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Article

Screening Mammography and Breast Cancer: Variation in Risk with Rare Deleterious or Predicted Deleterious Variants in DNA Repair Genes

by
Maximiliano Ribeiro-Guerra
1,2,3,4,5,
Marie-Gabrielle Dondon
1,2,3,4,
Séverine Eon-Marchais
1,2,3,4,
Dorothée Le Gal
1,2,3,4,
Juana Beauvallet
1,2,3,4,
Noura Mebirouk
1,2,3,4,
Muriel Belotti
6,
Eve Cavaciuti
1,2,3,4,
Claude Adenis-Lavignasse
7,
Séverine Audebert-Bellanger
8,
Pascaline Berthet
9,
Valérie Bonadona
10,11,
Bruno Buecher
6,
Olivier Caron
12,
Mathias Cavaille
13,
Jean Chiesa
14,
Chrystelle Colas
6,15,
Isabelle Coupier
16,17,
Capucine Delnatte
18,
Hélène Dreyfus
19,20,
Anne Fajac
21,
Sandra Fert-Ferrer
22,
Jean-Pierre Fricker
23,
Marion Gauthier-Villars
6,
Paul Gesta
24,
Sophie Giraud
25,
Laurence Gladieff
26,
Christine Lasset
10,11,
Sophie Lejeune-Dumoulin
27,
Jean-Marc Limacher
28,
Michel Longy
29,
Alain Lortholary
30,
Elisabeth Luporsi
31,
Christine M. Maugard
32,33,
Isabelle Mortemousque
34,
Sophie Nambot
35,36,
Catherine Noguès
37,38,
Pascal Pujol
16,17,
Laurence Venat-Bouvet
39,
Florent Soubrier
40,
Julie Tinat
41,
Anne Tardivon
42,
Fabienne Lesueur
1,2,3,4,
Dominique Stoppa-Lyonnet
6,43,44 and
Nadine Andrieu
1,2,3,4,*
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1
Inserm, U1331, 75248 Paris cedex 05, France
2
Institut Curie, 75248 Paris cedex 05, France
3
Mines ParisTech, 75272 Paris cedex 06, France
4
PSL Research University, 75006 Paris, France
5
Department of Public Health, Faculty of Medicine, Federal University of Juiz de Fora (UFJF), Juiz de Fora 36036-900, MG, Brazil
6
Institut Curie, Service de Génétique, 75248 Paris cedex 05, France
7
Polyclinique de la Louvière (Groupe Ramsay), 59800 Lille, France
8
Département de Génétique Médicale et Biologie de la Reproduction, Hôpital Morvan, CHU Brest, 29200 Brest, France
9
Unité de Pathologie Gynécologique, Centre François Baclesse, 14000 Caen, France
10
CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Université Lyon 1, 69622 Villeurbanne, France
11
Centre Léon Bérard, Unité de Prévention et Epidémiologie Génétique, 69008 Lyon, France
12
Gustave Roussy, Département de Médecine Oncologique, 94800 Villejuif, France
13
Centre Jean Perrin, Département d’Oncogénétique, Inserm, UMR 1240, Université Clermont Auvergne, 63001 Clermont Ferrand, France
14
Service d’Oncologie Médicale, CHRU Hôpital Caremeau, 30900 Nîmes, France
15
Institut Curie, Hôpital René Huguenin, 92210 Saint-Cloud, France
16
Service de Génétique Médicale et Oncogénétique, Hôpital Arnaud de Villeneuve, CHU Montpellier, 34090 Montpellier, France
17
Inserm, U896, CRCM Val d’Aurelle, 34090 Montpellier, France
18
Unité d’Oncogénétique, Institut de Cancérologie de l’Ouest, 44800 Saint-Herblain, France
19
Clinique Sainte Catherine, 84000 Avignon, France
20
Département de Génétique, Hôpital Couple-Enfant, CHU de Grenoble, 38700 Grenoble, France
21
Service d’Oncogénétique, Hôpital Tenon, 75020 Paris, France
22
Service de Génétique, Centre Hospitalier Métropole Savoie, 73000 Chambéry, France
23
Centre Paul Strauss, Unité d’Oncologie, 67200 Strasbourg, France
24
Service d’Oncogénétique Régional Poitou-Charentes, CH Georges Renon, 79000 Niort, France
25
Centre Hospitalier de la Côte Basque, Institut Bergonié, 33000 Bordeaux, France
26
Service d’Oncologie Médicale, Institut Claudius Regaud, IUCT-Oncopole, 31100 Toulouse, France
27
Clinique de Génétique Médicale Guy Fontaine, CHU Lille, 59000 Lille, France
28
Service d’Onco-Hématologie, Hôpital Pasteur, 68024 Colmar, France
29
Cancer Genetics Unit, Inserm U1312, Institut Bergonié, University of Bordeaux, 33000 Bordeaux, France
30
Service d’Oncologie Médicale, Centre Catherine de Sienne, 44200 Nantes, France
31
Service de Génétique, UF4128, CHR Metz-Thionville, Hôpital de Mercy, 57530 Ars-Laquenexy, France
32
UF1422, Génétique Oncologique Moléculaire, Département d’Oncobiologie, LBBM, Hôpitaux Universitaires de Strasbourg, 67200 Strasbourg, France
33
UF6948, Génétique Oncologique Clinique, Evaluation Familiale et Suivi, Hôpitaux Universitaires de Strasbourg, 67200 Strasbourg, France
34
Service de Génétique, Hôpital Bretonneau, 75018 Paris, France
35
Institut GIMI, Oncogénétique, CHU de Dijon, Hôpital d’Enfants, 21000 Dijon, France
36
Centre de Lutte Contre le Cancer Georges François Leclerc, 21000 Dijon, France
37
Département d’Anticipation et de Suivi des Cancers, Oncogénétique Clinique, Institut Paoli-Calmettes, 13009 Marseille, France
38
Inserm, IRD, SESSTIM, Aix Marseille University, 13009 Marseille, France
39
Service d’Oncologie Médicale, Hôpital Universitaire Dupuytren, 87000 Limoges, France
40
UMR_S 1166, Faculté de Médecine, SU Site Pitié-Salpêtrière, 75013 Paris, France
41
Service de Génétique Médicale, CHU De Bordeaux, Groupe Hospitalier Pellegrin, 33000 Bordeaux, France
42
Service de Radiologie, Institut Curie, 75005 Paris, France
43
Inserm, U830, 75005 Paris, France
44
Université Paris-Cité, 75006 Paris, France
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(7), 1062; https://doi.org/10.3390/cancers17071062
Submission received: 3 February 2025 / Revised: 14 March 2025 / Accepted: 17 March 2025 / Published: 21 March 2025
(This article belongs to the Section Cancer Epidemiology and Prevention)

Simple Summary

The association of screening mammography with breast cancer (BC) was investigated in cases with a hereditary predisposition unexplained by BRCA1 or BRCA2 and unrelated controls. Participants reported their lifetime mammography exposures in a questionnaire. Additionally, germline rare deleterious or predicted deleterious variants (D-PDVs) were investigated in 113 DNA repair genes. No association was found between having been exposed to mammograms (never vs. ever) and BC. However, when considering the number of mammograms, an increase in BC risk of 4% (95% CI: 1–6%) per additional exposure was found. When women were grouped according to their D-PDV carrier status and the estimated associated BC risk, mammograms doubled the BC risk of women carrying a D-PDV in a gene associated with BC with an odds ratio (OR) < 0.9, as compared to those carrying a D-PDV in a gene with an OR > 1.1. Even though mammographic screening reduces the risk of mortality from BC, the identification of populations more or less susceptible to ionizing radiation may be clinically relevant.

