Unlocking Osteoarthritis: Transcriptomic and Functional Analysis of Novel Osteoarthritis Effector Genes

Osteoarthritis is a leading cause of disability and chronic pain worldwide, with incidence rising sharply in ageing populations. As life expectancy increases, osteoarthritis imposes a growing socioeconomic and healthcare burden. Although osteoarthritis has a substantial heritable component, and genome-wide association studies (GWAS) have identified numerous associated loci, the functional mechanisms through which these genetic variants contribute to disease remain poorly understood. This knowledge gap hinders the development of effective disease-modifying therapies. My aim is to address this through focused functional investigations of novel osteoarthritis candidate genes identified through a machine learning framework. This integrative approach combines skeletal tissue transcriptomic data, curated literature evidence, and protein–protein interaction networks to prioritise genes based on their putative roles in osteoarthritis pathogenesis. Selection of candidate genes was further refined by their proximity to knee osteoarthritis risk variants identified by GWAS. Many of these candidates remain untested or under-characterised in osteoarthritis-relevant models. Objective 1 will evaluate the biological impact of 20 prioritised genes using CRISPR-Cas9-mediated knockout and lentiviral overexpression in primary human articular chondrocytes (HACs) derived from knee osteoarthritis arthroplasty tissue. I will generate 3D pellet cultures to model cartilage physiology and perform RNA sequencing to identify perturbation-induced changes in pathways relevant to cartilage homeostasis, matrix turnover, and inflammation. Objective 2 will focus on 3–5 candidates from Objective 1 that exhibit the most robust transcriptomic alterations. These genes will undergo in-depth functional characterisation, including assessment of extracellular matrix production, inflammatory mediator secretion, and context-specific assays — such as target gene profiling for transcription factors or signalling pathway analyses. These studies will be performed in HACs and, where appropriate, in other joint-resident cell types such as synoviocytes or osteoblasts to capture broader tissue-specific effects. Objective 3 will investigate the in-vivo role of the top candidate using conditional or global knockout mouse models. Osteoarthritis will be induced via anterior cruciate ligament (ACL) rupture, a well-established non-surgical model that mimics post-traumatic joint degeneration and demonstrates robust overlap with osteoarthritis pathogenesis. Disease progression will be assessed using histological scoring of joint pathology, matrix loss, and behavioural measures of pain and mobility. Together, this project will generate new mechanistic insight into the roles of under-characterised genes in osteoarthritis pathogenesis. By linking genetic risk to functional outcomes across in-vitro and in-vivo models, this work will help prioritise targets for therapeutic development and improve our understanding of molecular processes driving age-related joint degeneration. The proposed research directly aligns with the Vivensa Foundation’s mission to support healthy ageing and musculoskeletal health. By addressing a fundamental barrier to progress in osteoarthritis — the lack of functional insight into genetic risk — I aim to contribute to the long-term goal of developing targeted therapies that slow or prevent disease progression, ultimately supporting longer, healthier lives.