TY - JOUR

T1 - A multi-trait approach identified 7 novel genes for back pain

AU - Belonogova, Nadezhda M.

AU - Elgaeva, Elizaveta E.

AU - Zorkoltseva, Irina V.

AU - Kirichenko, Anatoliy V.

AU - Svishcheva, Gulnara R.

AU - Freidin, Maxim B.

AU - Williams, Frances M.K.

AU - Suri, Pradeep

AU - Axenovich, Tatiana I.

AU - Tsepilov, Yakov A.

PY - 2024/2

Y1 - 2024/2

N2 - Introduction: Back pain (BP) is a complex heritable trait with an estimated heritability of 40% to 60%. Less than half of this can be explained by known genetic variants identified in genome-wide association studies. Objectives: We applied a powerful multi-trait and gene-based approach to association analysis of BP to identify novel genes associated with BP. Methods: Using phenotypes and imputed genotypes from the UK Biobank 500k dataset, we generated a multi-trait phenotype by combining 3 BP-related phenotypes: chronic BP, dorsalgia, and intervertebral disk disorders. We performed gene-based association analysis for 3 BP-related phenotypes and multi-trait phenotype. Conditional analysis was applied to account for the effects of genetic variants outside the gene. Finally, we replicated significantly associated genes using the FinnGen database. Results: We identified 32 genes associated with BP and replicated 16 of them. Thirteen genes were detected using the multi-trait phenotype. Seven of the detected genes, MIPOL1, PTPRC, RHOA, MAML3, JADE2, MLLT10, and RERG, were not previously reported. Several new genes are known to be associated with traits genetically correlated with BP or to be involved in pathways associated with BP. Conclusion: Using new powerful methods of association analysis, we identified 7 novel genes associated with BP. Our results provide new insights into the genetics of back pain.

AB - Introduction: Back pain (BP) is a complex heritable trait with an estimated heritability of 40% to 60%. Less than half of this can be explained by known genetic variants identified in genome-wide association studies. Objectives: We applied a powerful multi-trait and gene-based approach to association analysis of BP to identify novel genes associated with BP. Methods: Using phenotypes and imputed genotypes from the UK Biobank 500k dataset, we generated a multi-trait phenotype by combining 3 BP-related phenotypes: chronic BP, dorsalgia, and intervertebral disk disorders. We performed gene-based association analysis for 3 BP-related phenotypes and multi-trait phenotype. Conditional analysis was applied to account for the effects of genetic variants outside the gene. Finally, we replicated significantly associated genes using the FinnGen database. Results: We identified 32 genes associated with BP and replicated 16 of them. Thirteen genes were detected using the multi-trait phenotype. Seven of the detected genes, MIPOL1, PTPRC, RHOA, MAML3, JADE2, MLLT10, and RERG, were not previously reported. Several new genes are known to be associated with traits genetically correlated with BP or to be involved in pathways associated with BP. Conclusion: Using new powerful methods of association analysis, we identified 7 novel genes associated with BP. Our results provide new insights into the genetics of back pain.

KW - Chronic back pain

KW - Dorsalgia

KW - GWAS summary statistics

KW - Intervertebral disk disorders

KW - Shared heritability

KW - Chronic back pain

KW - Dorsalgia

KW - GWAS summary statistics

KW - Intervertebral disk disorders

KW - shared heritability

UR - https://www.mendeley.com/catalogue/f04831d9-de38-3864-b122-682697701ca9/

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85214491999&origin=inward&txGid=ab6a9620bc492de685d509f154fb80c0

U2 - 10.1097/PR9.0000000000001218

DO - 10.1097/PR9.0000000000001218

M3 - Article

C2 - 39726856

VL - 10

JO - Pain Reports

JF - Pain Reports

SN - 2471-2531

IS - 1

M1 - e1218

ER -