Study Design: Longitudinal study of spine magnetic resonance imaging (MRI) in a large-scale population-based study.
Objective: To determine the order of appearance of degenerative change in vertebral bodies and intervertebral discs. We also sought to define the influence of endplate defect on low back pain (LBP) and to determine whether there is a genetic influence on endplate defect.
Summary Of Background Data: Endplate defect is a magnetic resonance imaging trait, found to be associated with intervertebral disc degeneration. There is a lack of understanding regarding the mechanism underlying lumbar disc degeneration (LDD). Recent attention has shifted to vertebral endplate defects and their role in spine degeneration pathology.
Methods: Individuals from the TwinsUK spine study having longitudinal T2-weighted lumbar MR scans at baseline (n = 996) and a decade later (n = 438) were included. LDD, vertebral endplate defect by calculating a total endplate score, and Modic change (MC) were assessed using standard techniques. Mixed-effects models were used to determine the association between the features of spine pathology, adjusted for covariates. Endplate defect heritability was estimated using variance component analysis.
Results: Significant association was found between endplate defect, LDD, MRI features of LDD and MC was observed. Endplate defect was associated with severe disabling LBP (P ≤ 0.013) in multivariate analysis. An association between disc degeneration (DD) at baseline and MC at follow-up was shown at upper lumbar levels. Total endplate score was heritable with estimated additive genetic component A = 55.3% (95% CI 43.0-65.4).
Conclusion: Endplate defect, LDD, and MC are all independent risk factors for episodes of severe and disabling LBP. Longitudinal analysis showed DD is followed by MC. Endplate defect has significant heritability of 55%. However, whether endplate defect triggers DD or these pathological changes occur concurrently could not be conclusively determined.
Level Of Evidence: 2.
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http://dx.doi.org/10.1097/BRS.0000000000002721 | DOI Listing |
N Am Spine Soc J
December 2024
Department of Information Engineering, University of Brescia, via Branze 38, Brescia 25123, Italy.
Background: In recent years, the integration of Artificial Intelligence (AI) models has revolutionized the diagnosis of Low Back Pain (LBP) and associated disc pathologies. Among these, SpineNetV2 stands out as a state-of-the-art, open-access model for detecting and grading various intervertebral disc pathologies. However, ensuring the reliability and applicability of AI models like SpineNetV2 is paramount.
View Article and Find Full Text PDFNeuromuscul Disord
December 2024
INMG-PGNM, UMR CNRS 5261 - INSERM U1315, Université Lyon 1, Lyon, France; Centre de Biotechnologie Cellulaire, Hospices Civils De Lyon, Lyon, France.
Skelet Muscle
October 2024
Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.
Background: Amyotrophic lateral sclerosis (ALS) is a devastating and incurable neurodegenerative disease. Accumulating evidence strongly suggests that intrinsic muscle defects exist and contribute to disease progression, including imbalances in whole-body metabolic homeostasis. We have previously reported that tumour necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) and fibroblast growth factor inducible 14 (Fn14) are significantly upregulated in skeletal muscle of the SOD1 ALS mouse model.
View Article and Find Full Text PDFVet Radiol Ultrasound
September 2024
Division of Diagnostic Imaging, Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht, The Netherlands.
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