Characterizing aging-related genetic and physiological determinants of spinal curvature

Frances M Wang; J Graham Ruby; Anurag Sethi; Matthew A Veras; Natalie Telis; Eugene Melamud

doi:10.1038/s43856-025-01003-5

Characterizing aging-related genetic and physiological determinants of spinal curvature

Commun Med (Lond). 2025 Jul 12;5(1):291. doi: 10.1038/s43856-025-01003-5.

Authors

Frances M Wang¹, J Graham Ruby¹, Anurag Sethi¹, Matthew A Veras¹, Natalie Telis¹, Eugene Melamud²

Affiliations

¹ Calico Life Sciences LLC, South San Francisco, California, USA.
² Calico Life Sciences LLC, South San Francisco, California, USA. eugene@calicolabs.com.

PMID: 40652108
DOI: 10.1038/s43856-025-01003-5

Abstract

Background: Increased 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.

Methods: 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. We carry out genome-wide association and epidemiological association studies to identify genetic and physiological risk factors for both traits.

Results: In 41,212 participants, we find that on average males and females gain 2.42° in kyphotic and 1.48° in lordotic angle per decade of life. Increased spinal curvature shows a strong association with decreased muscle mass and bone mineral density. Adiposity demonstrates opposing associations, with decreased kyphosis and increased lordosis. Using Mendelian randomization, we 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.

Conclusions: Our findings reveal a complex interplay between genetics, musculoskeletal health, and age-related changes in spinal curvature, suggesting potential drivers of this universal aging trait.

Plain language summary

In our study, we investigated how spinal curvature changes with age, and the underlying factors contributing to this phenomenon. We developed a machine learning model to precisely measure upper spine (kyphotic) and lower spine (lordotic) angles from X-ray scans. We observed a clear age-related increase in both angles, with sex-specific differences. Our analysis revealed significant associations with fat composition and musculoskeletal traits. Lower muscle mass and bone density was correlated with greater curvature. Through genetic analysis, we also identified several genes influencing spinal curvature. Our findings suggest a complex interaction between aging, physiology, and genetics in shaping spinal curvature, with potential implications for preventive and therapeutic strategies.