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Biomarker clusters differentiate phenotypes of lumbar spine degeneration and low back pain: The Johnston County Osteoarthritis Project.
Osteoarthritis and cartilage open. 2022 September
Objective: Describe the association between biomarkers and lumbar spine degeneration (vertebral osteophytes [OST], facet joint osteoarthritis [FOA], and disc space narrowing [DSN]), for persons with and without low back pain (LBP) and determine whether clusters based on biomarkers differentiate lumbar spine structure with and without LBP.
Methods: Using data from the Johnston County Osteoarthritis Project (2006-2010), we measured serum N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, HA, IL-6, BDNF, OPG, and NPY, and urinary CTX-II. Biomarkers were used to group participants using k-means cluster analysis. Logistic regression models were used to compare biomarker clusters.
Results: The sample consisted of 731 participants with biospecimens and lumbar spine radiographic data. Three biomarker subgroups were identified: one characterized by structural degenerative changes; another characterized by structural degenerative changes and inflammation, with pain; and a referent cluster with lower levels of biomarkers, pain, and structural degenerative changes. Compared to the referent subgroup, the structural change subgroup was associated with DSN (OR = 1.94, 95% CI 1.30-2.90) and FOA (OR = 1.72, 95% CI 1.12-2.62), and the subgroup with structural degenerative change, inflammation, and pain was associated with OST with LBP (OR = 1.60, 95% CI 1.04-2.46), FOA with LBP (OR = 1.59, 95% CI 1.04-2.45), and LBP (OR = 1.63, 95% CI 1.11-2.41). The subgroup with structural degenerative changes was more likely to have OST (OR = 1.82, 95% CI 1.06-3.13) and less likely to have FOA with LBP (OR = 0.62, 95% CI 0.40-0.96) compared to the group with inflammation and pain.
Conclusion: Clustering by biomarkers may assist in differentiating patients for specific clinical interventions aimed at decreasing LBP.
Methods: Using data from the Johnston County Osteoarthritis Project (2006-2010), we measured serum N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, HA, IL-6, BDNF, OPG, and NPY, and urinary CTX-II. Biomarkers were used to group participants using k-means cluster analysis. Logistic regression models were used to compare biomarker clusters.
Results: The sample consisted of 731 participants with biospecimens and lumbar spine radiographic data. Three biomarker subgroups were identified: one characterized by structural degenerative changes; another characterized by structural degenerative changes and inflammation, with pain; and a referent cluster with lower levels of biomarkers, pain, and structural degenerative changes. Compared to the referent subgroup, the structural change subgroup was associated with DSN (OR = 1.94, 95% CI 1.30-2.90) and FOA (OR = 1.72, 95% CI 1.12-2.62), and the subgroup with structural degenerative change, inflammation, and pain was associated with OST with LBP (OR = 1.60, 95% CI 1.04-2.46), FOA with LBP (OR = 1.59, 95% CI 1.04-2.45), and LBP (OR = 1.63, 95% CI 1.11-2.41). The subgroup with structural degenerative changes was more likely to have OST (OR = 1.82, 95% CI 1.06-3.13) and less likely to have FOA with LBP (OR = 0.62, 95% CI 0.40-0.96) compared to the group with inflammation and pain.
Conclusion: Clustering by biomarkers may assist in differentiating patients for specific clinical interventions aimed at decreasing LBP.
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