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Prediction of Crohn’s disease stricturing phenotype using a NOD2-derived genomic biomarker

Prediction of Crohn’s disease stricturing phenotype using a NOD2-derived genomic biomarker
Prediction of Crohn’s disease stricturing phenotype using a NOD2-derived genomic biomarker
Background
Crohn’s disease (CD) is highly heterogenous and may be complicated by stricturing behavior. Personalized prediction of stricturing will inform management. We aimed to create a stricturing risk stratification model using genomic/clinical data.

Methods
Exome sequencing was performed on CD patients, and phenotype data retrieved. Biallelic variants in NOD2 were identified. NOD2 was converted into a per-patient deleteriousness metric (“GenePy”). Using training data, patients were stratified into risk groups for fibrotic stricturing using NOD2. Findings were validated in a testing data set. Models were modified to include disease location at diagnosis. Cox proportional hazards assessed performance.

Results
Six hundred forty-five patients were included (373 children and 272 adults); 48 patients fulfilled criteria for monogenic NOD2-related disease (7.4%), 24 of whom had strictures. NOD2 GenePy scores stratified patients in training data into 2 risk groups. Within testing data, 30 of 161 patients (18.6%) were classified as high-risk based on the NOD2 biomarker, with stricturing in 17 of 30 (56.7%). In the low-risk group, 28 of 131 (21.4%) had stricturing behavior. Cox proportional hazards using the NOD2 risk groups demonstrated a hazard ratio (HR) of 2.092 (P = 2.4 × 10-5), between risk groups. Limiting analysis to patients diagnosed aged < 18-years improved performance (HR-3.164, P = 1 × 10-6). Models were modified to include disease location, such as terminal ileal (TI) disease or not. Inclusion of NOD2 risk groups added significant additional utility to prediction models. High-risk group pediatric patients presenting with TI disease had a HR of 4.89 (P = 2.3 × 10-5) compared with the low-risk group patients without TI disease.

Conclusions
A NOD2 genomic biomarker predicts stricturing risk, with prognostic power improved in pediatric-onset CD. Implementation into a clinical setting can help personalize management.
1536-4844
Ashton, James
03369017-99b5-40ae-9a43-14c98516f37d
Cheng, Guo
fdfb3e03-f185-49b1-9c53-05b93bb6c8d0
Stafford, Imogen S.
50987dc1-3772-408f-9093-9124f3d6b2cd
Kellermann, M.
e4cc843f-d5a5-4ec2-be22-1c83c9a46102
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
Fraser Cummings, J.R.
94314d88-1c39-44bc-82f8-e074a83a41d6
Coelho, Tracy
a78b627c-ea78-41e1-9553-0390921e3c93
Batra, Akshay
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Afzal, Nadeem A.
62505946-2503-42ba-9b02-85513bb3ec87
Beattie, R. Mark
55d81c7b-08c9-4f42-b6d3-245869badb71
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9
Ashton, James
03369017-99b5-40ae-9a43-14c98516f37d
Cheng, Guo
fdfb3e03-f185-49b1-9c53-05b93bb6c8d0
Stafford, Imogen S.
50987dc1-3772-408f-9093-9124f3d6b2cd
Kellermann, M.
e4cc843f-d5a5-4ec2-be22-1c83c9a46102
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
Fraser Cummings, J.R.
94314d88-1c39-44bc-82f8-e074a83a41d6
Coelho, Tracy
a78b627c-ea78-41e1-9553-0390921e3c93
Batra, Akshay
822f891e-87ca-41d9-b68d-27c395e88809
Afzal, Nadeem A.
62505946-2503-42ba-9b02-85513bb3ec87
Beattie, R. Mark
55d81c7b-08c9-4f42-b6d3-245869badb71
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9

Ashton, James, Cheng, Guo, Stafford, Imogen S., Kellermann, M., Seaby, Eleanor, Fraser Cummings, J.R., Coelho, Tracy, Batra, Akshay, Afzal, Nadeem A., Beattie, R. Mark and Ennis, Sarah (2022) Prediction of Crohn’s disease stricturing phenotype using a NOD2-derived genomic biomarker. Inflammatory Bowel Diseases. (doi:10.1093/ibd/izac205).

Record type: Article

Abstract

Background
Crohn’s disease (CD) is highly heterogenous and may be complicated by stricturing behavior. Personalized prediction of stricturing will inform management. We aimed to create a stricturing risk stratification model using genomic/clinical data.

Methods
Exome sequencing was performed on CD patients, and phenotype data retrieved. Biallelic variants in NOD2 were identified. NOD2 was converted into a per-patient deleteriousness metric (“GenePy”). Using training data, patients were stratified into risk groups for fibrotic stricturing using NOD2. Findings were validated in a testing data set. Models were modified to include disease location at diagnosis. Cox proportional hazards assessed performance.

Results
Six hundred forty-five patients were included (373 children and 272 adults); 48 patients fulfilled criteria for monogenic NOD2-related disease (7.4%), 24 of whom had strictures. NOD2 GenePy scores stratified patients in training data into 2 risk groups. Within testing data, 30 of 161 patients (18.6%) were classified as high-risk based on the NOD2 biomarker, with stricturing in 17 of 30 (56.7%). In the low-risk group, 28 of 131 (21.4%) had stricturing behavior. Cox proportional hazards using the NOD2 risk groups demonstrated a hazard ratio (HR) of 2.092 (P = 2.4 × 10-5), between risk groups. Limiting analysis to patients diagnosed aged < 18-years improved performance (HR-3.164, P = 1 × 10-6). Models were modified to include disease location, such as terminal ileal (TI) disease or not. Inclusion of NOD2 risk groups added significant additional utility to prediction models. High-risk group pediatric patients presenting with TI disease had a HR of 4.89 (P = 2.3 × 10-5) compared with the low-risk group patients without TI disease.

Conclusions
A NOD2 genomic biomarker predicts stricturing risk, with prognostic power improved in pediatric-onset CD. Implementation into a clinical setting can help personalize management.

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Accepted/In Press date: 2 September 2022
Published date: 26 September 2022

Identifiers

Local EPrints ID: 469900
URI: http://eprints.soton.ac.uk/id/eprint/469900
ISSN: 1536-4844
PURE UUID: caca3eaf-3564-4291-a0dd-a74048b0c801
ORCID for James Ashton: ORCID iD orcid.org/0000-0003-0348-8198
ORCID for Eleanor Seaby: ORCID iD orcid.org/0000-0002-6814-8648
ORCID for Sarah Ennis: ORCID iD orcid.org/0000-0003-2648-0869

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Date deposited: 28 Sep 2022 16:41
Last modified: 29 Sep 2022 02:00

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Contributors

Author: James Ashton ORCID iD
Author: Guo Cheng
Author: Imogen S. Stafford
Author: M. Kellermann
Author: Eleanor Seaby ORCID iD
Author: J.R. Fraser Cummings
Author: Tracy Coelho
Author: Akshay Batra
Author: Nadeem A. Afzal
Author: R. Mark Beattie
Author: Sarah Ennis ORCID iD

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