Back pain is the #1 cause of years lived with disability worldwide and one of the most common reasons for health care visits in developed countries, yet surprisingly little is known regarding the biology underlying this symptom. Chronic back pain is the major driver of the societal burden of back pain. Identifying biological pathways involved in chronic back pain through genetic association studies might reveal insights into the underlying mechanisms involved or suggest potential avenues for the development of new treatments. We conducted the first genome-wide association study meta-analysis to examine genetic variants associated with chronic back pain. We identified variants associated with chronic back pain in 158,025 individuals of European ancestry from 16 cohorts in Europe and North America, and replicated our findings in 283,752 UK Biobank participants of European ancestry not included in the discovery sample. Our study identifies three novel genome-wide significant associations with chronic back pain, and suggests possible shared genetic mechanisms with other traits such as cartilage, osteoarthritis, lumbar disc degeneration, depression, and height/vertebral development.
Genetic and epidemiological analyses of low back pain
We wish to perform genetic analysis and meta-analysis to identify markers associated with low back pain as part of the FP7 Pain_omics study. In addition, we would like to examine environmental risk factors for low back pain. Using the phenotypes reported in the UK biobank database we wish to study the detailed low back pain phenotype and associated genotype of all volunteers. We will classify subjects as cases who report low back pain and controls who don't. From GWAS analysis we hope to improve the knowledge of this common health condition and ultimately improve treatment of low back pain. We will perform epidemiological and genetic epidemiological studies of low back pain (LBP) by comparing profiles of individuals presenting with back pain to those who do not present with back pain. We note that many more people report LBP than don't. As such, it might be appropriate to
a. consider a combined phenotype with other chronic pain such as leg pain
b. consider the 'controls' as cases and regard the GWAS as a search for variants which protect against LBP.
We will also examine variables influencing LBP such as sex, age, BMI alcohol consumption, socioeconomic status, smoking, exercise, occupation. The full cohort (>500,000)and more as available
|Lead investigator:||Professor Frances Williams|
|Lead institution:||King's College London|
5 related Returns
|Return ID||App ID||Description||Archive Date|
|3207||18219||Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions||11 Mar 2021|
|3206||18219||Genome-wide meta-analysis identifies genetic locus on chromosome 9 associated with Modic changes||11 Mar 2021|
|3208||18219||ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study||11 Mar 2021|
|3209||18219||Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals||11 Mar 2021|
|3247||18219||Sequence variation at 8q24.21 and risk of back pain||19 Mar 2021|
|3211||Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain||Suri et al||2019||PLOS Genetics (2019)|