{"title":"From variability to stability: Sensitivity of network properties in IBD human gut microbiome studies.","authors":"Theresa Geese, Astrid Dempfle","doi":"10.1016/j.csbj.2025.05.005","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The gut microbiome's role in inflammatory bowel disease (IBD) is well-established, but capturing its complexity is challenging. Network analysis offers a valuable approach, but selecting suitable measures is crucial. This study examines the sensitivity of network properties to abundance variations. It evaluates whether these properties reflect the microbiome in IBD or are too sensitive to variability from e.g. laboratory conditions or intra-individual changes.</p><p><strong>Methods: </strong>Using genetically unrelated individuals from the KINDRED cohort (IBD n = 522, healthy controls n = 365) and the PRISM cohort (IBD n = 42, healthy controls n = 42), microbial networks were constructed with genera as nodes and significant pairwise correlations as edges, separately for IBD patients and controls. Important IBD-related nodes, identified through centrality measures, and non-disease-related nodes were varied in abundance ( ± 30 %), and networks were re-constructed and compared with initial networks regarding local and global properties.</p><p><strong>Results: </strong>Network properties in IBD were sensitive to abundance variations, with small and large changes producing similar effects. Sensitivity to increasing read counts of disease-related and non-disease-related genera was similar. Local properties showed magnitude-dependent changes of up to 50 % in response to the depletion of disease-related genera, relative to no modification applied, and an almost binary sensitivity pattern when modifying non-disease-related genera. Global case network properties changed less than 10 % in most settings, potentially indicating a certain stability of dysbiosis.</p><p><strong>Conclusion: </strong>Caution is needed with network-based approaches, as even small variations, stemming from sources of microbiome variability, can affect results and reproducibility. The relatively stable dysbiosis in IBD could pose challenges for microbiome-directed therapies.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"1945-1961"},"PeriodicalIF":4.4000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12145524/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and structural biotechnology journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.csbj.2025.05.005","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The gut microbiome's role in inflammatory bowel disease (IBD) is well-established, but capturing its complexity is challenging. Network analysis offers a valuable approach, but selecting suitable measures is crucial. This study examines the sensitivity of network properties to abundance variations. It evaluates whether these properties reflect the microbiome in IBD or are too sensitive to variability from e.g. laboratory conditions or intra-individual changes.
Methods: Using genetically unrelated individuals from the KINDRED cohort (IBD n = 522, healthy controls n = 365) and the PRISM cohort (IBD n = 42, healthy controls n = 42), microbial networks were constructed with genera as nodes and significant pairwise correlations as edges, separately for IBD patients and controls. Important IBD-related nodes, identified through centrality measures, and non-disease-related nodes were varied in abundance ( ± 30 %), and networks were re-constructed and compared with initial networks regarding local and global properties.
Results: Network properties in IBD were sensitive to abundance variations, with small and large changes producing similar effects. Sensitivity to increasing read counts of disease-related and non-disease-related genera was similar. Local properties showed magnitude-dependent changes of up to 50 % in response to the depletion of disease-related genera, relative to no modification applied, and an almost binary sensitivity pattern when modifying non-disease-related genera. Global case network properties changed less than 10 % in most settings, potentially indicating a certain stability of dysbiosis.
Conclusion: Caution is needed with network-based approaches, as even small variations, stemming from sources of microbiome variability, can affect results and reproducibility. The relatively stable dysbiosis in IBD could pose challenges for microbiome-directed therapies.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology