Background: Osteoarthritis (OA) and arthroplasty outcomes (e.g., chronic postsurgical pain [CPSP], functional limitation) are highly heterogeneous. While GWAS has identified risk loci, the downstream molecular effectors-spanning proteins and systemic metabolic states-and central nervous system (CNS) mechanisms remain obscure. We propose a “genetics-first,” multi-modal study to bridge genotype to phenotype.
Objectives:
1.Genomic Discovery: Perform GWAS and exome rare-variant burden tests for OA progression and post-arthroplasty outcomes, prioritizing receptor and ion-channel gene families (e.g., mechanoreceptors, nociceptors).
2.Molecular Mediation: Integrate UKB Pharma Proteomics (Olink) and NMR Metabolomics (Nightingale) data to decode the intermediate biology. We will identify circulating proteins and metabolic signatures (e.g., GlycA-inflammation, lipoprotein subclasses) that mediate genetic risk or drive “metabolic OA” phenotypes using Mendelian Randomization and Colocalization.
3.Brain-Joint Axis: Leverage multi-modal MRI (structural, dMRI, rs-fMRI) to define neuroimaging endotypes of “central sensitization” and explore their associations with metabolic-inflammatory profiles.
4.Translation: Construct multi-omic prediction models (incorporating PRS, proteomic/metabolomic scores, and imaging markers) for preoperative risk stratification and drug repurposing.
Methodology: We will define reproducible phenotypes using linked hospital (OPCS/ICD), primary care, and questionnaire data. Analyses involve BOLT-LMM/SAIGE for GWAS, pQTL/mQTL mapping, and causal inference pipelines to validate druggable targets.
Deliverables: We will return documented phenotype codebooks, derived variables (CPSP definitions, sensorimotor composites), PRS/burden weights, and summary statistics to UK Biobank.