Individual variability in response to radiation exposure is recognised and has often been reported as important in treatment planning. Despite many efforts to identify biomarkers allowing the identification of radiation sensitive patients, it is not yet possible to distinguish them with certainty before the beginning of the radiotherapy treatment. A comprehensive analysis of genome-wide single-nucleotide polymorphisms (SNPs) and a transcriptional response to ionising radiation exposure in twins have the potential to identify such an individual. In the present work, we investigated SNP profile and CDKN1A gene expression in blood T lymphocytes from 130 healthy Caucasians with a complex level of individual kinship (unrelated, mono- or dizygotic twins). It was found that genetic variation accounts for 66% (95% CI 37–82%) of CDKN1A transcriptional response to radiation exposure. We developed a novel integrative multi-kinship strategy allowing investigating the role of genome-wide polymorphisms in transcriptomic radiation response, and it revealed that rs205543 (ETV6 gene), rs2287505 and rs1263612 (KLF7 gene) are significantly associated with CDKN1A expression level. The functional analysis revealed that rs6974232 (RPA3 gene), involved in mismatch repair (p value = 9.68e−04) as well as in RNA repair (p value = 1.4e−03) might have an important role in that process. Two missense polymorphisms with possible deleterious effect in humans were identified: rs1133833 (AKIP1 gene) and rs17362588 (CCDC141 gene). In summary, the data presented here support the validity of this novel integrative data analysis strategy to provide insights into the identification of SNPs potentially influencing radiation sensitivity. Further investigations in radiation response research at the genomic level should be therefore continued to confirm these findings.
Bibliographical noteFunding Information:
Author contributions Conceived of designed study: Ghazi Alsbeih and Christophe Badie Performed research: Sylwia Kabacik, Grainne O’Brien, Salma Wakil and Najla Al-Harbi Analysed data: Joanna Polanska and Joanna Zyla Contributed new methods or models: Jaakko Kaprio, Joanna Polanska and Joanna Zyla Wrote the paper: Joanna Zyla, Joanna Polanska, Ghazi Alsbeih and Christophe Badie Funding information This work was funded by the National Science Centre, Poland grant 2013/08/M/ST6/00924 (JZ) and SUT grant 02/ 010/BK18/0102/8 (JP); the National Science, Technology and Innovation Plan (NSTIP), grant 11-BIO1429-20 and RAC# 2120 003 (SW, GA); and the Academy of Finland grant 308248, 312073 (JK). Calculations were carried out using the infrastructure of GeCONiI (POIG.02.03.01-24-099/13).
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
- Radiation response
- Twin study
- p value integration