Abstract

Background: Women with a familial predisposition to breast cancer (BC) are offered screening at earlier ages and more frequently than women from the general population. Methods: We evaluated the effect of screening mammography in 1552 BC cases with a hereditary predisposition to BC unexplained by BRCA1 or BRCA2 and 1363 unrelated controls. Participants reported their lifetime mammography exposures in a detailed questionnaire. Germline rare deleterious or predicted deleterious variants (D-PDVs) in 113 DNA repair genes were investigated in 82.5% of the women and classified according to the strength of their association with BC. Genes with an odds ratio (OR) < 0.9 was assigned to the Gene Group “Reduced”, those with OR ≥ 0.9 and ≤1.1 to Group “Independent”, and those with OR > 1.1 to Group “Increased”. Results: Overall, having been exposed to mammograms (never vs. ever) was not associated with BC risk. However, an increase in BC risk of 4% (95% CI: 1–6%) per additional exposure was found under the assumption of linearity. When grouped according to D-PDV carrier status, mammograms doubled the BC risk of women carrying a D-PDV in Group “Reduced”, as compared to those carrying a D-PDV in Group “Increased”. Conclusions: Our study is the first to investigate the joint effect of mammogram exposure and variants in DNA repair genes other than BRCA1 and BRCA2 in women at high risk of BC; therefore, further studies are needed to verify our findings. Even though mammographic screening reduces the risk of mortality from BC, the identification of populations that are more or less susceptible to ionizing radiation may be clinically relevant.

1. Introduction

Women with a genetic predisposition to breast cancer (BC) may be at increased risk of cancer after exposure to ionizing radiation. Screening mammography is associated with exposure of the breast to a small dose of radiation (i.e., the regulatory limit set at 3.0 mGy for each view of an average-sized breast and two views of each breast), which has not been found to increase BC risk in the general population [1]. However, women who are at increased genetic risk might be more sensitive to the DNA-damaging effect of ionizing radiation, in particular women carrying a deleterious variant in a gene involved in the repair of DNA damages like BRCA1 and BRCA2 [2]. Moreover, women with a family history of BC are offered screening at earlier ages and at more frequent intervals than women from the general population. Assuming there is no lower threshold dose in which radiation exposure does not cause damage, repeated exposure to ionizing radiation from screening mammographic procedures may increase the risk of BC, and the possible benefit of mammography screening could be reduced due to the risk of radiation-induced tumors.
While exposures to diagnostic ionizing radiation to the chest excluding mammograms have been studied in the population with a genetic predisposition to BC [2,3,4,5,6,7,8], few studies have investigated the effect of mammograms in such populations, and these studies were essentially conducted among BRCA1/2 pathogenic variant carriers [2,4,9,10,11,12,13]. Therefore, we evaluated the effect of radiation exposure from mammography screening on BC risk in women with a genetic predisposition to BC and tested negative for a BRCA1/2 pathogenic variant. Furthermore, we evaluated whether carrying a rare deleterious or predicted deleterious variant (D-PDV) (i.e., loss-of-function or missense variant with a predicted deleterious effect, phred CADD score ≥ 20 [14]) in 113 DNA repair genes (other than BRCA1/2) previously selected [15,16] modifies the association between mammography screening exposures and BC risk.

2. Methods

2.1. Study Population

The study population involved cases and unrelated controls enrolled in GENESIS between February 2007 and December 2013, a national study initially set up to investigate genetic factors involved in the susceptibility to BC other than BRCA1/2 [17]. Index cases were identified through the French family cancer clinics of the Groupe Génétique et Cancer (Unicancer) (i.e., 42 centers) and were eligible when diagnosed with infiltrating mammary or ductal adenocarcinoma, negative for BRCA1 and BRCA2 mutations, and had a sister with BC (Figure 1). The mutation screening strategy was similar for all the clinics (cf. Supplemental Methods). The unrelated controls were selected from among the unaffected friends and/or colleagues of the cases. The year of birth of controls was matched to that of the case (±3 years). All women completed a questionnaire on environmental, lifestyle, and reproductive factors and family history of cancer. Only women reporting European ancestry (i.e., over 95% of the study population) were considered for this study.

2.2. Screening Mammography

Participants reported their history of screening mammography in a detailed questionnaire at the time of their recruitment. To exclude mammograms that could have been performed because of BC diagnosis, we considered exposures that occurred up to one year prior to BC diagnosis for cases and one year prior to the date of questionnaire completion for controls. Variables considered in the analyses were ever vs. never exposed, lifetime number of screening mammograms, age at first mammography, and timing since the first mammography, i.e., the delay in years between the age at first mammography and the age at BC diagnosis for cases and the age at interview for the controls (i.e., age at censuring).
We excluded 52 women who underwent radiotherapy for a benign disease more than one year prior to age at censoring (2.19% cases; 1.23% controls). Among cases, we also excluded 10 women (0.63%) who underwent radiotherapy for a cancer other than BC before their BC diagnosis.

2.3. Variants in DNA Repair Genes

Contribution of germline rare D-PDVs (with minor allele frequency <0.5% in controls) in 113 DNA repair genes in familial BC was previously assessed by performing targeted sequencing of their entire coding sequence in 1207 cases and 1199 controls from the GENESIS study. Detailed information on the selection of genes, sequencing procedure, and variants filtering and annotation is described in Girard et al. [16]. Loss-of-function and missense variants with a phred CADD score ≥ 20 as a predictor of deleterious effect [14] and with minor allele frequency <0.5% in controls were selected and defined as D-PDV. Sequencing data were available for 82.5% of the women investigated in the present study, and no difference in the distribution of the characteristics such as education level, smoking, or ionizing exposures was observed between the subsets of cases and controls with and without sequencing data (see Supplemental Table 1 in Ribeiro-Guerra et al. [15]).
Because study participants carried very few rare D-PDVs per gene (pool of variants for each gene ranged between 0% and 4.1% in controls), we grouped the genes according to the value of their association with BC, i.e., the odds-ratio (OR) point estimate obtained in the study by Girard et al. [16] (whatever the degree of significance) and classified them as follows: Group “Reduced” including genes with OR < 0.9; Group “Independent”, including genes with 0.9 ≤ OR ≤ 1.1; and Group “Increased”, including genes with OR > 1.1. An individual could be assigned to more than one group if carrying several variants in genes belonging to different groups [15]. Results of the association tests per gene were first published [16]. Gene group assignation is defined in Ribeiro-Guerra et al. [15] and reported in Supplemental Table S1 to ease the reading. Additionally, we hypothesized that variants might have additive effects and built a Variant Risk Score (VRS = β1x1 + β2x2 +…+ β113x113 with β the per DNA repair gene minor allele mean effect, i.e., log OR for BC, and x equals 1 or 0 for being carrier or non-carrier, respectively) and performed analysis using the above bounds for ORs.

