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Multicenter Study
. 2025 May 8;19(5):jjae169.
doi: 10.1093/ecco-jcc/jjae169.

Characterization of Inflammatory Bowel Disease Heterogeneity Using Serum Proteomics: A Multicenter Study

Benita Salomon  1 , Padhmanand Sudhakar  2   3 , Daniel Bergemalm  4 , Erik Andersson  4 , Olle Grännö  5 , Marie Carlson  6 , Charlotte R H Hedin  7   8 , Johan D Söderholm  9   10 , Lena Öhman  11 ; BIO IBD Consortium, the COLLIBRI Consortium; Carl Mårten Lindqvist  1 , Robert Kruse  1   12   13 , Dirk Repsilber  1 , Bram Verstockt  2   14 , Séverine Vermeire  2 , Jonas Halfvarson  4
Collaborators, Affiliations
Multicenter Study

Characterization of Inflammatory Bowel Disease Heterogeneity Using Serum Proteomics: A Multicenter Study

Benita Salomon et al. J Crohns Colitis. .

Abstract

Background: Recent genetic and transcriptomic data highlight the need for improved molecular characterization of inflammatory bowel disease (IBD). Proteomics may advance the delineation of IBD phenotypes since it accounts for post-transcriptional modifications.

Aims: We aimed to assess the IBD spectrum based on inflammatory serum proteins and identify discriminative patterns of underlying biological subtypes across multiple European cohorts.

Methods: Using proximity extension methodology, we measured 86 inflammation-related serum proteins in 1551 IBD patients and 312 healthy controls (HC). We screened for proteins exhibiting significantly different levels among IBD subtypes and between IBD and HC. Classification models for differentiating between Crohn's disease (CD) and ulcerative colitis (UC) were employed to explore the IBD spectrum based on estimated probability scores.

Results: Levels of multiple proteins, such as interleukin-17A, matrix metalloproteinase-10, and fibroblast growth factor-19, differed (fold-change >1.2; false discovery rate <0.05) between ileal versus colonic IBD. Using multivariable models, a protein signature reflecting the IBD spectrum was identified, positioning colonic CD between UC and ileal CD, which were at opposite ends of the spectrum. Based on area under the curve (AUC) estimates, classification models more accurately differentiated UC from ileal CD (median AUCs > 0.73) than colonic CD (median AUCs < 0.62). Models differentiating colonic CD from ileal CD demonstrated intermediate performance (median AUCs: 0.67-0.69).

Conclusions: Our findings in serum proteins support the presence of a continuous IBD spectrum rather than a clear separation of CD and UC. Within the spectrum, disease location may reflect a more similar disease than CD versus UC, as colonic CD resembled UC more closely than ileal CD.

Keywords: Crohn’s disease; Montreal classification; biomarkers; disease location; serum proteins; ulcerative colitis.

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Conflict of interest statement

JH served as a speaker and/or advisory board member for AbbVie, BMS, Celgene, Celltrion, Dr. Falk Pharma and the Falk Foundation, Ferring, Galapagos, Gilead, Hospira, Index Pharma, Janssen, MEDA, Medivir, MSD, Novartis, Pfizer, Prometheus Laboratories Inc., Sandoz, Shire, Takeda, Thermo Fisher Scientific, Tillotts Pharma, Vifor Pharma, and UCB, and received grant support from Janssen, MSD, and Takeda. SV reports research support from AbbVie, Johnson & Johnson, Pfizer, and Takeda; lecture fees from AbbVie, Centocor, Ferring, Genentech/Roche, Hospira, Johnson & Johnson, Merck Sharp & Dohme, Pfizer, Takeda, and Tillotts, and consulting fees from AbbVie, Abivax, Celgene, Celltrion, Centocor, Ferring, Galapagos, Genentech/Roche, Gilead, GlaxoSmithKline, Hospira, Johnson & Johnson, Merck Sharp & Dohme, Mundipharma, Pfizer, ProDigest, Prometheus, Second Genome, Takeda, and Tillotts. BV has received research support for research from Pfizer, speaker’s fees from Abbvie, Biogen, Bristol Myers Squibb, Chiesi, Falk, Ferring, Galapagos, Janssen, MSD, Pfizer, R-Biopharm, Takeda, Truvion and Viatris and consultancy fees from Abbvie, Alimentiv, Applied Strategic, Atheneum, Bristol Myers Squibb, Galapagos, Guidepont, Ipsos, Janssen, Progenity, Sandoz, Sosei Heptares, Takeda, Tillots Pharma, and Viatris. DB served as a speaker and/or advisory board member for BMS, Janssen, Pfizer, Pharmacosmos, Sandoz, Takeda, and Tillotts Pharma. CRHH has served as a speaker and/or advisory board member for AstraZeneca, Dr Falk Pharma and the Falk Foundation, Galapagos, Janssen, Pfizer, Takeda, Tillotts Pharma, and received grant support from Tillotts and Takeda. MC has received speaker’s fees from ViforPharma. She is the national PI for clinical trials for AstraZeneca. None of these activities have any relation to the present study. LÖ has received financial support for research by Genetic Analysis AS, Biocodex, Danone Research, and AstraZeneca, and served as Consultant/Advisory Board member for Genetic Analysis AS, and as a speaker for Biocodex, Ferring Pharmaceuticals, Takeda, AbbVie, Novartis, Janssen-Cilag, and Meda. SA (included in the BIO IBD consortium) served as a member of Scientific committee/Advisory board of Pharmacosmos, Janssen, Takeda, as a consultant for Takeda, Janssen, and as a speaker: Galapagos, Janssen, Tillotts, received research grants from OrionPharma and Janssen. AC (included in the BIO IBD consortium) served as a speaker for Takeda and Tillotts Pharma. RU (included in the COLLIBRI consortium) served as a member of the Advisory Board and/or consulting for AbbVie, Bristol Myers Squibb, Celltrion, Janssen, Lilly, Pfizer, Roivant, and Takeda, and funded by a K23 Career Development Award K23 KD111995-01A1. KA (included in the COLLIBRI consortium) served as a speaker and/or advisory board member for BMS, Janssen, Pfizer, Falk, Lilly, Galapagos, and Takeda Pharma. The other authors report no disclosures relevant to the manuscript.

