• Pradeep Suri, Ian B Stanaway, Yanfei Zhang, Maxim B Freidin, Yakov A Tsepilov, David S Carrell, WilliamsFrances M KFMKDepartment of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, United Kingdom., Yurii S Aulchenko, Hakon Hakonarson, Bahram Namjou, David R Crosslin, Gail P Jarvik, and Ming Ta Lee.
• Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, WA, United States.
• Pain. 2021 Aug 1; 162 (8): 226322722263-2272.

AbstractIdentifying genetic risk factors for lumbar spine disorders may lead to knowledge regarding underlying mechanisms and the development of new treatments. We conducted a genome-wide association study involving 100,811 participants with genotypes and longitudinal electronic health record data from the Electronic Medical Records and Genomics Network and Geisinger Health. Cases and controls were defined using validated algorithms and clinical diagnostic codes. Electronic health record-defined phenotypes included low back pain requiring healthcare utilization (LBP-HC), lumbosacral radicular syndrome (LSRS), and lumbar spinal stenosis (LSS). Genome-wide association study used logistic regression with additive genetic effects adjusting for age, sex, site-specific factors, and ancestry (principal components). A fixed-effect inverse-variance weighted meta-analysis was conducted. Genetic variants of genome-wide significance (P < 5 × 10-8) were carried forward for replication in an independent sample from UK Biobank. Phenotype prevalence was 48.8% for LBP-HC, 19.8% for LSRS, and 7.9% for LSS. No variants were significantly associated with LBP-HC. One locus was associated with LSRS (lead variant rs146153280:C>G, odds ratio [OR] = 1.17 for G, P = 2.1 × 10-9), but was not replicated. Another locus on chromosome 2 spanning GFPT1, NFU1, and AAK1 was associated with LSS (lead variant rs13427243:G>A, OR = 1.10 for A, P = 4.3 × 10-8) and replicated in UK Biobank (OR = 1.11, P = 5.4 × 10-5). This was the first genome-wide association study meta-analysis of lumbar spinal disorders using electronic health record data. We identified 2 novel associations with LSRS and LSS; the latter was replicated in an independent sample.Copyright © 2021 International Association for the Study of Pain.

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