Subphenotypes of inflammatory bowel disease are characterized by specific serum protein profiles

Abstract

Objective: Genetic and immunological data indicate that inflammatory bowel disease (IBD) are characterized by specific inflammatory protein profiles. However, the serum proteome of IBD is still to be defined. We aimed to characterize the inflammatory serum protein profiles of Crohn's disease (CD) and ulcerative colitis (UC), using the novel proximity extension assay.

Methods: A panel of 91 inflammatory proteins were quantified in a discovery cohort of CD (n = 54), UC patients (n = 54), and healthy controls (HCs; n = 54). We performed univariate analyses by t-test, with false discovery rate correction. A sparse partial least-squares (sPLS) approach was used to identify additional discriminative proteins. The results were validated in a replication cohort.

Results: By univariate analysis, 17 proteins were identified with significantly different abundances in CD and HCs, and 12 when comparing UC and HCs. Additionally, 64 and 45 discriminant candidate proteins, respectively, were identified with the multivariate approach. Correspondingly, significant cross-validation error rates of 0.12 and 0.19 were observed in the discovery cohort. Only FGF-19 was identified from univariate comparisons of CD and UC, but 37 additional discriminant candidates were identified using the multivariate approach. The observed cross-validation error rate for CD vs. UC remained significant when restricting the analyses to patients in clinical remission. Using univariate comparisons, 16 of 17 CD-associated proteins and 8 of 12 UC-associated proteins were validated in the replication cohort. The area under the curve for CD and UC was 0.96 and 0.92, respectively, when the sPLS model from the discovery cohort was applied to the replication cohort.

Conclusions: By using the novel PEA method and a panel of inflammatory proteins, we identified proteins with significantly different quantities in CD patients and UC patients compared to HCs. Our data highlight the potential of the serum IBD proteome as a source for identification of future diagnostic biomarkers.

Conflict of interest statement

Competing Interests: JH has received research grants from the Swedish Research Council, the Örebro University Hospital Research Foundation, the Swedish Foundation for Strategic Research, and speaker's and/or consultancy fees from Abbvie, Cellgene, Hospira, Janssen, Medivir, MSD, Pfizer, Vifor Pharma, Takeda and Tillotts Pharma. DB has received grants from Bengt Ihre research foundation and grants from Region Örebro county, during the conduct of the study. EA, RK, GN, DR, MD have no personal conflicts of interests to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1. Venn diagram of significantly altered proteins (q 20%) from comparison of UC patients vs. healthy controls (HCs) and CD patients vs. HCs in the discovery cohort.

Seven markers were common between the analyses.

Fig 2. sPLS plot showing the distribution of all samples from CD patients, UC patients, and healthy controls (HCs) in the discovery cohort, based on the 20 most important proteins from the multivariate analysis.

Fig 3. sPLS plot showing the distribution of patients with ileal CD, colonic CD, and UC in the discovery cohort, based on the 20 most important proteins from the multivariate analysis.

Fig 4. Validated proteins.

Significant biomarkers (q 20%) from the discovery cohort that passed validation in the replication cohort shown with fold changes and 95% confidence intervals. Actual fold changes from the replication cohort are presented with a red dot in the graph. A: Proteins validated in CD versus HC samples. B: Validated proteins in UC versus HC samples.

Fig 5. Venn diagram of validated proteins from comparison of UC patients vs. healthy controls (HCs) and CD patients vs. HCs in the replication cohort.

Ten proteins were unique to CD and two were unique to UC.

Fig 6. Receiver operator characteristics curves (ROC) of the sparse partial least squares models applied on the replication cohort, with area under the curves (AUCs).

L2, colonic Crohn’s disease; L1/L3, ileal/ileocolonic Crohn’s disease; CD in remission, Crohn’s disease patients in clinical remission; UC in remission; ulcerative colitis patients in clinical remission.