Figures

Graphical Abstract
Graphical Abstract
Figure 1.
Figure 1.
Volcano plots of differential regulated inflammatory proteins in patients with ulcerative colitis (UC) and phenotypes of Crohn’s disease (CD) (N = 1551) compared to healthy controls (HC) (N = 312). Differentially regulated proteins are annotated and were selected based on fold-change >1.2 (equal to ~0.26 on a log2 scale) and significance (false discovery rate [FDR] < 0.05). Proteins with higher relative levels in CD subgroups or UC compared to HC are to the right, proteins with lower relative levels in CD or UC compared to HC are to the left. (A) ileal CD versus HC; (B) colonic CD versus HC; (C) ileocolonic CD versus HC; and (D) UC versus HC. (E) The Venn diagram visualizes proteins with higher estimates and lower estimates in patients with UC and with and ileal-, ileocolonic-, and colonic CD compared to HC. 4E-BP1, Eukaryotic translation initiation factor 4E binding protein 1; CASP-8, caspase-8; CCL, C-C motif chemokine; CD40, Tumor necrosis factor receptor superfamily member 5; CD8A, cluster of differentiation 8a; CDCP1, CUB domain-containing protein 1; CXCL, C-XC motif chemokine; EN-RAGE, protein S100-A12; FGF, fibroblast growth factor; FDR, false discovery rate; IL, interleukin; IL-18R1, interleukin-18 receptor 1; IFN-gamma, interferon gamma; MCP, monocyte chemotactic protein; MMP, Matrix metalloproteinase; OPG, osteoprotegerin; OSM, oncostatin M; SLAMF1, signaling lymphocytic activation molecule 1; SIRT2, SIR2-like protein 2; STAMBP, STAM-binding protein; TGF-alpha, transforming growth factor alpha; TNFSF14, tumor necrosis factor ligand superfamily member 14; TRANCE, TNF-related activation-induced cytokine; VEGFA, vascular endothelial growth factor A.
Figure 2.
Figure 2.
Volcano plots of inflammatory proteins from patients of groupwise comparisons based on fold-change >1.2 (equal to ~0.26 on a log2 scale) and false discovery rate (FDR) < 0.05. (A) ileal Crohn’s disease (CD) versus ulcerative colitis (UC); (B) colonic CD versus UC; (C) ileocolonic CD versus UC; (D) ileal CD versus colonic CD; (E) ileal CD versus ileocolonic CD; (F) ileocolonic CD versus colonic CD. CXCL9, C-X-C motif chemokine ligand 9; CXCL11, C-X-C motif chemokine ligand 11; FGF-19, fibroblast growth factor 19; IL, interleukin; MMP-10, matrix metalloproteinase-10.
Figure 3.
Figure 3.
(A) Predicted Crohn’s disease (CD) versus ulcerative colitis (UC) probability estimates from the penalized logistic regression model for UC, IBD unclassified (IBD-U), and phenotypes of CD. A value closer to 0 indicates a higher predicted probability of UC diagnosis, and a value closer to 1 a higher predicted probability of CD diagnosis. (B) Boxplots show coefficients of the UC versus CD models, indicating the importance of the respective proteins in the model. CCL, C-C motif chemokine; CDCP1, CUB domain-containing protein 1; CX3CL1, C-X3-C motif chemokine ligand 1; CXCL, C-X-C motif chemokine; DNER, Delta/Notch Like EGF Repeat Containing; FGF, fibroblast growth factor; IL, interleukin; IL-10RB, IL-10 receptor subunit beta; MCP-3, monocyte-chemotactic protein 3; MMP-10, matrix metalloproteinase 10; SLAMF1, Signaling lymphocytic activation molecule 1; CSF-1, colony stimulating factor 1; TNF, tumor necrosis factor; TRAIL, NF-related apoptosis inducing ligand; TRANCE, TNF-related activation-induced cytokine; TSLP, thymic stromal lymphopoietin; VEGF-A, vascular endothelial growth factor A.
Figure 4.
Figure 4.
Comparison of the performance of the different models delineating down-sampled subgroups of inflammatory bowel disease (IBD) (each N = 188). Performance was evaluated in a repeated 5-fold cross-validation. Area under the receiver-operating characteristic curves (AUCs) of the Random Forest (RF), least absolute shrinkage and selection operator (Lasso)-penalized logistic regression, smoothly clipped absolute deviations (SCAD) combined with ridge-penalized logistic regression, and regularized support vector machine with a radial kernel (SVM radial). SVMs were fitted by selected most important proteins for the model based on variable importance in the inner cross-validation. CD, Crohn’s disease; UC, ulcerative colitis.
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