Reasons for the Sex Bias in Osteoarthritis Research: A Review of Preclinical Studies

Madeline Franke, Chiara Mancino, Francesca Taraballi

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations


Osteoarthritis (OA) is one of the most common degenerative diseases of articular cartilage. During OA, all the elements that contribute to the joint undergo physiological and structural changes that impair the joint function and cause joint pain and stiffness. OA can arise naturally, with the aging population witnessing an increase in diagnoses of this pathology, but the root causes of OA have yet to be identified, and increasing interest is arising towards investigating biological sex as a risk factor. Clinical studies show increased prevalence and worse clinical outcomes for female patients, yet most clinical and preclinical studies have disproportionately focused on male subjects. This review provides a critical overview of preclinical practices in the context of OA, highlighting the underlying need for taking biological sex as both a risk factor and an important component affecting treatment outcome. A unique insight into the possible reasons for female underrepresentation in preclinical studies is offered, including factors such as lack of specific guidelines requiring the analysis of sex as a biological variable (SABV), research-associated costs and animal handling, and wrongful application of the reduction principle. Additionally, a thorough investigation of sex-related variables is provided, stressing how each of them could add valuable information for the understanding of OA pathophysiology, as well as sex-dependent treatment strategies.

Original languageEnglish (US)
Article number10386
JournalInternational journal of molecular sciences
Issue number12
StatePublished - Jun 20 2023


  • gender
  • gender bias
  • men
  • osteoarthritis
  • preclinical studies
  • sex
  • sex as a biological variable
  • sex difference
  • women

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry


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