Aging of the Spine: Characterizing genetic and physiological determinants of spinal curvature

Abstract

AbstractIncreased spinal curvature is one of the most recognizable aging traits in the human population. However, despite high prevalence, the etiology of this condition remains poorly understood. To gain better insight into the physiological, biochemical, and genetic risk factors involved, we developed a novel machine learning method to automatically derive thoracic kyphosis and lumbar lordosis angles from dual-energy X-ray absorptiometry (DXA) scans in the UK Biobank Imaging cohort. In 41,212 participants, we find that on average males and females gain 2.42° kyphotic and 1.48° lordotic angle per decade of life. Increased spinal curvature was strongly associated with decreased muscle mass and bone mineral density. Adiposity had opposing associations, with decreased kyphosis and increased lordosis. To gain further insight into the molecular mechanisms involved, we carried out a genome-wide association study and identified several risk loci associated with both traits. Using Mendelian randomization, we further show that genes fundamental to the maintenance of musculoskeletal function (COL11A1, PTHLH, ETFA, TWIST1) and cellular homeostasis such as RNA transcription and DNA repair (RAD9A, MMS22L, HIF1A, RAB28) are likely involved in increased spinal curvature.