Cervical spine pathologies-including degenerative cervical myelopathy (DCM), congenital canal stenosis, ossification of the posterior longitudinal ligament (OPLL), and cervical disc herniation-represent a major cause of disability, yet their molecular and environmental drivers remain poorly understood. While recent genome-wide association studies (GWAS) have identified susceptibility loci for spinal disorders, how genetic variation leads to downstream proteomic changes and modulates disease progression is largely unknown. Even less is known about how environmental factors interact with genetic and proteomic variation to influence risk.
This project aims to define the biological architecture of cervical spine disease by integrating genomic, exposomic, and proteomic data from the UK Biobank. We will: (1) perform GWAS and transcriptome-wide association studies (TWAS) of cervical spine phenotypes from diagnostic codes, surgical history, and imaging; (2) conduct environment-wide association studies (ExWAS) to identify relevant lifestyle and environmental exposures; and (3) leverage plasma proteomics data (Sun et al., 2022) to identify pQTLs and circulating biomarkers that mediate genetic risk.
Using integrative multi-omic methods-including Mendelian randomization, colocalization, and mediation analysis-we aim to uncover causal pathways linking genetic risk, environmental exposures, and proteins to cervical spine disease. Subgroup analyses will target DCM, OPLL, and canal stenosis to define shared and distinct mechanisms. In addition to discovery analyses, we will validate proteins already implicated in spinal pathology, including those involved in bone metabolism (e.g., SOST, TNFRSF11B), ECM remodeling (e.g., MMPs, TIMP1), and inflammation (e.g., IL6R, CRP).
This study will be among the first to map genome-exposome-proteome interactions in cervical spine disease and offers a scalable framework applicable to other spinal conditions.