Osteoarthritis (OA) drug trials fail, partly because OA is highly heterogeneous and we cannot yet identify earlier stages most likely to progress or respond to specific therapies. We will use clinical, plasma proteomic and other marker data to test whether distinct OA subgroups exist, focusing on two major life course risk events: joint injury and menopause. Acute knee injury greatly increases OA risk (post traumatic OA, PTOA). Painful OA also becomes more common in women around/after menopause (post menopausal OA), when falling sex hormone levels may influence joint tissues, inflammation, metabolism and pain, but causal pathways and high risk subgroups are unclear.
Overarching questions:
1. Do distinct OA “endotypes” or strata exist within these populations?
2. Can integration of life course event data or markers improve OA stratification?
Key objectives:
1. Earlier stage OA
-Identify “at risk” individuals (knee pain, no OA code) and define progressors vs non progressors vs true controls, using subsequent OA outcomes.
-Investigate plasma protein signatures (including those from our previous work) predicting OA progression.
-Form predictive models using clinical, protein and genetic factors.
2. Joint injury (PTOA)
-Compare proteomic profiles of PTOA, non traumatic OA and matched controls.
-Test whether injury linked markers improve prediction of earlier stage OA onset and progression.
-Establish whether PTOA reflects distinct biology or simply higher baseline risk.
3. Menopause
-Study if early/peri/postmenopausal OA shows a distinct proteomic/metabolic signature.
-Assess incidence, prevalence and relative risk of OA in women with early/sudden sex hormone loss (oophorectomy, early menopause !45 yrs, estrogen blockade) vs comparators.
-Investigate if low blood sex hormone levels are associated with OA and pain, when considering age.
Defining subgroups could enable earlier intervention with targeted, more effective OA treatments.