The aim of this study was to explore the association between occupational exposure to diesel exhaust and polycyclic aromatic hydrocarbons (PAH), respectively, and breast cancer subtypes.The study included 38 375 women <70 years with incident breast cancer, identified in the Danish Cancer Registry, and 5 breast cancer-free controls per case who were randomly selected from the Danish Civil Registration System and matched on year of birth. Full employment history was obtained for all study subjects from a nationwide pension fund, and exposure to diesel exhaust and PAH was assessed using a job exposure matrix. Conditional logistic regression was used for estimation of odds ratios (OR) with adjustment for reproductive factors and socioeconomic status.No noteworthy associations were observed for overall breast cancer in women exposed to diesel exhaust. However, diesel exhaust modestly elevated the risk of estrogen receptor negative breast tumors before age 50 . Duration– and dose–response relationships were further observed for this subtype in this age group. No notable risk patterns were generally observed for PAH exposure.Occupational exposure to diesel exhaust may increase the risk of early-onset estrogen receptor negative breast tumors in women. Future studies exploring this association are warranted. In addiMore recently, increasing levels of hormone-mimicking chemicals in the environment, including diesel exhaust and polycyclic aromatic hydrocarbons (PAH), have been suggested to play a role in breast cancer development  9). Com. Com9). The International Agency for Research on Cancer (IARC) has classifed both diesel exhaust and specific PAH as carcinogenic to humans (group 1), but this classification was primarily based on lung cancer  9). Mor. Mor9). Nevertheless, only a limited number of incidence studies have examined the effect of these occupational exposures on the risk of breast cancer among women –22. MoreThrough the use of lifetime information on employment history and a job exposure matrix (JEM), we conducted a nationwide registry-based case–control study exploring the association between occupational exposure to diesel exhaust and PAH, respectively, and the risk of subtypes of breast cancer in different groups of Danish women.Cases were initially identified in the national Danish Cancer Registry. Since 1943, this registry has systematically registered all cancers in Denmark and holds individual-based information on the date of diagnosis and details of pathological characteristics. Until 1978, the International Classification of Disease revision 7 (ICD-7) was used to categorize breast cancer. From 1978 to 2003, a converted version of ICD-10 was used and subsequently revision 10 (ICD-10) . EmploymThe Danish Breast Cancer Group (DBCG) database was founded in 1975 and has obtained comprehensive information on diagnostics, treatment and control since 1978 . We retrDemographic information on all residents in Denmark has been registered systematically in the Danish Civil Registration System since 1968 . Five coThe Danish Supplementary Pension Fund Register (ATP) was established in 1964 and has held compulsory membership for all wage earners working ≥9 hours/week. All jobs are registered with information on the unique PIN of the employee, date of start and end of each employment, company name, and a unique 8-digit company number for tax purposes. All information is kept even if a company closes or employees emigrate or die . StatistTo translate the industrial employments into exposure to diesel exhaust and PAH, respectively, a Danish JEM (NOCCA-DANJEM) was used, which includes metrics of the probability of job-specific exposure (P) and mean intensity level of exposure (L) for each relevant agent of exposure and occupational group. Further, this information is available for four periods of time .The JEM is based on the Nordic Occupational Cancer Study job exposure matrix (NOCCA-JEM) , and as In order to improve specificity, we categorized employment with a probability of exposure ≤20% and women employed less than one year as unexposed. As the JEM did not entail measurements of exposure after 1995, metrics of exposure probability and level for this period were assumed to reflect those in the most recent era (1985–1995).www.sjweh.fi/show_abstract.php?abstract_id=3923), figure S1 provides a directed acyclic graph (DAG) with an overview of the presumed causal interplay of risk factors for breast cancer, and obtainment of information on potential confounders was partly based on this. As a result, we included information from the Danish Civil Registration System on job title reflecting socioeconomic status (SES) and reproductive factors were included. Information on last known job title was self-reported and was initially attained from annual tax returns or official change of address forms. We grouped this information according to SES using the Danish Institute of Social Sciences’ definition: group 1 (highest status) included academics, group 2 included middle education, group 3 included shorter education, group 4 included skilled workers, and group 5 included unskilled workers  with corresponding 95% confidence intervals (CI), and all analyses were thereby conditioned on the matching variable, ie, year of birth. The full adjusted models further included age at first live birth, parity and work-related physical activity. Due to the relatively large proportion of women who had missing data on SES, we conducted a subsequent full case analysis including women with no missing data on this variable, which yielded analogous results . All analyses were stratified according to the women’s age at the index date , approximating menopausal status.We used different dimensions of exposure, including duration of exposure as well as cumulative exposure. Duration of exposure was calculated by summing the years of employment in all exposed calendar periods across all industries . Further, cumulative exposure was the product of the proportion exposed, intensity level and years worked in each exposed time period, which was summed over all exposed jobs in a woman’s occupational history. The categorization of cumulative exposure was based on the percentiles among the controls . Trend tests were conducted to explore duration- and dose–response relationships by using ordinal scores.Analyses exploring the impact of lag time  on the main results  as well as timing of exposure among parous women (before versus after first live birth) were conducted as well. In addition, the same analyses were conducted with a further stratification by ER status. We also conducted a stratified analysis exploring the effect of parous status on the risk of overall breast cancer in the two age groups. Lastly, as the population of women in the study were ≤70 years of age, the lag time for women exposed late in their work life would have been too short for potential breast tumors to develop. Hence, we conducted a sensitivity analysis excluding women exposed after age 50.All analyses were performed with Stata statistical software v 14.2 .A consequence of restricting the study population to women aged ≤70 years in 2016 was the relatively high proportion of breast cancer cases diagnosed before age 50. The distribution of known major breast cancer risk factors in both age groups was consistent with current knowledge, ie, cases were generally more likely than controls to have a higher SES, lower parity, and higher age at first full-term birth, although a slightly higher proportion had never been employed in work with heavy physical requirements . RegardiAdjustment for the selected potential confounders did not affect our results, which showed no striking elevation in the risk of breast cancer before or after age 50 years in women exposed to diesel exhaust and PAH . CumulatWhen conducting a further stratification by hormonal subtype of breast cancer, diesel exhaust was primarily associated with a modest increased risk of ER- tumors before age 50 . Before age 50, longer duration of exposure to diesel exhaust was also positively associated with the risk of ER- tumors and cumulative exposure was indicated to increase the risk of both ER- and ER+ breast cancers in a dose–response-like manner, but this observation was most pronounced for ER- tumors. In addition, women exposed >20 years prior to the index date had the highest risk of ER- tumors . Exposure to diesel exhaust after first live birth also increased the risk of ER- breast cancer before age 50 . After age 50, no convincing associations between diesel exhaust and hormonal subtypes of breast cancer were observed . SubsequThe present study showed no marked elevated risk of overall breast cancer diagnosed before or after age 50 following occupational exposure to diesel exhaust and PAH, respectively. However, diesel exhaust modestly elevated the risk of early-onset (before age 50) ER- tumors, and duration– and dose–response relationships were also observed for this particular subtype in this age group as well as a positive association with longer latency. Diesel exhaust exposure after first live birth increased the risk of early-onset ER- tumors. After age 50, diesel exhaust was associated with an increased risk of overall breast cancer among nulliparous women. No other notable positive risk patterns were observed for diesel exhaust exposure after age 50 as well as for PAH exposure in both age groups.Previous similar studies exploring the association between diesel exposure and breast cancer incidence in women are somewhat inconsistent. A Swedish cohort study using a similar JEM for the exposure assessment reported an increased risk of post-menopausal breast cancer with longer duration  and higher cumulative exposure  . Using tAn Australian case–control study used occupational experts to assess exposure to diesel exhaust and reported a modest increased risk of pre-menopausal breast cancer , but no risk elevations were observed for post-menopausal breast cancer . A FinisOur somewhat consistent findings of an increased risk of ER- tumors before age 50 among women exposed to diesel exhaust may be biologically plausible; diesel exhaust is classified as carcinogenic to humans  and chemIn this present study, nulliparous women exposed to diesel exhaust were observed to have an increased risk after age 50, which supports the hypotheses that undifferentiated breast cell structures in these women are more susceptible to carcinogenic exposures –14. To tOur explorations of a potential effect of PAH exposure on breast cancer risk did not yield any convincing positive findings. This is generally not supported by previous incidence studies indicating an increased breast cancer risk among women with occupational PAH exposure , 19, 21.More importantly, it was not possible to account for potential confounding due to certain lifestyle factors such as obesity, alcohol consumption, physical inactivity, use of oral contraceptives and hormone replacement therapy . As seveThe exposures under study are also found in the general environment, however, normally to a lower extent than in some sectors of the working environment. Not being able to account for individual level exposure outside work is generally considered to be a limitation in occupational studies, including this one.The strengths of this study include the large nationwide population-based case–control design, which allowed us to evaluate the risk of a high number of incident breast cancer cases, including specific subtypes, with life-time occupational exposures. Moreover, a uniqueness of the study was its unusual high number of breast cancer cases in relatively young women allowing us to explore rare subtypes by different age groups. Using reliable registry data on occupational history and a validated JEM with objective workplace exposure measurements and features such as probability and intensity scores in different time periods, which refined the exposure assessment, were also considered major strengths. Especially information on lifetime occupational history on Danish women with historical high workforce participation rates  allowed This study shows no notable association between occupational diesel exhaust and overall breast cancer risk, and the same applies to PAH exposure. However, our results show a pattern indicating that diesel exhaust may increase the risk of ER- tumors in women before 50 years. Future studies on this issue that differentiate between subtypes of breast cancer in different age groups and explore the effect of reproductive status and exposure time windows are needed.


