Proteomic patterns of colonic mucosal tissues delineate Crohn's colitis and ulcerative colitis

Abstract

Purpose: Although Crohn's colitis (CC) and ulcerative colitis (UC) share several clinical features, they have different causes, mechanisms of tissue damage, and treatment options. Therefore, the accurate diagnosis is of paramount importance in terms of medical care. The distinction between CC/UC is made on the basis of clinical, radiologic, endoscopic, and pathologic interpretations but cannot be differentiated in up to 15% of inflammatory bowel disease patients. Correct management of this "indeterminate colitis" depends on the accuracy of future, and yet not known, destination diagnosis (CC/UC).

Experimental design: We have developed a proteomic methodology that has the potential to discriminate between UC/CC. The histologic layers of 62 confirmed UC/CC tissues were analyzed using MALDI-MS for proteomic profiling.

Results: A Support Vector Machine algorithm consisting of 25 peaks was able to differentiate spectra from CC and UC with 76.9% spectral accuracy when using a leave-20%-out cross-validation. Application of the model to the entire dataset resulted in accurate classification of 19/26 CC patients and 36/36 UC patients when using a 2/3 correct cutoff. A total of 114 peaks were found to have Wilcoxin rank sum p-values of less than 0.05.

Conclusion and clinical relevance: This information may provide new avenues for the development of novel personalized therapeutic targets.

Keywords: Colon tissue profiling; Crohn's colitis; Mass spectrometry; Ulcerative colitis.

Conflict of interest statement

Conflict of interest: The authors disclose no conflicts.

© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Figures

Figure 1

Histology-directed mass spectral protein profiling. A, A 12 μm thick tissue section is placed on a gold-coated MALDI target. B, a serial section is mounted on microscope a slide for H&E staining. C, a pathologist marks areas of interest on a photomicrograph of the H&E stained section (blow up for detail) D, the H&E picture is merged with a picture of the MALDI target and coordinates are generated. E, tissue is spotted with matrix in the designated areas using a robotic spotter. F, spectra are generated from the matrix spots corresponding to different cell types.

Figure 2

Average spectra from CC (blue) and UC (red). Insets show areas that encompass peaks that are part of the Support Vector Machine model, denoted by *. A total of 25 peaks were included in the SVM model, 7 of which (m/z 3409, 3651, 3729, 5655, 5696, 6695, and 6815) are highlighted here.

Figure 3

Graphical representation of the percentage of spectra classified correctly. CC patients are in blue and UC are in red. UC showed overall higher classification accuracy as noted by larger proportion of patients with a higher percentage of spectra correctly classified.