MicroRNA signature for early prediction of knee osteoarthritis structural progression using integrated machine and deep learning approaches.

Journal: Osteoarthritis and cartilage
Published Date: Nov 29, 2024

Abstract

OBJECTIVE: Conventional methodologies are ineffective in predicting the rapid progression of knee osteoarthritis (OA). MicroRNAs (miRNAs) show promise as biomarkers for patient stratification. We aimed to develop a miRNA prognosis model for identifying knee OA structural progressors/non-progressors using integrated machine/deep learning tools.

Authors

  • Afshin Jamshidi
    Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada.
  • Osvaldo Espin-Garcia
    Department of Biostatistics, Schroeder Arthritis Institute and Krembil Research Institute, University Health Network, Toronto, Canada; Dalla Lana School of Public Health and Department of Statistical Sciences, University of Toronto, Toronto, Canada; Department of Epidemiology and Biostatistics, University of Western Ontario, London, Canada, Toronto, Canada. Electronic address: oespinga@uwo.ca.
  • Thomas G Wilson
    Henry Ford Health + Michigan State University Health Sciences, Detroit, USA. Electronic address: twilso20@hfhs.org.
  • Ian Loveless
    Henry Ford Health + Michigan State University Health Sciences, Detroit, USA. Electronic address: ilovele1@hfhs.org.
  • Jean-Pierre Pelletier
    Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada.
  • Johanne Martel-Pelletier
    Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada. jm@martelpelletier.ca.
  • Shabana Amanda Ali
    Henry Ford Health + Michigan State University Health Sciences, Detroit, USA; Center for Molecular Medicine and Genetics, Wayne State University, Detroit, USA. Electronic address: sali14@hfhs.org.

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