The incidence of breast cancer is increasing in Pakistan as well as globally. Awareness of women about breast cancer plays a cornerstone role in its early detection, better management, and prevention. Keeping this in mind, a cross-sectional study was carried out to assess the awareness of female university students about breast cancer’s risk factors, signs and symptoms, and breast cancer examination. The data was collected from female university students studying in Pakistan. A total of 774 participants completed the survey and recorded their responses on an online pre-tested self-administered questionnaire. Only 29.8% of the participants have identified breast cancer history in their first-degree relatives as a risk factor. Moreover, 14.1% of the participant considered that the use of oral contraceptives for more than 5 years can increase the risk of developing breast cancer. In addition, inward pulled nipple, wounds around the nipple, and abrupt changes in the breast size were considered as the sign and symptoms of breast cancer by 25.2%, 25.7%, and 31.7% of the participants, respectively. Moreover, only 20.9% of the participants identified the correct year for starting breast cancer examination and 44.4% of the respondents marked that mammography should be initiated after 40 years. Overall, the university female students of Pakistan were poorly aware of breast cancer’s risk factors, signs and symptoms, and breast examination. This study has highlighted the need for initiation of aggressive strategies regarding breast cancer awareness in both the literate and illiterate female population of Pakistan. Breast cancer is a disease in which breast cells start an uncontrolled growth and produce an undifferentiated cell mass . The AmeIt has been reported that increasing age is highly associated with the incidence of breast cancer . AdditioBreast self-examination (BSE), clinical breast examination, and mammography are the most widely used screening techniques . BSE is Globally, the ratio of breast cancer cases is increasing day by day and it is the second leading cause of mortality . In 2020Awareness about the disease play important role in its early diagnosis. This awareness helps the population to avoid risk factors associated with the disease. A heightened awareness of breast cancer disease can aid the women in adherence to its screening guidelines. This adherence will lead the population to the early diagnosis of breast cancer that will help the healthcare provider for better management and also will increase the surveillance rate of the patients. The university female students were less touched in the previous reports from Pakistan, and they were limited to a single location and specific domain like some were focused on risk factors other were sign and symptoms and breast cancer examination –19. TherA cross-sectional approach was used in the current study. The study participants were university female students that were enrolled in the different universities of Pakistan. The students that were Pakistani nationals, had ages greater than 18 years, and who gave their consent to participate were included in the study. The term undergraduate includes bachelor programs (BS), while the post-graduate includes master (MPhil/MS), and doctorate programs (Ph.D.) in the current study.A self-administered questionnaire was developed based on previous reports –22. The The questionnaire was validated through face validation followed by a pilot study (N = 75). The Cronbach’s alpha value of 0.81 was obtained, which indicated a good internal consistency.A total of 774 respondents have completed the survey that enrolled in different universities located in four provinces  of Pakistan through an online survey. Google forms  were used to create the pre-tested questionnaire, and a link was shared with participants via social media platforms . An online written informed consent was taken from each participant before recruitment in the study. Participant confidentiality was maintained throughout the study. The hard file was kept in the department lab locker and the soft file was maintained in the password-protected folder. The online data was collected as per the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) guidelines , 24.The current study was reviewed and approved by the Department of Pharmacy Practice, Faculty of Pharmacy, BZU Multan (Reference No: Acad/PRAC/21/04) and conducted as per the Declaration of Helsinki. The current study was reported according to “The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)” guidelines .The statistical package for social science (SPSS)  was used for data analysis. The descriptive statistics and cross-tabulation were performed and the frequency and percentage were calculated to illustrate categorical variables. The Chi-square test was applied to assess the association between study questions and education level. A p-value ≤ 0.05 was considered significant for all the statistical analysis. The Bonferroni correction was used to counteract with multiple comparisons.A total of 774 participants were participated in the study out of 852 and the response rate was 90.2% as shown in Regarding the breast cancer risk factors, most of the participants were unaware of the risk factors associated with breast cancer. only a small portion of the respondents was known to risk factors of breast cancer like the history of breast cancer in their first-degree relatives (29.8%) and benign breast disease (28%), use of oral contraceptives more than 5 years (14.1%), and after menopause use of hormone therapies (19.5%). More than one-quarter of the participants considered radiation as a risk factor for breast cancer (27.9%). Furthermore, risk factors such as a history of breast cancer (p = 0.005), benign breast illnesses (p = 0.008), hormone therapy after menopause (p = 0.009), and radiation at a younger age (p = 0.038) were found to differ significantly across educational levels. The undergraduate females were more knowledgeable about risk factors of breast cancer including the history of breast cancer in their relatives (UG: 76.2% vs PG: 23.8%) and benign diseases (UG: 79.7% vs PG: 20.3%), use hormone therapy (UG: 72.2% vs PG: 27.8%), and high exposure to radiations (UG: 76.9% vs PG: 23.1%) as shown in A small number of the participants considered early menstruation (19.1%), late menopause (16.5%), and giving birth for the first time after age 30 (14%) as risk factors for breast cancer. The female that enrolled in undergraduate programs had more knowledge about the early menstruation at age 12 as a risk factor for breast cancer . The detail can be seen in A poor knowledge about breast cancer’s risk factors was reported by the participants. As a small number of participants considered overweight and obesity (34.9%), lack of breastfeeding (28.3%), and low consumption of vegetables and fruits (43.5%) as the risks to breast cancer. Stress , high intake of red meat  and fatty food  were highly considered as risk factors for breast cancer by female undergraduate students. Participants’ Knowledge of breast cancer’s risk factors related to physical activities and lifestyle can be seen in Most of the participants were unknown to the signs and symptoms of breast cancer. The sign and symptoms like painless and palpable breast lump, painless mass under the armpit, and bleeding or discharge from the nipple were reported by 38.6%, 35.5%, and 28.4% of the participant, respectively. In addition, inward pulled nipple, wound around the nipple, and abrupt changes in the breast size were considered as the sign and symptoms by 25.2%, 25.7%, and 31.7% of the participants, respectively. There was a significant difference between undergraduate and postgraduate female participants regarding painless and palpable breast lump , painless mass under armpit , and wounds around the nipple . The detail can be seen in Regarding the best time to start the breast exam by the doctor or midwife, only 20.9% of the participants identified the correct year for starting breast cancer examination. Most of the participants correctly favored that mammography should be initiated after 40 years (44.4%). Majority of the participant was of the opinion that breast self-examination should be started after 20 years (80%) and should perform on monthly basis (71.5%). The undergraduate female participants were more in favor to start self-breast examination  and mammography  should instructed after 20 years as shown in The current study was conducted to assess the knowledge and understandings of university female students about breast cancer. The participants reported overall poor knowledge regarding breast cancer risk factors, and signs and symptoms. Additionally, the knowledge was also poor regarding the best time for examination of breast cancer.A good knowledge of risk factors can help in the prevention of breast cancer in the female population . The hisThe early detection of breast cancer in females can only be possible when they are familiar with their signs and symptoms. In the current study, participants were little known to the signs and symptoms of breast cancer that include painless and palpable breast lump (38.6%), and painless mass under the armpit (35.5%). A comparatively higher knowledge about these signs and symptoms was reported from Ethiopia   and in aThe knowledge of screening tests for breast cancer has a vital importance in the early detection of cancer. The United States Preventive Services Task Force has recommended that women with an age range of 20–30 years should perform clinical breast examination by a healthcare provider every three years while women having age greater than 40 years should perform every year. The current study result was comparable with the recommendation as most of the participants suggested that clinical breast examination by a healthcare provider should be started after the age of 20 years (55.6%). While this frequency was low as compared to the study reported from nurses in the United Arab Emirates (96.1%). The difference in knowledge may be due to the study participants, as the study respondents were nurses which may have greater clinical experience.The social norms of the Pakistani population have a significant effect on the participant’s knowledge. For instance, it has been reported that Pakistan women feel shyness, personal modesty, and embarrassment during the examination of breasts, especially in rural regions. The open discussion of issues, related to the breast, between women, mothers, daughters, and spouses or the extended family system is considered as a social taboo. This means that breast cancer is a socially unacceptable disease. Moreover, socioeconomic and cultural factors, such as age, employment status, lack of information, fear of surgery, trust in traditional therapies, and spiritual healing, lead the women in Pakistan to seek health facilities only at the end stages of breast cancer. Therefore, these factors are considered as a major barrier to breast cancer screening. That’s why they are diagnosed at the last stage when there is the only option of surgery –38. SimiThis study was subjected to various limitations. Firstly, the study was based on the questionnaire, therefore recall biases cannot be ignored. Secondly, the study population was university female students, however, the responses may be different from the illiterate population that was not included in the current study. Thirdly, as the majority of the participants are from the biological and medical backgrounds, therefore, response bias cannot be completely neglected. Lastly, the current study utilized online data collection, where responses from the population having no access to the internet were not collected.In summary, university female students reported a poor knowledge about breast cancer’s risk factors, signs and symptoms, and breast examination. Interestingly, although most of the participants were from pharmaceutical and medical sciences, still the knowledge was poor. It has been seen that good knowledge about breast cancer’s risk factors, signs and symptoms, and self, and clinical examination practices play an important role in the early detection of this cancer. The early diagnosis increases the chance of recovery and also improves the surveillance rate of breast cancer patients. In contrast, the current study showed poor knowledge about breast cancer that increases the risk of a diagnosis of this cancer at later stages. The late diagnosis negatively impacts the recovery and surveillance of breast cancer patients and also increases the burden on the healthcare system. Therefore, the government health administration and other related bodies  should play a role in awareness of the general public by arranging seminars. Moreover, it is suggested that awareness weeks in the educational sectors should be included in their policies. In addition, the breast cancer examination techniques should be included in their course content. Moreover, the government should encourage the health professional to spread the awareness among general population and the health facilities should be accessible to the population living in the countryside.S1 File(PDF)Click here for additional data file.


