Back pain (BP) is a common condition of major social importance and poorly understood pathogenesis. Combining data from the UK Biobank and CHARGE consortium cohorts allowed us to perform a very large genome-wide association study (total N = 509,070) and examine the genetic correlation and pleiotropy between BP and its clinical and psychosocial risk factors. We identified and replicated 3 BP-associated loci, including one novel region implicating SPOCK2/CHST3 genes. We provide evidence for pleiotropic effects of genetic factors underlying BP, height, and intervertebral disk problems. We also identified independent genetic correlations between BP and depression symptoms, neuroticism, sleep disturbance, overweight, and smoking. A significant enrichment for genes involved in the central nervous system and skeletal tissue development was observed. The study of pleiotropy and genetic correlations, supported by the pathway analysis, suggests at least 2 strong molecular axes of BP genesis, one related to structural/anatomical factors such as intervertebral disk problems and anthropometrics, and another related to the psychological component of pain perception and pain processing. These findings corroborate with the current biopsychosocial model as a paradigm for BP. Overall, the results demonstrate BP to have an extremely complex genetic architecture that overlaps with the genetic predisposition to its biopsychosocial risk factors. The work sheds light on pathways of relevance in the prevention and management of low BP.
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|
|3210||18219||Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain||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|
|3247||18219||Sequence variation at 8q24.21 and risk of back pain||19 Mar 2021|