Large-scale Meta-genome-wide Association Study Reveals Common Genetic Factors Linked to Radiation-induced Acute Toxicities Across Cancer Types

Background: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).

Methods: A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.

Results: Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).

Conclusions: There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Citing Articles

To trust or not to trust: evaluating the reliability and safety of AI responses to laryngeal cancer queries.

Ostrowska M, Kacala P, Onolememen D, Vaughan-Lane K, Sisily Joseph A, Ostrowski A Eur Arch Otorhinolaryngol. 2024; 281(11):6069-6081.

PMID: 38652298 PMC: 11512842. DOI: 10.1007/s00405-024-08643-8.

Applicability of Online Chat-Based Artificial Intelligence Models to Colorectal Cancer Screening.

Atarere J, Naqvi H, Haas C, Adewunmi C, Bandaru S, Allamneni R Dig Dis Sci. 2024; 69(3):791-797.

PMID: 38267726 DOI: 10.1007/s10620-024-08274-3.

References

Maldonado-Saldivia J, van den Bergen J, Krouskos M, Gilchrist M, Lee C, Li R . Dppa2 and Dppa4 are closely linked SAP motif genes restricted to pluripotent cells and the germ line. Stem Cells. 2006; 25(1):19-28. DOI: 10.1634/stemcells.2006-0269. View

Visscher P, Wray N, Zhang Q, Sklar P, McCarthy M, Brown M . 10 Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet. 2017; 101(1):5-22. PMC: 5501872. DOI: 10.1016/j.ajhg.2017.06.005. View

de Leeuw C, Mooij J, Heskes T, Posthuma D . MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015; 11(4):e1004219. PMC: 4401657. DOI: 10.1371/journal.pcbi.1004219. View

Guo Z, Shu Y, Zhou H, Zhang W, Wang H . Radiogenomics helps to achieve personalized therapy by evaluating patient responses to radiation treatment. Carcinogenesis. 2015; 36(3):307-17. DOI: 10.1093/carcin/bgv007. View

Grove J, Ripke S, Als T, Mattheisen M, Walters R, Won H . Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019; 51(3):431-444. PMC: 6454898. DOI: 10.1038/s41588-019-0344-8. View

Ui A, Yasui A . Collaboration of MLLT1/ENL, Polycomb and ATM for transcription and genome integrity. Nucleus. 2016; 7(2):138-45. PMC: 4916901. DOI: 10.1080/19491034.2016.1177681. View

Fachal L, Gomez-Caamano A, Barnett G, Peleteiro P, Carballo A, Calvo-Crespo P . A three-stage genome-wide association study identifies a susceptibility locus for late radiotherapy toxicity at 2q24.1. Nat Genet. 2014; 46(8):891-4. DOI: 10.1038/ng.3020. View

Naderi E, Crijns A, Steenbakkers R, van den Hoek J, Boezen H, Alizadeh B . A two-stage genome-wide association study of radiation-induced acute toxicity in head and neck cancer. J Transl Med. 2021; 19(1):481. PMC: 8626989. DOI: 10.1186/s12967-021-03145-1. View

Naderi E, Schack L, Welsh C, Sim A, Aguado-Barrera M, Dudding T . Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer. Radiother Oncol. 2022; 176:138-148. DOI: 10.1016/j.radonc.2022.09.016. View

10.

. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013; 45(6):580-5. PMC: 4010069. DOI: 10.1038/ng.2653. View

11.

Watanabe K, Taskesen E, van Bochoven A, Posthuma D . Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017; 8(1):1826. PMC: 5705698. DOI: 10.1038/s41467-017-01261-5. View

12.

Willer C, Li Y, Abecasis G . METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010; 26(17):2190-1. PMC: 2922887. DOI: 10.1093/bioinformatics/btq340. View

13.

Evans L, Tahmasbi R, Vrieze S, Abecasis G, Das S, Gazal S . Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits. Nat Genet. 2018; 50(5):737-745. PMC: 5934350. DOI: 10.1038/s41588-018-0108-x. View

14.

Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D . PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007; 81(3):559-75. PMC: 1950838. DOI: 10.1086/519795. View

15.

Vivier E, Tomasello E, Baratin M, Walzer T, Ugolini S . Functions of natural killer cells. Nat Immunol. 2008; 9(5):503-10. DOI: 10.1038/ni1582. View

16.

Chen H, Wang T, Yang J, Huang S, Zeng P . Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics. Front Genet. 2020; 11:592461. PMC: 7744760. DOI: 10.3389/fgene.2020.592461. View

17.

De Ruyck K, Duprez F, Werbrouck J, Sabbe N, Sofie D, Boterberg T . A predictive model for dysphagia following IMRT for head and neck cancer: introduction of the EMLasso technique. Radiother Oncol. 2013; 107(3):295-9. DOI: 10.1016/j.radonc.2013.03.021. View

18.

Bulik-Sullivan B, Loh P, Finucane H, Ripke S, Yang J, Patterson N . LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015; 47(3):291-5. PMC: 4495769. DOI: 10.1038/ng.3211. View

19.

Bulik-Sullivan B, Finucane H, Anttila V, Gusev A, Day F, Loh P . An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015; 47(11):1236-41. PMC: 4797329. DOI: 10.1038/ng.3406. View

20.

Tanaka Y, Horinouchi T, Koike K . New insights into beta-adrenoceptors in smooth muscle: distribution of receptor subtypes and molecular mechanisms triggering muscle relaxation. Clin Exp Pharmacol Physiol. 2005; 32(7):503-14. DOI: 10.1111/j.1440-1681.2005.04222.x. View