Background: People consume nitrates, nitrites, nitrosamines, and NOCs compounds primarily through processed food. Many studies have yielded inconclusive results regarding the association between cancer and dietary intakes of nitrates and nitrites. This study aimed to quantify these associations across the reported literature thus far. Methods: We performed a systematic review following PRISMA and MOOSE guidelines. A literature search was performed using Web of Science, Embase, PubMed, the Cochrane library, and google scholar up to January 2020. STATA version 12.0 was used to conduct meta-regression and a two-stage meta-analysis. Results: A total of 41 articles with 13 different cancer sites were used for analysis. Of these 13 cancer types/sites, meta-regression analysis showed that bladder and stomach cancer risk was greater, and that pancreatic cancer risk was lower with increasing nitrite intakes. Kidney and bladder cancer risk were both lower with increasing nitrate intakes. When comparing highest to lowest (reference) categories of intake, meta-analysis of studies showed that high nitrate intake was associated with an increased risk of thyroid cancer . When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma . No other associations between cancer risk and dietary intakes of nitrates or nitrites were observed. Conclusion: This study showed varied associations between site-specific cancer risks and dietary intakes of nitrate and nitrite. Glioma, bladder, and stomach cancer risks were higher and pancreatic cancer risk was lower with higher nitrite intakes, and thyroid cancer risk was higher and kidney cancer risk lower with higher nitrate intakes. These data suggest type- and site-specific effects of cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.  Cancer is a leading cause of death worldwide, accounting for nearly 10.0 million (approximately one in six) deaths, in 2020 . N-nitroso compounds (NOC) [Over the past few years, new evidence has led a paradigm change in our understanding of the role of both dietary nitrate and nitrite on human health, particularly in relation to cancer risk ,5,6,7. Hds (NOC) ,4,8. Nowds (NOC) ,10. Numeds (NOC) ,12,13 ands (NOC) ,15,16,17Nitrates and nitrites are also widely used in food processing, such as in processed meats  where they are used to reduce microbial spoilage and preserve meat products ,19. HighDespite the carcinogenic potential of NOCs, some epidemiologic studies found no association between dietary nitrate, nitrite, and NOC intake and cancer in humans ,35,36. CMeta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modeled using a between-study variance parameter, is usually an additional aim . Meta-reWe performed a systematic review following PRISMA and MOOSE guidelines. This study evaluated the association and clarified the relationship between dietary nitrate, nitrite, and selected, site-specific cancers. Two investigators independently searched literature on the Web of Science, Embase, PubMed, the Cochrane library, and google scholar up to January 2020. 3-N OR NO3- OR nitrite OR nitrites OR N-nitroso compounds OR NO2-N OR NO2- OR sodium nitrate OR NaNO3 OR sodium nitrite OR NaNO2 OR ammonium nitrate OR NH4NO3 OR nitrosamine OR Nitrite amine OR NH2NO2 OR DMNA OR NDMA OR NDBA OR NMEA OR NDEA OR NPIP OR NPYR OR NMOR OR NDPA) AND  AND (Dietary OR Diet OR food). The full search strategy is provided in the online A literature search was performed on all the databases by using the following keywords: . Exclusion criteria: All articles with animal experiments, articles not published in English, articles with a short commentary, short notes, no data or no records, or incomplete results and letters were excluded. Search results were screened for inclusion and exclusion criteria by four authors.Qualitative analysis: the data were extracted using a self-developed data extraction form. For selected studies, data included the study characteristics: first author, year published and country, study design, exposure categories (nitrate and nitrite intake mg/day), reported Risk ratios (RR), odds ratios (OR), and hazard ratios (HR) with their 95% CIs, cancer sites, and adjustment. Quantitative analysis: the data included: Nitrate dosages and nitrite dosages from dietary intake; OR/RR/HR, with their 95% CI for each category of exposure.Data collection and quality assessment processes were performed by four authors , and any disagreement was settled by group discussion. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the quality of the included studies. Scores ranged from 0 to 9; studies with a score ≥7 were seen as high-quality studies .Software: STATA version 12.0  was used to conduct meta-regression and meta-analysis ). .Analysis of data: All nitrate and nitrite dosage, and their related compounds, OR, RR, and HR, with 95% CIs were extracted . The RRs and HRs were assumed to be the accurate estimates of ORs. The median intake of nitrate and nitrite dosage was calculated from the range given, (formula = lowest dosage (lower limit) + highest dosage (upper limit) divided by two in each given quartile). When the median intake was given, the data was used directly. When the interval of a quartile of any category of nitrate or nitrite dosage was not provided, the width of the class interval of quartile before this quartile was used to calculate and estimate the interval, . Logarithm of the ORs (LogOR) was calculated. Standard error was also calculated,  divided by 3.92) using Microsoft Office Excel.Conversion of nitrate units and nitrite dosage: mg/day was the standard unit for nitrite and nitrate dosage from dietary intake used for analysis because most of the articles used these units in their analyses. The recommended daily calorie intake in the US is around 2500 kcal for men and 2000 kcal for women ; for thip ≤ 0.05. A sensitivity analysis was performed whereby extreme dosages were removed, including their ORs. Any cancer site that had less than three studies was not included in the meta-regression (these included ovarian cancer and uterus corpus).Meta-regression: The parameters for meta-regression calculation were the dependent variable (y) = LogOR; covariates = median (the median intake of nitrate and nitrite dosage); and within-study variability = standard error was used for analysis. Meta-regression analysis was conducted to determine the associations between nitrate and nitrite exposure and cancer risk. A meta-regression coefficient was considered statistically significant at p  >  0.05 or I2 ≤  50%), we used a fixed-effects analysis described by Mantel-Haenszel [Meta-analysis: Meta-analysis was performed using two different approaches. The first approach compared the effect sizes (ORs (95% CI)) for site-specific cancer risk of the highest category of dietary nitrate and nitrite against the lowest (reference) category. were compared. The second approach pooled the effect sizes (ORs (95% CI)) for site-specific cancer risk in all intake categories and compared it against the lowest (reference) category. When I2 statistics do not present a notable heterogeneity  and stomach cancers  were positively associated with the dosage of dietary nitrite   and bladder cancers  were inversely associated . There was no evidence of association between the risk of cancers of the reproductive organs (ovary and uterine corpus), breast, non-Hodgkin’s lymphoma, stomach, pancreatic, esophageal, bladder, kidney, colon, or rectal cancer and dietary nitrate and nitrite (When comparing highest to lowest (reference) categories of intake, meta-analysis of studies showed that high nitrate intake was associated with an increased risk of thyroid cancer  . Little  nitrite . p = 0.661). There was no evidence of association between the risk of cancers of the reproductive organs (ovary and uterine corpus), breast, non-Hodgkin’s lymphoma, stomach, pancreatic, esophageal, bladder, kidney, colon and rectal cancer, and dietary nitrate or nitrite consumption.When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma  . Little All results are shown in p = 0.019; Begg, p = 0.016; p = 0.000; Begg, p = 0.006; p = 0.000; Begg, p = 0.000; p = 0.027; p = 0.141). The Begg’s test showed statistical evidence of bias for glioma and nitrates . No other evidence of bias was indicated (Both the Egger and Begg tests of bias indicated asymmetry (publication bias) for both cancer of the kidney  categories of intake, meta-analysis showed that high nitrate intake was associated with an increased risk of thyroid cancer . When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma . Meta-regression analysis showed that bladder and stomach cancer risk was greater, and that pancreatic cancer risk was lower, with increasing nitrite intakes. Kidney and bladder cancer risk were both lower with increasing nitrate intakes. No other associations between cancer risk and dietary intakes of nitrates or nitrites were observed. These data suggest type- and site-specific effects on cancer risk, including protective effects, from dietary intakes of nitrate and nitrite. These findings from a meta-analysis of the literature are an important contribution, as individual studies on their own have reported seemingly inconsistent findings. Some studies have shown positive, and others, negative associations with cancer risk at different intakes of dietary nitrate and nitrite. For example, Kilfoya et al.  reportedp-trend = 0.06). Positive associations were observed between N-nitrosodimethylamine intake and esophageal squamous cell carcinoma (ESCC) risk  and gastric non-cardia adenocarcinoma (GNCA) risk  in men. Meanwhile Cross et al., 2011, [Many studies have shown that a long period of exposure/daily dietary intake that contains nitrate, nitrite, and NOC compounds can lead to specific health issues, but these results are still contradictory. Keszei, et al. (2013)  conducte., 2011,  conductep = 0.63) and vitamin E (p = 0.62), did not appear to be significant effect modifiers in the association between nitrate exposure from food and bladder cancer risk. Catsburg et al., (2014) [p trend = 0.007). Some studies showed no association at all [Individually, most of the research articles included in this systematic review did not find any association between nitrate and nitrite and any type of cancer in humans. However, when analyzed together, greater exposure to dietary nitrate and nitrite increased the risk of getting some cancers  and decreased the risk of getting others (pancreatic and kidney). Most of these cancers can be considered cancers of the digestive system. The risk of these types of cancers have been shown to be modified by other dietary and lifestyle factors. For example, some studies have shown an inverse association of vegetable and fruit intake with these cancers’ risk . Other s, (2014)  showed tn at all ,67,80. Notwithstanding the null findings of some studies, it is widely accepted that it is important that people consume diets high in fresh fruits and vegetables that contain a lot of vitamins and essential minerals and reduce meat, fatty food, and processed food intake to improve their health. This may be important in modifying any harmful effects of dietary nitrates and nitrites on particularly susceptible tissues in the digestive system and elsewhere in the body. Cases of cancer are considered to be linked to nutritional factors. Scientific evidence suggests that food/diet is most convincingly linked to cancer of the lung, stomach, rectum, colon, pharynx, nasopharynx, esophagus, and mouth ,82,83. FMost of the studies included in this systematic review were conducted in Europe and the U.S., and very few or no studies from South America, Africa, Australia, and Asia were retrieved. Many studies and awareness of early screening for different types of cancers are needed in South America, Africa, Australia, and Asia to better understand this issue on a larger scale with different demographics. A proper and comprehensive assessment of nitrate and nitrite from dietary intake, including inhibitors of endogenous nitrosation and intakes of antioxidants, are needed in future studies. Many studies lacked information about study participants’ water consumption and dietary intake that contain nitrate and nitrite simultaneously, which may be essential to better analyze the links between dietary intakes and cancers. Future studies should also pay close attention to the different duration or lengths (years) of food intake with nitrite and nitrate, especially to understand the effects of exposure. There is still no precise standard maximum contaminant level for nitrate and nitrite in food to protect people from non-communicable diseases like cancer. This might be because noncommunicable diseases, such as cancer, can take a long time to occur and the casualty has not yet been fully established. Using two different statistical analyses for each cancer site is the strength of this research. It can help to better understand the robustness of the associations. However, the study’s limitations are as follows; first, very few articles were available for each type of cancer, some with three or fewer studies, and so the results for this analysis should be treated with caution. More detailed, well-designed studies with accurate and precise information about study participants’ food intake and other lifestyle factors may be essential to more accurately estimate associated risk. Secondly, this research was unable to adjust for potential confounders or examine effect modification  due to lack of available data in the included studies. Some studies included vitamin C, D, and E, and folate and red/processed meat intake; however, most did not. We recommend that such research should include dietary vitamin C, D, and E, intake, as well as folate intake, polyphenols, red/processed meat, heme iron intake, and other nutrients/minerals and compounds  from food and drinking water that could affect nitrosation in the body, to enable more precise estimation of risks and more sophisticated analyses.Third, there was a wide range of nitrate and nitrite intake values from different studies, which resulted in different ranges across the analyses performed in this meta-analysis. For example, dietary nitrite ranged from 0 to 2.4 mg/day in the analysis against bladder cancer risk and from 0 to 22 mg/day in the analysis against stomach cancer risk. This variation in range in the independent variable across different analyses could be partly responsible for the variation in association with the dependent variables (the different site-specific cancer risks) observed in this study. A lack of standardized units for reporting dietary intakes of nitrates and nitrites in the literature made it necessary to convert the data to a common unit for meta-regression. Whilst this is not a major limitation, it has the potential to introduce error. Moreover, a lack of standardized units might pose a problem to efforts to implement a limit or precise standard maximum contaminant level to protect people from health risks of having a type of cancer. Lastly, many cohort and case-control studies should be done in different parts of the world to understand this topic better, especially noting other confounding factors and nutrient intake.This study showed varied associations between site-specific cancer risks and dietary intakes of nitrate and nitrite. Glioma, bladder, and stomach cancer risks were higher, but pancreatic cancer risk was lower with higher nitrite intakes. Thyroid cancer risk was higher, but kidney and bladder cancer risks were lower with higher nitrate intakes. These data suggest type- and site-specific effects of cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.


