This study aimed to explore women's views about breast cancer risk and alcohol use, to inform the design of a prototype for an intervention in breast clinics about alcohol as a modifiable risk factor for breast cancer.Women recruited in NHS breast screening and symptomatic clinics in Southampton, UK, were invited to take part in semi‐structured telephone interviews or a focus group to discuss their perspectives of breast cancer risk, alcohol consumption and their information needs about these topics. Data were analysed thematically. Twenty‐eight women took part in telephone interviews, and 16 attended one of three focus groups.While most women reported a personal responsibility for their health and were interested in advice about modifiable risk factors, few without (or prior to) experience of breast symptoms independently sought information. Many considered alcohol advice irrelevant as the association with breast cancer was largely unknown, and participants did not consider their drinking to be problematic. Women reported trusting information from health organisations like the NHS, but advice needs to be sensitive and non‐blaming.NHS breast screening and symptomatic clinics offer a “teachable moment” to engage women with context‐specific advice about alcohol and cancer risk that, if targeted correctly, may assist them in making informed lifestyle choices. Recruitment was by posters/postcards in clinic areas inviting eligible participants to contact the research team. Participants from another phase of the study (a web‐based survey of clinic attenders) were also invited to participate. Participants were told they would be asked to give their opinion about advice on modifying the risk of developing breast cancer and possible methods for delivering this information. All participants gave informed consent to take part and for interviews/focus groups to be audio recorded. The appropriate NHS Ethics Committee approved the study (Reference: 17/LO/0953).n = 16) and 28 telephone interviews were conducted with women ≥18 years who had attended a symptomatic breast clinic (72.7%) or an NHS breast screening programme mammogram (27.3%) within the past 2 years.Three focus groups  to facilitate discussion. Interviews lasted ~25 min and focus groups ~90 min.Data were transcribed verbatim and transferred into the qualitative software programme, NVivo11, to facilitate analysis. Thematic analysis was used to explore and interpret patterns in the data, pertaining to the concepts listed above We have a responsibility to look after our bodies and so we need to be as well informed as we possibly can about what risk factors are, and how to keep ourselves healthy. Most women said they have a personal responsibility for taking care of their health, and acquisition of reliable and accurate information is imperative in this process:However, various tensions (both explicit and implicit) were identified in participants’ accounts which may challenge the effectiveness of an intervention seeking to educate women about alcohol as a major modifiable risk factor for breast cancer. Table 3.13.1.1(TI21)To be honest with you, I probably wouldn’t look anything up unless I had symptoms. Analysis revealed a reactive, rather than preventative, approach to dealing with breast cancer: “People don't often discuss cancerous things…unless they've found something like a lump, it's just not spoken about” (TI22). This was echoed in participants’ passivity in seeking information to understand risk factors:were interested in understanding more about breast health, most women agreed they would search  for “symptoms of breast cancer”; only a minority said they would search for “risks” or “causes.” However, when asked explicitly during interview the importance of knowing about risk factors, every participant stated it was “very” or “extremely” important, particularly “if there are definite things that you can change” (TI17). Nevertheless, despite this assertion, women's apparent bias towards a reactive approach to breast cancer may reduce their receptivity to information about making healthier lifestyle choices, particularly if they are asymptomatic: “I would read it for interest and discard it” .When pressed for the kinds of information they would seek if they (TI21)When you need to know about it, you probably don’t want to know about it, which is when you’re a lot younger…you don’t think about the consequences because you’re so young at the time. Without breast symptoms, women explained it can be easy to ignore health information: “If I feel healthy, I would continue on with what I'm doing rather than check” (TI27); “I'd just want to brush it under the carpet” . One participant suggested this is particularly true of younger women:(TI16)I went to this appointment; now I believe it’s important [to know about risk factors], but before, it was something I didn’t really think about because it was just not on my radar. Avoidance of information was also associated with fear of cancer , and other times, invincibility . Attendance at a breast clinic was therefore described as a window of opportunity for learning about risk factors, as concerns for breast health are made salient:3.1.2(TI27)I was on the [contraceptive] pill for X number of years and I strongly believe that my oestrogen pill fed my cancer. (TI04)The one thing that I do think has linked to the breast cancer, certainly in my sister’s case, is stress; massive, massive stress. Personal and/or familial experience appeared to have a particularly influential role in the formation of beliefs about the causes of, and risk factors for, breast cancer. While participants identified numerous factors that may lead to cancer generally, those with lived experience of breast cancer often attributed their diagnosis (or that of a close friend/relative) to one cause. For example:(TI27).I know of people who are, eat totally bad, had a bad lifestyle foodwise, smoking, drinking, and they live until they’re 100. I also know people who are very healthy, never smoked in their life, never drank in their life, vegetarians, or whatever, and they still get cancer. Moreover, numerous participants detailed stories of individuals they knew who appeared to defy evidence about the risks of modifiable factors for developing cancer:The frequency with which participants described such cases suggests they carry significant weight in how risks for breast cancer are understood and evaluated. Importantly, anecdotal evidence appeared to reduce acceptance of “evidence‐based” information which did not match participants’ personal narratives, particularly that relating to modifiable factors: “What you said about the drinking, um, I've sort of, rarely drank…I still got cancer.” . Similarly, women with familial history of breast cancer often described a cancer diagnosis as predetermined; “there's nothing you can do about it” (TI12), “it's what you're born with” (TI09). A fatalistic approach to breast cancer risk may therefore present as a challenge for women considering preventative information about factors such as alcohol consumption.3.23.2.1Bearing in mind this is breast cancer research, I’d like to ask you why you’re concentrating on alcohol? (TI06)(TI01)I’m confused as to why this is a breast cancer care topic. There was an apparent bias against discussions around risky alcohol consumption within the context of breast health in several interviews and focus groups, which may challenge effective intervention delivery within clinical settings. While numerous participants recognised that “drinking too much alcohol is bad for your health” (T103), and concern about health was considered a valid reason for reduced consumption or abstinence, very few discussed alcohol in association with breast cancer risk specifically. In fact, several women appeared confused by questions relating to alcohol use within the context of breast cancer research:If you’re sitting in a waiting clinic, your head isn’t exactly on…‘how much alcohol did I consume last week?’ It’s a, it’s a slightly alien distraction. Participants often dismissed the relevance of alcohol information for them personally , or as a topic for discussion within breast clinics:(TI21)I didn’t know until I saw you at the clinic that it was specifically one of the risk factors for breast cancer…I haven’t been looking, but I haven’t noticed any leaflets relating to alcohol and breast cancer anywhere. Another common theme was the belief that information about alcohol harms would be better directed at younger generations because of the perceived disparity in level of risk . Moreover, some women said alcohol interventions would be delivered “too late” for those attending symptomatic clinics as “the damage has been done” . Thus, perceptions of alcohol information as being irrelevant for women at their stage of life may reduce their willingness to engage with such information in breast clinics. However, despite prior ignorance to the association between alcohol and breast cancer risk, many participants appeared interested to learn more as part of the research process:(TI05).I told my mum today. She’s a nurse. I was telling her about the research – she didn’t even know that [alcohol is a risk factor for breast cancer]. Several also explained how their participation had prompted discussions about alcohol with others in their life, which suggests a readiness to discuss the topic once initial barriers to doing so had been overcome:3.2.2“Pt01:That’s an alcoholic, and that person will end up in the gutter and lose their home, and you know that’s kind of the extreme picture.Pt02:That’s not me.Pt01:Yeah exactly, that’s not me because I’m normal.”Analysis highlighted that entrenched discourses around what constitutes “normal drinking” in England may also impede discussions about alcohol consumption as a risk factor for breast cancer. Participants typically described problematic drinking as synonymous with dependent or “alcoholic” drinking and characterised by loss of control and severe harm. This appeared to generate an “othering” effect in which some participants considered themselves fundamentally different to those with an alcohol “problem” (FG2):If you had an alcohol problem, then yes, they [the apps] were very useful…I would suggest that it wasn’t necessarily relevant to where we’re coming from. Women's self‐defined identity as a “normal drinker,” characterised by sociability and personal control, even if that is at levels that increase the risk of breast cancer, may hinder efforts to engage them in discussions about making changes to their consumption. Indeed, in discussing the alcohol‐specific digital apps explored during a focus group, one participant said:.Nevertheless, several participants reported “lying” to medical professionals about the number of alcohol units they consumed, or more commonly, admitted they were either unsure of current national drinking guidelines, or paid little attention to them. This highlights a gap in participants’ knowledge about alcohol consumption beyond its associated risk for breast cancer (the UK lower risk drinking level is 14 units or 112 g of ethanol per week). Information given as part of an alcohol intervention in breast health setting therefore needs to make salient its relevance for individuals who are drinking at levels that increase their risk for breast cancer, but are not aware of this, and do not consider their drinking problematic. Indeed, several participants reported a willingness to share alcohol‐related information to others for whom they perceived needed it more: “I would happily send on to all the young people I know” 3.33.3.1Participants described a landscape of mixed messages about risk factors for cancer, and the subsequent difficulty in obtaining accurate and reliable health information: “the advice you're given constantly changes, so it's sort of, quite fickle” (TI17); “you get so much conflicting information [about modifiable risk factors for cancer] that you don't know which way to turn” (TI12). Women most often referred to the NHS, healthcare professionals, or breast cancer charities as trustworthy sources of information. Those who reported using the Internet tended to limit their search to websites provided by these sources: “I only look at the NHS websites because I don't trust most of the internet” .(TI13)Often you get things reported, and you think, ‘oh wow, that’s fantastic’, and then you find out that they’ve just done research on mice, or it’s been in a petri dish. (TI24)I’d want to see the full research…show me your study and how it’s been managed and how you’ve come to these conclusions. The information imparted by researchers and scientists was often considered less reliable, and rarely taken at face value:Generally, participants were only convinced by research that had been vetted by a “respected” organisation such as the NHS, or had been conducted by a clinician with expertise in that area of health: “if there were doctors that I was aware of that had actually written the article or contributed to the article, or the study, or the research, then that would be a big plus” (TI19).(TI23)I would take it with a pinch of salt because there’s so much information nowadays on the internet and in the media, social media and that, fake news. I’d want it backed up by information on the NHS websites. Although participants often read health‐related information communicated in the media , they unanimously agreed it cannot be trusted or taken seriously:“Interviewer:How do you know what is a real risk factor?Participant:Only from what you hear, and from other people.” (TI22)Despite this, many women reported discussing information they had seen in the media with female peers and family members: “We gossip…I would say something like, ‘did you see such‐and‐such or did you read this magazine article?’” (TI19). Indeed, some participants confirmed “hearsay” to be the main source of their knowledge about risk factors for breast cancer:(T105)Companies are very good at making these alcoholic beverages appealing to people, especially the ‘a glass of wine, red wine, a day is good for you’. They’re so clever, aren’t they? With inconsistent media messages about modifiable risk factors such as alcohol consumption, women highlighted the difficulty in navigating information to inform their decisions about lifestyle choices:3.3.2(TI26)It’s a really emotional thing…so I guess somehow in the communications or information, making sure we’re really aware of the emotions that people may be going through and make sure we’re sensitive and responsive to that. A final theme running throughout the data was the need for information about risk factors that is not pejorative or blaming towards women for making “bad” lifestyle choices: “that's where the vilification comes in…we are just trying to lead a normal life, and maybe we'll have a glass of wine every now and again, and we are being told that's wrong” . Several women spoke of the emotional sequelae of attending a breast clinic or experiencing breast symptoms, and the need for this to be considered when communicating health information:(TI12)I don’t believe that you’re in the situation at the moment that anyone can categorically put their finger on something and say this is exactly what caused it; I think the term ‘contributing factor’ is far more reasonable. There was a preference for messages that incorporated clear facts about risks but with an acknowledgement that scientific knowledge is incomplete, and numerous, intertwining factors can contribute to one's risk of cancer. Participants alluded to the importance of language in communicating such information, with several averse to definitive statements about “causes” of cancer which could “create a blame culture”:The same participant suggested that subtle changes in terminology can have a profound impact on women's receptivity to breast health information, a point echoed in several other interviews: “by changing the terminology…you're removing yourself from the finger pointing aspect of it.”(TI25)The balance comes if the risks are strong enough, and if I’m aware enough…I would evaluate that on conversations with health professionals in terms of my own personal risk factors. Participants also discussed the need to respect an individuals’ decision for not taking steps to change their lifestyle when it may reduce their risk of cancer: “I know I drink too much, and I know that potentially could be a risk factor but that's a considered choice on my behalf” (TI24). Several described a “balancing act” between taking responsibility for optimising one's health longer term, and their prerogative to make lifestyle choices on a given day. However, in order to manage this tension, women agreed that they need impartial and personally relevant information:4Health events, such as cancer screening or investigation of symptoms, are considered ideal “teachable moments” for prevention interventions, as they can optimise already‐heightened patient motivation into changing risk‐inducing behaviours like alcohol consumption  experience breast cancer symptoms, reported no attempts to seek information about risk factors, or disregarded information they had found; this was often due to perceptions that such information was irrelevant, fear‐inducing or pejorative. Moreover, participants who expressed fatalistic views about cancer appeared more resistant to information regarding modifiable risk factors—and recent research found an association of such views with engagement in unhealthy behaviours  drink above the UK Chief Medical Officer's current guidelines of 14 units of alcohol per week (Health & Social Care Information Centre, Nevertheless, despite some initial hesitancy to engage in discussions about alcohol, most participants in the present study were interested to learn of its association with breast cancer and appeared willing to share this information with female friends and family members. Integrating alcohol advice within a broader healthy lifestyle intervention may be one way to increase women's receptivity, although this needs further investigation. Moreover, participants’ mistrust of much information about breast cancer and lifestyle, with the exception of that provided by the NHS, suggests that NHS breast clinics provide an ideal setting in which to deliver such advice, and facilitate discussions that women might ordinarily be reluctant to have. Supporting this, Stead, Caswell, Craigie, Eadie, and Anderson  argue th4.1The results presented in this paper reflect the views of a small number of women seen in screening and symptomatic clinics in one city in the UK. While this is broadly the target population for whom our intervention is being designed, these findings may not be generalisable to other parts of the UK. Moreover, all participants were willing and able to discuss the topics of breast cancer and alcohol, and although not systematically recorded, several participants reported personal experience of cancer, which may have had an impact on the opinions given. This is an important consideration as only ~10% of women attending symptomatic clinics, and <1% attending screening clinics in the UK, receive a breast cancer diagnosis (Adams, Midha, Postulka, & Ortiz, 5Women reported a personal responsibility for their health and expressed interest in learning about modifiable risk factors for breast cancer, especially from trusted organisations such as the NHS. Breast screening and symptomatic clinics present an opportunity for a “teachable moment” for preventative breast cancer advice, supporting prior research in this setting, for example (Anderson et al., None for any author. Click here for additional data file.


It is unclear whether alcohol consumption may impact survival after breast cancer diagnosis. To clarify the association between pretreatment alcohol consumption and survival in breast cancer patients, a prospective patient cohort study was conducted.The cohort comprised 1,420 breast cancer patients diagnosed during 1997–2013 at a single institute in Japan. Alcohol drinking and other lifestyle factors were assessed by questionnaire survey at the initial admission. The patients were followed until December 31, 2016. The crude associations of pretreatment alcohol intake with survival were evaluated by Kaplan-Meier analysis. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) controlled by confounders.During a median follow-up period of 8.6 years, 261 all-cause and 193 breast cancer-specific deaths were documented. Survival curves showed that ever-drinkers tended to have better survival than never-drinkers . Better survival was also observed for light drinkers with an intake of <5.0 g per day. In the Cox model, ever-drinking was associated with a decreased risk of all-cause  and breast cancer-specific death . Light drinkers had a lower risk of breast cancer-specific death . In terms of hormone receptor status, a significantly decreased risk of death associated with ever-drinking was observed among women with receptor-negative cancer .Pretreatment, i.e., pre-diagnosis alcohol consumption is unlikely to have an adverse effect on survival after breast cancer diagnosis. Light alcohol consumption may have a beneficial effect on patient survival. Epidemiologic studies have shown that alcohol consumption is associated with an increased risk of breast cancer, and it is now regarded as an established risk factor for the disease , 2. DataIn order to clarify the association between alcohol consumption and survival after breast cancer diagnosis, we conducted a hospital-based prospective patient cohort study. Data on alcohol-related measures and clinical information for breast cancer patients were obtained from a questionnaire survey at their first admission and from a hospital-based cancer registry at a single institute in Japan, and a long-term follow-up survey was conducted. In this study, we evaluated the risk of all-cause and breast cancer-specific death stratified by hormone receptor status as well as the risk among the patients overall.This study was approved by the Management Committee of the Miyagi Cancer Center  and the Ethics Committee of the Miyagi Cancer Center  and conducted in accordance with the principles specified in the Declaration of Helsinki. The questionnaire survey in connection with the present study was started with the approval of the Management Committee. The Ethics Committee independently reviewed the protocol of the present study that used the questionnaire data and cancer registry data. The purpose of the study was stated on the cover page of the questionnaire. We considered the return of self-administered questionnaires signed by the patients to imply their consent to participate in the study.Between January 1997 and December 2013, 1,570 first-admitted female patients aged 20 years or over without a history of cancer were diagnosed as having breast cancer at the Miyagi Cancer Center Hospital (MCCH). At the time of admission, these patients were requested to complete a self-administered questionnaire including history of alcohol drinking. After diagnosis, the patients were registered to the hospital-based cancer registry and followed up. Details of the questionnaire survey and cancer registry have already been described elsewhere , 26. AmoThe questionnaire covered demographic characteristics, personal and family histories of cancer and other diseases, current height and weight, general lifestyle factors including alcohol intake, dietary history, cigarette smoking, physical activity, and menstrual and reproductive histories, and referral status. We obtained data on alcohol consumption and other lifestyle factors from this questionnaire. Dietary history and alcohol intake were evaluated using a food frequency questionnaire (FFQ). The FFQ has been validated in general population, whose residential area was roughly the same as that of our study subjects .Clinical information including tumor stage based on the UICC TNM classification, and initial adjuvant treatment was obtained from the MCCH cancer registry. Information on estrogen/progesterone receptor (ER/PR) expression were extracted from medical records.At the MCCH, in principle, detailed diagnostic tests and initial therapy are initiated after admission. Therefore, exposure data  collected by the questionnaire survey were considered to be pretreatment or pre-diagnosis data.sake, Japanese spirits (shochu), beer, whisky, wine and others]. For each type of alcohol beverage consumed, they were also asked to state the volume drunk after conversion into the Japanese sake equivalent by reference to a conversion table . The amount of alcohol consumed per day was calculated as: ) x (frequency of drinking per week) / 7 [For assessment of alcohol intake, the FFQ asked initially if the study subjects were never, past, or current drinkers. Past or current drinkers were asked to state age at start of drinking, frequency of drinking per week, and the types of alcohol beverages consumed [Japanese on table  Files. Oeek) / 7 .The exposure variables related to alcohol consumption included history of alcohol drinking , frequency of drinking per week , age at start of drinking , and amount of alcohol consumed per day . Although, in our previous case-control and cohort studies of breast cancer, the quantitative exposure variable had been classified based on finer categories , 29, theFollow-up of patients was performed by reference to the MCCH cancer registry up to December 2016. The registry conducted active follow-up by accessing hospital visit records, resident registration cards and permanent domicile data. For deceased patients, information on the date and cause of death was obtained with permission from the Ministry of Justice. As a general rule for this registry, each individual follow-up ends in the 11th year after diagnosis . TherefoThe end point of our analysis was all-cause death and breast cancer-specific death according to the International Classification of Disease for Oncology, Tenth Edition (ICD-10). Survival time was calculated for each patient from the date of diagnosis to the date of death or the end of follow-up.To investigate the risk of all-cause and breast cancer-specific death, Kaplan-Meier survival analysis and Cox proportional hazards model were used. The crude associations of exposures with survival were evaluated by Kaplan-Meier analysis. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) controlled by confounders. We considered the following variables to be potential confounders: age, year of diagnosis, tumor stage , hormone receptor status , menopausal status , radiation therapy , chemotherapy , endocrine therapy , family history of breast cancer in father, mother, brother or sister , body mass index (BMI) , physical activity , occupation , referral status , and comorbidities . Comorbidities included hypertension, ischemic heart disease, stroke and diabetes mellitus. Reproductive factors including menarche and parity, history of smoking and folate intake were also considered as confounders. Our previous studies had revealed associations of reproductive factors, BMI and smoking with patient survival , 26, 30.For analysis using the Cox model, we first evaluated HRs according to exposure among the patients overall. Second, separate analyses were conducted by dividing the patients according to hormone receptor status. Third, some stratified analyses were performed to examine whether the association of alcohol intake with survival differed in relation to selected factors including menopausal status, BMI, and folate intake. Results were regarded as significant if the two-sided P values were <0.05. For each analysis, the proportional hazards assumption was assessed based on log–log plots of survival and testing time dependent cross-product terms of the survival time and exposures. The cross-product terms were not significant in any of the models, indicating no significant violation of the assumptions. Statistical analyses were performed using the SAS software package  and JMP software .During a median follow-up period of 8.6 years , 261 all-cause and 193 breast cancer-specific deaths were observed. In this hospital-based patient cohort study, we clarified the association between pretreatment alcohol intake and the risk of all-cause and breast cancer-specific death among Japanese women with breast cancer. Ever-drinking tended to be associated with a decreased risk of all-cause and breast cancer-specific death. In terms to hormone receptor status, the decreased risk of death appeared to be limited to women with receptor-negative cancer. To our knowledge, our study is the first to have investigated the association of alcohol consumption with breast cancer survival in Asian women, whose alcohol intake is low relative to that of Caucasian women , 24. TheAlcohol consumption has been considered an established risk factor for breast cancer. However, it has been unclear whether alcohol intake before breast cancer diagnosis affects the risk of mortality after diagnosis. One meta-analysis found that moderate drinkers had better overall survival, although it was not possible to estimate the combined risk for breast cancer-specific mortality because of the data heterogeneity among individual studies . AnotherPrevious studies have demonstrated some health effects of alcohol consumption. Among community-dwelling women, light to moderate alcohol drinking was associated with a decreased risk of all-cause death , 36. It In terms of hormone receptor status, the decreased risk of death associated with ever-drinking was observed among patients with receptor-negative cancer but not among those with receptor-positive cancer . Several previous studies have investigated the risk according to hormone receptor status, but the results have been inconsistent , 21, 22.Analyses stratified by other selected factors have found improved survival among premenopausal women who drink alcohol. In some previous studies, heavy drinking was associated with an increased risk of all-cause and breast cancer-specific death among postmenopausal patients , 14, 16.The present study had both strengths and limitations. One of the strengths was a high quality of follow-up; only 3 patients (0.2%) were lost to follow-up. The quality of the clinical data was also high. For example, there were very few patients for whom hormone receptor status was unknown . AnotherIn conclusion, the present patient cohort study of Japanese women with breast cancer has shown that pretreatment alcohol consumption was associated with a decreased risk of all-cause and breast cancer-specific death. According to alcohol consumption level, the decreased risk of breast cancer-specific death was found for light drinkers. In terms of hormone receptor status, a decreased risk of death associated with ever-drinking was observed among women with receptor-negative cancer but not among those with receptor-positive cancer. These findings suggest that pre-diagnosis alcohol intake is unlikely to have an adverse effect on survival after breast cancer diagnosis. Light alcohol consumption may have a beneficial effect on patient survival. However, alcohol drinking is associated with an increased risk of breast cancer. To improve breast cancer risk and survival, further studies will need to clarify the appropriate levels and timing of alcohol consumption.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.


Metabolites are genetically and environmentally determined. Consequently, they can be used to characterize environmental exposures and reveal biochemical mechanisms that link exposure to disease. To explore disease susceptibility and improve population risk stratification, we aimed to identify metabolic profiles linked to carcinogenesis and mortality and their intrinsic associations by characterizing subgroups of individuals based on serum biomarker measurements. We included 13,615 participants from the Swedish Apolipoprotein MOrtality RISk Study who had measurements for 19 biomarkers representative of central metabolic pathways. Latent Class Analysis (LCA) was applied to characterise individuals based on their biomarker values , which were then examined as predictors of cancer and death using multivariable Cox proportional hazards models.LCA identified four metabolic profiles within the population: (1) normal values for all markers (63% of population); (2) abnormal values for lipids (22%); (3) abnormal values for liver functioning (9%); (4) abnormal values for iron and inflammation metabolism (6%). All metabolic profiles (classes 2–4) increased risk of cancer and mortality, compared to class 1 , 1.67 (95% CI: 1.47–1.90), and 1.21 (95% CI: 1.05–1.41) for class 2, 3, and 4, respectively).We present an innovative approach to risk stratify a well-defined population based on LCA metabolic-defined subgroups for cancer and mortality. Our results indicate that standard of care baseline serum markers, when assembled into meaningful metabolic profiles, could help assess long term risk of disease and provide insight in disease susceptibility and etiology.The online version of this article (10.1186/s12860-019-0210-7) contains supplementary material, which is available to authorized users. Cancer is a multi-pathway disease, assembled as a heterogeneous and hierarchically organized system, and still one of the major causes of death worldwide – with an increasing burden given the aging population –3. CanceWith the overall goal of identifying statistical methods to stratify individuals based on their underlying risk of developing cancer and risk of increasing mortality, we conducted a data driven approach utilizing standard serum markers available from routine health check-ups to study susceptibility to cancer and death in a well-defined cohort of 13,615 participants from the AMORIS study  , 20. MorA total of 1,956 individuals (14.37%) developed cancer after at least 3 years of follow-up, including 655 breast and genito-urinary cancers, 330 cases of digestive cancer, 133 cases of respiratory cancers and 129 lymphatic and hematopoietic cancers during a mean follow-up time for cancer of 16.6 years, median follow-up time in the cohort of 17.22 years with a minimum of 3.01 years and a maximum of 24.77. Three thousand one hundred fifty-eight participants (23.20%) died during a mean follow-up of 17.3 years, comprising 706 cancer-specific deaths. Study population characteristics by cancer status is illustrated in Table LCA was executed using the dichotomized values of the biomarkers to facilitate the biological interpretation of the results. The Chi-squared distribution criterion for model selection indicated a best fit model comprehend of four LCA classes, while AIC and BIC stabilized at 4 classes Fig. a, b 21]21]. All Table A validation of the characterization of the population performed with the Latent class methodology is outlined in Additional file We then investigated the prediction capabilities of the four LCA-derived metabolic profiles to estimate overall cancer risk, specific cancer types risk, cancer mortality and overall mortality, assigning the reference level to the healthy metabolic profile Class 1 Tables  and 4.TaAll metabolic profiles increased risk of cancer and mortality compared to Class 1. For instance, individuals in Class 3  had a higher risk of overall cancer (HR: 1.28 (95% CI: 1.10–1.50)), but also a worse cancer-specific survival and overall survival as compared to those in Class 1 Tables . Class 2When assessing the risk of specific cancer types, several patterns occurred Tables  and 4. IMoreover, the connective tissue and endocrine glands cancer risk was higher in individuals grouped in liver metabolic profile (HR: 2.65 (95% CI: 1.00–7.02) and in participants belonging to the iron markers and inflammation (HR: 3.00 (95% CI: 1.11–8.11)). Similar associations were observed when using the age scale for the multivariable cox proportional hazard regression model Tables .We demonstrated that standard of care baseline serum markers when assembled into meaningful metabolic profiles can help stratify the population for cancer risk, cancer mortality and overall mortality. More specifically, we observed that abnormal values for markers of the lipid metabolism, liver function and inflammatory and iron metabolism distinguish participants into metabolic profiles, which are predictive of long term cancer risk and/or mortality.Among the biological pathways addressed in our LCA, abnormalities in the lipid metabolism were the most common. Hyperlipidemia was present in about a quarter of the study population explaining the largest abnormal metabolic profile. The weight of the lipid profile in the analysis was consistent with the reported global prevalence of hypercholesterolemia among adults  as reported in the Global Health Observatory in 2008 estimates by the World Health Organization (WHO) and the results from the Swedish population in the WHO MONICA project . DyslipiThe above-described three classes of abnormal metabolic profiles were all associated with an increased risk of cancer and worse survival, as compared to the healthy class. The findings therefore confirm the key importance of these metabolisms in the maintenance of the intracellular homeostasis and how their unbalance can be related with the etiology of cancer disease and mortality . The LCAabnormal liver function markers carried worse outcomes in terms of overall cancer risk and cancer death, and a positive association with digestive, connective and endocrine cancers diagnosis. Moreover, the participants with this profile had a higher probability of overall death. These results are consistent with previous published data. A positive association between elevated GGT and overall cancer risk, with no interaction of ALT, was found in the AMORIS cohort previously [More specifically, individuals presenting eviously , and it eviously , 32. Theeviously . Howevereviously . Moreoveeviously . In the lipid profile presented positive associations with cancer mortality, and overall mortality and higher risk of lymphatic and hematopoietic cancers. The link between hyperlipidemia and mortality has been studied broadly, with associations with established links for cancer and all-cause mortality [Individuals allocated to the ortality –38. The ortality , 40. Howortality .unbalanced iron profile and inflammation had an increased risk of endocrine, buccal and oral cancers and were observed to have a higher risk of all-causes death. Altered inflammation and iron metabolisms are key metabolic ‘hallmarks of cancer’ [Participants clustered in the  cancer’ , 42, 43.The modulation effect of population heterogeneity on the association between potential risks factors and disease is a new avenue to understand the variability of risk in the population . For insn > 13000), however not every marker of the central metabolic pathways was available in the database (i.e. Complete Blood Count). Life-style factors established as cancer risk factors such as tobacco smoking, low physical activity, poor diet, alcohol intake, obesity and hypertension were partially available in AMORIS which limited their used in the study. To mitigate the lack of some of these external factors such as BMI, the analyses have been adjusted for Charlson Comorbidity Index which includes comorbidities such as obesity and hypertension. The lack of others life-style factors such as alcohol consumption was mitigated by using information on serum biomarkers such as gamma glutamyl transferase and other liver enzymes. All participants were selected by analyzing blood samples from health check-ups in non-hospitalized individuals from the greater Stockholm area ensuring good internal validity in the study. Future studies will benefit from a longitudinal approach with repeated serum markers measurements that will capture the population phenotypic variations in relation to disease over long periods of time and will help to improve our understanding of the biomarkers’ impact on carcinogenesis and mortality.The present study has been conducted in a large and well-defined population, applying a multi-faced approach covering main biological pathways to assess biomarker profiles that could indicate cancer risk, cancer survival and mortality. The major strength of these analyses lies in the innovative avenue to study population heterogeneity and susceptibility to disease and mortality in a large cohort of participants with multiple measurements, all measured on fresh blood samples on the same day at the same clinical laboratory. We included all the markers available in the cohort for a large population , which were all measured on the same day, using fully automated methods with automatic calibration performed on fresh blood samples, at the same laboratory (CALAB) of high quality according to international blinded testing [9 cells/L), C-reactive protein (CRP) (mg/L), iron (FE) (μmol/L), total iron binding capacity (TIBC) (mg/dL), creatinine (μmol/L), phosphate (mmol/L) and calcium (mmol/L). All methods have previously been described [From the AMORIS cohort, we included all individuals aged 20 years or older with measurements for the following serum biomarkers  and glucose metabolism , liver function , inflammation , iron metabolism (FE and TIBC), kidney function (Creatinine) and phosphate . The blood metabolites included in the analysis were all the standard serum markers available from routine health check-ups. Most of the markers included have been previously studied individually in AMORIS, however no systemic integrative approach to examine the metabolic markers interactions and susceptibility to cancer has been conducted to date , 50–59. The main exposure variables for the analyses were the above-mentioned metabolic biomarkers, for which the values were categorized using standardized clinical cut-offs based on recognized medical criteria to facilitate interpretation of the results  calculated based on data from the National Patient Register. The CCI comprises 19 disease categories, all assigned a weight. The sum of an individual’s weights was used to create the CCI ranging from no comorbidity to severe comorbidity  .Pearson correlation coefficients to measure the strength of association between the biomarkers included in the analysis. Pearson’s correlation analyses showed strong correlation between the different biomarkers in the lipid metabolism ; HDL and ApoA-I (r > 0.8)). We replaced the individual lipid biomarkers by the established ApoB/ApoA-I ratio and log (TG/HDL) ratio [First, we calculated L) ratio , 61, 62 L) ratio . Most ofLatent Class Analysis (LCA) [is (LCA) , 64 is ais (LCA)  and has is (LCA) , 66. Moris (LCA)  and to eis (LCA)  in R stamultivariable Cox proportional hazard regression to examine whether the LCA-derived metabolic classes were associated with long term risk of overall cancer as well as specific cancer types. In addition, we evaluated how the classes were associated with all cause-death and cancer-specific death. All models were adjusted for age, sex, and CCI. We performed a sensitivity analysis using age as a time-scale, as this is potentially a strong confounder. Moreover, Schoenfeld residuals were tested to ensure the proportional hazard assumption of the multivariable cox proportional hazard regression analysis.Once each subject was assigned to its LCA-derived metabolic class, we conducted Data management and statistical analyses were performed using Statistical Analysis Systems (SAS) release 4.3  and R version 3.0.2 .Additional file 1:Table S1. Laboratory fully automated methods with automatic calibration were performed at one accredited laboratory


Our aim was to assess the role of breast density on breast cancer mortality and recurrences, considering patient and tumour characteristics and the treatments received among women attending population-based screening programmes.  We conducted a retrospective cohort study among women aged 50–69 years attending population-based screening programmes, diagnosed with invasive breast cancer between 2000 and 2009, and followed up to 2014. Breast density was categorised as low density (≤25% dense tissue), intermediate density (25–50%), and high density (≥50%). Cox proportional hazards regression models were fitted to estimate the adjusted hazard ratios (aHR) and 95% confidence intervals (95% CI) for death and recurrences, adjusting by patient characteristics, mode of detection , and tumour features. p=0.011 for death; p=0.037 for recurrences). Adjusted Cox proportional hazards regression models revealed that women with intermediate- and high-density breasts had a higher risk of death than women with low-density breasts, being statistically significant for intermediate densities . No association was found between breast density and recurrences.  The percentage of deaths and recurrences was higher among women with intermediate- and high-density breasts than among women with low-density breasts ( Breast density was associated with a higher risk of death, but not of recurrences, among women participating in breast cancer screening. These findings reinforce the need to improve screening sensitivity among women with dense breasts and to routinely assess breast density, not only for its role as a risk factor for breast cancer but also for its potential influence on cancer prognosis. Mammographic breast density is defined as the relative amount of radiolucent elements (fatty tissue) and radiopaque elements of the breast (fibroglandular tissue). It has become a key element in breast cancer screening because of its dual effect on breast cancer risk: high breast density impairs the detection of abnormalities in the breast, decreasing the sensitivity of mammography , and is Variations in breast density during a woman's lifetime may be influenced by several internal and external factors related to the hormonal environment. Breast density is inversely associated with age, with premenopausal women younger than 50 years being more likely to have dense breasts . The useHowever, whereas increased breast density is a well-recognised risk factor for breast cancer, the relationship between breast density and breast cancer prognosis is still controversial. Some studies have reported an increased risk of death for women with dense breasts , 11, whiOur aim was to assess the role of breast density on mortality and recurrences, taking into account patient and tumour characteristics and the treatments received among women attending population-based screening programmes.This study was carried out among a retrospective cohort of 1,086 women with breast cancer, aged between 50 and 69 years, who underwent breast cancer screening in two Spanish regions . All of them were diagnosed with breast cancer between 2000 and 2009 and were followed up until June 2014. The study included asymptomatic women with cancers detected in routine screening mammograms and symptomatic women with cancers detected between two screening mammograms .Mammography screening in Spain follows the recommendations of the European Guidelines for quality assurance in breast cancer screening and diagnosis , offerinAs breast density is not routinely recorded by all participating screening programmes, we determined breast density for a subsample of cases. Sample size was calculated to estimate a hazard ratio of 2.5 , with a The study protocol was approved by the Ethics Committee of Parc de Salut Mar, Barcelona . Specific patient consent was not required.For the purpose of this study, breast density was retrospectively evaluated by three experienced radiologists who followed a consensus-based protocol, as detailed elsewhere . In briePatient information, including age at diagnosis, menopausal status, hormone replacement therapy (ever/never), and first-degree family history of breast cancer, was obtained from the databases of the screening programmes. To obtain information on the burden of disease at diagnosis, we manually reviewed clinical records to identify the presence of comorbidities and construct the Charlson comorbidity index (CCI) . The CCIInformation on mode of detection was obtained from the screening programme databases and by merging data with population-based cancer registries, the hospital minimum basic dataset, and hospital-based cancer registries. We differentiated between breast cancers detected by routine screening mammograms  and cancers detected between 2 screening mammograms, or within 24 months for women who reached the upper age limit . Further details on the identification of interval cancers are explained elsewhere . Tumour-From the review of the clinical records, we obtained information on the treatments received. We considered two types of surgery: radical  and conservative. Information on breast surgery and axillary lymph node dissection (ALND) treatments was collapsed into a single explicative variable. Information on adjuvant treatment was categorised as follows: chemotherapy, radiotherapy, and hormonal therapy; radiotherapy and hormonal therapy; and other treatments.Information on recurrences , second breast neoplasms, and vital status at the end of follow-up  was obtained from the cancer registries and clinical records. Locoregional recurrence was defined as disease recurrence within the ipsilateral breast or chest wall, in the ipsilateral axillary nodes, internal mammary nodes, or supraclavicular nodes. Distant recurrence was defined as disease recurrence in sites other than the breast or regional lymph nodes . A second neoplasm was considered as a second primary carcinoma developing in the ipsilateral or contralateral breast.Overall survival was computed from the date of breast cancer diagnosis to death from any cause. Patients were censored at the date of their last hospital visit. Recurrence-free survival was computed from the date of breast cancer diagnosis to the first locoregional or distant recurrence, whichever occurred first. Women lost to follow-up or those who died were censored either at the last visit or at death. The median follow-up period was 8.7 years (interquartile range (IQR): 7.2–10.6).Descriptive analyses of patient and tumour characteristics and the treatments received according to breast density categories were explored using contingency tables.Survival curves for overall mortality and for recurrences were generated by using the Kaplan–Meier method and were compared by the log-rank test. Recurrence-free survival and overall survival were plotted by breast density categories. 5-year and 10-year survival rates and their 95% confidence intervals (95% CI) were computed.We fitted two multivariate Cox proportional hazards regression models to estimate the hazard ratios (HR) and their 95% CI for death and recurrences using a stepwise backward variable selection approach. The initial model included all predictors. In the final models, we forced to include age, screening programme, and CCI as adjusting variables, although they were not statistically significant. The proportional hazards assumption was ascertained by assessment of log-log survival plots. To test the statistical significance of breast density variable as a whole, we performed a Wald test in both models.p values <0.05 were considered statistically significant. Analyses were performed using the statistical software IBM SPSS Statistics version 23.0  and R statistical software version 3.3.2 (http://www.r-project.org).All statistical tests were two-sided. A total of 375 invasive breast cancers were included in this study, most of them detected among women with low-density breasts .Patient characteristics by breast density categories are summarized in Tumour characteristics according to breast density categories are shown in p=0.010) and poorer relapse-free survival (p=0.032) among women with high-density breasts  but not for predicting recurrences . Women with intermediate- and high-density breasts had a higher risk of death than women with low-density breasts, reaching statistical significance for intermediate densities  . Node-poThe results of the current study suggest that higher breast density is associated with a greater risk of death in women participating in breast cancer screening, while breast density showed no association with the risk of recurrences.The positive association between dense tissue and risk of death is consistent with some , 15, butSome authors have hypothesized that the association between higher density and worse survival would be explained by the diagnosis delay due to the masking effect. In that sense, we do observe a higher percentage of larger, node-positive, and interval cancers among women with high-density breasts in the descriptive data. In the adjusted analyses, lymph node involvement and detection as an interval cancer were also associated with mortality, along with intermediate breast densities so that the current results would support this hypothesis, since breast density as well as other factors related to diagnostic delay remained associated with the risk of death. These findings reinforce the need to improve screening sensitivity among women with dense breasts, which is currently been proposed by means of shifting the conventional one-size-fits-all screening approach towards more personalized screening strategies based on the individual risk of breast cancer.Other authors have postulated that the relationship between breast density and survival may be explained by the tumour characteristics of cancers arising in epithelial tissue. It has been suggested an increased proliferation and growth factors in dense tissue , 27 thatContrasting with prior series, we did not find association between breast density and the risk of recurrences –31. ThosOur study is limited by the relatively small number of events in some categories, which prevented us from including all breast density categories of Boyd's scale in the adjusted model. Nevertheless, most studies assessing the effect of breast density on mortality outcomes collapse breast density data into two or three categories, making our data more comparable with those of previous works. Second, we were not able to explore breast-specific cancer mortality. Previous studies exploring both breast-specific cancer mortality and mortality from other causes found that the latter was not associated with breast density . TherefoThe current study is strengthened by the homogeneity of the study population included. Restricting the study to screening participants allowed us to explore the effect of breast density on a relatively homogeneous group of patients in terms of age range and tumour stage. Thus, the conclusions drawn from the current work are robust and informative within the framework of population-based screening and are of interest for tailored screening strategies. In addition, the availability of data on comorbidities, patient and tumour characteristics, and the treatments received allowed us to control for important prognostic factors and to explore—for the first time among women participating in breast cancer screening—the effect of breast density on mortality considering both patient and tumour characteristics and treatments received.In conclusion, our findings reveal that increased breast density was associated with worse survival outcomes among women participating in breast cancer screening. This association seems to be mainly explained as a result of the masking effect of dense tissue, although an underlying biological mechanism in the stroma composition may also play a role. These findings reinforce the need to improve screening sensitivity among women with dense breasts by means of more personalized screening approaches as well as the importance to routinely assess and record information on breast density during the screening process, both because of its utility as a predictive factor for breast cancer and because of its role in breast cancer prognosis.


To examine whether sleep traits have a causal effect on risk of breast cancer.Mendelian randomisation study.UK Biobank prospective cohort study and Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.156 848 women in the multivariable regression and one sample mendelian randomisation (MR) analysis in UK Biobank (7784 with a breast cancer diagnosis) and 122 977 breast cancer cases and 105 974 controls from BCAC in the two sample MR analysis.Self reported chronotype (morning or evening preference), insomnia symptoms, and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.Breast cancer diagnosis.In multivariable regression analysis using UK Biobank data on breast cancer incidence, morning preference was inversely associated with breast cancer , whereas there was little evidence for an association between sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated with sleep duration, and 57 SNPs associated with insomnia symptoms, one sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk  but imprecise estimates for sleep duration and insomnia symptoms. Two sample MR using data from BCAC supported findings for a protective effect of morning preference  and adverse effect of increased sleep duration  on breast cancer risk (both oestrogen receptor positive and oestrogen receptor negative), whereas evidence for insomnia symptoms was inconsistent. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.Findings showed consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of increased sleep duration on breast cancer risk. In 2007 the World Health Organization’s International Agency for Research on Cancer classified shift work that involves circadian disruption as being probably carcinogenic to humans.In a meta-analysis of 28 studies, strong evidence suggested a positive association between circadian disruption and breast cancer risk . However, the association with short sleep duration (<7 hours a night) in seven contributing studies was much less conclusive , and no dose-response association with sleep deficiency was observed.Mendelian randomisation (MR) uses genetic variants that are robustly associated with potentially modifiable risk factors to explore causal effects on outcomes.We used genetic variants robustly associated with chronotype, sleep duration, and insomnia symptoms identified in three recent UK Biobank GWASwww.ukbiobank.ac.uk/wp-content/uploads/2011/11/UK-Biobank-Protocol.pdf) and more details are published elsewhere.We used data on women from the UK Biobank, which recruited more than 500 000 participants (55% women) out of 9.2 million eligible adults aged between 40 and 70 years in the UK who were invited to participate (5.5% response rate).At baseline assessment, conducted in one of 22 UK Biobank assessment centres between 2006 and 2010, participants completed a touchscreen questionnaire, which included questions about sociodemographic status, lifestyle and environment, early life and family history, health and medical history, and psychosocial factors. Participants were asked about their chronotype (morning or evening preference), average sleep duration, and insomnia symptoms.v 7-8 hours) and long sleep duration (>8 hours v 7-8 hours) were also derived. To assess insomnia symptoms, participants were asked: “Do you have trouble falling asleep at night or do you wake up in the middle of the night?” with responses “Never/rarely,” “Sometimes,” “Usually,” or “Prefer not to answer.” Those who responded “Prefer not to answer” were set to missing. We derived a three level ordinal variable for insomnia symptoms where “Never/rarely,” “Sometimes,” and “Usually” were coded as 0, 1, and 2, respectively.Chronotype (morning or evening preference) was assessed in the question “Do you consider yourself to be?” with one of six possible answers: “Definitely a ‘morning’ person,” “More a ‘morning’ than ‘evening’ person,” “More an ‘evening’ than a ‘morning’ person,” “Definitely an ‘evening’ person,” “Do not know,” or “Prefer not to answer.” We derived a five level ordinal variable for chronotype where “Definitely a ‘morning’ person,” “More a ‘morning’ than ‘evening’ person,” “More an ‘evening’ than a ‘morning’ person,” “Definitely an ‘evening’ person,” “Do not know,” or “Prefer not to answer” were coded as 2, 1, −1, −2, 0, and missing, respectively. Sleep duration was assessed by asking: “About how many hours sleep do you get in every 24 hours? (please include naps).” The answer could only contain integer values. Binary variables for short sleep duration  codes and cancer deaths. The endpoints in these analyses were first diagnosis of invasive breast cancer , or breast cancer listed as the underlying cause of death on the death certificate for women who died during follow-up but were not captured by the cancer registers. We excluded all women with any other cancer diagnosis from the analysis. At the time of analysis, mortality data were available up to February 2016 and cancer registry data up to April 2015. Prevalent cases were defined as women with a diagnosis of breast cancer before date of recruitment to the UK Biobank. Incident cases were defined as women with a diagnosis of breast cancer or dying from it during follow-up.We considered several factors to be potential confounders of the association between sleep traits and breast cancer risk: education, body mass index (BMI), alcohol intake, smoking, strenuous physical activity, family history of breast cancer, age at menarche, parity, use of oral contraceptives, menopause status, and hormone replacement therapy.BMI was derived from weight and height measured when participants attended the initial assessment centre, whereas information on other potential confounders was obtained from questionnaire responses completed at baseline (see methods in supplementary file). Additional information extracted from the initial assessment visit included centre of initial assessment visit, age at recruitment derived from date of birth, and date of attending assessment centre. Participants who were employed were also asked whether their current job involved night shifts: never/rarely, sometimes, usually, or always.The full data release in UK Biobank contains the cohort of successfully genotyped people (n=488 377). A total of 49 979 people were genotyped using the UK BiLEVE genotyping chip and 438 398 using the UK Biobank axiom genotyping chip. Pre-imputation quality control, phasing, and imputation of the UK Biobank genetic data have been described elsewhere.In the MR analysis, we used a total of 341 single nucleotide polymorphisms (SNPs) associated with chronotype,We carried out separate multivariable Cox regression between chronotype, insomnia symptoms, and sleep duration and incident breast cancer to investigate prospective associations between these sleep traits and to minimise the likelihood of reverse causality in observational associations. To minimise the role of confounding, we adjusted analyses for age, assessment centre, and the top 40 genetic principal components  to detect and quantify the genetic structure of populations). A second model additionally adjusted for education, BMI, alcohol intake, smoking, strenuous physical activity, family history of breast cancer, age at menarche, parity, menopause status, use of oral contraceptives, and hormone replacement therapy. For one sample MR, the genetic variants used were extracted genotypes from the UK Biobank imputation dataset (imputed to the Haplotype Reference Consortium reference panel), which performed extensive quality control including exclusion of most third degree or closer relatives from a genetic kinship analysis, as well as those who were not classified as white British based on questionnaire and PCAA two stage method was implemented to give a population average causal hazard ratio. The first stage model consisted of a regression of the sleep trait  on the allele score and the second stage model consisted of a Cox regression of breast cancer status on the fitted values from the first stage regression, with adjustment for age at recruitment, assessment centre, 40 genetic principal components, and genotyping chip in both stages. To check the proportional hazards assumption, we used Pearson correlations to test Schoenfeld residuals from both multivariable Cox regression and one sample MR Cox regression models for an association with follow-up time.To assess the specificity of our findings to breast cancer, we performed multivariable regression and one sample MR analysis to assess the causal effect of the sleep traits on other cancer diagnoses and on all cause mortality.We also performed MR analysis using only those genetic variants that replicated at Bonferroni significance in a large independent dataset for chronotype−3) as a further sensitivity analysis.To test the MR assumption that genetic variants should not be associated with confounders of the exposure-outcome relation, we investigated associations between the allele scores and potential confounders in UK Biobank. We then performed one sample MR analysis adjusted for any potential confounders found to be strongly associated with the allele scores  in a logistic regression analysis in UK Biobank, and performed sensitivity analysis removing participants who reported currently working night shifts .We conducted a two sample MR analysis of sleep traits on breast cancer risk using female specific estimates of the associations between the genetic instruments and sleep traits identified in the respective GWASGWAS of chronotype , sleep duration (continuous variable), and insomnia symptoms  were performed among women of European ancestry (n=241 350 - 245 767) in the UK Biobank. This was done using BOLT-LMMThe GWAS of breast cancer involved 122 977 women with the disease (oestrogen receptor positive and oestrogen receptor negative combined) and 105 974 controls of European ancestry from BCAC.2=0.8. We then performed harmonisation of the direction of effects between exposure and outcome associations, where palindromic SNPs were aligned when minor allele frequencies were less than 0.3, or they were otherwise excluded. We then used an inverse variance weighted method to meta-analyse the SNP specific Wald estimates (SNP outcome estimate divided by SNP exposure estimate) using random effects, to obtain an estimate for the causal effect of the sleep trait on breast cancer risk.Two sample MR analyses were conducted using “TwoSampleMR,” an R package for such analyses,The inverse variance weighted random effects method will return an unbiased estimate in the absence of horizontal pleiotropy, or when horizontal pleiotropy is balanced.http://phewas.mrbase.org/).To further detect and correct obtained causal estimates for potential violation of the MR assumptions,To evaluate the potential impact of winner’s curse, we performed two sample MR analysis using 242 genetic variants that replicated at Bonferroni significance in a large independent dataset for chronotypev 7-8 hours) and eight SNPs associated with long sleep (>8 hours v 7-8 hours)Given potential non-linear associations between sleep duration and breast cancer risk,Finally, we performed two sample MR using genetic variants robustly associated with accelerometer derived sleep traits in UK Biobank, to be compared with causal estimates obtained using genetic variants associated with self reported traits. For this we used genetic variants identified in GWAS in relation to three accelerometer based measures: timing of the least active five hours (L5 timing) (6 SNPs), nocturnal sleep duration (11 SNPs), and number of nocturnal sleep episodes (21 SNPs) in up to 85 205 participants, as previously describedAll analyses were conducted