Identifying reproducible biomarkers for microbiome association studies requires thousands of sample sizes, Zhang et al, 2025

Yann04

Yann04

Senior Member (Voting Rights)
No abstract provided, first paragraph instead:

Interest in the relationship between gut microbiota and human health has mounted, whereas conflicting findings are often reported [1], [2], [3], making it difficult to identify a definite signature that affects specific phenotypes. The factors that may lead to poor reproducibility, such as insufficient sample sizes and numerous confounders [3], [4], need to be addressed. Although existing studies have provided insights into sample size and power calculations for typical microbiome studies—such as comparing microbial community structure between different groups using distance metrics or the entire vector of abundances [5], [6], [7], [8]—many microbiome studies still lack statistical methods to predetermine sample size. Previous studies have exhibited a wide variation in sample sizes, ranging from merely twenty to thousands of cases. Determining the optimal number of participants remains a largely unresolved issue. On the one hand, this can be partly attributed to the complexity and variability of microbiome data, which makes classic sample size calculation unsuitable for this field [9]. On the other hand, it is not easy to carry out the task of obtaining realistic estimates from preliminary data for sample size determination, especially when researchers face situations where the data is either unavailable or comes from small pilot studies.
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There was a news headline on newatlas.com about how Chinese scientists could tell which city you're from by your microbiome. Well, actually they could tell the difference between two widely separated cities, with different cultural diets.

So, if people with different diets have significant variations in their microbiome, how will you find differences due to disease?
 
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