Osteoarthritis (OA) is the most common joint disease in the elderly, with hip OA causing severe pain and limiting mobility. The diagnosis of hip OA is based on clinical symptoms and radiographic analysis. However, radiographic changes can only be identified when the disease is already progressed, that is once articular cartilage and bone have already been damaged. Current treatment for OA is limited to pain management and hip replacement for end stage joint degeneration. Thus, identifying genetic loci responsible for increasing susceptibility to hip OA may benefit early diagnosis and the development of new treatment options.
Recent research has shown that hip joint shape influences susceptibility to the development and progression of hip OA. The identification of loci that influence hip joint morphology may thus also indicate loci contributing to OA susceptibility. Statistical models of shape and appearance will be utilised to capture the variation in hip joint morphology. To achieve this, a set of 2D pelvic radiographs showing both OA affected and OA unaffected hip joints will be analysed. Based on the results of shape and appearance modelling, a series of quantitative traits capturing the shape and appearance variation of OA-affected hip joints will be derived. A genome-wide QTL association study analysis will then be performed to identify the loci that account for these traits and hence for hip OA susceptibility.