Semi Zouiouich, Yunhu Wan, Emily Vogtmann, Carolina Porras, Christian C Abnet, Jianxin Shi, Rashmi Sinha
{"title":"Sample Size Estimations Based on Human Microbiome Temporal Stability Over 6 Months: A Shallow Shotgun Metagenome Sequencing Analysis.","authors":"Semi Zouiouich, Yunhu Wan, Emily Vogtmann, Carolina Porras, Christian C Abnet, Jianxin Shi, Rashmi Sinha","doi":"10.1158/1055-9965.EPI-24-0839","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Biological factors affect the human microbiome, highlighting the need for reasonably estimating sample sizes in future population studies.</p><p><strong>Methods: </strong>We assessed the temporal stability of fecal microbiome diversity, species composition, and genes and functional pathways through shallow shotgun metagenome sequencing. Using intraclass correlation coefficients (ICC), we measured biological variability over 6 months. We estimated case numbers for 1:1 or 1:3 matched case-control studies, considering significance levels of 0.05 and 0.001 with 80% power, based on the collected fecal specimens per participant.</p><p><strong>Results: </strong>The fecal microbiome's temporal stability over 6 months varied (ICC < 0.6) for most alpha and beta diversity metrics. Heterogeneity was seen in species, genes, and pathways stability (ICC, 0.0-0.9). Detecting an OR of 1.5 per SD required 1,000 to 5,000 cases (0.05 significance for alpha and beta; 0.001 for species, genes, and pathways) with equal cases and controls. Low-prevalence species needed 15,102 cases, and high-prevalence species required 3,527. Similar needs applied to genes and pathways. In a 1:3 matched case-control study with one fecal specimen, 10,068 cases were needed for low-prevalence species and 2,351 for high-prevalence species. For ORs of 1.5 with multiple specimens, cases needed for low-prevalence species were 15,102 (one specimen), 8,267 (two specimens), and 5,989 (three specimens).</p><p><strong>Conclusions: </strong>Detecting disease associations requires a large number of cases. Repeating prediagnostic samples and matching cases to more controls could decrease the needed number of cases for such detections.</p><p><strong>Impact: </strong>Our results will help future epidemiologic study designs and implement well-powered microbiome studies.</p>","PeriodicalId":9458,"journal":{"name":"Cancer Epidemiology Biomarkers & Prevention","volume":" ","pages":"588-597"},"PeriodicalIF":3.7000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology Biomarkers & Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/1055-9965.EPI-24-0839","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Biological factors affect the human microbiome, highlighting the need for reasonably estimating sample sizes in future population studies.
Methods: We assessed the temporal stability of fecal microbiome diversity, species composition, and genes and functional pathways through shallow shotgun metagenome sequencing. Using intraclass correlation coefficients (ICC), we measured biological variability over 6 months. We estimated case numbers for 1:1 or 1:3 matched case-control studies, considering significance levels of 0.05 and 0.001 with 80% power, based on the collected fecal specimens per participant.
Results: The fecal microbiome's temporal stability over 6 months varied (ICC < 0.6) for most alpha and beta diversity metrics. Heterogeneity was seen in species, genes, and pathways stability (ICC, 0.0-0.9). Detecting an OR of 1.5 per SD required 1,000 to 5,000 cases (0.05 significance for alpha and beta; 0.001 for species, genes, and pathways) with equal cases and controls. Low-prevalence species needed 15,102 cases, and high-prevalence species required 3,527. Similar needs applied to genes and pathways. In a 1:3 matched case-control study with one fecal specimen, 10,068 cases were needed for low-prevalence species and 2,351 for high-prevalence species. For ORs of 1.5 with multiple specimens, cases needed for low-prevalence species were 15,102 (one specimen), 8,267 (two specimens), and 5,989 (three specimens).
Conclusions: Detecting disease associations requires a large number of cases. Repeating prediagnostic samples and matching cases to more controls could decrease the needed number of cases for such detections.
Impact: Our results will help future epidemiologic study designs and implement well-powered microbiome studies.
期刊介绍:
Cancer Epidemiology, Biomarkers & Prevention publishes original peer-reviewed, population-based research on cancer etiology, prevention, surveillance, and survivorship. The following topics are of special interest: descriptive, analytical, and molecular epidemiology; biomarkers including assay development, validation, and application; chemoprevention and other types of prevention research in the context of descriptive and observational studies; the role of behavioral factors in cancer etiology and prevention; survivorship studies; risk factors; implementation science and cancer care delivery; and the science of cancer health disparities. Besides welcoming manuscripts that address individual subjects in any of the relevant disciplines, CEBP editors encourage the submission of manuscripts with a transdisciplinary approach.