using Stata (version 15) and R (version 3.4.1).The current research was not informed by patient and public involvement because it used secondary data. However, future research following on from our findings should be guided by patient and public opinions.No patients were involved in setting the research question or the outcome measures, nor were they involved in developing plans for design or implementation of the study. No patients were asked to advise on interpretation or writing up of results. The results of the research will be disseminated to study participants on request, and to stakeholders and the broader public as relevant. Of the 180 216 women in the UK Biobank who had been successfully genotyped and passed the genetic quality control, and after excluding 23 368 who had a diagnosis of other types of cancer, 7784/156 868 (4.9%) had received an exclusive diagnosis of breast cancer. Of these, 5036/156 868 (3.2%) were defined as prevalent cases and 2740/156 868 (1.7%) developed incident breast cancer over a median follow-up of 2.98 years.Women with a breast cancer diagnosis  were more likely to be older, have a higher BMI, be less physically active, have had an earlier age at menarche, be postmenopausal, have ever used hormone replacement therapy, have a family history of breast cancer, and be nulliparous. They were less likely to be never smokers, work night shifts, and have ever used oral contraceptives  comparedIn multivariable Cox regression analysis, an inverse association was observed between morning preference and risk of breast cancer, which remained similar in the fully adjusted model  but there was no clear association between sleep duration and insomnia symptoms with risk of breast cancer . The proWhen incident and prevalent cases were combined and associations investigated in a logistic regression framework, evidence was consistent for an inverse association between morning preference and breast cancer risk , as well a positive association between both sleep duration  and insomnia symptoms  with breast cancer risk, potentially reflecting reverse causation . Cox regression estimates were similar after excluding participants who reported working night shifts .Among UK Biobank female participants, allele scores explained 2.3% of the variance in chronotype, 0.7% of the variance in sleep duration, and 0.4% of the variance in insomnia symptoms . Some evWhen using only the genetic variants that replicated in an independent dataset (242 variants in 23andMe) for chronotype, estimates of effect on breast cancer risk were similar ; although with wider confidence intervals given that the replicated variants explained less of the variance in chronotype (1.6%) .Although most of the confounding factors were not associated with the sleep trait allele scores in UK Biobank, after accounting for multiple testing the chronotype allele score was associated with parity and vigorous activity; the sleep duration allele score was associated with age at menarche and BMI, and the insomnia allele score was associated with using hormone replacement therapy and age at menarche . Further sensitivity analysis was undertaken adjusting for these potential confounders in the one sample MR analysis, and effect estimates were consistent .Findings of a protective effect of morning preference were supported in analysis of all breast cancer cases  in logistic regression. Evidence for sleep duration and insomnia symptoms was weaker, although both had effect estimates in the positive direction . In analyses excluding women who reported working night shifts, findings were also consistent with the main results from Cox regression .2≥0.8) for chronotype . Two sample MR supported the findings of a protective effect of morning preference   as well as an adverse effect of increased sleep duration  on breast cancer risk . Little evidence for a causal effect of insomnia symptoms was observed  . After harmonisation of the SNP effects in the two summary datasets (UK Biobank and BCAC), 305 SNPs were used to instrument chronotype, 82 SNPs were used to instrument sleep duration, and 50 SNPs were used to instrument insomnia symptoms. This included three proxy SNPs  in two sample MR . Furthermore, the MR Egger test of directional pleiotropy was consistent with the null for all analyses .Evidence for heterogeneity in causal effects for most of the models  could still indicate potential violations of the MR assumptions. We used radial plots to aid in the detection of outlying variants. Radial MR analysis identified six outliers for chronotype, three for sleep duration, and two for insomnia symptoms in both inverse variance weighted and MR Egger . The pleiotropic effect of many of these outliers was indicated in a PheWAS of the SNPs on all existing traits in the MR-Base database . With removal of outliers, inverse variance weighted and MR Egger effect estimates were largely unchanged .Effect estimates for the causal effect of chronotype on breast cancer risk were consistent when using the 242 genetic variants associated with chronotype, which replicated at Bonferroni significance in 23andMe,Findings of an adverse effect of increased sleep duration on breast cancer risk were supported using genetic variants specifically associated with short and long sleep duration, with evidence for a protective effect of short sleep duration on breast cancer  and adverse effect of long sleep duration  .Finally, we performed two sample MR using genetic variants robustly associated with accelerometer derived sleep traits in UK Biobank, to be compared with causal estimates obtained using genetic variants associated with self reported traits. Supplementary table 25 shows the genetic correlations between these traits. Using genetic variants robustly associated with accelerometer derived sleep traits in UK Biobank, we found no clear evidence of association with L5 timing measured objectively  . However, an adverse effect of increased sleep duration was supported using estimates from objectively measured sleep duration   and there was some evidence for a causal effect of increased fragmentation on breast cancer risk  . Given the limited availability of SNPs being used to proxy for L5 timing to evaluate its causal role on breast cancer, and given the strong association found between chronotype and L5 timing ,Mendelian randomisation (MR) uses genetic variation to investigate causal relations between potentially modifiable risk factors and health outcomes. In this study we compared observational estimates from multivariable regression with those from MR analyses to make inferences about the likely causal effects of three sleep traits on breast cancer risk. In multivariable regression analysis using data on breast cancer incidence in the UK Biobank study, morning preference was inversely associated with breast cancer, whereas there was little evidence for an association with sleep duration and insomnia. Using genetic variants associated with chronotype, sleep duration, and insomnia symptoms, one sample MR analysis in UK Biobank provided some evidence for a protective effect of morning preference but imprecise estimates for sleep duration and insomnia. Findings for a protective effect of morning preference and adverse effect of increased sleep duration on breast cancer (both oestrogen receptor positive and oestrogen receptor negative) were supported by two sample MR using data from the Breast Cancer Association Consortium (BCAC), whereas there was inconsistent evidence for insomnia symptoms. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.Previous studies have found an enrichment of circadian pathway genetic variants in breast cancer.Findings of an adverse effect of evening preference on breast cancer risk in all analyses performed go some way to supporting hypotheses around carcinogenic light-at-night Evidence for an adverse effect of increased sleep duration on breast cancer risk contrasts with the observational findings in UK Biobank as well as much of the literature on circadian disruption and breast cancer risk,Overall, we found inconsistent evidence about the causal effect of insomnia symptoms on breast cancer risk in multivariable and MR analyses. A previous study of incident breast cancer in the Nord-Trøndelag Health Study (HUNT) revealed no strong evidence of an association with individual insomnia symptoms,Key strengths of the study are the integration of multiple approaches to assess the causal effect of sleep traits on breast cancer, the inclusion of data from two large epidemiological resources—UK Biobank and BCAC—as well as use of data derived from both self reported and objectively assessed measures of sleep. Furthermore, for MR analysis we used the largest number of SNPs identified in the genome-wide association studies (GWAS) literature, with full summary statistics available to obtain strong genetic instruments for MR analysis and to explore potential pleiotropic pathways.The approaches of multivariable Cox regression of incident cases, multivariable logistic regression of prevalent and incident cases, one and two sample MR, each have different strengths and limitations in terms of key sources of bias . In multivariable analysis, attempts were made to mitigate key sources of bias, including confounding and reverse causation, with the use of multivariable Cox regression analysis of incident cases of breast cancer and adjustment for several hypothesised confounders. Nonetheless, residual or unmeasured confounding, selection bias, and measurement error could also have distorted effect estimates. We used MR analysis to minimise the likelihood of bias due to measurement error, confounding, and reverse causation. In addition, we conducted a series of sensitivity analyses to assess the core assumptions that the genetic instruments are strongly associated with the exposures of interest, are not influenced by confounding factors, and do not directly influence the outcome other than through the exposure.One limitation of this study related to the self reported measures used in multivariable regression analyses and used to identify genetic variants for MR analysis. In particular, the measure of sleep duration might capture time spent napping and the any insomnia variable is really a measure of insomnia symptoms and not necessarily clinical insomnia. However, both these measures have been validated with the use of objective measures from accelerometer data in the UK Biobank and concordance is good, particularly for the effects of the genetic variants identified.Another limitation relates to the selection of participants. Analysis in the two large epidemiological studies included here (UK Biobank and BCAC) was restricted to women of European ancestry. Further work is required to investigate whether these findings translate to women in other ancestry groups. Although the UK Biobank represents a large and well characterised epidemiological resource, it is not representative of the UK population owing to low participation.In all MR analyses, SNP exposure estimates were obtained from the UK Biobank as this has formed a major component of the GWAS of sleep traits conducted to date.We were unable to apply the same approach to investigate the impact of winner’s curse in the sleep duration and insomnia analysis owing to the relatively small sample size of the replication datasets in those studies, meaning genetic associations could be imprecise. Although we are aware of a large GWAS for insomnia that was conducted using data from both UK Biobank and 23andMe, full summary data for the top SNPs in the replication analysis are not freely available.Although associations between the allele