{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T19:29:16Z","timestamp":1779910156791,"version":"3.53.1"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T00:00:00Z","timestamp":1750809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Inflammatory bowel disease (IBD), encompassing Crohn\u2019s disease (CD) and ulcerative colitis (UC), is linked to significant alterations in gut microbiota. Conventional diagnostic approaches frequently rely on invasive procedures, contributing to patient discomfort; hence, non-invasive diagnostic models present a valuable clinical alternative.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Metagenomic and amplicon sequencing data were collected from fecal samples of patients with IBD and healthy individuals across diverse geographic regions. Diagnostic models were developed using Logistic Regression (LR), Support Vector Machine (SVM), Na\u00efve Bayes (NB), and Feedforward Neural Network (FFNN), complemented by an ensemble model <jats:italic>via<\/jats:italic> a voting mechanism. Five-fold cross-validation facilitated the differentiation between normal controls (NC) and IBD, as well as between CD and UC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>K-mer-based methods leveraging metagenomic sequencing data demonstrated robust diagnostic performance, yielding ROC AUCs of 0.966 for IBD vs. NC and 0.955 for CD vs. UC. Similarly, models based on amplicon sequencing achieved ROC AUCs of 0.831 for IBD vs. NC and 0.903 for CD vs. UC. In comparison, k-mer-based approaches outperformed traditional microbiota-based models, which produced lower ROC AUCs of 0.868 for IBD vs. NC and 0.810 for CD vs. UC. Across all machine learning frameworks, the FFNN consistently attained the highest ROC AUC, underscoring its superior diagnostic performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The integration of k-mer-based feature extraction with machine learning offers a non-invasive, highly accurate approach for IBD diagnosis, surpassing traditional microbiota-based models. This method holds considerable potential for clinical use, offering an effective alternative to invasive diagnostics and enhancing patient comfort.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmicb.2025.1578005","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T15:24:14Z","timestamp":1750865054000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Constructing inflammatory bowel disease diagnostic models based on k-mer and machine learning"],"prefix":"10.3389","volume":"16","author":[{"given":"Liwei","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiamin","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chongze","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuqing","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiean","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e70001","DOI":"10.1002\/imt2.70001","article-title":"EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research.","volume":"4","author":"Bai","year":"2025","journal-title":"Imeta"},{"key":"B2","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s13073-016-0290-3","article-title":"Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions.","volume":"8","author":"Baxter","year":"2016","journal-title":"Genome Med."},{"key":"B3","doi-asserted-by":"publisher","first-page":"2114","DOI":"10.1093\/bioinformatics\/btu170","article-title":"Trimmomatic: A flexible trimmer for Illumina sequence data.","volume":"30","author":"Bolger","year":"2014","journal-title":"Bioinformatics"},{"key":"B4","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1080\/17474124.2021.1829971","article-title":"Patients\u2019 perception of colonoscopy and acceptance of colonoscopy based IBD related colorectal cancer surveillance.","volume":"15","author":"Braithwaite","year":"2021","journal-title":"Expert Rev. Gastroenterol. Hepatol."},{"key":"B5","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1016\/j.cell.2021.01.029.","article-title":"Massive expansion of human gut bacteriophage diversity.","volume":"184","author":"Camarillo-Guerrero","year":"2021","journal-title":"Cell"},{"key":"B6","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1038\/s41576-019-0113-7","article-title":"Clinical metagenomics.","volume":"20","author":"Chiu","year":"2019","journal-title":"Nat. Rev. Genet."},{"key":"B7","doi-asserted-by":"publisher","first-page":"j5145","DOI":"10.1136\/bmj.j5145","article-title":"The role of the gut microbiome in systemic inflammatory disease.","volume":"360","author":"Clemente","year":"2018","journal-title":"BMJ"},{"key":"B8","doi-asserted-by":"publisher","first-page":"107593","DOI":"10.1016\/j.ypmed.2023.107593","article-title":"Socioeconomic differences in expected discomfort from colonoscopy and colon capsule endoscopy.","volume":"173","author":"Deding","year":"2023","journal-title":"Prev. Med."},{"key":"B9","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s40291-023-00678-7","article-title":"The genetics of inflammatory bowel disease.","volume":"28","author":"El Hadad","year":"2024","journal-title":"Mol. Diagn. Ther."},{"key":"B10","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","article-title":"Array programming with NumPy.","volume":"585","author":"Harris","year":"2020","journal-title":"Nature"},{"key":"B11","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1186\/s40168-021-01114-w","article-title":"HumGut: A comprehensive human gut prokaryotic genomes collection filtered by metagenome data.","volume":"9","author":"Hiseni","year":"2021","journal-title":"Microbiome"},{"key":"B12","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1126\/science.1212665","article-title":"Untangling genomes from metagenomes: Revealing an uncultured class of marine Euryarchaeota.","volume":"335","author":"Iverson","year":"2012","journal-title":"Science"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2015.0202","article-title":"Principal component analysis: A review and recent developments.","volume":"374","author":"Jolliffe","year":"2016","journal-title":"Philos. Trans. A Math. Phys. Eng. Sci."},{"key":"B14","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1038\/s41579-018-0029-9","article-title":"Best practices for analysing microbiomes.","volume":"16","author":"Knight","year":"2018","journal-title":"Nat. Rev. Microbiol."},{"key":"B15","doi-asserted-by":"publisher","first-page":"e00020-16","DOI":"10.1128\/mSystems.00020-16","article-title":"MetaPalette: A k-mer painting approach for metagenomic taxonomic profiling and quantification of novel strain variation.","volume":"1","author":"Koslicki","year":"2016","journal-title":"mSystems"},{"key":"B16","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1038\/nmeth.1923","article-title":"Fast gapped-read alignment with Bowtie 2.","volume":"9","author":"Langmead","year":"2012","journal-title":"Nat. Methods"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1053\/j.gastro.2023.07.003.","article-title":"Incidence, prevalence, and racial and ethnic distribution of inflammatory bowel disease in the United States.","volume":"165","author":"Lewis","year":"2023","journal-title":"Gastroenterology"},{"key":"B18","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1016\/j.synbio.2021.10.003","article-title":"Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease.","volume":"6","author":"Liang","year":"2021","journal-title":"Synth. Syst. Biotechnol."},{"key":"B19","doi-asserted-by":"publisher","first-page":"1054","DOI":"10.1016\/j.cmet.2017.04.001.","article-title":"Gut microbiome-based metagenomic signature for non-invasive detection of advanced fibrosis in human nonalcoholic fatty liver disease.","volume":"25","author":"Loomba","year":"2017","journal-title":"Cell. Metab."},{"key":"B20","doi-asserted-by":"publisher","first-page":"e61217","DOI":"10.1371\/journal.pone.0061217","article-title":"phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data.","volume":"8","author":"McMurdie","year":"2013","journal-title":"PLoS One"},{"key":"B21","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1093\/ageing\/afw044","article-title":"Associations between multimorbidity, healthcare utilisation and health status: Evidence from 16 European countries.","volume":"45","author":"Palladino","year":"2016","journal-title":"Age Ageing"},{"key":"B22","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1038\/nbt.3935","article-title":"Shotgun metagenomics, from sampling to analysis.","volume":"35","author":"Quince","year":"2017","journal-title":"Nat. Biotechnol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1093\/ecco-jcc\/jjw055","article-title":"European Crohn\u2019s and colitis organisation topical review on prediction, diagnosis and management of fibrostenosing Crohn\u2019s disease.","volume":"10","author":"Rieder","year":"2016","journal-title":"J. Crohns Colitis."},{"key":"B24","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1038\/nature12352","article-title":"Insights into the phylogeny and coding potential of microbial dark matter.","volume":"499","author":"Rinke","year":"2013","journal-title":"Nature"},{"key":"B25","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1038\/nmeth.4458","article-title":"Critical assessment of metagenome interpretation-a benchmark of metagenomics software.","volume":"14","author":"Sczyrba","year":"2017","journal-title":"Nat. Methods"},{"key":"B26","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1053\/j.gastro.2021.10.035.","article-title":"Colorectal cancer in inflammatory bowel disease: Mechanisms and management.","volume":"162","author":"Shah","year":"2022","journal-title":"Gastroenterology"},{"key":"B27","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1146\/annurev-med-042320-021020","article-title":"The gut microbiome and inflammatory bowel diseases.","volume":"73","author":"Shan","year":"2022","journal-title":"Annu. Rev. Med."},{"key":"B28","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1186\/s40168-024-01832-x","article-title":"Gut virome-wide association analysis identifies cross-population viral signatures for inflammatory bowel disease.","volume":"12","author":"Tian","year":"2024","journal-title":"Microbiome"},{"key":"B29","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1038\/nri2653","article-title":"Intestinal mucosal barrier function in health and disease.","volume":"9","author":"Turner","year":"2009","journal-title":"Nat. Rev. Immunol."},{"key":"B30","doi-asserted-by":"publisher","first-page":"2835","DOI":"10.3390\/diagnostics13172835","article-title":"Crohn\u2019s disease prediction using sequence based machine learning analysis of human microbiome.","volume":"13","author":"Unal","year":"2023","journal-title":"Diagnostics (Basel)"},{"key":"B31","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1093\/bioinformatics\/btv683","article-title":"Large-scale machine learning for metagenomics sequence classification.","volume":"32","author":"Vervier","year":"2016","journal-title":"Bioinformatics"},{"key":"B32","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1038\/s41591-019-0406-6","article-title":"Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer.","volume":"25","author":"Wirbel","year":"2019","journal-title":"Nat. Med."},{"key":"B33","doi-asserted-by":"publisher","first-page":"R46","DOI":"10.1186\/gb-2014-15-3-r46","article-title":"Kraken: Ultrafast metagenomic sequence classification using exact alignments.","volume":"15","author":"Wood","year":"2014","journal-title":"Genome Biol."},{"key":"B34","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1186\/s13059-019-1891-0","article-title":"Improved metagenomic analysis with Kraken 2.","volume":"20","author":"Wood","year":"2019","journal-title":"Genome Biol."},{"key":"B35","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1093\/ecco-jcc\/jjab029","article-title":"The burden of inflammatory bowel disease in Europe in 2020.","volume":"15","author":"Zhao","year":"2020","journal-title":"J. Crohns. Colitis."}],"container-title":["Frontiers in Microbiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2025.1578005\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T15:24:21Z","timestamp":1750865061000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2025.1578005\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,25]]},"references-count":35,"alternative-id":["10.3389\/fmicb.2025.1578005"],"URL":"https:\/\/doi.org\/10.3389\/fmicb.2025.1578005","relation":{},"ISSN":["1664-302X"],"issn-type":[{"value":"1664-302X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,25]]},"article-number":"1578005"}}