T. Addissouky, Majeed M. A. Ali, Ibrahim El Tantawy El Sayed, Yuliang Wang
{"title":"糖尿病研究的革命性创新:从生物标记物到基因组医学","authors":"T. Addissouky, Majeed M. A. Ali, Ibrahim El Tantawy El Sayed, Yuliang Wang","doi":"10.18502/ijdo.v15i4.14556","DOIUrl":null,"url":null,"abstract":"Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia resulting from inadequate insulin signaling. Current management relies on biomarkers such as hemoglobin A1c (HbA1c) to guide therapy, but emerging tools offer opportunities to transform care through more personalized approaches. Molecular biomarkers, including microRNAs, metabolites, and proteins, may enable better prediction of disease course and risk of complications in individuals. Genomic medicine leverages knowledge of genetic architecture to guide tailored prevention and treatment based on an individual’s genomic profile. Stem cell research differentiates functional insulin-secreting cells for transplantation into patients as an alternative to exogenous insulin. Gene silencing techniques such as RNA interference can restore defective insulin production and secretion pathways by inhibiting dysregulated gene expression. Artificial intelligence applications automate glucose monitoring, insulin delivery, diagnostic screening for complications, and digital health coaching. Despite barriers to translation, these technologies have disruptive potential for predictive, preventive, precise, and participatory care paradigms in diabetes management. Continued research on molecular biomarkers, pharmacogenomics, stem cell therapies, gene editing, and artificial intelligence (AI) aims to improve patient outcomes through more personalized approaches tailored to the specific biological vulnerabilities underlying each individual’s diabetes.","PeriodicalId":33205,"journal":{"name":"Iranian Journal of Diabetes and Obesity","volume":"51 52","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Revolutionary Innovations in Diabetes Research: From Biomarkers to Genomic Medicine\",\"authors\":\"T. Addissouky, Majeed M. A. Ali, Ibrahim El Tantawy El Sayed, Yuliang Wang\",\"doi\":\"10.18502/ijdo.v15i4.14556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia resulting from inadequate insulin signaling. Current management relies on biomarkers such as hemoglobin A1c (HbA1c) to guide therapy, but emerging tools offer opportunities to transform care through more personalized approaches. Molecular biomarkers, including microRNAs, metabolites, and proteins, may enable better prediction of disease course and risk of complications in individuals. Genomic medicine leverages knowledge of genetic architecture to guide tailored prevention and treatment based on an individual’s genomic profile. Stem cell research differentiates functional insulin-secreting cells for transplantation into patients as an alternative to exogenous insulin. Gene silencing techniques such as RNA interference can restore defective insulin production and secretion pathways by inhibiting dysregulated gene expression. Artificial intelligence applications automate glucose monitoring, insulin delivery, diagnostic screening for complications, and digital health coaching. Despite barriers to translation, these technologies have disruptive potential for predictive, preventive, precise, and participatory care paradigms in diabetes management. Continued research on molecular biomarkers, pharmacogenomics, stem cell therapies, gene editing, and artificial intelligence (AI) aims to improve patient outcomes through more personalized approaches tailored to the specific biological vulnerabilities underlying each individual’s diabetes.\",\"PeriodicalId\":33205,\"journal\":{\"name\":\"Iranian Journal of Diabetes and Obesity\",\"volume\":\"51 52\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iranian Journal of Diabetes and Obesity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18502/ijdo.v15i4.14556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Diabetes and Obesity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18502/ijdo.v15i4.14556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Revolutionary Innovations in Diabetes Research: From Biomarkers to Genomic Medicine
Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia resulting from inadequate insulin signaling. Current management relies on biomarkers such as hemoglobin A1c (HbA1c) to guide therapy, but emerging tools offer opportunities to transform care through more personalized approaches. Molecular biomarkers, including microRNAs, metabolites, and proteins, may enable better prediction of disease course and risk of complications in individuals. Genomic medicine leverages knowledge of genetic architecture to guide tailored prevention and treatment based on an individual’s genomic profile. Stem cell research differentiates functional insulin-secreting cells for transplantation into patients as an alternative to exogenous insulin. Gene silencing techniques such as RNA interference can restore defective insulin production and secretion pathways by inhibiting dysregulated gene expression. Artificial intelligence applications automate glucose monitoring, insulin delivery, diagnostic screening for complications, and digital health coaching. Despite barriers to translation, these technologies have disruptive potential for predictive, preventive, precise, and participatory care paradigms in diabetes management. Continued research on molecular biomarkers, pharmacogenomics, stem cell therapies, gene editing, and artificial intelligence (AI) aims to improve patient outcomes through more personalized approaches tailored to the specific biological vulnerabilities underlying each individual’s diabetes.