These variants were used to investigate causal relationships with breast  and prostate  cancer using univariable, bidirectional and multivariable MR. In females, we found evidence for: I) Reduced risk of breast cancer per category increase in morning-preference ; II) Increased risk of breast cancer per SD increase in bioavailable testosterone  and total testosterone ; III) Bidirectional effects between morning-preference and both bioavailable and total testosterone . In males, we found evidence for: I) Reduced risk of prostate cancer per category increase in morning-preference  and II) Increased risk of prostate cancer per SD increase in bioavailable testosterone . No bidirectional effects were found between morning-preference and testosterone in males. While testosterone levels were causally implicated with both chronotype and cancer, there was inconsistent evidence for testosterone as a mediator of the relationship. The protective effect of morning-preference on both breast and prostate cancer is clinically interesting, although it may be difficult to effectively modify chronotype. Further studies are needed to investigate other potentially modifiable intermediates.Morning-preference chronotype has been found to be protective against breast and prostate cancer. Sex hormones have been implicated in relation to chronotype and the development of both cancers. This study aimed to assess whether sex hormones confound or mediate the effect of chronotype on breast and prostate cancer using a Mendelian Randomization (MR) framework. Genetic variants associated with chronotype and sex hormones  (p<5×10 Although previous studies have demonstrated that morning-preference chronotype is associated with reduced breast and prostate cancer risk, the role of sex hormones in this relationship has yet to be elucidated. In this study we use genetic variants strongly associated with morning-preference chronotype, total testosterone, bioavailable testosterone, sex-hormone binding globulin and oestradiol to explore the potential of these sex hormones to act as either mediators or confounders of this relationship. The findings of this study implicate testosterone as a potential mediator of the relationship between chronotype and both prostate and breast cancer risk, although results were inconsistent between methods. As such, further studies are warranted to better understand the mechanisms underlying this relationship in order to inform the development of sleep-based intervention studies that may help to reduce breast and prostate cancer risk in high-risk populations. Breast and prostate cancers are hormonally related tumours with a significant burden of morbidity and mortality: an estimated 2.1 million women and 1.3 million men were diagnosed with these conditions in 2018, with age-standardised mortality rates of 13.0 and 7.6 per 100,000 respectively , 5, theyCircadian rhythms underlying the sleep-wake cycle are implicated in cancer development, particularly in breast and prostate cancers , 8. VariAn individual’s chronotype is largely determined by genetic variants , externaHormones, such as cortisol, melatonin and some sex steroids, have previously been studied in relation to chronotype –21 and sMR is an approach which uses genetic variants robustly associated with exposures to estimate potential causal effects on outcomes. It attempts to overcome some potential limitations of conventional analyses used in observational studies, including confounding and reverse causation, though has additional potential biases –26. UsinUsing two-sample MR, recent studies have reported a 7% reduction in breast cancer risk  and a 9%Regarding the effect of chronotype on breast cancer, in our previous study, we used results from both one-sample and two-sample MR analysis to support the multivariable regression result of a protective causal effect of morning chronotype on breast cancer risk  .The aims of this study were to use two-sample MR to explore whether: (i) the causal effect of chronotype on breast cancer risk found previously  remains Our overall strategy was to perform a series of two-sample MR analyses. First, univariable MR (uvMR) was used to estimate the effects of: chronotype on breast and prostate cancer risk step 1, ; and sexSummary genetic data for chronotype and sex hormones were obtained from GWAS conducted in the UK Biobank (UKB). UKB identified the chronotype of each participant with the question “do you consider yourself to be” and six possible options: definitely an ‘evening’ person; more an ‘evening’ than a ‘morning’ person; neither (do not know); more a ‘morning’ person than ‘evening’ person; definitely a ‘morning’ person and prefer not to answer. Participants who chose ‘prefer not to answer’ were excluded and the remaining categories were treated as a score to give per category outcomes from definitely an ‘evening’ person to definitely a ‘morning’ person. More details on the study, the genotyping procedure, and the data sources for chronotype and the sex hormones are described in While GWAS summary statistics for both chronotype and sex hormones using data from UK Biobank currently exist , 35, we For breast and prostate cancer outcomes, genome-wide association studies (GWAS) summary data were obtained from the Breast Cancer Association Consortium (BCAC) , 37; andThe GWAS of overall breast cancer included 133,384 cases and 113,789 controls from 67 studies, using data from OncoArray and iCOGS arrays which were meta-analysed . SummaryThe GWAS for prostate cancer included data from the PRACTICAL  and ELLIPSE  consortia , 39. TheWe next identified genetic instruments for chronotype and sex hormones, for which single nucleotide polymorphism (SNP)-exposure estimates were obtained from the sex-specific GWAS for chronotype and sex hormones in UK Biobank.−8) in the sex specific GWAS within UKB. This will have less statistical power and may be more prone to weak instrument bias but may be a more relevant sex-specific instrument. Following LD-clumping, to obtain independent SNP-associations for our genetic instrument (using a threshold of R2 = 0.001), there were 190 and 195 SNPs for chronotype in females and males, respectively for the first approach and 54 and 32 SNPs, respectively in the second approach. Tables A and B in For chronotype, we identified two genetic instruments. The first comprised SNPs identified in the largest published GWAS of meta-analysed women and men combined from UKB and 23andme  . Of the Sex specific genetic instruments for total testosterone, bioavailable testosterone and SHBG were obtained from the previously published GWAS’ conducted in UKB . The GWAThe number of SNPs used to instrument chronotype and each of the sex hormone measures can be found in For uvMR, bdMR and mvMR analysis, the TwoSampleMR package was used to combine and harmonize genetic summary data for chronotype, sex hormones and breast and prostate cancer. The inverse variance weighted (IVW) approach was used for the main analysis, whereby a causal effect is estimated from the slope of a regression line through the weighted SNP-mean exposure vs SNP-mean outcome associations (orientated to be positive) with the line constrained to have an intercept of zero. Since only 1 SNP contributed to the female oestradiol instrument, MR results were instead calculated using a Wald ratio .MR analysis relies on three key assumptions: i) IVs must be robustly associated with the exposure of interest; ii) IVs must be independent of confounders of the exposure-outcome association; iii) IVs must only influence the outcome through the exposure of interest .2 statistics were used to estimate the proportion of the variance between IV estimates that is due to heterogeneity [We conducted sensitivity analyses to test MR assumptions. Univariable and conditional F-statistics were calculated to assess the strength of the relationship between the IVs and phenotype, and thus to indicate potential bias in the MR estimate due to weak instruments –44. To togeneity . Radial-ogeneity . To asseogeneity . Steigerogeneity . Since oTo accommodate additional two-sample MR assumptions, we restricted analysis to European-only individuals in all datasets and ensured sex-specific GWAS were used to meet the assumption that the exposure and outcome samples come from the same underlying population. We also performed harmonization of the direction of effects between the SNPs in the exposure and outcome GWAS. Palindromic SNPs were harmonized if they were aligned and the minor allele was <0.3, otherwise they were excluded.While sample overlap between UKB, BCAC and PRACTICAL/ELLIPSE is negligible, for the bdMR analysis, genetic estimates for both chronotype and sex hormones were determined in the same sample (UKB), violating the assumption of independent samples in two-sample MR. A supplementary analysis was carried out to investigate the magnitude of bias caused by overlapping samples . To eval2 statistic was calculated to assess variability in causal estimates between breast cancer subtypes [Supplementary analyses were conducted to evaluate the effects of chronotype and sex hormones on breast cancer stratified by subtype: Luminal A ; Luminal B ; Luminal B ; HER2 ; and Triple Negative . An Isubtypes .In addition, evidence from previous research suggests that adiposity is intrinsically linked with certain sleep traits , 56, sexMR analyses used the R packages “Two SampleMR”  and “MVM2 of 1.8% and an F-statistic of 22.75, and in males (190 SNPs) had an r2 of 1.7% and an F-statistic of 17.18  and for overall prostate cancer was 26%  (Table C in 2GX [The correlation (r) of the effect estimates for the 341 SNPs for chronotype in males and females was 0.60 . The genC in 2GX  was alsoC in 2GX  were conWe observed a reduction in risk of breast cancer per category increase in chronotype from extreme evening preference to extreme morning preference  . There w2 = 26%)  .Using UKB-only sex-specific instruments for chronotype, the results for chronotype on breast  and prostate  cancer were consistent with those in the main analysis, although less precisely estimated  and bioavailable  testosterone, but not in relation to SHBG  . Amongst2 for MR of sex hormones on overall breast cancer was 62–69% and for overall prostate cancer was 58–74% (Table G in There was moderate to high heterogeneity between SNPs used within the sex hormone instruments (excluding oestradiol): the IFor MR of sex hormones stratified by breast cancer subtype , the inc2) explained by the Steiger-filtered chronotype instrument was 1.9% compared to 3.9%, and 3.8% for total testosterone and bioavailable testosterone respectively  effect is likely to be minimal. The effect of oestradiol on breast and prostate cancer was very imprecisely estimated and may have been influenced by weak instrument bias as we only had one SNP to instrument for oestradiol in females, and two SNPs in males. Having so few SNPs meant that we could not explore potential bias due to unbalanced horizontal pleiotropy and therefore we did not explore this sex hormone further.2 = 0.001 vs 0.01) and the larger sample size of the breast cancer GWAS [The effect of morning-preference on breast cancer risk is consistent, although more conservative, than our previously reported two-sample MR findings  . This macer GWAS  . However, germline genetic variants used in MR should not plausibly be