2.4. Statistical Analyses

To assess the association between mammography exposure and BC risk, we used logistic regression models adjusted for variables described in Supplemental Methods.
We assessed associations between mammography exposure and BC by DNA repair gene group and used likelihood ratio tests to test for heterogeneity and multiplicative interaction. Additionally, we adjusted for other gene groups when the analysis was stratified by gene group.
We assessed heterogeneity between ER tumor status using a multinomial logistic regression model and tested the equality of coefficients between equations by the difference between the log-likelihoods.
All p-values using Z-tests were two-sided, and a 5% level of significance was used. All analyses were performed using Stata software version 14 [18].

3. Results

Characteristics of the study population are described in Table 1. “Most of the cases were prevalent with a mean delay between diagnosis and interview of 8.3 years (SD: ±7.1). The mean age at BC diagnosis was 50.2 years (SD: ±9.3) and the mean age at interview for the controls was 55.8 years (SD: ±9.9)” as described in Ribeiro-Guerra et al. [15].
Compared to controls, index cases were more likely to have a basic education level, lower body mass index, and as expected, a stronger family history of BC at censure. Regarding birth cohort, cases were more likely to be born before 1945 than controls. Among the subset of participants who had been sequenced for the 113 DNA repair genes (74.1%), 20% had no D-PDV, 31% carried 1 D-PDV, 26%, 2 D-PDVs, and 23% carried 3 or more D-PDVs. Cases were more likely to carry a variant in a gene from the “Increased” risk group than controls (57.7% and 42.6%, respectively) (Table 1). Mammography exposure characteristics are described in Table 2. More controls had mammograms than cases (91.9% and 81.9%, respectively). The mean number of exposures was similar for cases and controls, and the first exposure occurred earlier for cases than for controls (38.9 years and 43.1 years, respectively).
As a whole, we did not find an association between BC and having been exposed to mammograms when measured as ever vs. never (OR = 0.99; 95% CI: 0.69–1.43) (Table 3) or when categorized according to the number of mammograms. However, when the number of mammograms was considered as a continuous variable, under the assumption of linearity, we found a significant trend in BC risk (OR = 1.04; 95% CI: 1.01–1.06) with an increased risk of 4% by additional exposure. We did not find a significant association between BC and age at the first mammogram exposure and time since first exposure although we found an OR point estimate increasing as the age at first exposure decreases from age 40 to age 30 (OR = 1.52; 95% CI: 0.91–2.53). Among exposed women, under the assumption of linearity, we found a significant decrease in BC risk of 2% per additional year for age at first exposure (95% CI: 1–4%).
When analyses were performed according to the estrogen (ER) status of the tumor (Table 4), there were no differences in ORs between ER− and ER+ tumors for almost all mammogram exposure variables except for the number of mammograms, with a significant trend observed for women with ER+ tumors (8% per additional exposure, 95% CI: 4–11%).
As expected, having at least one D-PDV in a gene from Group “Reduced” is associated with a significant decrease in BC risk of 0.62 (95% CI: 0.50–0.77) compared to not having D-PDV in a gene from Group “Reduced”; having at least one D-PDV in a gene from Group “Independent” is associated with a non-significant BC risk of 1.02 (95% CI: 0.84–1.25), and having at least one D-PDV in a gene from Group “Increased” is associated with a significant increased BC risk of 1.98 (95% CI: 1.62–2.42) compared to not having D-PDV in a gene from Group “Increased” (Table 5). When stratifying women according to the group of altered genes, we found a difference in the association between having been exposed to mammograms and BC but not in the expected direction. The effect of mammograms’ exposure on BC risk was significantly higher for women carrying at least one variant in Group “Reduced” than for those carrying at least one variant in the other groups and especially in Group “Increased” (Pint = 0.02) (Table 6) (ever vs. never: “Reduced”(OR<0.9): OR = 2.17; “Independent”(0.9≤OR≤1.1): OR = 1.25; “Increased”(OR>1.1): OR = 0.92).
In the three groups, there was no significant association with the categorized number of mammograms although a significant trend was found, with an increased risk of 6% (95% CI: 2–10%) by additional exposure for both Group “Independent” and Group “Increased”. Additionally, we found significant multiplicative interactions for Group “Increased” (Pint = 0.020 and 0.019 for 1 to 4 and 5 to 9 exposures, respectively). Having been first exposed before age 30 increased the risk of BC significantly only in Group “Reduced” with an OR of 3.16 (95% CI: 1.01–9.89). For the three other age classes at first exposure, we found significant interactions for Group “Increased” (Pint = 0.019, 0.021, and 0.057, respectively). As for the whole study population, we did not find an association between BC and time since first exposure in any gene group. Additionally, as ~80% of participants carried more than one D-PDV (Table 1) and could be categorized into more than one DNA repair gene group, we hypothesized that variants might have additive effects and built a DNA repair VRS (Figure 2) and estimated the risk of BC per quintile of VRS. As expected, BC risk increased as VRS increased (Table 7). When stratifying women according to VRS quintiles, results for association between mammograms and BC confirmed the trend observed in the previous analyses, i.e., a decrease in BC risk associated with mammograms as DNA repair VRS increased (<ln(0.8): OR = 2.56; ≥ln(0.8) & <ln(0.95): OR = 3.88; ≥ln(0.95) & <ln(1.1): OR = 2.29; ≥ln(1.1) & <ln(1.5): OR = 1.24; ≥ln(1.5): OR = 0.30; Pint = 0.006) (Table 7). The same trend is observed as VRS increased when first exposed after age 40 or before age 40, but with point estimates higher for the latest group of women (Table 7).
Because we used a priori bounds for ORs for defining the DNA repair gene groups, we performed several sensitivity analyses using different bounds, and we found similar trends in the difference in the BC risk between groups (Supplemental Table S2).
We also performed a sensitivity analysis that included in the “Increased” Group only the genes that were found significantly (or borderline) associated with BC in our population [16] (i.e., ATM, CHEK2, PALB2, FANCM, MAST1) or confirmed as pathogenic or predicted to be pathogenic for BC by international consortia [19,20] (i.e., PALB2, TP53, CHEK2, PTEN, ATM, BARD1, MSH6, RAD51C, RAD51D). Only a few participants had never been exposed to mammography among those D-PDV carriers (28 and 24, respectively), and similar point estimates are however observed (ever vs. never: OR = 0.32; 95% CI: 0.07–1.54 and OR = 0.22; 95% CI: 0.04–1.23, respectively).
Finally, the magnitude and direction of the effect estimates based on analyses using an extra class for missing data or a multiple imputation strategy were similar (Table 3 and Table 8, Supplemental Tables S2 and S3).

