Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn's disease

Author:

Ungaro Ryan C.1ORCID,Hu Liangyuan2,Ji Jiayi2,Nayar Shikha3,Kugathasan Subra4,Denson Lee A.5,Hyams Jeffrey6ORCID,Dubinsky Marla C.7,Sands Bruce E.1,Cho Judy H.3

Affiliation:

1. The Henry D. Janowitz Division of Gastroenterology Icahn School of Medicine at Mount Sinai New York NY USA

2. Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai New York NY USA

3. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA

4. Department of Pediatrics Emory University School of Medicine Atlanta GA USA

5. Division of Pediatric Gastroenterology Cincinnati Children’s Hospital Medical Center Cincinnati OH USA

6. Division of Gastroenterology, Hepatology, and Nutrition Connecticut Children's Medical Center Hartford CT USA

7. Department of Pediatrics Icahn School of Medicine at Mount Sinai New York NY USA

Abstract

SummaryBackgroundThere is a need for improved risk stratification in Crohn's disease.AimTo identify novel blood protein biomarkers associated with future Crohn's disease complicationsMethodsWe performed a case‐cohort study utilising a paediatric inception cohort, the Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's disease (RISK) study. All patients had inflammatory disease (B1) at baseline. Outcomes were development of stricturing (B2) or penetrating (B3) complications. We assayed 92 inflammation‐related proteins in baseline plasma using a proximity extension assay (Olink Proteomics). An ensemble machine learning technique, random survival forests (RSF), selected variables predicting B2 and B3 complications. Selected analytes were compared to clinical variables and serology only models. We examined selected proteins in a single‐cell sequencing cohort to analyse differential cell expression in blood and ileum.ResultsWe included 265 patients with mean age 11.6 years (standard deviation [SD] 3.2). Seventy‐three and 34 patients, respectively, had B2 and B3 complications within mean 1123 (SD 477) days for B2 and 1251 (442) for B3. A model with 5 protein markers predicted B3 complications with an area under the curve (AUC) of 0.79 (95% confidence interval [CI] 0.76‐0.82) compared to 0.69 (95% CI 0.66‐0.72) for serologies and 0.74 (95% CI 0.71‐0.77) for clinical variables. A model with 4 protein markers predicted B2 complications with an AUC of 0.68 (95% CI 0.65‐0.71) compared to 0.62 (95% CI 0.59‐0.65) for serologies and 0.52 (95% CI 0.50‐0.55) for clinical variables. B2 analytes were highly expressed in ileal stromal cells while B3 analytes were prominent in peripheral blood and ileal T cells.ConclusionsWe identified novel blood proteomic markers, distinct for B2 and B3, associated with progression of paediatric Crohn's disease.

Funder

National Institutes of Health

Publisher

Wiley

Subject

Pharmacology (medical),Gastroenterology,Hepatology

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