influenced by confounding factors, and as such, concerns about violation of the second MR assumption usually focus on confounding by population stratification or as a result of selection bias . Steps wIn terms of two-sample MR specific assumptions, the use of overlapping sample populations between exposures and outcomes may also introduce bias . For anaAnother potential concern is the overlap in the UKB sample used for both conducting the discovery GWAS for chronotype and sex hormones and for obtaining the effect estimates for the genetic instruments in MR analysis, given the potential for Winner’s curse bias. For chronotype, this was addressed previously  whereby The analyses presented here demonstrate inconsistent evidence for the role of testosterone as a mediator for the effect of chronotype on cancer, therefore further investigation is required. For example, to improve the robustness of the findings in this study, it would be interesting to investigate the effect of morning-preference on breast cancer subtypes using more objective measures of chronotype, such as L5 timing . We beliIn conclusion, this study has extended previous findings regarding the protective effect of chronotype on breast cancer and has found evidence to support recent findings that morning-preference also reduces prostate cancer risk in men. While testosterone levels were found to be closely linked with both chronotype and cancer risk, there was inconsistent evidence for the role of testosterone in mediating the effect of morning preference chronotype on both breast and prostate cancer. Findings regarding the potential protective effect of chronotype on both breast and prostate cancer risk are clinically interesting although this may not serve as a direct target for intervention, since it is difficult to modify someone’s morning/evening preference. However, a personalised breast cancer screening that considers chronotype as a causal risk factor may help to improve prevention in the future. Given this, further studies are needed to investigate the mechanisms underlying this effect and to identify potential modifiable intermediates.S1 MethodsText A: Study design. Text B: Genotyping, Imputation and association analysis (UKB). Text C: Genotyping and Imputation (BCAC). Text D: Genotyping and Imputation (ELLIPSE/PRACTICAL). Text E: Assessment of MR Assumptions(PDF)Click here for additional data file.S1 DataTable A: Table of Female exposures used in main MR analyses. Table B: Table of Male exposures used in main MR analyses. Table C: Table of heterogeneity and instrument strength for morning-preference chronotype instruments. Table D: Table of results for morning-preference chronotype effect on breast and prostate cancer. Table E: Table of results for Radial MR analyses for morning-preference chronotype on breast cancer risk. Table F: Table of results for morning-preference chronotype effect on breast and prostate cancer using sex-specific instruments. Table G: Table of heterogeneity and instrument strength for hormone trait instruments. Table H: Table of results for hormone trait effect on breast and prostate cancer. Table I: Table of results for Radial MR analyses for hormone trait effect on breast and prostate cancer risk. Table J: Table of results for hormone trait effect on breast cancer subtypes. Table K: Sensitivity tests for bidirectional MR analyses. Table L: Table of results for Radial MR analyses for morning-preference chronotype and hormone trait bidirectional MR. Table M: Table of results for mvMR analyses. Table N: Table of results for qhet_mvMR analyses. Table O; Table of results for trivariate mvMR including BMI. Table P: Table of results for age at diagnosis for each of the breast cancer subtypes.(XLSX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 FigStudy numbers = 1. Luminal A ; 2. Luminal B ; 3. Luminal B ; 4. HER2 ; and 5. Triple Negative .(TIF)Click here for additional data file.S3 FigForest plot of uvMR results for A) total testosterone, B) bioavailable testosterone and C) SHBG effects on breast cancer subtypes.(TIF)Click here for additional data file.S4 FigForest plot of split sample bdMR results for morning preference and sex hormones in female (A) and male (B) datasets. All instruments in these analyses have been subjected to Steiger-filtering.(TIF)Click here for additional data file.S5 FiguvMR results provided for comparison.(TIF)Click here for additional data file.S6 FiguvMR results provided for comparison.(TIF)Click here for additional data file.


In France, more than 10 million women at ”average” risk of breast cancer (BC), are included in the organized BC screening. Existing predictive models of BC risk are not adapted to the French population. Thus, we set up a new score in the French Hérault region and looked for subgroups at a graded level of risk in women at ”average” risk. We recruited a retrospective cohort of women, aged 50 to 60, who underwent the organized BC screening, and included 2241 non-cancer women and 527 who developed a BC during a 12-year follow-up period (2006-2018). The risk factors identified were high breast density (ACR BI-RADS grading), a history of maternal breast cancer , and socioeconomic difficulties . While early menopause  and an age at menarche after 12 years  were protective factors. We identified 3 groups at risk: lower, average, and higher, respectively. A low threshold was characterized at 1.9% of 12-year risk and a high threshold at 4.5% 12-year risk. Mean 12-year risks in the 3 groups of risk were 1.37%, 2.68%, and 5.84%, respectively. Thus, 12% of women presented a level of risk different from the average risk group, corresponding to 600,000 women involved in the French organized BC screening, enabling to propose a new strategy to personalize the national BC screening. On one hand, for women at lower risk, we proposed to reduce the frequency of mammograms and on the other hand, for women at higher risk, we suggested intensifying surveillance. The earlier breast cancer is detected, the greater the chances of recovery. For a breast cancer detected at an early stage, 5-year survival is 99%, and 27% for a metastatic cancer2. The difference in the detection stage also influences the cost of medical care3. While high risk women4 including women with a deleterious constitutional mutation predisposing to breast cancer, women for whom a surgical intervention with biopsy has shown an histological risk factor as well as women with a personal history of breast cancer receive an individualized monitoring, the majority of women aged from 50 to 74 are included in the nationwide organized breast cancer screening. In France, this screening consists of a mammography (2 views) every two years with a double reading of mammographic images, and targets a population of more than 10 million women5. Current participation is about 50% with a target of 65%. The number of women actually screened in France is therefore between 5 and 6.5 million.Breast cancer is the most common cancer in women and the leading cause of death from cancer in women in France6 based on the recommendations of the National Cancer Institute and at the request of the women interviewed during the citizen consultation to determine the levels of risk for the population at ”average” risk7. This reorganization plan aimed to enable a more personalized organized screening, and encouraged research projects on tools and methods for assessing the level of risk, including scoring. The aim of our study was to explore whether, among the 10 million women at ”average-risk” targeted by the French organized screening, some women would be at lower-risk than average risk and others at higher risk. The aim of this personalized organized screening is to optimize the available resources to make screening as efficient as possible. As it was a request from the women interviewed during the citizen consultation, it could also make them more involved in organized breast cancer screening and increase the participation rate.In April 2017, the Ministry of Health published an action plan to renovate the organized breast cancer screening8, BRCAPRO9, BODICEA10, Tyrer-Cuzick11, or PROCAS12 models. But they are not adapted to some European populations13 and most of them include BRCA1 and BRCA2 mutations. However, in France, women presenting with these mutations are not included in the organized nationwide screening and, as explained in PROCAS12, mutations in breast cancer genes such as BRCA1 and BRCA2 are too infrequent to affect risk prediction appreciably in the models for the general population. Moreover, it is difficult to estimate an individual risk precisely15.There are also some studies on European populations performed in England12. We, therefore, intended to set up a new risk model, including new variables, adapted to the French population, and enabling to explore whether in this average risk population it was possible to identify women at lower risk of breast cancer  in order to adapt the organized screening accordingly by proposing a different organized screening strategy depending on the level of risk identified.Several predictive models already exist, such as Gailsample function of the R software applied to the list of 32,962 unique identifiers.We used the database of the Center that coordinates breast cancer screening (CRCDC-OC) in the Hérault department, France. This database registers women with precise, verified, and consolidated information on the occurrence of breast cancer during the follow-up of their screening. The data are also consolidated by the Hérault tumor register which provides an exhaustive information on the occurrence of breast cancer, including interval cancers during the follow-up period. We enrolled women, aged 50 to 60 at inclusion, who experienced a 12-year breast cancer screening from 2006. We extracted a database of 33,858 women, including 805 women who developed a breast cancer in 3-12 years following inclusion. We did not include women who have been diagnosed with breast cancer during the first two years of follow-up to avoid including women who might have already developed a cancer prior to inclusion, but not yet diagnosed at inclusion. Data were recovered by a telephone survey. It was not possible to interview 33,000 women. Therefore, on one hand we selected all the women who developed a breast cancer during the follow-up period, and on the other hand, we randomly selected 5000 women among those who did not develop breast cancer using the We hypothesized a risk ratio We looked for the risk factors for breast cancer in average risk women reported in the literature prior to creating the study questionnaire. We elaborated a text mining algorithm-assisted search (TEMAS) (available at shiny.temas-bonnet.site) to optimize the bibliographic search on very large volumes of scientific articles. We also included the variables used in Gail’s model relative to women at average risk. The study questionnaire is provided in Supplementary material Data were collected by telephone by two trained investigators. An explanatory leaflet  was achieved (age was forced in the model) in order to obtain 27 defined below.iIt enabled to estimate a risk function F for each individual as a function of her covariates :Our goal was to define an individual score. Therefore, to estimate As we performed a random sampling among women without breast cancer, in