Abstract
BACKGROUND CONTEXT
Chronic back pain (CBP) is a common debilitating condition with substantial societal
impact. While understanding genotype-by-environment (GxE) interactions may be crucial
to achieving the goals of personalized medicine, there are few large-scale studies
investigating this topic for CBP. None of them systematically explore multiple CBP
risk factors.
PURPOSE
To estimate the extent to which genetic effects on CBP are modified by known demographic
and clinical risk factors.
RESEARCH DESIGN
Case-control study, genome-wide GxE interaction study.
PATIENT SAMPLE
Data on up to 331,610 unrelated participants (57,881 CBP cases and 273,729 controls)
from the UK Biobank cohort were used. UK Biobank is a prospective cohort with collected
deep genetic and phenotypic data on approximately 500,000 individuals across the UK.
OUTCOME MEASURES
Self-reported chronic back pain.
METHODS
We applied a whole-genome approach to estimate the proportion of phenotypic variance
explained by interactions between genotype and 12 known risk factors. We also analyzed
if effects of common single-nucleotide polymorphisms on CBP are changed in presence
of known risk factors.
RESULTS
The results indicate a modest, if any, modification of genetic effects by examined
risk factors in CBP. Our estimates suggest that detecting such weak effects would
require a sample size of millions of individuals.
CONCLUSIONS
The GxE interactions with examined common risk factors for CBP are either weak or
absent. Interactions of such magnitude are unlikely to have the potential to inform
and influence treatment strategies. Risk estimation models may use common genetic
variation and the considered risk factors as independent predictors, without accounting
for GxE.
Keywords
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References
- The global burden of low back pain: estimates from the Global Burden of Disease 2010 study.Ann Rheum Dis. 2014; 73: 968-974https://doi.org/10.1136/annrheumdis-2013-204428
- Epidemiology of low back pain in adults.Neuromodulation. 2014; 17: 3-10https://doi.org/10.1111/ner.12018
- Incidence and risk factors for first-time incident low back pain: a systematic review and meta-analysis.Spine J. 2014; 14: 2299-2319https://doi.org/10.1016/j.spinee.2014.01.026
- Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.PLoS Genet. 2018; 14e1007601https://doi.org/10.1371/journal.pgen.1007601
- Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals.Pain. 2019; 160: 1361-1373https://doi.org/10.1097/j.pain.0000000000001514
- Introduction to quantitative genetics.Longman Group, Essex, UK1996
- Genetics and analysis of quantitative traits. 1. Sinauer, Sunderland, MA1998
- Towards precision medicine.Nat Rev Genet. 2016; 17: 507-522https://doi.org/10.1038/nrg.2016.86
- Gene-environment and gene-treatment interactions in type 2 diabetes: progress, pitfalls, and prospects.Diabetes Care. 2013; 36: 1413-1421https://doi.org/10.2337/dc12-2211
- Differential effects of environmental and genetic factors on T and B cell immune traits.Cell Rep. 2016; 17: 2474-2487https://doi.org/10.1016/j.celrep.2016.10.053
- Genome-wide interaction analysis of air pollution exposure and childhood asthma with functional follow-up.Am J Respir Crit Care Med. 2017; 195: 1373-1383https://doi.org/10.1164/rccm.201605-1026OC
- GCTA: a tool for genome-wide complex trait analysis.Am J Hum Genet. 2011; 88: 76-82https://doi.org/10.1016/j.ajhg.2010.11.011
- MTG2: an efficient algorithm for multivariate linear mixed model analysis based on genomic information.Bioinformatics. 2016; 32: 1420-1422https://doi.org/10.1093/bioinformatics/btw012
- Genotype-covariate interaction effects and the heritability of adult body mass index.Nat Genet. 2017; 49: 1174-1181https://doi.org/10.1038/ng.3912
- Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model.Nat Commun. 2019; 10: 2239https://doi.org/10.1038/s41467-019-10128-w
- GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data.Genome Biol. 2021; 22: 183https://doi.org/10.1186/s13059-021-02403-1
- VarExp: estimating variance explained by genome-wide GxE summary statistics.Bioinformatics. 2018; 34: 3412-3414https://doi.org/10.1093/bioinformatics/bty379
