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Background and Aims: Diagnostic differentiation between Crohn's disease (CD) and ulcerative colitis (UC) is crucial for timely and suitable therapeutic measures. The current gold standard for differentiating between CD and UC involves endoscopy and histology, which are invasive and costly. We aimed to identify blood plasma proteomic signatures using a Protein-Wide Association Study (PWAS) approach to differentiate CD from UC and evaluate the efficacy of these signatures as features in machine learning (ML) classifiers., Methods: Among participants (n=1,106; n CD =636; n UC =470) of the Study of a Prospective Adult Research Cohort with IBD (SPARC), plasma protein (n=2,920) levels were estimated using Olink proteomics. A PWAS with Bonferroni correction for multiple testing was used to identify proteins associated with disease states after controlling for age, sex, and disease severity. ML classifiers examined the diagnostic utility of these models. Feature importance was determined via SHapley Additive exPlanations (SHAP) analysis., Results: Thirteen proteins which were significantly differentially abundant in CD vs UC (all |β|s > 0.22, all adjusted p values < 8.42E-06). Random forest models of proteins differentiated between CD and UC with models trained only on PWAS identified proteins (Average ROC-AUC 0.73) outperforming models trained of the full proteome (Average ROC-AUC 0.62). SHAP analysis revealed that Granzyme B, insulin-like peptide 5 (INSL5), and interleukin-12 subunit beta (IL-12B) were the most important features., Conclusions: Our findings demonstrate that PWAS-based feature selection approaches are a powerful method to identify features in complex, noisy datasets. Importantly, we have identified novel peptide based biomarkers such as INSL5, that can be potentially used to complement existing strategies to differentiate between CD and UC., Competing Interests: PD: has received research support under a sponsored research agreement unrelated to the data in the paper and/or consulting from AbbVie, Arena Pharmaceuticals, Boehringer Ingelheim, Bristol Myers Squibb, Janssen, Pfizer, Prometheus Biosciences, Takeda Pharmaceuticals, Roche Genentech, Scipher Medicine, Fresenius Kabi, Teva Pharmaceuticals, Landos Pharmaceuticals, Iterative scopes and CorEvitas, LLC. U.J. has received research support from Boehringer Ingelheim.

Purpose: Tumor testing for microsatellite instability and/or mismatch repair-deficiency (MSI/IHC) and clinical prediction models effectively screen for Lynch syndrome (LS)-associated colorectal cancer (CRC) and endometrial cancer (EC), but they have not been assessed for their ability to identify non-LS forms of inherited risk. The aim of this study was to compare MSI/IHC and the PREMM 5 prediction model to identify carriers of LS and non-LS pathogenic variants (PVs) among patients with CRC and EC., Patients and Methods: Data were retrospectively analyzed from two single-institution cohorts: 706 patients with CRC and/or EC referred for genetic evaluation/testing (high-risk cohort) and 1,058 consecutively ascertained patients with CRC (oncology clinic cohort), unselected for familial risk. All participants underwent germline multigene panel testing. PREMM 5 scores were calculated from personal/family cancer history. The primary outcome was the proportion of individuals with germline PVs (LS PVs, high-penetrance PVs, and any PVs) who had abnormal MSI/IHC testing and/or PREMM 5 score ≥ 2.5%., Results: MSI/IHC and PREMM 5 had comparable sensitivity for identifying LS carriers in high-risk (89.3% v 85.7%; P = .712) and oncology clinic patients (96.6% v 96.6%; P = 1.000), although MSI/IHC had significantly superior specificity for LS (81.3% v 20.1%; P < .001; 92.3% v 24.3%; P < .001). In both cohorts, PREMM 5 had superior sensitivity to MSI/IHC at identifying patients with any high-penetrance PVs and any low-, moderate-, and high-penetrance PVs. Among patients with normal MSI/IHC, PREMM 5 identified 84.2% and 83.3% of high-risk patients with CRC/EC and oncology clinic CRC patients with high-penetrance PVs, respectively., Conclusion: MSI/IHC and PREMM 5 effectively identify patients with CRC and/or EC with LS, although MSI/IHC has better specificity for LS. Because PREMM 5 identifies non-LS, high-penetrance germline PVs, patients with CRC and/or EC with PREMM 5 score ≥ 2.5%, including those with normal MSI/IHC, should be offered multigene panel testing.