Sa Xiao, Long Lin, Xiao-Hong Chen, Lu-Wen Lei, Min Wang
{"title":"药物性胰岛素自身免疫综合征:FAERS数据库和网络药理学分析。","authors":"Sa Xiao, Long Lin, Xiao-Hong Chen, Lu-Wen Lei, Min Wang","doi":"10.2174/0118715303382179250808052834","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Insulin Autoimmune Syndrome (IAS) is a rare yet clinically significant drug-induced adverse reaction, characterized by hypoglycemic episodes caused by insulin autoantibodies. While individual drug associations are documented in case reports, systematic pharmacovigilance analyses supporting drug-induced IAS are lacking in the literature. This study aims to identify drugs associated with IAS through pharmacovigilance analysis and explore potential molecular mechanisms.</p><p><strong>Methods: </strong>We conducted a comprehensive analysis of IAS reports in the FDA Adverse Event Reporting System (FAERS) database (2004-2024) using multiple disproportionality analysis methods. Drug-gene interaction networks were constructed using DGIdb, GeneCards, and SwissTarget- Prediction databases, with subsequent protein-protein interaction analysis and pathway enrichment performed using STRING and DAVID databases.</p><p><strong>Results: </strong>Analysis of 228 IAS reports revealed significant associations with 17 medications, 16 of which were not documented in the current IAS literature. Captopril showed the strongest association (ROR: 1777, 95% CI: 1051-3005), followed by thiamazole and clopidogrel. Network analysis identified enrichment in the PI3K-Akt signaling pathway, insulin resistance, and AMPK pathways, suggesting these pathways may play a role in the development of IAS.</p><p><strong>Discussion: </strong>This study identified novel drug associations with IAS, highlighting the high risk of captopril in patients with the HLA-DRB1*0406 genotype, and the need for close monitoring of elderly patients on thiamazole or clopidogrel, particularly for hypoglycemia. Additionally, monitoring PI3K-Akt pathway disruption is crucial, as it may impair Treg function and promote the production of autoantibodies against insulin.</p><p><strong>Conclusions: </strong>The study identified 17 medications associated with IAS and emphasized the potential role of the PI3K-Akt pathway, recommending avoidance of certain drugs and enhanced monitoring in high-risk patients.</p>","PeriodicalId":94316,"journal":{"name":"Endocrine, metabolic & immune disorders drug targets","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drug-Induced Insulin Autoimmune Syndrome: A FAERS Database and Network Pharmacology Analysis.\",\"authors\":\"Sa Xiao, Long Lin, Xiao-Hong Chen, Lu-Wen Lei, Min Wang\",\"doi\":\"10.2174/0118715303382179250808052834\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Insulin Autoimmune Syndrome (IAS) is a rare yet clinically significant drug-induced adverse reaction, characterized by hypoglycemic episodes caused by insulin autoantibodies. While individual drug associations are documented in case reports, systematic pharmacovigilance analyses supporting drug-induced IAS are lacking in the literature. This study aims to identify drugs associated with IAS through pharmacovigilance analysis and explore potential molecular mechanisms.</p><p><strong>Methods: </strong>We conducted a comprehensive analysis of IAS reports in the FDA Adverse Event Reporting System (FAERS) database (2004-2024) using multiple disproportionality analysis methods. Drug-gene interaction networks were constructed using DGIdb, GeneCards, and SwissTarget- Prediction databases, with subsequent protein-protein interaction analysis and pathway enrichment performed using STRING and DAVID databases.</p><p><strong>Results: </strong>Analysis of 228 IAS reports revealed significant associations with 17 medications, 16 of which were not documented in the current IAS literature. Captopril showed the strongest association (ROR: 1777, 95% CI: 1051-3005), followed by thiamazole and clopidogrel. Network analysis identified enrichment in the PI3K-Akt signaling pathway, insulin resistance, and AMPK pathways, suggesting these pathways may play a role in the development of IAS.</p><p><strong>Discussion: </strong>This study identified novel drug associations with IAS, highlighting the high risk of captopril in patients with the HLA-DRB1*0406 genotype, and the need for close monitoring of elderly patients on thiamazole or clopidogrel, particularly for hypoglycemia. Additionally, monitoring PI3K-Akt pathway disruption is crucial, as it may impair Treg function and promote the production of autoantibodies against insulin.</p><p><strong>Conclusions: </strong>The study identified 17 medications associated with IAS and emphasized the potential role of the PI3K-Akt pathway, recommending avoidance of certain drugs and enhanced monitoring in high-risk patients.</p>\",\"PeriodicalId\":94316,\"journal\":{\"name\":\"Endocrine, metabolic & immune disorders drug targets\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Endocrine, metabolic & immune disorders drug targets\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/0118715303382179250808052834\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine, metabolic & immune disorders drug targets","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0118715303382179250808052834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drug-Induced Insulin Autoimmune Syndrome: A FAERS Database and Network Pharmacology Analysis.
Introduction: Insulin Autoimmune Syndrome (IAS) is a rare yet clinically significant drug-induced adverse reaction, characterized by hypoglycemic episodes caused by insulin autoantibodies. While individual drug associations are documented in case reports, systematic pharmacovigilance analyses supporting drug-induced IAS are lacking in the literature. This study aims to identify drugs associated with IAS through pharmacovigilance analysis and explore potential molecular mechanisms.
Methods: We conducted a comprehensive analysis of IAS reports in the FDA Adverse Event Reporting System (FAERS) database (2004-2024) using multiple disproportionality analysis methods. Drug-gene interaction networks were constructed using DGIdb, GeneCards, and SwissTarget- Prediction databases, with subsequent protein-protein interaction analysis and pathway enrichment performed using STRING and DAVID databases.
Results: Analysis of 228 IAS reports revealed significant associations with 17 medications, 16 of which were not documented in the current IAS literature. Captopril showed the strongest association (ROR: 1777, 95% CI: 1051-3005), followed by thiamazole and clopidogrel. Network analysis identified enrichment in the PI3K-Akt signaling pathway, insulin resistance, and AMPK pathways, suggesting these pathways may play a role in the development of IAS.
Discussion: This study identified novel drug associations with IAS, highlighting the high risk of captopril in patients with the HLA-DRB1*0406 genotype, and the need for close monitoring of elderly patients on thiamazole or clopidogrel, particularly for hypoglycemia. Additionally, monitoring PI3K-Akt pathway disruption is crucial, as it may impair Treg function and promote the production of autoantibodies against insulin.
Conclusions: The study identified 17 medications associated with IAS and emphasized the potential role of the PI3K-Akt pathway, recommending avoidance of certain drugs and enhanced monitoring in high-risk patients.