Rebecca A S Palu, Katie G Owings, John G Garces, Audrey Nicol
{"title":"自然遗传变异筛选确定了胰岛素信号、神经元通讯和先天性免疫是 Sirt1 缺失时高血糖的调节因子。","authors":"Rebecca A S Palu, Katie G Owings, John G Garces, Audrey Nicol","doi":"10.1093/g3journal/jkac090","DOIUrl":null,"url":null,"abstract":"<p><p>Variation in the onset, progression, and severity of symptoms associated with metabolic disorders such as diabetes impairs the diagnosis and treatment of at-risk patients. Diabetes symptoms, and patient variation in these symptoms, are attributed to a combination of genetic and environmental factors, but identifying the genes and pathways that modify diabetes in humans has proven difficult. A greater understanding of genetic modifiers and the ways in which they interact with metabolic pathways could improve the ability to predict a patient's risk for severe symptoms, as well as enhance the development of individualized therapeutic approaches. In this study, we use the Drosophila Genetic Reference Panel to identify genetic variation influencing hyperglycemia associated with loss of Sirt1 function. Through analysis of individual candidate functions, physical interaction networks, and gene set enrichment analysis, we identify not only modifiers involved in canonical glucose metabolism and insulin signaling, but also genes important for neuronal signaling and the innate immune response. Furthermore, reducing the expression of several of these candidates suppressed hyperglycemia, making them potential candidate therapeutic targets. These analyses showcase the diverse processes contributing to glucose homeostasis and open up several avenues of future investigation.</p>","PeriodicalId":14813,"journal":{"name":"Journal De Radiologie","volume":"87 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157059/pdf/","citationCount":"0","resultStr":"{\"title\":\"A natural genetic variation screen identifies insulin signaling, neuronal communication, and innate immunity as modifiers of hyperglycemia in the absence of Sirt1.\",\"authors\":\"Rebecca A S Palu, Katie G Owings, John G Garces, Audrey Nicol\",\"doi\":\"10.1093/g3journal/jkac090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Variation in the onset, progression, and severity of symptoms associated with metabolic disorders such as diabetes impairs the diagnosis and treatment of at-risk patients. Diabetes symptoms, and patient variation in these symptoms, are attributed to a combination of genetic and environmental factors, but identifying the genes and pathways that modify diabetes in humans has proven difficult. A greater understanding of genetic modifiers and the ways in which they interact with metabolic pathways could improve the ability to predict a patient's risk for severe symptoms, as well as enhance the development of individualized therapeutic approaches. In this study, we use the Drosophila Genetic Reference Panel to identify genetic variation influencing hyperglycemia associated with loss of Sirt1 function. Through analysis of individual candidate functions, physical interaction networks, and gene set enrichment analysis, we identify not only modifiers involved in canonical glucose metabolism and insulin signaling, but also genes important for neuronal signaling and the innate immune response. Furthermore, reducing the expression of several of these candidates suppressed hyperglycemia, making them potential candidate therapeutic targets. These analyses showcase the diverse processes contributing to glucose homeostasis and open up several avenues of future investigation.</p>\",\"PeriodicalId\":14813,\"journal\":{\"name\":\"Journal De Radiologie\",\"volume\":\"87 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157059/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal De Radiologie\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/g3journal/jkac090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal De Radiologie","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/g3journal/jkac090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A natural genetic variation screen identifies insulin signaling, neuronal communication, and innate immunity as modifiers of hyperglycemia in the absence of Sirt1.
Variation in the onset, progression, and severity of symptoms associated with metabolic disorders such as diabetes impairs the diagnosis and treatment of at-risk patients. Diabetes symptoms, and patient variation in these symptoms, are attributed to a combination of genetic and environmental factors, but identifying the genes and pathways that modify diabetes in humans has proven difficult. A greater understanding of genetic modifiers and the ways in which they interact with metabolic pathways could improve the ability to predict a patient's risk for severe symptoms, as well as enhance the development of individualized therapeutic approaches. In this study, we use the Drosophila Genetic Reference Panel to identify genetic variation influencing hyperglycemia associated with loss of Sirt1 function. Through analysis of individual candidate functions, physical interaction networks, and gene set enrichment analysis, we identify not only modifiers involved in canonical glucose metabolism and insulin signaling, but also genes important for neuronal signaling and the innate immune response. Furthermore, reducing the expression of several of these candidates suppressed hyperglycemia, making them potential candidate therapeutic targets. These analyses showcase the diverse processes contributing to glucose homeostasis and open up several avenues of future investigation.