Article

P018 Proteomic profile of serum and urine in newly diagnosed patients with Inflammatory Bowel Disease: new approach for biomarker discovery

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Abstract

Background Currently, endoscopy is the gold standard for the evaluation of disease activity and inflammation in clinical practice. However, it is an invasive procedure for the patient, costly and time-consuming. Therefore, there is an urgent need to identify non-invasive biomarkers with the potential clinical utility to diagnose inflammatory bowel disease (IBD) patients, improve the patient′s quality of life and increase efficiency in the Health Systems. Methods A label-free quantitative proteomics method was used to profile the urinary and serum proteomes of 100 patients with newly diagnosed IBD, before starting any treatment [50 patients with Crohn′s disease (CD) and 50 patients with ulcerative colitis (UC)] and 50 healthy controls (HC). The resulting peptides were separated by NanoLC (EVOSEP ONE) and coupled online by electrospray to Trapped Ion Mobility Spectrometry (TIMS) TOF Pro for tandem mass spectrometry analysis. Mass spectrometry data were processed and analyzed with MaxQuant and Perseus software. Proteins with p≤0.05 and ratio>1.5 in any sense, were considered as significantly dysregulated. Bioinformatic analysis of differentially expressed proteins was performed to characterize involved biological processes, molecular functions, cell locations and proteins pathways (PANTHER and STRING v11.5). Results A total of 2,500 proteins were identified in the urine, and 468 proteins were identified in the serum with at least two different peptides at FDR<1%. Of the urine proteins, 110 were significantly changed in UC versus HC, 50 proteins were differentially expressed between CD and HC, and a total of 31 proteins were significantly changed in CD compared with UC patients (Figure 1). In serum samples, a total of 45 differentially expressed proteins were identified in the comparison between UC and HC groups, 32 proteins significantly expressed in CD versus HC, and 12 proteins in CD compared with UC (Figure 2). Finally, biological information analysis was performed according to these differential proteins. The molecular functions, biological processes, and pathways enriched mainly involved the neutrophil degranulation, complement and coagulation cascades and immune system responses (Figures 3 and 4). Conclusion Proteome profiling revealed significantly differences in newly diagnosed patients with CD or UC. Both serum and urine seem to be appropriate biological matrixes for this approach. Next steps of our research will be to understand the role of candidate proteins as well as to validate those with potential as biomarkers in independent cohort.

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Introduction: Ulcerative colitis (UC) is a chronic illness requiring lifelong management that could be enhanced by personalizing care using biomarkers. Areas covered: The main biomarker discovery modalities are reviewed, highlighting recent results across the spectrum of applications, including diagnostics (serum anti-αvβ6 antibodies achieving an area under the curve [AUC] = 0.99; serum oncostatin M AUC = 0.94), disease activity assessment (fecal calprotectin and serum trefoil factor 3: AUC > 0.90), prognostication of the need for treatment escalation (whole blood transcriptomic panels and CLEC5A/CDH2 ratio: AUC > 0.90), prediction of treatment response, and early identification of patients with subclinical disease. The use of established biomarkers is discussed, along with new evidence regarding autoantibodies, proteins, proteomic panels, transcriptomic signatures, deoxyribonucleic acid methylation patterns, and UC-specific glycomic and metabolic disturbances. Expert opinion: Novel biomarkers will pave the way for optimized UC care. However, validation, simplification, and direct clinical translation of complex models may prove challenging. Currently, few candidates exist to assess key characteristics, such as UC susceptibility, histological disease activity, drug response, and long-term disease behavior. Further research will likely not only reveal new tools to tackle these issues but also contribute to understanding UC pathogenesis mechanisms.
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