Non-Invasive Diagnosis of Crohn's Disease Using Surface-Enhanced Raman Spectroscopy

Background: Crohn’s disease (CD) is an idiopathic chronic inflammatory bowel disease without a cure. Most of the CD patients are firstly diagnosed by invasive endoscopy, clinical and pathological examination are further required to confirm the diagnosis. Hence, development of a non-invasive, rapid and accurate diagnosis method for CD patients is essential. Methods: In this study, the urine samples from 95 CD patients (including 58 active CD (aCD) patients and 37 inactive CD (iCD) patients) and 48 healthy controls (HC) were investigated by surface-enhanced Raman spectroscopy (SERS). Statistical analysis of three different groups (i.e., CD/HC, aCD/HC and iCD/HC) were performed on the measured data. Principal component analysis (PCA)-support vector machine (SVM) and PCA-linear discriminant analysis (LDA) were then employed to establish classification models to distinguish patients and HC. Findings: For the average SERS spectra of patients and HC, the Raman peaks belonging to lipids, proteins and nucleic acid were stronger in patients than HC. It showed that the classification accuracy of CD/HC based on PCA-SVM was higher than PCA-LDA (82.5% vs 69.9%). And the classification model we established was able to distinguish aCD and HC with 86.2% sensitivity, 86.8% accuracy and 87.5% specificity. Interpretation: Our findings are helpful for clinicians to diagnose CD patients, and monitor progress and recurrence of the disease. Funding: This study was supported by the National Natural Science Foundation of China (No.81670476, 82000481, 51676130), the Natural Science Foundation of Shanghai (No.20ZR1438900). Declaration of Interests: The authors have declared that no competing interest exists. Ethics Approval Statement: This study was approved by the Institutional Ethics Committee of the Tenth People's Hospital of Tongji University, Shanghai, China (SHSY-IEC-4.1 /20-40/01).