Altered leptin level in autism spectrum disorder and meta-analysis of adipokines.

BACKGROUND: Increasing evidence suggests that leptin is involved in the pathology of autism spectrum disorder (ASD). In this study, our objective was to investigate the levels of leptin in the blood of children with ASD and to examine the overall profile of adipokine markers in ASD through meta-analysis. METHODS: Leptin concentrations were measured using an enzyme-linked immunosorbent assay (ELISA) kit, while adipokine profiling, including leptin, was performed via meta-analysis. Original reports that included measurements of peripheral adipokines in ASD patients and healthy controls (HCs) were collected from databases such as Web of Science, PubMed, and Cochrane Library. These studies were collected from September 2022 to September 2023 and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Standardized mean differences were calculated using a random effects model for the meta-analysis. Additionally, we performed meta-regression and explored heterogeneity among studies. RESULTS: Our findings revealed a significant increase in leptin levels in children with ASD compared to HCs (p = 0.0319). This result was consistent with the findings obtained from the meta-analysis (p < 0.001). Furthermore, progranulin concentrations were significantly reduced in children with ASD. However, for the other five adipokines analyzed, there were no significant differences observed between the children with ASD and HCs children. Heterogeneity was found among the studies, and the meta-regression analysis indicated that publication year and latitude might influence the results of the meta-analysis. CONCLUSIONS: These findings provide compelling evidence that leptin levels are increased in children with ASD compared to healthy controls, suggesting a potential mechanism involving adipokines, particularly leptin, in the pathogenesis of ASD. These results contribute to a better understanding of the pathology of ASD and provide new insights for future investigations.

Blood exosome sensing via neuronal insulin-like growth factor-1 regulates autism-related phenotypes.

The development and progression of autism spectrum disorder (ASD) is characterized by multiple complex molecular events, highlighting the importance of the prefrontal brain regions in this process. Exosomes are nanovesicles that play a critical role in intercellular communication. Peripheral systems influence brain function under both physiological and pathological conditions. We investigated whether this influence was mediated by the direct sensing of peripheral blood exosomes by brain cells. Administration of serum exosomes from rats with valproic acid-induced ASD resulted in ASD-related phenotypes in mice, whereas exosomes from normal rats did not exhibit such effects. RNA sequencing and bioinformatics analysis suggested that negative regulation of medial prefrontal cortex (mPFC) insulin-like growth factor 1 (IGF-1) by exosome-derived miR-29b-3p may contribute to these ASD-associated effects. Further evidence showed that miR-29b-3p-enriched exosomes crossed the blood-brain barrier to reach the mPFC, subsequently inducing the suppression of IGF-1 expression in neurons. Optogenetic activation of excitatory neurons in the mPFC improved behavioral abnormalities in exosome-treated mice. The addition of exogenous IGF-1 or inhibition of miR-29b-3p expression in the mPFC also rescued the ASD-related phenotypes in mice. Importantly, administration of miR-29b-3p-enriched serum exosomes from human donors with ASD into the mouse medial prefrontal cortex was sufficient to induce hallmark ASD behaviors. Together, our findings indicate that blood-brain cross-talk is crucial for ASD pathophysiology and that the brain may sense peripheral system changes through exosomes, which could serve as the basis for future neurological therapies.

Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS. METHODS: This study was carried out in the Department of Obstetrics and Gynecology of the Maternal and Child Health Hospital of Hunan Province from December 2014 to July 2016. In this study, the urine samples of 21 women with PCOS and 16 healthy controls were assessed through gas chromatography-mass spectrometry to investigate the urine metabolite characteristics of PCOS and identify useful biomarkers for the diagnosis of this disorder. The Student's t-test and rank sum test were applied to validate the statistical significance of the between the two groups. RESULTS: In total, 35 urine metabolites were found to be significantly different between the PCOS patients and the controls. In particular, a significant increase in the levels of lactose (10.01 [0,13.99] mmol/mol creatinine vs. 2.35 [0.16, 3.26] mmol/mol creatinine, P = 0.042), stearic acid (2.35 [1.47, 3.14] mmol/mol creatinine vs. 0.05 [0, 0.14] mmol/mol creatinine, P < 0.001), and palmitic acid (2.13 [1.07, 2.79] mmol/mol creatinine vs. 0 [0, 0] mmol/mol creatinine, P < 0.001) and a decrease in the levels of succinic acid (0 [0, 0] mmol/mol creatinine vs. 38.94 [4.16, 51.30] mmol/mol creatinine, P < 0.001) were found in the PCOS patients compared with the controls. It was possible to cluster the PCOS patients and the healthy controls into two distinct regions based on a principal component analysis model. Of the differentially expressed metabolites, four compounds, including stearic acid, palmitic acid, benzoylglycine, and threonine, were selected as potential biomarkers. CONCLUSIONS: This study offers new insight into the pathogenesis of PCOS, and the discriminating urine metabolites may provide a prospect for the diagnosis of PCOS.