1-SD unit increase in leptin level; 95% CI, 0.87-4.53; p = 0.10). In addition, the sOB-R level showed no causal effect on the SCZ risk using IVW (OR = 0.98 for per 1-SD unit increase in sOB-R level; 95% CI, 0.97-1.00; p = 0.06). Our sensitivity analysis results confirmed our MR findings. Conclusions: By estimating the causal effect of leptin on SCZ risk using the MR methods, we identified no effect of genetically predicted circulating leptin or the sOB-R level on SCZ. As such, our study suggests that leptin might not be a risk factor for SCZ.