our database, the distribution between women who developed cancer and the others was no longer representative of the starting population. To remedy this, we performed bootstrap samples. Bootstrap is a resampling method that uses random sampling with replacement. This method allowed to avoid skewing cancer rates compared to the population of interest without introducing bias. We computed 100,000 bootstrap databases using stratified random sampling with replacement among women for whom we obtained answers to all the covariates of the final Cox model, in order to obtain a database close to the initial CRCDC database .F(12|Z) to obtain a risk score of developing a breast cancer during the follow-up period.In these databases, mean risk was identical to the one of the CRCDC database. Then, we estimated, for each woman, M represents the event ”developing a breast cancer during the 12 years follow-up”;R represents the risk as determined by the score.This method then enabled to delineate 3 groups according to the level of risk: lower risk, average risk, and higher risk.In France, the number of women actually screened is between 5 and 6.5 million. Among these women, we hypothesized that 10% of them might have a risk different from the “average” risk of breast cancer, either lower or higher. This average 12-year risk was 2.6% in the organized screening population. From a clinical standpoint, we looked for women that might have a risk two times lower than this “average” risk. This group was considered as at lower-risk. We also looked for women that might have a risk two times higher than this “average” risk. This group was considered as at higher-risk. We then searched for the corresponding thresholds. We looked for s, the likelihood ratios (LR) either positive (+) or negative (-) were as follows:Given that, for each threshold We plotted the curves LR+(s) and LR-(s) curves and looked for entclass1pt{minimaWomen with a risk score below the ”low threshold” will be considered at lower risk of breast cancer, women with a risk level between ”low threshold” and ”high threshold” will be considered at average risk and finally, women with a risk score above the ”high threshold” will be considered at higher risk of breast cancer in this population of women at average risk.We obtained the authorization No.: 2200402v0 from the CNIL’s . We also received the agreement (No.: A0246039) of the ethics committee of the CPP . All methods were performed in accordance with the relevant guidelines and regulations.An explanatory leaflet  we had for women who could not be reached or who refused to answer our questions. The results are shown in Tables The final model, presented in Table 28.The risk factors selected by the model were high breast density (ACR BI-RADS grading) , history of maternal breast cancer , and socioeconomic difficulties . While early menopause  and an age at menarche after 12 years . Age  and interaction between age at menarche and menopause  have been forced in the model. The interaction between age at menarche and menopause was forced in the model to take into account the duration of estrogen impregnation, a notable risk factor in our literature searchesF(t) was calculated for all women in the 100,000 databases.We computed 100,000 bootstrap databases using random sampling with replacement among the 2768 women for whom we had answers to all the covariates of the final Cox model. The risk function Pre-test prevalence of the disease was the percentage of breast cancer in the CRCDC-OC database i.e. 2.6%.So, as described in Supplementary material We then plot LR+(s) and LR-(s) in Fig. On one hand, 9.39% of women  presented a 12-year risk lower than 1.9%. Among this group, the mean 12-year risk was 1.37%. On the other hand, 2.85% of women  presented a 12-year risk higher than 4.5% with a mean 12-year risk of 5.84%. All this results are presented in Table This work was dedicated to explore whether it was possible to offer a personalized risk based screening to the population of women at « average » risk of BC. In a retrospective cohort of French women, aged 50 to 60, at « average » risk of breast cancer and followed-up for 12 years, from 2006 to 2018, who underwent the BC organized screening, we identified two additional levels of risk, either twice lower than the average-risk, or twice higher. Our partition into three groups at risk of breast cancer in these women showed that the level of risk in the so-called « average » risk population is not homogeneous.In a first step we built a score of breast cancer risk that included six variables, two of which (age and breast density) were already included in the databases of the French CRCDCs. Only four more questions were required to be asked in order to establish the score. This information is easy and simple to collect at the time of the mammogram.In a second step, based on the score and likelihood ratios, we identified three levels of risk with a risk ratio of at least 2 between the group at average risk and the group at lower risk on one hand, and on the other hand with the group at higher risk. It lead to fairly large group sizes. Thus, 12.3% of women belonged either to the lower risk group (9.4%) or to the higher risk group (2.9%). We chose to look for a risk divided or multiplied by a factor two. This choice remains arbitrary, though clinically relevant. Moreover, sensitivity analysis could be carried out by varying this ratio according to complementary hypotheses of epidemiologists or physicians specialized in these field. Furthermore, the choice could be supported by a cost function taking into account monetary cost and years of life adjusted for quality of life.29. The term used by the Nice guidelines of « moderate » BC risk is based on a lifetime risk from age 20 of developing breast cancer of at least 17% but less than 30%. A moderate risk between ages 40 to 50 was estimated between 3% and 8%. The recommendations on surveillance for women at moderate BC risk are modulated according to age. As the likelihood of getting breast cancer increases with age, all women aged from 50 to their 71st birthday who are registered with a GP are automatically invited for breast cancer screening by mammography every 3 years (www.nhs.uk). The term « average » risk was retained by the National Comprehensive Cancer Network in the US30. For the NCCN Panel, increased risk of developing BC is defined by the modified Gail model for women 31. However, the NCCN recommendations are different. For a woman aged 35 years of age or older, with a 5-year risk The levels of BC risk are difficult to compare between countries since the clinical guidelines where risk-based screening is recommended differ from country to country, or even in the same country for instance in the United States of America (USA). For the United Kingdom (UK) three levels of risk were delineated by the National Institute for Health and Care Excellence (NICE): near population risk, moderate risk and high risk4. Several contexts justify a specific exploration in women who already experienced a personal history of breast cancer, ductal or in situ lobular carcinoma or atypical lobular or ductal hyperplasia, in women who have had high dose medical chest irradiation , and those who experienced some family history of BC. In the event of a BC family history with an Eisinger score equal or greater than 3, which leads to an oncogenetic consultation, AND in the absence of a BRCA 1 or 2 mutation in the family, it is the oncogeneticist that assesses the woman’s personal risk of BC. Women at « high risk » or « very high risk » benefit from individualized monitoring and are not integrated in the French organized BC screening.In France, the term “average risk” refers here to the sub-population of women aged 50 to 70 years of age for whom BC screening is indicated, i.e. asymptomatic women who are not at « high risk » . The lifetime risk from age 20 of developing breast cancer in our population was 15.2%. The terms « high risk » or « very high risk » are reserved for women presenting with known risk factors, particularly familial risk factors, or genetic factors such as BRCA-1-2. The Haute Autorité de Santé defined “high” or “very high” risk women32. The NCCN recommendations for Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic are also available33.Clinical Guideline CG164 for family history of BC were provided by the NICE entitled : classification, care and managing breast cancer and related risks in people with a family history of breast cancer35 targeted breast cancer susceptibility genes in order to better personalize the screening procedure. Moreover, two ongoing studies explore risk based screening strategies that include genomic tests and polygenic risk scores. The “WISDOM” study (Women Informed to Screen Depending On Measures of risk) is a multicenter trial comparing risk-based screening to annual screening in 100,000 women aged 40-74, initially launched in the Athena Breast Health Network in California and the Midwest36. It is based on personalized breast cancer screening recommendations based on individual risk assessments. Components of individual risk assessment are based on integral biomarkers: Breast Cancer Surveillance Consortium 5-year risk; genomic tests for rare high/moderate-penetrance mutations in a number of genes, including the following: BRCA1, BRCA2, ATM, CDH1, CHEK2, PALB2, PTEN, STK11 and TP53; and polygenic risk score from 96 lower-risk common genetic variants (SNPs) with known association to breast cancer, updated as data emerge. Two primary endpoints were defined: safety is explored through a non-inferiority hypothesis comparing the rate of stage IIB cancers or higher diagnosed in annual versus risk-based screening arms. Morbidity evaluation is based on a reduced rate of recall and breast biopsy between arms. Another ongoing study is « MyPebs » 37 which is an international randomized, open-label, multicentric study assessing the effectiveness of a risk-based breast cancer screening strategy, which uses clinical risk scores and polymorphisms, compared to standard screening, according to the current national guidelines in each participating country, in detecting stage II or higher breast cancers. Women aged 40 to 70 years old are differentially screened for 4 years38.Since we focused our study on women at average risk, we did not include information on genomics or susceptibility genes in our questionnaire. However, several studiesThe recruitment of WISDOM or MyPebs studies differ from our’s. In our study, we included women aged 50 to 62 years, and followed-up for 12 years. Moreover, the French screening is not based on annual screening but on biennial mammogram. Moreover, unlike these two studies, we took into account all types of breast cancer and not just stage II or higher cancers.33. In effect, it remains difficult to estimate penetrance when a particular PGV is discovered in a woman who lacks a significant pretest probability of carrying this particular PGV41.In our study we did not include genomic tests, neither search for genetic variants. In our sample, only 1.5% of women of the lower risk group had a mother who presented a BC. It was 6.1% in the average group. Conversely, it was 71.7% in the higher risk group. We considered that genomic tests including 9 genes and 96 to 258 SNPs in women at average risk is not currently a