4. Discussion

Overall, we found that mammography exposure, measured as ever vs. never, is not associated with the risk of developing a BC in women with a hereditary predisposition to BC unexplained by a BRCA1 or BRCA2 pathogenic variant. However, this risk increases with the number of mammograms, with an increase of 4% for each additional exposure. An increased risk is also suggested when first exposure occurs before age 40. To our knowledge, only three studies investigated diagnostic radiation exposure to the chest among women with a hereditary predisposition to BC and almost all without BRCA1/2 pathogenic variant [5,15,21], and only one considered mammograms by assessing the effect of age at first exposure and did not find evidence for an increased BC risk for women exposed before 37 years of age compared to women first exposed between the ages of 40 and 46 years [21]. Only four studies assessed the effect of a history of mammography among BRCA1/2 pathogenic variant carriers [2,4,9,10,11,12,13] and only one found an increased point estimate with a hazard ratio of 1.43 for women first exposed before age 30 [2], which is in line with our findings.
Surprisingly, our findings suggested that radiation delivered by mammograms double the risk of BC in women carrying a D-PDV in a DNA repair gene negatively associated with the risk of BC, while such an exposure appears not to be associated with BC in women carrying a D-PDV in a gene associated with an increased risk of BC. This finding is counterintuitive and not in line with our previous study [15], where we found a difference in the association between having been exposed to chest X-ray and BC with a significantly higher risk for women carrying at least one D-PDV in DNA repair genes associated with an increased risk of BC.
A possible weakness of our study is the use of nonrandomly selected friends or colleagues as controls. However, this approach offered the advantage of making it easier to identify suitable controls compared to random selection from the general population, and a higher comparability for unmeasured factors with, however, a likely indication bias for mammograms. Indeed, a strong family history of BC could be an indication for mammographic screening, especially at a young age. We investigated this potential bias away from the null by looking at the distribution of the family history by category of age at first exposure and did not find difference (chi2 = 23.3, df = 23, p = 0.438) (Supplemental Table S4).
However, to take into account potential confounders and indication biases, we adjusted the analyses for numerous variables like age at censure, birth cohort, being eligible for national screening, and the number of BC in the family at censure.
Because the mammography technique has evolved over time, as has the level of dose received for each image, we are aware that an estimation of the doses received at each examination according to when and where the examination was carried out would have generated more precise exposure data. However, retrospective studies are not able to trace and standardize mammography procedures through medical record reviews because of the difficulties in accessing medical records. For this reason, information on lifetime mammograms’ exposures was self-reported with accompanying potential recall biases and exposure misclassification (see also Supplemental Table S6). Therefore, even if some studies have shown that self-reported mammography data were widely reliable for epidemiologic research [22,23], we cannot totally rule out such a bias. Thus, to avoid the potential effect of exposure misclassification, indication, and recall biases, we performed case-only analyses and assessed the interaction effects between the groups of D-PDVs and mammograms’ exposure (under the assumption of independence). We found an ORinteraction = 1.62 (p = 0.10) between mammograms’ exposure and DNA repair genes potentially decreasing BC risk, ORinteraction = 0.84 (p = 0.48) between mammograms’ exposure and those with no effect, and ORinteraction = 0.68 (p = 0.14) between mammograms exposure and those with increasing BC risk). Even though not statistically significant, these results are in line with the observed trend in our case–control analyses.
One strength of our study is that it was conducted in a homogeneous sample of high-risk women and population controls with detailed lifetime information on mammograms. Our study is unique in that sequencing data for 113 DNA repair genes are available for an important subset of the study population [16]. Indeed, our study is the first to investigate not only the effect of mammograms but also the joint effect of mammogram exposure and D-PDVs in DNA repair genes in women at high risk of BC. We cannot exclude potential biases first due to the classification of the genes according to the ORs calculated in the same population and second due to a classification based on point estimates with, for many of them, insufficient power to characterize precisely their effects. However, the latter potential misclassification should be differential according to gene groups to lead to the observed differential association with mammograms, which is unlikely. Moreover, defining the group of genes with a point estimate falling in a large range of ORs around 1 as the group of genes “not associated with BC” might have an impact on the findings. Therefore, we performed numerous sensitivity analyses performing case-only analysis, changing the boundaries and assuming additivity of the effects of genes, and we found similar trends in the difference in the BC risk between groups.
Finally, the observed difference in the association between mammography and BC risk between the DNA repair gene groups cannot be explained by potential differences in characteristics like age at the diagnostic or educational level or even the number of BC in the family at censure (Supplemental Table S5).
Our exploratory findings showed that mammogram exposure (ever vs. never) does not increase BC risk, even among women carrying a rare D-PDV in a DNA repair gene potentially increasing BC risk, except when first exposure occurred before age 30. Surprisingly, a D-PDV in a DNA repair gene potentially decreasing BC risk may increase sensibility to mammograms’ exposure.
The evaluation of low doses in epidemiological studies is challenged by many potential limitations like lack of statistical power, unheeded time dependency, misclassification in exposure assessment, inappropriate evaluation of confounding risk factors, and failure to take hormesis into account [24]. Therefore, we acknowledge that both the lifetime numbers of mammograms as a surrogate for X-ray doses received at breasts and the potential misclassification of the D-PDVs might weaken our observations. However, our study is the first to investigate the joint effect of mammogram exposure and D-PDV in DNA worth checking our findings in further studies on larger populations, ideally with prospectively recorded detailed exposure data and evaluating other genes that could modify radiation sensitivity.

