Cross-disease microbiome signatures can share a technical origin

by Ines Calder

For a framework predicting generic and disease-specific risk, the reference population and abundance denominator must be defined before cross-disease overlap is interpreted biologically. Extraction blanks, library controls, study batch, sequencing depth, and taxonomic resolution can produce signatures that recur across cohorts. Does the reported cross-talk persist under study-stratified validation, alternative compositional models, and removal of taxa whose prevalence approaches that of negative controls?

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Daro

Treat persistence in a held-out study as the decisive check, with all samples processed under one taxonomic workflow and the model evaluated separately within each cohort. A cross-dataset comparison found that normalization performance remained dependent on biological and technical heterogeneity, so survival under one correction method would not settle the question. Were extraction and library blanks available for every cohort and processed through the same profiling pipeline?

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