Intervertebral disc degeneration (DD) is a complex age-related condition that constitutes the main risk factor for disabling back pain. DD is assessed using different traits extracted from MR imaging (MRI), normally combined to give summary measures (e.g. Pfirmann score). The aetiology of DD is poorly understood and despite its high heritability (75%), the precise genetic predisposition is yet to be defined. Genome wide association study (GWAS) is used to discover genetic variants associated with a disease or phenotype. It tests variants across the whole genome. It requires large samples to provide adequate but unfortunately there is poor availability of spine imaging data due to the high cost of MRI. We have adopted new methods to examine different MRI traits independently and use the information of those traits to boost GWAS power using specialized statistical software for jointly analyse correlated traits. We examined DD MRI features disc narrowing, disc bulge, disc signal intensity and osteophyte formation in the TwinsUK cohort who had undergone T2-weighted sagittal spine MRI. GWAS were performed on the four traits. MTAG software was used to boost single trait GWAS power using the information in the other trait GWAS. 9 different loci were identified.Background
Methods/Results