- LD Score regression distinguishes confounding from polygenicity in genome-wide association studies.Nat Genet. 2015; 47: 291-295https://doi.org/10.1038/ng.3211
- Sex- and age-specific genetic analysis of chronic back pain.Pain. 2021; 162: 1176-1187https://doi.org/10.1097/j.pain.0000000000002100
- The UK Biobank resource with deep phenotyping and genomic data.Nature. 2018; 562: 203-209https://doi.org/10.1038/s41586-018-0579-z
- Genome-wide association studies.Nat RevMethods Primers. 2021; 1: 1-21https://doi.org/10.1038/s43586-021-00056-9
- Integrating common and rare genetic variation in diverse human populations.Nature. 2010; 467: 52-58https://doi.org/10.1038/nature09298
- ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.Eur Spine J. 2020; 29: 686-691https://doi.org/10.1007/s00586-019-06224-6
- Causal effects of psychosocial factors on chronic back pain: a bidirectional Mendelian randomisation study.Eur Spine J. 2022; 31: 1906-1915https://doi.org/10.1007/s00586-022-07263-2
- Sitting-to-standing height ratio is a sex-specific risk factor for chronic back pain.in: Abstracts from the 54th European Society of Human Genetics (ESHG) Conference: e-Posters, vol. 30, European Journal of Human Genetics. 2022: 88-608https://doi.org/10.1038/s41431-021-01026-1
- Adjusting for heritable covariates can bias effect estimates in genome-wide association studies.Am J Hum Genet. 2015; 96: 329-339https://doi.org/10.1016/j.ajhg.2014.12.021
- Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations.Int J Epidemiol. 2021; 50: 1639-1650https://doi.org/10.1093/ije/dyaa266
Shaun Purcell, Christopher Chang PLINK 2.0. Available at: http://www.cog-genomics.org/plink/2.0/. Accessed May 15, 2023.
- Second-generation PLINK: rising to the challenge of larger and richer datasets.Gigascience. 2015; 4https://doi.org/10.1186/s13742-015-0047-8
- An integrated map of structural variation in 2,504 human genomes.Nature. 2015; 526: 75-81https://doi.org/10.1038/nature15394
- The behavior of maximum likelihood estimates under nonstandard conditions.in: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability: Weather Modification. University of California Press, Berkeley, CA1967: 221
- Various versatile variances: an object-oriented implementation of clustered covariances in R.J Stat Softw. 2020; 95: 1-36https://doi.org/10.18637/jss.v095.i01
- On the so-called “Huber Sandwich Estimator” and “Robust Standard Errors.Am Stat. 2006; 60: 299-302https://doi.org/10.1198/000313006X152207
- Heritability of threshold characters.Genetics. 1950; 35: 212-236
- dbSNP: the NCBI database of genetic variation.Nucleic Acids Res. 2001; 29: 308-311https://doi.org/10.1093/nar/29.1.308
- A global reference for human genetic variation.Nature. 2015; 526: 68-74https://doi.org/10.1038/nature15393
- The mutational constraint spectrum quantified from variation in 141,456 humans.Nature. 2020; 581: 434-443https://doi.org/10.1038/s41586-020-2308-7
- Similarities in degenerative findings on magnetic resonance images of the lumbar spines of identical twins.J Bone Joint Surg Am. 1995; 77: 1662-1670https://doi.org/10.2106/00004623-199511000-00004
- The Twin Spine Study: contributions to a changing view of disc degeneration.Spine J. 2009; 9: 47-59https://doi.org/10.1016/j.spinee.2008.11.011
- Comparison of the prevalence of low back pain and related spinal diseases among smokers and nonsmokers: using Korean National Health Insurance Database.Clin Orthop Surg. 2020; 12: 200-208https://doi.org/10.4055/cios19095
- Why does the magnitude of genotype-by-environment interaction vary?.Ecol Evol. 2018; 8: 6342-6353https://doi.org/10.1002/ece3.4128
Article info
Publication history
Published online: April 17, 2023
Accepted:
April 11,
2023
Received in revised form:
April 6,
2023
Received:
August 19,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
FDA device/drug status: Not applicable.
Author disclosures: IAK: Nothing to disclose. YAT: Nothing to disclose. MBF: Nothing to disclose. FMKW: Nothing to disclose. PS: Nothing to disclose. YSA: Nothing to disclose.
YSA is a founder of PolyOmica and PolyKnomics, private organizations providing services, research and development in the field of computational and statistical (gen)omics.
Identification
Copyright
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