Daniel McDonald, Mady Hornig, Catherine Lozupone, Justine Debelius, Jack A Gilbert, Rob Knight
{"title":"开展大队列比较研究,明确影响ASD患者肠道微生物群落结构的因素。","authors":"Daniel McDonald, Mady Hornig, Catherine Lozupone, Justine Debelius, Jack A Gilbert, Rob Knight","doi":"10.3402/mehd.v26.26555","DOIUrl":null,"url":null,"abstract":"<p><p>Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase. </p>","PeriodicalId":18568,"journal":{"name":"Microbial Ecology in Health and Disease","volume":"26 ","pages":"26555"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3402/mehd.v26.26555","citationCount":"25","resultStr":"{\"title\":\"Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients.\",\"authors\":\"Daniel McDonald, Mady Hornig, Catherine Lozupone, Justine Debelius, Jack A Gilbert, Rob Knight\",\"doi\":\"10.3402/mehd.v26.26555\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase. </p>\",\"PeriodicalId\":18568,\"journal\":{\"name\":\"Microbial Ecology in Health and Disease\",\"volume\":\"26 \",\"pages\":\"26555\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3402/mehd.v26.26555\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microbial Ecology in Health and Disease\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3402/mehd.v26.26555\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2015/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbial Ecology in Health and Disease","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3402/mehd.v26.26555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2015/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients.
Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase.