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. 2022 Aug 24;10:133. doi: 10.1186/s40168-022-01331-x

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Multi-omics identifies features both common and unique features of ileal- and colonic-isolated diseases. A Enrichr-generated gene ontology enrichment graph using host proteome features significantly greater in CCD compared to ICD, sorted by Enrichr combination score [23]. B Comparison of neutrophil-associated proteins and SES-CD Spearman correlation scores, binned by CD location. Significance derived using Welch’s t test, *** = p < 0.0001. n = 49 features, all active disease ICD (n = 31) and CCD (n = 24) subjects used in comparison. C Heatmap of neutrophil-associated protein abundance (x-axis) compared in healthy controls, CD subtypes, and UC. Abundance is column scaled to enhance visibility. D Bar plot comparing log2-transformed relative protein abundance between ICD (n = 31) and CCD (n = 24). *p < 0.05, ***p < 0.0001, Welch’s t test. E Comparison of dipeptide/amino acid abundances between ICD (n = 31) and CCD (n = 24). Mean abundance levels plotted. Each dot represents a different amino acid/dipeptide identified and lines connecting dots denote the same metabolite in the disease location specified. F Comparison of blood-related proteins (complement C4, fibrinogen, and serum albumin) found in ICD (n = 31) and CCD (n = 24) stool samples. **** = p < 0.0001, Welch’s t test. G PCA biplot of individual CD locations, overlayed with SES-CD severity scores. Color ramping from purple to yellow denotes increasing severity score. Only five most contributing features (combined PCA1 + 2 contribution) plotted for ease of viewing. H Scatter plot comparing SES-CD scores (x-axis) and B. vulgatus metagenomic abundance. Linear model used to plot trend line. ICD n = 31, Rho = 0.29, p = 0.16; CCD n = 24, Rho = 0.48, p = 0.03; ICCD n = 11, Rho = 0.84, p = 0.07. I Bar plot comparing Spearman correlation values (n = 89 corr. pairs) of B. vulgatus levels and neutrophil related proteins, split by ICD and CCD. ****p < 0.0001, Welch’s t test. J Bar plot comparing significant (p < 0.05) Spearman correlation values of B. vulgatus levels and dipeptide metabolomic features, split by ICD (n = 6 features), and CCD (n = 31 features). ****p < 0.0001, Welch’s t test