| Application: | 18219, Genetic and epidemiological analyses of low back pain |
| Title: | Genome-wide meta-analysis identifies genetic locus on chromosome 9 associated with Modic changes |
| Size: | 657 B |
| Archived: | 11 Mar 2021 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 3206
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Notes
Background:Low back pain (LBP) is a common disabling condition. Lumbar disc degeneration (LDD) may be a contributing factor for LBP. Modic change (MC), a distinct phenotype of LDD, is presented as a pathological bone marrow signal change adjacent to vertebral endplate on MRI. It is strongly associated with LBP and has heritability around 30%. Our objective was to identify genetic loci associated with MC using a genomewide meta-analysis. Methods:
Presence of MC was evaluated in lumbar MRI in the Northern Finland Birth Cohort 1966 (n=1182) and TwinsUK (n=647). Genome-wide association analyses were carried out using linear regression model. Inversevariance weighting approach was used in the metaanalysis. Results:
A locus associated with MC (p<5e-8) was found on chromosome 9 with the lead SNP rs1934268 in an intron of the PTPRD gene. It is located in the binding region of BCL11A, SPI1 and PBX3 transcription factors. The SNP was nominally associated with LBP in TwinsUK (p=0.001) but not associated in the UK Biobank (p=0.914). Suggestive signals (p<1e-5) were identified near XKR4, SCIN, MGMT, DLG2, ZNF184 and OPRK1. Conclusion:
PTPRD is a novel candidate gene for MC that may act via the development of cartilage or nervous system; further work is needed to define the mechanisms underlying the pathways leading to development of MC. This is the first genome-wide meta-analysis of MC, and the results pave the way for further studies on the genetic factors underlying the various features of spine degeneration and LBP.
Application 18219
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 |
| 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 |
| 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 |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3207 | Genome-wide meta-analysis identifies genetic locus on chromosome 9 associated with Modic changes | Maxim Freidin (+8) | 2019 | Journal of Medical Genetics |
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