Serum proteomic panel validated for prediction of knee osteoarthritis progression.

Cartilage Osteoarthritis Progression Proteomics Serum

Journal

Osteoarthritis and cartilage open
ISSN: 2665-9131
Titre abrégé: Osteoarthr Cartil Open
Pays: England
ID NLM: 101767068

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 18 07 2023
accepted: 01 12 2023
medline: 20 12 2023
pubmed: 20 12 2023
entrez: 20 12 2023
Statut: epublish

Résumé

To further validate a serum proteomics panel for predicting radiographic (structural) knee OA progression. Serum peptides were targeted by multiple-reaction-monitoring mass spectrometry in the New York University cohort (n ​= ​104). Knee OA progression was defined as joint space narrowing ≥1 in the tibiofemoral compartment of one knee per study participant over a 24-month follow-up. The discriminative ability of an 11-peptide panel was evaluated by multivariable logistic regression and area under the receiver operating characteristic curve (AUC), without and with demographic characteristics of age, sex, and body mass index. The association of each peptide with OA progression was assessed by odds ratios (OR) in multivariable logistic regression models adjusted for demographics. The cohort included 46 (44%) knee OA progressors. The panel of 11 peptides alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]) for discriminating progressors from non-progressors; demographic traits alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]). Together the 11 peptides and demographics yielded AUC ​= ​0.72 (95% CI [0.62, 0.83]). CRAC1 had the highest odds for predicting OA progression (OR 2.014, 95% CI [0.996, 4.296], p ​= ​0.058). We evaluated a parsimonious serum proteomic panel and found it to be a good discriminator of knee radiographic OA progression from non-progression. Since these biomarkers are quantifiable in serum, they could be deployed relatively easily to provide a simple, cost-effective strategy for identifying and monitoring individuals at high risk of knee OA progression.

Identifiants

pubmed: 38116469
doi: 10.1016/j.ocarto.2023.100425
pii: S2665-9131(23)00092-4
pmc: PMC10726242
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100425

Informations de copyright

© 2023 The Author(s).

Auteurs

Virginia Byers Kraus (VB)

Duke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Department of Medicine, Duke University School of Medicine, Durham, NC, USA.

Alexander Reed (A)

Duke Molecular Physiology Institute, Duke University, Durham, NC, USA.

Erik J Soderblom (EJ)

Duke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.

M Arthur Moseley (MA)

Duke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.

Ming-Feng Hsueh (MF)

Duke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Department of Orthopaedic Surgery, Duke University, Durham, NC, USA.

Mukundun G Attur (MG)

Division of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.

Jonathan Samuels (J)

Division of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.

Steven B Abramson (SB)

Division of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.

Yi-Ju Li (YJ)

Duke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.

Classifications MeSH