No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIACitation formats

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  • Childhood Arthritis Prospective Study (CAPS) Group

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No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA. / Childhood Arthritis Prospective Study (CAPS) Group.

In: Rheumatology (Oxford, England), 07.01.2022.

Research output: Contribution to journalArticlepeer-review

Harvard

Childhood Arthritis Prospective Study (CAPS) Group 2022, 'No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA', Rheumatology (Oxford, England). https://doi.org/10.1093/rheumatology/keab942

APA

Childhood Arthritis Prospective Study (CAPS) Group (2022). No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA. Rheumatology (Oxford, England), [keab942]. https://doi.org/10.1093/rheumatology/keab942

Vancouver

Childhood Arthritis Prospective Study (CAPS) Group. No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA. Rheumatology (Oxford, England). 2022 Jan 7. keab942. https://doi.org/10.1093/rheumatology/keab942

Author

Childhood Arthritis Prospective Study (CAPS) Group. / No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA. In: Rheumatology (Oxford, England). 2022.

Bibtex

@article{90422656225f4611b0511c64e8fb7f87,
title = "No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA",
abstract = "OBJECTIVES: The clinical progression of juvenile idiopathic arthritis (JIA) is unpredictable. Knowing who will develop severe disease could facilitate rapid intensification of therapies. We use genetic variants conferring susceptibility to JIA to predict disease outcome measures.METHODS: Seven hundred and thirteen JIA patients with genotype data and core outcome variables (COVs) at diagnosis (baseline) and 1 year follow up were identified from the Childhood Arthritis Prospective Study (CAPS). A weighted genetic risk score (GRS) was generated, including all SNPs previously associated with JIA susceptibility (p-value < 5x10-08). We used multivariable linear regression to test the GRS for association with COVS (limited joint count, active joint count, physician global assessment, parent/patient general evaluation, childhood health assessment questionnaire and ESR) at baseline and change in COVS from baseline to 1 year, adjusting for baseline COV and ILAR category. The GRS was split into quintiles to identify high (quintile 5) and low (quintile 1) risk groups.RESULTS: Patients in the high-risk group for the GRS had a younger age at presentation (median low risk 7.79, median high risk 3.51). No association was observed between the GRS and any outcome measures at 1 year follow up or baseline.CONCLUSION: For the first time we have used all known JIA genetic susceptibility loci (p = <5x10-08) in a GRS to predict changes in disease outcome measured over time. Genetic susceptibility variants are poor predictors of changes in core outcome measures, it is likely that genetic factors predicting disease outcome are independent to those predicting susceptibility. The next step will be to conduct a genome-wide association analysis of JIA outcome.",
author = "{Childhood Arthritis Prospective Study (CAPS) Group} and Annie Yarwood and Stephanie Shoop-Worrall and Elena Lopez-Isac and Smith, {Samantha Louise} and Morris, {Andrew P} and Bowes, {John David} and Melissa Tordoff and Hyrich, {Kimme L} and Wendy Thomson and Stephen Eyre",
note = "{\textcopyright} The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.",
year = "2022",
month = jan,
day = "7",
doi = "10.1093/rheumatology/keab942",
language = "English",
journal = "Rheumatology (Print)",
issn = "1462-0324",
publisher = "Oxford University Press",

}

RIS

TY - JOUR

T1 - No evidence that genetic predictors of susceptibility predict changes in core outcomes in JIA

AU - Childhood Arthritis Prospective Study (CAPS) Group

AU - Yarwood, Annie

AU - Shoop-Worrall, Stephanie

AU - Lopez-Isac, Elena

AU - Smith, Samantha Louise

AU - Morris, Andrew P

AU - Bowes, John David

AU - Tordoff, Melissa

AU - Hyrich, Kimme L

AU - Thomson, Wendy

AU - Eyre, Stephen

N1 - © The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.

PY - 2022/1/7

Y1 - 2022/1/7

N2 - OBJECTIVES: The clinical progression of juvenile idiopathic arthritis (JIA) is unpredictable. Knowing who will develop severe disease could facilitate rapid intensification of therapies. We use genetic variants conferring susceptibility to JIA to predict disease outcome measures.METHODS: Seven hundred and thirteen JIA patients with genotype data and core outcome variables (COVs) at diagnosis (baseline) and 1 year follow up were identified from the Childhood Arthritis Prospective Study (CAPS). A weighted genetic risk score (GRS) was generated, including all SNPs previously associated with JIA susceptibility (p-value < 5x10-08). We used multivariable linear regression to test the GRS for association with COVS (limited joint count, active joint count, physician global assessment, parent/patient general evaluation, childhood health assessment questionnaire and ESR) at baseline and change in COVS from baseline to 1 year, adjusting for baseline COV and ILAR category. The GRS was split into quintiles to identify high (quintile 5) and low (quintile 1) risk groups.RESULTS: Patients in the high-risk group for the GRS had a younger age at presentation (median low risk 7.79, median high risk 3.51). No association was observed between the GRS and any outcome measures at 1 year follow up or baseline.CONCLUSION: For the first time we have used all known JIA genetic susceptibility loci (p = <5x10-08) in a GRS to predict changes in disease outcome measured over time. Genetic susceptibility variants are poor predictors of changes in core outcome measures, it is likely that genetic factors predicting disease outcome are independent to those predicting susceptibility. The next step will be to conduct a genome-wide association analysis of JIA outcome.

AB - OBJECTIVES: The clinical progression of juvenile idiopathic arthritis (JIA) is unpredictable. Knowing who will develop severe disease could facilitate rapid intensification of therapies. We use genetic variants conferring susceptibility to JIA to predict disease outcome measures.METHODS: Seven hundred and thirteen JIA patients with genotype data and core outcome variables (COVs) at diagnosis (baseline) and 1 year follow up were identified from the Childhood Arthritis Prospective Study (CAPS). A weighted genetic risk score (GRS) was generated, including all SNPs previously associated with JIA susceptibility (p-value < 5x10-08). We used multivariable linear regression to test the GRS for association with COVS (limited joint count, active joint count, physician global assessment, parent/patient general evaluation, childhood health assessment questionnaire and ESR) at baseline and change in COVS from baseline to 1 year, adjusting for baseline COV and ILAR category. The GRS was split into quintiles to identify high (quintile 5) and low (quintile 1) risk groups.RESULTS: Patients in the high-risk group for the GRS had a younger age at presentation (median low risk 7.79, median high risk 3.51). No association was observed between the GRS and any outcome measures at 1 year follow up or baseline.CONCLUSION: For the first time we have used all known JIA genetic susceptibility loci (p = <5x10-08) in a GRS to predict changes in disease outcome measured over time. Genetic susceptibility variants are poor predictors of changes in core outcome measures, it is likely that genetic factors predicting disease outcome are independent to those predicting susceptibility. The next step will be to conduct a genome-wide association analysis of JIA outcome.

U2 - 10.1093/rheumatology/keab942

DO - 10.1093/rheumatology/keab942

M3 - Article

C2 - 35015833

JO - Rheumatology (Print)

JF - Rheumatology (Print)

SN - 1462-0324

M1 - keab942

ER -