screening approach that can be extended in France to 10 million women aged between 50 and 74 years. Moreover, the costs efficiency of such a strategy, financial as well as organizational, has not been evaluated yet. It is also worth noting that the penetrance of a particular pathogenic germline variant (PGV) in a patient without a pretest probability that satisfies the National Comprehensive Cancer Network recommendations for targeted testing for that PGV, is unclear for most PGVs42, thanks to advances in research, and to become more personalized according to individual risk factors. Physicians, also consulted, mentioned the value of determining the level of individual risk43. They also ask for a score in French women in order to substantiate the levels of risk. In this perspective, we developed a user friendly computer application, mainly dedicated to physicians, that enables estimating the value of BC risk for a given woman, and provides an aid to personalizing the organized screening accordingly (application available at shiny.temas-bonnet.site/breast_cancer).Women interviewed during the French citizen consultation on breast cancer screening in 2017, expected the organized screening to be more targeted45.In France, the organized BC screening enables a regular follow-up of invited women, aged 50 to 74, to get a biennial mammogram, covered by health insurance, in the radiology office of their choice. Moreover, even if the initial reading of the mammogram does not present any anomaly, a second reading is systematically performed by another radiologist. The second independent reading is a guarantee of reliability, with almost 8% of the breast cancers detected by the independent second readingThe principle of an organized breast cancer screening has been challenged given the claims of over-diagnosis or over-treatment (references). A reassessment of the organized screening that would allow a personalization according to the individual level of risk, would enable a standardized and quality monitoring of women, while producing evaluative data.Depending on the presence or level of clinical, genetic or biological markers, treatment strategies are personalized to be as effective as possible. This approach can be extended to public health and in particular for primary and secondary prevention. Indeed, offering personalized prevention strategies could increase adherence to the the screening program, and effectiveness as well. Thus, identifying new groups at risk among women at average BC risk offers new perspectives. According to the two highlighted thresholds of lower and higher risk, 12% of women were thus identified, corresponding to more than 600,000 women in the French population. In this population at ”average” risk of breast cancer, a new screening strategy might therefore be proposed for the groups at lower or higher risk. For the group at average-risk of breast cancer, corresponding to 88% of the presently screened population, the current screening rate, i.e. a mammogram every two years, would be maintained as such.For the group at lower risk that includes 9.4% of the screened population with a level of risk of 1.37% of developing breast cancer within the 12 years of follow-up, we propose to reduce the frequency of mammograms with a mammogram every three or more years instead of the two years currently in force. This mammogram spacing could reduce the risk of over-diagnosis while maintaining a regular follow-up. Moreover, it would reduce, the risk of radiation-induced cancer, even if it is already very low. However, the risk of interval cancer can’t be excluded. This proposal will have thus to be tested with an appropriate design.4 an oncogenetic consultation is required. Otherwise, particularly in the group of high breast density, increasing the frequency of mammograms is conceivable. However, high breast density is an important risk factor for this group where the distribution of high or very high breast density was 60% compared to 28% in the group at average risk and 3% in the group at lower risk. Furthermore, the mammogram sensitivity falls to 63%46 for very dense breasts. The sensitivity of cancer detection via a mammogram appeared inversely proportional to breast density47. Thus, it did not seem that increasing the frequency of mammograms would bring a significant benefit. Based on recent results, an alternative would be to offer these women an abbreviated breast MRI, which appeared associated with a higher rate of breast cancer detection among women with dense breasts48, while maintaining a two-year frequency for surveillance.For 2.9% of women at higher risk that we identified among women of our BC screening population, if they fulfill the criteria above defined by the Haute Autorité de Santé5, although the target is 65%.Such a personalization of the organized screening might make women feeling more involved. For women at lower risk, a mammogram every three years would be less restrictive than every two years. For women at higher risk (excluding women for whom an oncogenetic consultation is indicated), offering an intensified surveillance may increase their adhesion to an adapted screening. This strategy might contribute to increase the participation of French women to the organized screening which is currently around 50%49. Analysis of the medico-economic gain should be carried out taking into account, among other things, interval cancers, over-diagnosis and the stage of detected BC. In this observational survey, the difficulty to contact women is inherent in this type of design and might introduce a selection bias. In our study, among non-participating women, 4 out of 5 were not reachable by phone, however it did not introduce a selection bias since it is at random. Conversely, 1 in 5 women indeed refused to answer the questionnaire which might have introduced a selection bias, even if the majority of them alleged a lack of time to fill out the questionnaire. We considered that it was not obviously linked to the level of BC risk, though limiting a potential selection bias.As previously stated, the case finding costs (including diagnosis and treatment costs) should be economically balanced in connection with possible expenditure on medical care as a whole50. Moreover, information of interest for the creation of our score was collected at An internal validation on another database, for example of women aged 40 to 50 in the Hérault department, would be of interest. External geographic validation might be carried out on the databases from other CDCRCs and/or a database from another countrySupplementary Information 1.Supplementary Information 2.Supplementary Information 3.


Ageing is the strongest cancer risk factor, and men and women exhibit different risk profiles in terms of incidence and survival. DNA methylation is known to strongly vary by age and sex. Epigenetic drift refers to age-related DNA methylation changes and the tendency for increasing discordance between epigenomes over time, but it remains unknown to what extent the epigenetic drift contributes to cancer risk and survival. The aims of this study were to identify age-associated, sex-associated and sexually dimorphic age-associated (age-by-sex-associated) DNA methylation markers and investigate whether age- and age-by-sex-associated markers are associated with cancer risk and survival. Our study, which used a total of 2754 matched case–control pairs with DNA methylation in pre-diagnostic blood, is the first large study to examine the association between sex-specific epigenetic drift and cancer development and progression. The results may be useful for cancer early diagnosis and prediction of prognosis.n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869) and urothelial (n = 428) cancers, and mature B-cell lymphoma (n = 438). Linear mixed-effects models were conducted to identify age-, sex- and age-by-sex-associated methylation markers using a discovery (controls)-replication (cases) strategy. Replication was further examined using summary statistics from Generation Scotland (GS). Associations between replicated markers and risk of and survival from cancer were assessed using conditional logistic regression and Cox models (hazard ratios (HR)), respectively. We found 32,659, 23,141 and 48 CpGs with replicated associations for age, sex and age-by-sex, respectively. The replication rates for these CpGs using GS summary data were 94%, 86% and 91%, respectively. Significant associations for cancer risk and survival were identified at some individual age-related CpGs. Opposite to previous findings using epigenetic clocks, there was a strong negative trend in the association between epigenetic drift and risk of colorectal cancer. Methylation at two CpGs overlapping TMEM49 and ARX genes was associated with survival of overall  and colorectal  cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.To investigate age- and sex-specific DNA methylation alterations related to cancer risk and survival, we used matched case–control studies of colorectal ( Ageing is the strongest risk factor for cancer overall, and for the majority of individual cancer types . AdvanceEpigenetic drift is the tendency for increasing discordance between epigenomes over the lifetime . Larger In this study, our aims were (i) to identify age-associated and sex-associated DNA methylation markers; (ii) to identify sexually dimorphic age-associated (age-by-sex-associated) DNA methylation markers; (iii) to investigate whether age- and age-by-sex-associated methylation markers are associated with cancer risk and survival.The characteristics of the Melbourne Collaborative Cohort Study (MCCS) samples used in this study are presented in p < 1.0 × 10−7) methylation sites in Models 1.1 and 1.2 , respectively; for methodology details, see Materials and Methods, and p < 1.0 × 10−7) between age and sex using Models 2.1 and 2.2 that included an age × sex interaction term. Among these markers, we replicated, using participants who were selected as cases: 32,659 age-associated CpGs      , 23,141 −6, 88%) , and 48 −4, 66%) . Regressp < 1.8 × 10−6), 86% sex-associated (p < 5.1 × 10−6) and 91% age-by-sex-associated (p < 0.0015) CpGs were replicated in GS data (We further examined the replicated methylation markers using summary statistics results from two datasets from the Generation Scotland (GS) study . We foun GS data . The 30 HLA-DPB2 and cg05497216 in ANKRD11) were associated with risk of cancer overall , and six  were associated with risk of mature B-cell lymphoma (p < 1.5 × 10−6) (p > 0.001 = 0.05/48). A potential age-by-sex-related CpG, cg26738106 , detected in the discovery set (beta = 0.09 and p = 3.0 × 10−9 in Model 2.2) was associated with colorectal cancer risk with OR = 0.58 (95% CI: 0.44–0.77), p = 0.0001 in Model 3.1, and OR = 0.59 (95% CI: 0.44–0.78), p = 0.0002 after adjustment for smoking, alcohol consumption and BMI (Model 3.2). However, this CpG was not replicated as showing age-by-sex-related methylation in the set of MCCS cases (beta = 0.01 and p = 0.36 in Model 2.2) and not included in the EPIC array used by McCartney et al. [Of the 32,659 age-related methylation sites, two (cg25119261 in  × 10−6) . These C × 10−6)  and (2)  × 10−6) . We founy et al. ’s GS stup < 2.2 × 10−16) between associations of methylation with age and associations with overall cancer risk; the correlation was