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Meta-Analysis
. 2023 Oct 31;7(6):pkad088.
doi: 10.1093/jncics/pkad088.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

Elnaz Naderi  1   2   3 Miguel E Aguado-Barrera  4   5 Line M H Schack  6   7   8 Leila Dorling  9 Tim Rattay  10 Laura Fachal  11   12 Holly Summersgill  13 Laura Martínez-Calvo  4   5 Ceilidh Welsh  14 Tom Dudding  15   16 Yasmin Odding  17 Ana Varela-Pazos  18 Rajesh Jena  19 David J Thomson  20   21 Roel J H M Steenbakkers  2 Joe Dennis  12 Ramón Lobato-Busto  22 Jan Alsner  6 Andy Ness  15 Chris Nutting  23 Antonio Gómez-Caamaño  5   18 Jesper G Eriksen  6 Steve J Thomas  15 Amy M Bates  14 Adam J Webb  24 Ananya Choudhury  25 Barry S Rosenstein  26 Begona Taboada-Valladares  5   18 Carsten Herskind  27 David Azria  28 David P Dearnaley  29 Dirk de Ruysscher  30 Elena Sperk  27 Emma Hall  31 Hilary Stobart  32 Jenny Chang-Claude  33   34 Kim De Ruyck  35 Liv Veldeman  36   37 Manuel Altabas  38 Maria Carmen De Santis  39 Marie-Pierre Farcy-Jacquet  40 Marlon R Veldwijk  27 Matthew R Sydes  41 Matthew Parliament  42 Nawaid Usmani  42 Neil G Burnet  21 Petra Seibold  33 R Paul Symonds  43 Rebecca M Elliott  25 Renée Bultijnck  36   37 Sara Gutiérrez-Enríquez  44 Meritxell Mollà  38 Sarah L Gulliford  45 Sheryl Green  26 Tiziana Rancati  46 Victoria Reyes  38 Ana Carballo  5   18 Paula Peleteiro  5   18 Paloma Sosa-Fajardo  5   18 Chris Parker  45 Valérie Fonteyne  37 Kerstie Johnson  10 Maarten Lambrecht  47 Ben Vanneste  36   37   48 Riccardo Valdagni  39   49 Alexandra Giraldo  38 Mónica Ramos  38 Brenda Diergaarde  50 Geoffrey Liu  51 Suzanne M Leal  3   52 Melvin L K Chua  53   54 Miranda Pring  15 Jens Overgaard  6 Luis M Cascallar-Caneda  18 Fréderic Duprez  36   37 Christopher J Talbot  24 Gillian C Barnett  19 Alison M Dunning  12 Ana Vega  4   5   55 Christian Nicolaj Andreassen  6   56 Johannes A Langendijk  2 Catharine M L West  57 Behrooz Z Alizadeh  1 Sarah L Kerns  58 Radiogenomics Consortium
Collaborators, Affiliations
Meta-Analysis

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

Elnaz Naderi et al. JNCI Cancer Spectr. .

Abstract

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.

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Conflict of interest statement

The authors declare no conflicts of interest. No one was paid to write this article by a pharmaceutical company or agency.

Figures

Figure 1.
Figure 1.
Histograms of STATacute and rSTATacute distribution per cancer type and curve of normal log distribution. STAT = standardized total average toxicity.
Figure 2.
Figure 2.
Manhattan (left) and Q-Q (right) plots of the overall meta-analysis for STATacute and rSTATacute. Mirror. Manhattan plot: The GWAS for STATacute and rSTATacute are displayed in the top and bottom panels, respectively. The x-axis represents genomic locations, while the y-axis indicates ‒log10P values for SNV associations with the outcome. Each SNV is a dot. Q-Q plot: Observed ‒log10P values are on the y-axis, and expected ‒log10P values are on the x-axis. Every SNV is represented as a dot, with the red line signifying the null hypothesis of no genuine association. Notable deviations from the expected P value distribution appear primarily at the tail, complemented by the λ coefficients, indicating effective control of population stratification. GWAS = genome-wide association study; Q-Q = quintile-quintile; SNV = single-nucleotide variant; STAT = standardized total average toxicity.
Figure 3.
Figure 3.
Locus zoom plot for the top locus associated with rSTATacute. The purple diamond shows the top single-nucleotide variant and variants in red are in linkage disequilibrium with the top single-nucleotide variant. The y-axis shows observed −log10P values, and the x-axis shows the position across the genome, with genes mapped there. STAT = standardized total average toxicity
Figure 4.
Figure 4.
Tissue expression analysis in 53 tissue types for genes related to overall rSTATacute. Tissue expression analysis testing the positive relationship between all annotated genes using the full distribution of single-nucleotide variant P values and the average expression of genes per tissue type based on Genotype-Tissue Expression RNA sequencing data. DEG = differentially expressed gene set; STAT = standardized total average toxicity.

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