5. Conclusions

Our results showed that mammogram exposure (ever vs. never) does not increase BC risk, even among women carrying a D-PDV in a DNA repair gene potentially increasing BC risk, except when first exposure occurred before age 30. Surprisingly, D-PDVs in a DNA repair gene potentially decreasing BC risk may increase sensitivity to mammograms’ exposure. Further studies on larger populations are needed to verify our findings and to evaluate other genes that could modify radiation sensitivity. Even though the current data are clear in demonstrating that mammographic screening thanks to early diagnosis significantly reduces the risk of mortality from BC [25,26], identification of sub-populations that are more or less susceptible to ionizing radiation is much more important and clinically relevant.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/cancers17071062/s1, Supplemental methods. Table S1. Association of rare coding variants with breast cancer, for the 113 DNA repair genes sequenced in the GENESIS population [15,16]. Table S2. Sensitivity analyses with varying bounds of ORs for the definition of genetic variant group: effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure and time since first exposure. Table S3. Sensitivity analyses with varying bounds of ORs for the definition of genetic variant group: effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure and time since first exposure (Multiple Imputation). Table S4. Number of breast cancer in the family at censure according to age at mammography first exposure. Table S5. Characteristics of GENESIS participants according to DNA repair gene groups. Table S6. Cross table between lifetime number of mammograms and lifetime number of views. References [18,27,28,29,30] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, N.A.; data curation, M.R.-G. and M.-G.D.; formal analysis, M.R.-G. and N.A.; funding acquisition, F.L., D.S.-L. and N.A.; investigation, S.E.-M., D.L.G., J.B., N.M., M.B. and E.C.; methodology, N.A.; resources, C.A.-L., S.A.-B., P.B., V.B., B.B., O.C., M.C., J.C., C.C., I.C., C.D., H.D., A.F., S.F.-F., J.-P.F., M.G.-V., P.G., S.G., L.G., C.L., S.L.-D., J.-M.L., M.L., A.L., E.L., C.M.M., I.M., S.N., C.N., P.P., L.V.-B., F.S., J.T., A.T. and D.S.-L.; supervision, N.A.; writing—original draft, M.R.-G. and N.A.; writing—review and editing, M.R.-G., M.-G.D., F.L., D.S.-L. and N.A. All authors have read and agreed to the published version of the manuscript.

Funding

Brazilian National Council for the Improvement of Higher Education—CAPES, for the fellowship (process number: BEX 5852/15-3) to M.R. Guerra. Financial support for GENESIS was provided by the Ligue Nationale contre le Cancer (3 grants: PRE05/DSL and PRE07/DSL to D. Stoppa-Lyonnet; PRE11/NA to N. Andrieu), the French National Institute of Cancer (INCa, Grant b2008-029/LL-LC), and the comprehensive cancer center SiRIC (Site de Recherche Intégrée sur le Cancer: Grant INCa-DGOS-4654) to N. Andrieu. Sequencing was supported by the France Génomique National infrastructure, funded as part of the «Investissements d’Avenir» program managed by the Agence Nationale pour la Recherche (ANR-10-INBS-09), the Centre National de Recherche en Génomique Humaine (CNRGH), CEA, the Ligue Comité de Paris (grant RS15/75-78), and the Fondation ARC pour la recherche sur le cancer (grant PJA 20151203365).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the appropriate ethics committee (Comité de Protection des Personnes Ile-de-France III, 3 October 2006, agreement no. 2373).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data underlying this article will be shared upon reasonable request to the corresponding author.

Acknowledgments

We wish to thank the genetic epidemiology platform (the PIGE, Plateforme d’Investigation en Génétique et Epidémiologie: S. Eon-Marchais, M. Marcou, D. Le Gal, L. Toulemonde, J. Beauvallet, N. Mebirouk, E. Cavaciuti, A. Fescia), the biological resource center (C. Verny-Pierre, L. Barjhoux, V. Sornin, N. Mebirouk, F. Lesueur), and all the GENESIS collaborating cancer clinics (Clinique Sainte Catherine, Avignon: H. Dreyfus; Hôpital Saint Jacques, Besançon: M-A. Collonge-Rame; Institut Bergonié, Bordeaux: M. Longy, A. Floquet, E. Barouk-Simonet; CHU, Brest: S. Audebert; Centre François Baclesse, Caen: P. Berthet; Hôpital Dieu, Chambéry: S. Fert-Ferrer; Centre Jean Perrin, Clermont-Ferrand: Y-J. Bignon; Hôpital Pasteur, Colmar: J-M. Limacher; Hôpital d’Enfants CHU—Centre Georges François Leclerc, Dijon: L. Faivre-Olivier; CHU, Fort de France: O. Bera; CHU Albert Michallon, Grenoble: D. Leroux; Hôpital Flaubert, Le Havre: V. Layet; Centre Oscar Lambret, Lille: P. Vennin , C. Adenis; Hôpital Jeanne de Flandre, Lille: S. Lejeune-Dumoulin, S. Manouvier-Hanu; CHRU Dupuytren, Limoges: L. Venat-Bouvet; Centre Léon Bérard, Lyon: C. Lasset, V. Bonadona; Hôpital Edouard Herriot, Lyon: S. Giraud; Institut Paoli-Calmettes, Marseille: F. Eisinger, L. Huiart; Centre Val d’Aurelle—Paul Lamarque, Montpellier: I. Coupier; CHU Arnaud de Villeneuve, Montpellier: I. Coupier, P. Pujol; Centre René Gauducheau, Nantes: C. Delnatte; Centre Catherine de Sienne, Nantes: A. Lortholary; Centre Antoine Lacassagne, Nice: M. Frénay, V. Mari; Hôpital Caremeau, Nîmes: J. Chiesa; Réseau Oncogénétique Poitou Charente, Niort: P. Gesta; Institut Curie, Paris: D. Stoppa-Lyonnet, M. Gauthier-Villars, B. Buecher, A. de Pauw, C. Abadie, M. Belotti; Hôpital Saint-Louis, Paris: O. Cohen-Haguenauer; Centre Viggo-Petersen, Paris: F. Cornélis; Hôpital Tenon, Paris: A. Fajac; GH Pitié Salpétrière et Hôpital Beaujon, Paris: C. Colas, F. Soubrier, P. Hammel, A. Fajac; Institut Jean Godinot, Reims: C. Penet, T. D. Nguyen; Polyclinique Courlancy, Reims: L. Demange , C. Penet; Centre Eugène Marquis, Rennes: C. Dugast; Centre Henri Becquerel, Rouen: A. Chevrier, T. Frebourg ††, J. Tinat, I. Tennevet, A. Rossi; Hôpital René Huguenin/Institut Curie, Saint Cloud: C. Noguès, L. Demange , E. Mouret-Fourme; CHU, Saint-Etienne: F. Prieur; Centre Paul Strauss, Strasbourg: J-P. Fricker, H. Schuster; Hôpital Civil, Strasbourg: O. Caron, C. Maugard; Institut Claudius Regaud, Toulouse: L. Gladieff, V. Feillel; Hôpital Bretonneau, Tours: I. Mortemousque; Centre Alexis Vautrin, Vandoeuvre-les-Nancy: E. Luporsi; Hôpital de Bravois, Vandoeuvre-les-Nancy: P. Jonveaux; Gustave Roussy, Villejuif: A. Chompret , O. Caron). We wish to pay tribute to Olga M. Sinilnikova who was one of the initiators and principal investigators of GENESIS and who died prematurely on 30 June 2014. Deceased prematurely. †† Suddenly passed away on 13 March 2021.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

BCbreast cancer
BRCA1/2BRCA1 or BRCA2
CIconfidence interval
D-PDVdeleterious or predicted deleterious variant
DNAdeoxyribonucleic acid
ORodds ratio
VRSvariant risk score

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Figure 1. Recruitment process in GENESIS study.
Figure 1. Recruitment process in GENESIS study.
Cancers 17 01062 g001
Figure 2. DNA repair Variant Score Risk distribution. Legend: Horizontal axis: Variant Risk Scores; vertical axis: % participants; Blue: controls; Orange: cases. Note: For each participant, a Variant Risk Score (VRS = β1x1 + β2x2 +…+ β113x113) was built with βi per DNA repair gene minor allele mean effect, i.e., ln odds ratio (OR) for breast cancer, and xi equals 1 or 0 for being carrier of the i-th DNA repair gene minor allele or not, respectively.
Figure 2. DNA repair Variant Score Risk distribution. Legend: Horizontal axis: Variant Risk Scores; vertical axis: % participants; Blue: controls; Orange: cases. Note: For each participant, a Variant Risk Score (VRS = β1x1 + β2x2 +…+ β113x113) was built with βi per DNA repair gene minor allele mean effect, i.e., ln odds ratio (OR) for breast cancer, and xi equals 1 or 0 for being carrier of the i-th DNA repair gene minor allele or not, respectively.
Cancers 17 01062 g002
Table 1. Characteristics of GENESIS participants.
Table 1. Characteristics of GENESIS participants.
CharacteristicsCases
N = 1552
Controls
N = 1363
No.%No.%
Birth cohort
≤194548831.429421.6
1946–195979751.470651.8
≥196026717.236326.6
Age at censoring, years
Mean (SD)50.2 (9.3)55.8 (9.9)
≤4551333.120114.8
46–5033621.719714.5
51–6047330.548535.6
>6023014.848035.2
Education level
Intermediate/High78050.391667.2
Basic71446.043431.8
No graduated583.7120.9
Missing00.010.1
Body Mass Index
≥18.5 and <25101965.686963.8
<18.5694.5322.3
≥25 and <3034122.034525.3
≥301207.71178.6
Missing30.200.0
Smoking
No83253.668049.9
Current15910.215811.6
Past55035.451437.7
Missing110.7110.8
Number of full-term pregnancies
>244528.741130.2
1–292159.376356.0
018511.918713.7
Missing10.120.1
Number of breast cancers in the family
at censure a
None 42727.595970.4
181852.718713.7
≥230719.821615.9
Tumor estrogen receptors (ERs)
ER+81852.7
ER−16810.8
Missing56636.5
Total number of variants in DNA repair genes
019119.224120.7
129429.537432.2
226526.629125.0
315115.216013.8
4616.1645.5
5262.6282.4
650.540.3
730.300.0
810.100.0
Missing55535.820114.8
DNA repair gene group b
Group “Reduced”
072346.672152.9
≥127417.744132.4
Group “Independent”
057537.165948.4
≥142227.250336.9
Group “Increased”
042227.266748.9
≥157537.149536.3
a Excluding one affected sister when all affected sisters were diagnosed with breast cancer before the index case. b Individuals carrying at least one rare variant in one of the Gene Groups: Group “Reduced” (OR < 0.9); Group “Independent” (0.9 ≤ OR ≤ 1.1); Group “Increased” (OR > 1.1) as defined in Girard et al. [16].
Table 2. Mammography exposure characteristics.
Table 2. Mammography exposure characteristics.
Characteristics aCases
N = 1552
Controls
N = 1363
No.%No.%
Mammography
Never26617.11027.5
Ever127181.9125291.9
Missing151.090.7
Lifetime number of mammograms
1–461439.648335.4
5–940926.353739.4
≥1024816.023217.0
No exposure26617.11027.5
Missing151.090.7
Mean b (SD b) 6.04 (5.21)6.25 (4.19)
Lifetime number of mammogram views
1–92081.416512.1
10–1919812.822716.7
20–2915810.223317.1
30–391237.918913.9
≥4020613.323016.9
No exposure26617.11027.5
Missing39225.321715.9
Mean b (SD b)27.9 (25.2)27.7 (19.5)
Age at first exposure (years)
≥501479.529521.6
40–4948731.461845.3
30–3948331.126919.7
<301328.5594.3
No exposure26617.11027.5
Missing372.4201.5
Mean b (SD b)38.9 (8.52)43.1 (8.25)
Duration since first exposure (years)
≤526617.118813.8
6–1031520.329621.7
11–2044828.950637.1
>2022014.225118.4
No exposure26617.11027.5
Missing372.4201.5
Mean b (SD b)12.7 (8.28)13.9 (7.82)
a Lifetime exposures up to one year prior to diagnosis for cases and up to one year prior to the date of questionnaire completion for controls. b Among exposed.
Table 3. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure.
Table 3. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure.
Number ofOR a95% CIMultiple Imputation
CasesControls OR a95% CI
Mammography exposure
Never2661021 1
Ever127112520.990.69–1.430.980.68–1.42
Number of mammograms
02661021 1
1–46144831.040.72–1.511.020.70–1.49
5–94095370.820.54–1.240.820.55–1.24
≥102482321.360.86–2.161.360.86–2.16
Continuous (incl 0) 1.041.01–1.06
Age at first exposure, years b
No exposure2661021 1
≥501472950.560.34–0.910.560.34–0.91
40–494576180.670.45–0.990.670.45–0.99
30–394832691.220.82–1.801.200.81–1.77
<30132591.520.91–2.531.460.88–2.45
≥501472951 1
40–494576181.200.87–1.641.200.87–1.65
30–394832692.171.49–3.182.151.47–3.15
<30132592.711.60–4.582.631.55–4.46
No exposure2661021.791.10–2.901.791.10–2.93
Continuous (no exposure excluded) 0.980.96–0.99
Time since first exposure, years b
No exposure2661020.980.65–1.480.990.66–1.49
≤52661881 1
6–103152960.900.64–1.260.900.64–1.26
11–204485060.970.70–1.350.970.69–1.34
>202202511.170.77–1.781.140.75–1.75
Continuous (no exposure excluded) 1.021.01–1.04
Abbreviations: OR (95% CI): odds ratio (95% confidence interval); missing values coded as an additional category. a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), educational level (intermediate/high; basic; no graduated), BMI (18.5–24.9; <18.5; ≥25), smoking (no; current; past), and number of relatives with breast cancer (0; 1; ≥2), chest X-ray exposure (ever vs. never), being eligible for the national screening (yes/no), with missing included in reference categories for each variable when no multiple imputation. Chest X-ray exposure includes pulmonary radiological examinations in the field of preventive/occupational medicine or for lung disease, preoperative radiological examinations, and radiological examinations of heart and thoracic vessels for all the reported procedures. b Adjusted as a plus number of mammography (<10; ≥10).
Table 4. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by ER status of the breast tumor.
Table 4. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by ER status of the breast tumor.
ER−ER+
Number of Number of
Cases
N = 168
Controls
N = 1363
OR a95% CICases
N = 818
Controls
N = 1363
OR a95% CI
Mammography exposure
Never251021 1071021
Ever14012521.780.83–3.8370612521.420.92–2.19
Number of mammograms
0251021 671021
1–4774831.870.87–4.002444831.460.94–2.26
5–9505371.290.54–3.073145371.270.77–2.09
≥10132321.010.35–2.926052322.401.38–4.15
Continuous (incl 0) 0.990.93–1.06 1.081.04–1.11
Age at first exposure, years b
No exposure251021 1071021
≥50172951.210.42–3.461332950.780.43–1.41
40–49576181.350.58–3.141766180.910.57–1.47
30–39552692.190.99–4.832462691.671.05–2.65
<3011591.530.55–4.39138592.331.30–4.17
Continuous (no exposure excluded) 0.990.96–1.03 0.970.95–0.99
Time since first exposure, years b
No exposure251020.530.23–1.181071020.710.44–1.15
≤5361881 801881
6–10362960.850.46–1.572772960.990.67–1.47
11–20535060.980.53–1.792575061.040.71–1.52
>20152510.740.30–1.84792511.290.79–2.09
Continuous (no exposure excluded) 1.000.97–1.04 1.031.01–1.05
Abbreviations: OR (95% CI): odds ratio (95% confidence interval); missing values coded as an additional category. a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), educational level (intermediate/high; basic; no graduated), BMI (18.5–24.9; <18.5; ≥25), smoking (no; current; past), number of relatives with breast cancer (0; 1; ≥2), chest X-ray exposure (ever vs. never), being eligible for the national screening (yes/no), with missing included in reference categories for each variable. Chest X-ray exposure includes pulmonary radiological examinations in the field of preventive/occupational medicine or for lung disease, preoperative radiological examinations, and radiological examinations of heart and thoracic vessels for all the reported procedures. b Adjusted as a plus number of mammography (<10; ≥10).
Table 5. Main effect of variant carrier status on breast cancer.
Table 5. Main effect of variant carrier status on breast cancer.
DNA Repair Rare Variants Multiple Imputation for the Adjustment Variables
Number of
CasesControlsOR a95% CIOR a95% CI
“Reduced” b
No7237211 1
Yes2744410.620.50–0.770.620.50–0.77
Number of variants
07237211 1
12273410.66 0.53–0.840.670.53–0.84
244850.520.34–0.810.510.33–0.79
≥33150.260.07–1.030.250.06–1.01
Continuous 0.690.59–0.810.690.59–0.81
“Independent” c
No5756591 1
Yes4225031.020.84–1.251.030.84–1.25
Number of variants
05756591 1
13093890.970.78–1.210.970.78–1.21
296921.160.81–1.671.170.82–1.67
≥317221.320.62–2.801.320.62–2.77
Continuous 1.070.93–1.221.060.93–1.22
“Increased” d
No4226671 1
Yes5754951.981.62–2.421.981.62–2.42
Number of variants
04226671 1
13813571.861.49–2.321.811.45–2.26
21421161.991.44–2.741.951.42–2.68
≥352223.912.15–7.083.882.15–7.01
Continuous 1.521.34–1.711.511.34–1.71
Abbreviations: OR (95% CI): odds ratio (95% confidence interval). a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), mammography use (never; ever), educational level (intermediate/high; basic; not graduated), BMI (18.5–24.99; <18.5; ≥25 and <30; ≥30), smoking (no; current; past), and other DNA repair genes groups. b At least one variant in a gene from the “Reduced” group. c At least one variant in a gene from the “Independent” group. d At least one variant in a gene from the “Increased” group.
Table 6. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by DNA repair gene group.
Table 6. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by DNA repair gene group.
“Reduced”“Independent”“Increased”
Number of Number of Number of Pint
Cases
N = 274
Controls N = 441OR a95% CICases
N = 422
Controls
N = 503
OR a95% CICases
N = 575
Controls
N = 495
OR a95% CI“Independent”“Increased”
Mammography exposure
Never19321 44291 62281
Ever2514062.170.92–5.153774711.250.62–2.545094640.920.48–1.75ns0.021
Number of
mammograms
019321 44291 62281
1–41051492.270.95–5.411581621.340.66–2.742071580.990.52–1.90ns0.020
5–9921781.770.68–4.651312191.040.47–2.301802120.740.36–1.52ns0.019
≥1054792.340.81–6.7488902.300.96–5.54122941.490.67–3.30nsns
Continuous incl 0 1.030.98–1.08 1.061.02–1.10 1.061.02–1.10
Age at first exposure, years b
No exposure19321 44291 62281
≥50291001.650.53–5.08401111.010.39–2.62621110.750.32–1.73ns0.019
40–491041951.770.70–4.461542390.930.43–2.021932230.760.38–1.53ns0.021
30–3990882.220.91–5.54138971.480.70–3.111961020.990.50–1.94ns0.057
<3025183.161.01–9.8942231.610.64–4.0152211.200.51–2.80nsns
Continuous (no exposure excluded) 1.000.97–1.05 0.990.96–1.02 0.990.96–1.01
Time since first
exposure, years b
No exposure19320.390.16–0.9944290.690.32–1.5162280.980.48–2.010.0170.008
≤551611 62651 79581
6–1060910.740.37–1.47901110.830.45–1.511321080.840.48–1.46nsns
11–20981660.780.40–1.531481910.870.49–1.551901880.940.54–1.62nsns
>2039830.550.23–1.33741000.830.40–1.721021030.990.51–1.94ns0.051
Continuous (no exposure excluded) 0.990.96–1.03 1.010.98–1.04 1.010.99–1.04
Abbreviations: OR (95% CI): odds ratio (95% confidence interval); missing values coded as an additional category. a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), educational level (intermediate/high; basic; no graduated), BMI (18.5–24.9; <18.5; ≥25), smoking (no; current; past), chest X-ray exposure (ever vs. never), being eligible for the national screening (yes/no), number of relatives with breast cancer (0; 1; ≥2), and the two other DNA repair genes groups, with missing included in reference categories for each variable. Chest X-ray exposure includes pulmonary radiological examinations in the field of preventive/occupational medicine or for lung disease, preoperative radiological examinations, and radiological examinations of heart and thoracic vessels for all the reported procedures. b Adjusted as a plus number of mammography (<10; ≥10).
Table 7. Effect of mammography exposure according to the DNA repair Variant Score Risk.
Table 7. Effect of mammography exposure according to the DNA repair Variant Score Risk.
Number ofOR a95% CIp
CasesControls
Mammography exposure
No exposure92741
Ever and VRS < ln(0.8)832142.560.94–6.94
Ever and ln(0.8) ≤ VRS < ln(0.95)821343.881.39–10.8
Ever and ln(0.95) ≤ VRS < ln(1.1)2473322.291.07–4.92Phet = 0.104
Ever and ln(1.1) ≤ VRS < ln(1.5)2322431.240.54–2.87Pint b = 0.006
Ever and VRS ≥ ln(1.5)2541570.300.10–0.87
Age at first exposure, years
No exposure92741
≥40 and VRS < ln(0.95)872561.410.57–3.48
≥40 and ln(0.95) ≤ VRS < ln(1.1)1242451.050.50–2.19
≥40 and ln(1.1) ≤ VRS < ln(1.5)1221800.740.33–1.66ns
≥40 and VRS ≥ ln(1.5)1261090.330.14–0.82
<40 and VRS < ln(0.95)76902.601.03–6.55
<40 and ln(0.95) ≤ VRS < ln(1.1)116832.361.10–5.05
<40 and ln(1.1) ≤ VRS < ln(1.5)108621.590.68–3.71ns
<40 and VRS ≥ ln(1.5)126440.640.25–1.60
Variant Risk Score
<ln(0.8)28831
≥ln(0.8) and <ln(0.95)1492931.710.96–3.02
≥ln(0.95) and <ln(1.1)2723642.291.32–3.99
≥ln(1.1) and <ln(1.5)2572593.121.78–5.46
≥ln(1.5)2911635.713.23–10.1
Abbreviations: p: p value; Phet: P heterogeneity; Pint: P interaction; a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), educational level (intermediate/high; basic; no graduated), BMI (18.5–24.9; <18.5; ≥25), smoking (no; current; past), chest X-ray exposure (ever vs. never), being eligible for the national screening (yes/no), number of relatives with breast cancer (0; 1; ≥2), and VRS. Chest X-ray exposure includes pulmonary radiological examinations in the field of preventive/occupational medicine or for lung disease, preoperative radiological examinations, and radiological examinations of heart and thoracic vessels for all the reported procedures. b Interaction was tested with VRS as a continuous variable.
Table 8. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by DNA repair gene group (Multiple Imputation).
Table 8. Effect of lifetime mammography exposure (any exposure) on breast cancer risk according to the number of exposures, the age at first exposure, and time since first exposure by DNA repair gene group (Multiple Imputation).
“Reduced”“Independent”“Increased”
Number of Number of Number of
Cases
N = 274
Controls
N = 441
OR a95% CICases
N = 422
Controls
N = 503
OR a95% CICases
N = 575
Controls
N = 495
OR a95% CI
Mammography
exposure
Never19321 44291 62281
Ever2514062.110.89–5.023774711.220.61–2.505094640.890.46–1.70
Number of
mammograms
019321 44291 62281
1–452812.250.89–5.6663841.100.50–2.3987830.930.45–1.62
5–951971.830.71–4.69821121.210.56–2.601031110.730.37–1.45
≥10982052.460.93–6.511552431.560.72–3.402202361.370.67–2.82
Age at first exposure, years b
No exposure19321 44291 62281
≥50291001.520.60–4.89401110.750.30–1.85621110.640.28–1.47
40–491041951.720.68–4.351542390.810.38–1.741932230.660.33–1.32
30–3990882.120.85–5.29138971.360.65–2.871961020.880.44–1.74
<3025182.850.90–9.0442231.460.58–3.6852210.970.41–2.30
Time since first
exposure, years b
No exposure51610.420.16–1.0544290.760.35–1.6562281.060.51–2.18
≤519321 62651 79581
6–1060910.700.35–1.43901110.780.42–1.451321080.750.42–1.34
11–20981660.700.33–1.501481910.820.43–1.581901880.760.41–1.40
>2039830.560.23–1.39741001.080.35–1.651021031.000.50–1.98
Abbreviations: OR (95% CI): odds ratio (95% confidence interval); missing values coded as an additional category. a Adjusted for age at censoring, birth cohort (≤1945; 1946–1959; ≥1960), number of full-term pregnancies (>2; 1–2; 0), educational level (intermediate/high; basic; no graduated), BMI (18.5–24.9; <18.5; ≥25), smoking (no; current; past), chest X-ray exposure (ever vs. never), being eligible for the national screening (yes/no), number of relatives with breast cancer (0; 1; ≥2), and the two other DNA repair genes groups. Chest X-ray exposure includes pulmonary radiological examinations in the field of preventive/occupational medicine or for lung disease, preoperative radiological examinations, and radiological examinations of heart and thoracic vessels for all the reported procedures. b Adjusted as a plus number of mammography (<10; ≥10).
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Ribeiro-Guerra, M.; Dondon, M.-G.; Eon-Marchais, S.; Le Gal, D.; Beauvallet, J.; Mebirouk, N.; Belotti, M.; Cavaciuti, E.; Adenis-Lavignasse, C.; Audebert-Bellanger, S.; et al. Screening Mammography and Breast Cancer: Variation in Risk with Rare Deleterious or Predicted Deleterious Variants in DNA Repair Genes. Cancers 2025, 17, 1062. https://doi.org/10.3390/cancers17071062

