P035 Potential biomarkers for diagnosis through proteomics, in patients with Inflammatory Bowel Disease
Muñoz-Villafranca, C.(1);Aresti Goiriena, U.(2);Ispizua, N.(1);Irigoyen Muñoz, M.(3);Rivera Garcia, N.A.(2);Ortiz de Zárate, J.(1);Arreba Gonzalez , P.(1);Calderón García, Á.J.(1);
(1)Hospital Universitario de Basurto, Gastroenterology, Bilbao, Spain;(2)Hospital Universitario de Basurto, Research, Bilbao, Spain;(3)Hospital Universitario Príncipe de Asturias, Internal Medicine, Alcala de Henares, Spain
Background
Currently,endoscopy,an invasive medical procedure, is the gold standard for diagnosis of inflammatory bowel disease (IBD) and to determine mucosal activity.Our main goal was to identify biomarkers in saliva samples that can be used as a screening tool for the diagnosis of ulcerative colitis(UC) and Crohn`s disease(CD).
Methods
100 saliva samples were collected from: healthy individuals(20), UC-active stage(10),UC-remission stage(31),CD-active stage(7) and CD-remission stage(32) patients. The samples were thawed on ice and centrifugated at 10,000g for 15 min at 4ºC.The supernatants were aliquoted and stored at -80ºC.
The protein extracts were digested with trypsin and peptides resulting from digestion were loaded onto a nano Acquity UPLC chromatograph and analysed in a nano Elute coupled on-line to a timsTOF Pro(Bruker).The data obtained was then processed and loaded onto the Progenesis LC-MS software (Nonlinear Dynamics) for Orbitrap data and PEAKS(Bioinformatics Solutions Inc.) for timsTOF Pro data. Finally, this information was converted to deregulation patterns at protein level and relative quantification was done.
Saliva protein levels were compared between healthy (always as control) and CD remission,UC remission,UC active and CD active stages respectively.The identification of potential biomarkers was carried out with classical statistic methods(p value<0,05 and ratio> 1,5) and data Mining mathematical model( p-value<0,05, balanced accuracy ≥ 70, sensitivity ≥ 60 and specificity ≥ 60).
Results
We have chosen the most relevant classifiers according to statistical and biological criteria, based on their biological function and the pathogenesis of UC or CD(figure 1).
We have identified 152 classifiers(biomarkers),118 single and 34 dual, defined by one or two proteins of a list of 135 proteins(table 1).The classifiers are shown for each cohort compared to healthy control:42 biomarkers were found in Active UC,16 in Remission UC, 99 in Active CD and 13 in Remission CD,all of them compared to healthy controls.
Figure1. Best threshold to separate samples from different cohorts with best accuracy(P-value cross validation< 0.05).
| Classifiers | A.UC vs H | R.UC vs H | A.CD vs H | R.CD vs H |
|---|---|---|---|---|
| Single | 33 | 6 | 91 | 4 |
| Dual | 9 | 10 | 8 | 9 |
| Total | 42 | 16 | 99 | 13 |
Table 1. Number of potential molecular classifiers identified.A.UC: Active UC; R.UC: Remission UC; A.CD: Active CD; R.CD: Remission CD
Conclusion
Multiple potential biomarkers have been identified in saliva in relation to IBD.
Biomarkers with significant value have been found for identifying and classifying UC as well as CD, compared to controls.The number of biomarkers found in CD has been higher than in UC.
The simple biomarker option(versus dual) is recommended,since its application involves fewer errors.