ArticleJournal of pain research2026
Dissecting the Genetic Basis of Low Back Pain Independent of BMI Through Genomic Structural Equation Modeling.
Article in Journal of pain research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
12 authors.
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Abstract
Background: Low back pain (LBP) is a leading cause of disability worldwide. Although body mass index (BMI) is a well-established risk factor for LBP, a substantial proportion of patients with LBP do not present with abnormal BMI, suggesting the involvement of BMI-independent mechanisms. However, the genetic architecture underlying BMI-independent LBP remains poorly understood. This study aimed to identify and characterize genetic variants associated with LBP that are independent of BMI. Methods: This study was a secondary analysis of publicly available genome-wide association study (GWAS) summary statistics. Genetic associations were analyzed using a Genomic Structural Equation Modeling (Genomic SEM) framework. BMI summary statistics were obtained from the Genetic Investigation of ANthropometric Traits (GIANT) consortium (~700,000 individuals of European ancestry), and LBP data were derived from the FinnGen cohort, including 60,099 cases and 440,249 controls of European ancestry, with LBP defined by the International Classification of Diseases, 10th Revision (ICD-10) code M54. Genome-wide association study by subtraction (GWAS-by-subtraction) was applied to identify BMI-independent LBP associations. Statistical fine-mapping, transcriptome-wide association studies (TWAS), proteome-wide association studies (PWAS), and colocalization analyses were subsequently performed to prioritize putative causal genes. Results: Three independent genome-wide significant loci associated with BMI-independent LBP were identified: rs6916321 at B7NZA1 (P = 2.41 × 10 Conclusion: This study refines the genetic architecture of BMI-independent LBP and identifies novel loci with convergent multi-omic evidence implicating CHST3 in disease susceptibility. The results highlight biological mechanisms beyond adiposity that may contribute to LBP risk and provide a foundation for future functional and translational research.
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