AMA Style

Ribeiro-Guerra M, Dondon M-G, Eon-Marchais S, Le Gal D, Beauvallet J, Mebirouk N, Belotti M, Cavaciuti E, Adenis-Lavignasse C, Audebert-Bellanger S, et al. Screening Mammography and Breast Cancer: Variation in Risk with Rare Deleterious or Predicted Deleterious Variants in DNA Repair Genes. Cancers. 2025; 17(7):1062. https://doi.org/10.3390/cancers17071062

Chicago/Turabian Style

Ribeiro-Guerra, Maximiliano, Marie-Gabrielle Dondon, Séverine Eon-Marchais, Dorothée Le Gal, Juana Beauvallet, Noura Mebirouk, Muriel Belotti, Eve Cavaciuti, Claude Adenis-Lavignasse, Séverine Audebert-Bellanger, and et al. 2025. "Screening Mammography and Breast Cancer: Variation in Risk with Rare Deleterious or Predicted Deleterious Variants in DNA Repair Genes" Cancers 17, no. 7: 1062. https://doi.org/10.3390/cancers17071062

APA Style

Ribeiro-Guerra, M., Dondon, M.-G., Eon-Marchais, S., Le Gal, D., Beauvallet, J., Mebirouk, N., Belotti, M., Cavaciuti, E., Adenis-Lavignasse, C., Audebert-Bellanger, S., Berthet, P., Bonadona, V., Buecher, B., Caron, O., Cavaille, M., Chiesa, J., Colas, C., Coupier, I., Delnatte, C., ... Andrieu, N. (2025). Screening Mammography and Breast Cancer: Variation in Risk with Rare Deleterious or Predicted Deleterious Variants in DNA Repair Genes. Cancers, 17(7), 1062. https://doi.org/10.3390/cancers17071062

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