also strongly positive for kidney , lung  and urothelial  cancers and mature B-cell lymphoma ; a negative correlation was observed for colorectal  and prostate  cancers.We further examined the trend of the association between epigenetic drift and risk of overall and specific cancers using the 32,659 age-associated CpGs. p < 1.5 × 10−6)  with HR = 0.88 (95% CI: 0.83–0.93), p = 2.3 × 10−6 in Model 4.1 and HR = 0.91 (95% CI: 0.86–0.96), p = 7.7 × 10−4 after adjustment for lifestyle-related confounders (Model 4.2). Of the 32,659 age-related CpGs, 126  were associated with survival of cancer overall ( × 10−6) . The resARX (X chromosome) that was associated with survival of colorectal cancer with HR = 1.59 (95% CI: 1.28–1.97), p = 2.3 × 10−5 in Model 4.1 and HR = 1.52 (95% CI: 1.22–1.89), p = 1.8 × 10−4 in Model 4.2. There was no evidence to support an association of age-by-sex-associated methylation sites with survival of other cancer types.We also examined the associations of age-related blood DNA methylation with survival for each individual cancer type and detected associations for gastric cancer , lung cancer  and mature B-cell lymphoma  . There wFLNA, IDS, IGBP1 and MID1IP1 were among the 114 XCI escapees.Aging, as the main risk factor for most cancer types, captures the effects of cumulative exposure to exogenous and endogenous risk factors in one’s lifetime, and thus the epigenetic drift reflects molecular alterations caused by both genetic and environmental risk factors . SeveralHLA-DPB2) was reported to be differentially methylated between tumor and matched adjacent normal tissues in the context of oral squamous cell [MXRA5) was negatively associated with risk of colorectal cancer in our data, but the age-by-sex interaction observed in the set of controls was not replicated in the set of cases and therefore requires further investigation. It is, however, interesting to note that MXRA5 was shown to be aberrantly expressed in colorectal tumor tissue [MXRA5 as a cancer gene frequently mutated in non-small cell lung carcinoma [MXRA5 was also nominally significantly associated (p < 0.05) with survival from lung cancer in our data: HR = 1.59 (95% CI: 1.17–2.15), p = 0.003 in Model 4.1 and HR = 1.58 (95% CI: 1.16–2.14), p = 0.004 in Model 4.2.Our results suggest that DNA methylation at several individual age-related CpGs is negatively associated with risk of cancer overall and mature B-cell lymphoma . In the ous cell  and hepaous cell . These cr tissue . A studyarcinoma , and cg2TMEM49  was negatively associated with overall cancer survival. TMEM49 has been widely reported as a cancer-relevant cell cycle modulator and its expression regulates the invasion and metastatic potential of cancer cells [ARX is a homeobox-containing gene which is expressed primarily in the central and/or peripheral nervous system. Our study suggests that blood DNA methylation at cg21729122, located in the TSS1500 region of ARX, may be associated with sex-specific survival from colorectal cancer. Although these findings should be interpreted with caution given methylation was measured in different tissues, they altogether suggest potential for blood DNA methylation in this region to provide a sex-specific mode of early detection and prediction of cancer.One age-by-sex-associated CpG cg12054453 in er cells ,43,44. APhenoAge, a composite biomarker of mortality, and GrimAge, a predictor of lifespan generated using several DNA methylation surrogates for plasma proteins and smoking history [GrimAge, we found that associations were in the same direction as the epigenetic drift (current results) with risk of most cancer types: overall (OR = 1.11), kidney (OR = 1.28), lung (OR = 2.03), urothelial (OR = 1.22), gastric (OR = 0.95), prostate (OR = 0.84) cancers and mature B-cell lymphoma (OR = 1.03) [GrimAge (OR = 1.12), PhenoAge (OR = 1.18) [Our results also showed a positive trend in the association between epigenetic drift and risk of cancer overall (slope = 0.17) and cancers of the kidney (slope = 0.04), lung (slope = 0.13), and urothelium (slope = 0.33) and mature B-cell lymphoma (slope = 0.88), as well as a negative trend for gastric (slope = −0.01), prostate (slope = −0.12) and colorectal (slope = −0.09) cancers . This in history . For exa = 1.03) . We obse = 1.18)  and “firy OR = 1., lung (O = 1.18) . For proThere are several limitations in this study. First, there might have been a small proportion of closely related individuals between discovery and replication samples, which may result in some inflation of replicated signals. The fact that controls and cases were sampled from the same population and were all processed at the same time and using the same normalization pipeline may also result in somewhat overconfident replication, compared with completely independent samples. Assessing associations using the set of cases may also result in collider bias, but it would likely be small in our setting given the matching of cases and controls ,46. SecoN = 835), gastric (N = 170), kidney (N = 143), lung (N = 332), prostate (N = 869) and urothelial (N = 428) cancers, and mature B-cell lymphoma (N = 438) nested within the MCCS. Cases and controls were matched on age at blood draw, sex, country of birth  and sample type  using incidence density sampling. To minimize batch effects, samples from each matched case–control pair were plated to adjacent wells on the same BeadChip microarray, with plate, chip and position assigned randomly. Case–control pairs with missing values for the confounders (smoking status (current/former/never) and pack-years (log-transformed), alcohol consumption in the previous week (in grams/day) and body mass index (in kg/m2)) were excluded. The Melbourne Collaborative Cohort Study (MCCS) is an Australian prospective cohort study of 41,513 people of white European descent recruited between 1990 and 1994 in Melbourne metropolitan area. DNA was extracted from pre-diagnostic peripheral blood taken at recruitment (1990–1994) or at a subsequent follow-up visit (2003–2007) in cancer-free participants. More details about the cohort profile, blood collection, DNA extraction and cancer ascertainment can be found elsewhere . Here we2 (beta/(1 − beta)), were then used for the analyses since these are thought to be more statistically valid for detection of differential methylation [DNA methylation in the MCCS was measured using the Illumina HumanMethylation450 (HM450) assay . Quality control (QC) details for processing methylation beta values have been reported previously . Brieflyhylation .To identify age-, sex- and age-by-sex-related methylation markers (Aims 1 and 2), we used all control subjects from the MCCS sample as a discovery set. After excluding duplicated controls across the seven studies , 3008 participants were available for the discovery phase analysis. After QC of methylation data on the discovery sample, there remained 484,828 available CpGs. All study cases were then used as the replication set. After excluding duplicates across the seven studies  and participants with samples that overlapped with the discovery set , 2754 participants were available for the replication phase analysis.McCartney et al.  recentlyTo assess associations of age and sex with DNA methylation (Aim 1), we conducted epigenome-wide association studies (EWAS). We fitted linear mixed regression models of methylation M-values at individual CpGs on age, sex, country of birth and sample type as fixed effect variables, and study of specific cancer type, assay plate and slide as random effect variables. A first model (Model 1.1) was adjusted for white blood cell composition , and a (Model 1.1)(Model 1.2)To investigate sex-specific ageing-associated changes in DNA methylation (Aim 2), we added an interaction term age × sex to the same models (Model 2.1 and Model 2.2).(Model 2.1)(Model 2.2).p < 0.05/484,828 = 1.0 × 10−7) for all Model 1s and 2s. The same models were then carried out using the replication set. Replicated findings were further examined using the GS summary statistics [p-value threshold for replication was based on Bonferroni correction) and same effect directions. A flowchart detailing the study design and analysis pipeline was presented in In the discovery phase, we used the Bonferroni correction for multiple testing to declare statistical significance  and cancer at seven specific sites, using conditional logistic regression models (Models 3.1 and 3.2) to estimate odds ratio (OR) and 95% confidence intervals (CI), expressed per standard deviation (SD). In Model 3.1, we adjusted for age, country of birth and white blood cell composition. Sex and sample type were exactly matched between cases and controls so were not adjusted for. Model 3.2 was additionally adjusted for smoking status (current/former/never) and pack-years, alcohol consumption in the previous week  and BMI (continuous). The methylation sites at which associations were significant after Bonferroni correction for multiple comparisons in both Models 3.1 and 3.2 were considered to be associated with risk of cancer.n = 1931 deaths were included in the analysis. Time since diagnosis was used as the timescale, and person-years of follow-up were calculated from the diagnosis date until the date of death, and censored at the date of departure from Australia or end of follow-up. Where a participant was diagnosed with several cancers, we considered only the first diagnosis to count follow-up time. Number of deaths by cancer type was as follows: colorectal cancer: n = 526, gastric cancer: n = 144, kidney cancer: n = 80, lung cancer: N = 311, prostate cancer: n = 435, urothelial cancer: n = 234, and mature B-cell lymphoma: n = 286. In Model 4.1, we adjusted for age, sex, country of birth, sample type and white blood cell composition. Model 4.2 was additionally adjusted for smoking status and pack-years, alcohol consumption and BMI. The methylation sites at which associations were Bonferroni-significant in both Models 4.1 and 4.2 were considered to be associated with cancer survival. All statistical analyses were performed using R version 3.6.0.We used Cox models (Models 4.1 and 4.2) to estimate hazard ratios (HR) per SD for the associations between M-values at individual age- and age-by-sex-associated CpG sites and risk of death  following cancer diagnosis. The survival analysis was thus restricted to cancer cases. A total of TMEM49 and ARX loci) were associated with survival of all cancers and colorectal cancer, respectively. Our results could be useful for developing strategies of early diagnosis of cancer and prediction of cancer prognosis. Additional studies are required to replicate our findings and identify the potential mechanisms by which epigenetic drift is associated with cancer risk and survival.Our study is the first large-scale study to examine potential genes at which blood DNA methylation is age-related (including modification by sex) and associated with cancer development and progression. Significant associations with cancer risk and survival were identified at several individual age-related CpG sites. We also observed a strong negative trend in the association between epigenetic drift and risk of colorectal cancer, i.e., in opposite direction to our previous findings using epigenetic clocks. Two CpGs at which the effect of age on DNA methylation was different in males and females (at the