ArticleComputational and structural biotechnology journal2024
Identification of key modules in metabolic syndrome induced by second-generation antipsychotics based on co-expression network analysis.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Effects of Empagliflozin and Lifestyle Intervention on Improving Body Weight and Other Metabolic Parameters in Atypical Antipsychotics-treated Patients with Schizophrenia Spectrum Disorders-A Double-blind Randomized Placebo-controlled Trial.Schizophrenia bulletin · 2026Trial
- Peripheral blood RNA-seq analysis in bipolar and schizophrenia spectrum disorders: modest influence of antipsychotic treatment.Frontiers in pharmacology · 2026Article
- Linking Metabolic Disorders and Immune System Phenomena in Schizophrenia: The Role of Adipose Tissue and Inflammation.Biomedicines · 2025Review
- Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis.European journal of medical research · 2025Article
- Transcriptional coordination between intergenic RNA polymerase II-bound regions and nearby genes reveals functional specialization and disease associations in peripheral blood.Computational and structural biotechnology journal · 2025Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
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Abstract
Background: Second-generation antipsychotics (SGAs) frequently cause metabolic syndrome (MetS), which raises the risk of heart disease, type 2 diabetes, morbid obesity, atherosclerosis, and hypertension. MetS also impairs cognitive function in patients with schizophrenia. However, the fundamental reasons of MetS caused by SGAs are not yet fully understood. Thus, we aimed to identify potential therapeutic targets for MetS induced by SGAs. Methods: The serum biochemical parameters and the RNA-sequencing of peripheral blood mononuclear cells were measured in three groups (healthy controls and patients with schizophrenia with and without MetS taking SGAs). The study of the weighted gene co-expression network was utilized to pinpoint modules that were significantly connected to clinical markers. Results: Statistical analysis showed significant differences in triglyceride and high-density lipoprotein among the three groups. The TNF signaling pathway, TGF-β signaling pathway, fatty acid metabolism, NF-kappa B signaling pathway, MAPK signaling pathway, and Toll-like receptor signaling pathway were the pathways that were primarily enriched in the two unique co-expression network modules that were found. Finally, five specific genes (TNF, CXCL8, IL1B, TIMP1, and ESR1) associated with metabolism and immunity pathways were identified. Conclusions: This study indicated that SGAs differentially induced MetS of patients with schizophrenia through metabolic and inflammation-related pathways. Therefore, the potential side effects of drugs on inflammatory processes need to be considered when using SGAs for the treatment of schizophrenia.
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