scores and confounders in UK Biobank imply violation of the MR assumption that genetic variants should not be associated with confounding factors, there are several explanations for these findings. Previous MR studies have identified causal effects of sleep traits on reproductive traits, body mass index, and activity levels,As well as attempting to mitigate key sources of bias for each epidemiological approach applied, we also assessed the consistency in estimates between the approaches to provide the best inference about the causal effect of sleep traits on breast cancer. This is aligned with the practice of triangulation, which aims to obtain more reliable answers to research questions through the integration of results from different approaches, where each approach has different sources of potential bias that are unrelated to each other.Findings of a protective effect of morning preference on breast cancer risk add to other evidence from MR supporting a possible beneficial effect of morning preference on decreased risk of schizophrenia and depression.In this study, both multivariable regression and MR analysis were used to provide strong evidence for a causal effect of chronotype on breast cancer risk. Furthermore, some evidence suggested a causal effect of sleep duration on risk of breast cancer, although findings for these traits were less consistent across the different methods applied. However, the biological role of many of the genetic variants used to instrument these traits in MR and mechanistic pathways underlying the observed effects are not well understood. Previously reported pathways between sleep disruption and mammary oncogenesis include immunological, molecular, cellular, neuroendocrine, and metabolic processes.The World Health Organization’s International Agency for Research on Cancer classifies shift work involving circadian disruption as probably carcinogenic to humansMuch of the literature on breast cancer risk has focused on the potentially adverse effects of night shift work and exposure to light at night, and less into the potential adverse effects of traits such as chronotype (morning or evening preference), sleep duration, and insomniaGenetic variants robustly associated with chronotype, sleep duration, and insomnia symptoms have recently been identified in large genome-wide association studiesThis study found consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of increased sleep duration on breast cancer riskThe evidence for insomnia symptoms was inconclusiveThese findings have potential implications for influencing sleep habits of the general population to improve health


Non-statistically significant reduced risk of pancreatic cancer was found among users of β-blockers . Average sRAGE levels were higher in β-blockers users than users of other anti-HT medications . Future studies are warranted to confirm these findings and elucidate potential mechanisms by which anti-HT medications influence development of pancreatic cancer.Pancreatic cancer is the fourth leading cause of cancer death. Soluble receptor for glycation end products (sRAGE), which is modulated by anti-hypertensive (HT) medications, has been inversely associated with pancreatic cancer. However, the association between commonly used anti-HT medications and risk of pancreatic cancer is unknown. A total of 145,551 postmenopausal women from the Women Health Initiative (WHI) Study were included in analysis. Use of angiotensin converting enzyme inhibitors (ACEi), β-blockers, calcium channel blockers (CCBs) and diuretics was ascertained at baseline (1993–1998). Baseline sRAGE levels were measured among a subset of 2104 participants using an immunoassay. Multivariable Cox proportional hazard regression model was performed to estimate hazard ratios (HRs) and its 95% confidence intervals (CIs) for pancreatic cancer in association with anti-HT medications. Increased risk of pancreatic cancer was found among users of short-acting CCB  and long-term (≥3 years) users of short-acting CCB  compared to users of other anti-HT medications. Average sRAGE levels were lower in short-acting CCB users than users of other anti-HT medications (1173 versus 1454 pg/mL,  Pancreatic cancer is the fourth leading cause of cancer-related death in the United States . EstabliMultiple anti-HT medications have been extensively studied in relation to risk of developing cancer. A recent meta-analysis of 70 clinical trials found no significant associations between angiotensin II receptor blockers (ARBs), angiotensin-converting enzyme inhibitor (ACEi), β-blockers, calcium-channel blockers (CCBs), or diuretics and overall risk of developing cancer . HoweverWe previously showed a significant inverse association between soluble receptor for advanced glycation end products (sRAGE) and risk of incident pancreatic cancer ,7. The aTherefore, we examined the associations between the use of ACEi, β-blockers, CCBs and diuretics and risk of developing incident pancreatic cancer in a large prospective cohort. We hypothesized that use and long-term use of ACEi, β-blockers, CCBs and diuretics are associated with a reduced risk of pancreatic cancer. Additionally, we explored the association between sRAGE levels and the anti-HT medication use in a subset of study participants for a mechanistic explanation. n = 16,255) were excluded from the current analysis. We included a total of 145,551 postmenopausal women from the WHI-OS and CT for the present analysis. To study the long-term effect of interventions on health outcomes, two extension studies were initiated in 2005 (extension study I) and 2010 (extension study II) with a re-consent rate of 72% and 59%, respectively. The study protocol was approved by the Institutional Review Board of both Baylor College of Medicine (BCM) and the Michael E. DeBakey VA Medical Center in Houston, TX, USA.The Women’s Health Initiative (WHI) Study is a long-term prospective cohort study in the U.S. aiming to investigate preventative strategies against heart diseases, breast and colorectal cancers and osteoporotic fractures. Study participants were either assigned into the randomized clinical trial (CT) or observational study (OS) . The maiAt baseline interview, all participants were asked to bring currently used medications and supplement bottles used for at least two weeks. The interviewers entered product and generic name, dosage form, medic strength, therapeutic class and ingredients directly from the containers into a database that assigned drug codes using Medi-Span software , a pharmaceutical reference database. The study participants also reported the duration of medication use.Types of medication were determined based on the 6-digit medication therapeutic class code (TCC) as following: ACEi , β-blockers  and diuretics  [Pancreatic cancer cases were ascertained through self-administered questionnaires semi-annually for CT participants and annually for OS participants. Pancreatic cancer was defined using the ICD-O-2 code of C25.0–C25.4, C25.7–C25.9. All the cases were locally and centrally adjudicated by trained physicians using pathology/cytology report, operative report, hospital discharge summary, outpatient, day surgery or short stay record . We asceInformation on age, race/ethnicity, education, income, marital status, smoking habit, alcohol consumption, medical history and recreational physical activity at baseline were obtained by recruitment survey. Height, weight, hip and waist circumference were measured by trained clinic staff at the first clinic visit . HistoryIn two previous nested case-control studies within the WHI, we measured baseline serum levels of sRAGE ,18 usingBecause we observed that the CCBs use to be associated with increased risk of pancreatic cancer, baseline demographic characteristics, lifestyle factors, dietary factors and selected medical history were compared according to CCB use, use of non-CCBs medications  and non-use of any anti-HT medications at baseline. p < 0.25) and with the use of medications (p < 0.25). Final model included age, race/ethnicity , BMI , smoking status , alcohol consumption more than 3 drink/day (yes vs. no), self-reported type 2 diabetes (yes vs. no) and hypertension (yes vs. no). Further adjustment of other variables such as OS/CT assignment, family history of cancer, physical activity, or saturated fat intake did not meaningfully alter the association. The same set of covariates (except for hypertension) was adjusted in the multivariable model in evaluating the association between hypertension and risk of pancreatic cancer. Competing risk of non-pancreatic cancer deaths were further accounted for by using the Fine and Gray model [Cox proportional hazard regression model was performed to assess the association between hypertension and anti-HT medication use and risk of developing incident pancreatic cancer. Due to low rate of monotherapy in study participants, we included both monotherapy and polytherapy in defining medication use. We used two reference groups in data analysis: (1) non-users of any anti-HT medications; (2) users of anti-HT medications other than the one under study. The number of years of follow-up was calculated from the baseline recruitment until pancreatic cancer diagnosis, death, loss to or end of follow-up (29 August 2014), whichever occurred first. Test for proportional hazard assumption was conducted based on the statistical significance of correlation between Schoenfeld residuals and ranked survival time. We found no violation of the proportional hazard assumptions. Adjusted variables were selected if they were: (1) established risk factor for pancreatic cancer based on literature review; or (2) associated with risk of pancreatic cancer in the univariable analysis (ay model . Restric2), cardiovascular diseases, type 2 diabetes and sRAGE levels (using median among controls as the cutoff). Time-varying Cox regression by using years 3 (OS and CT) and 6 (CT only) data on anti-HT medication use status were performed to further assess the association between over-time use and risk of pancreatic cancer [Because we observed the association between CCB use and risk of pancreatic cancer, we further examined whether the duration and type of CCB use  were associated with risk of pancreatic cancer. Among users of CCBs, duration of use was dichotomized as <3 years (median cutoff for users) versus ≥3 years. Duration of use was also included in the model as a continuous variable to test for the linear trend. Additional stratified analyses were performed according to WHR (< or ≥0.80), BMI  and monotherapy plus polytherapy (n = 1522) among controls. Sidak multiple comparison adjustment was applied [Among 1615 controls who had sRAGE levels measured, anti-HT medication use information was documented for 1522 participants. Furthermore, a total of 1388 participants reported non-use or use of only one anti-HT medications. Least square means of sRAGE concentration were compared across non-users of any anti-HT medications and users of single anti-HT medication by adjusting for age, BMI, smoking status, alcohol consumption ≥3 drinks/day and self-reported hypertension. We reported sRAGE levels by both the monotherapy  software. Two-sided With an average of 13.8 (standard deviation = 4.8) years of follow-up, a total of 841 incident pancreatic cancer cases were ascertained. Compared with non-users of any anti-HT medications, users of CCBs were more likely to be older, in a minor racial/ethnic category, less educated, current smokers, obese, inactive and to have hypertension, pancreatitis and type 2 diabetes . Overall, hypertension at baseline was associated with moderately increased risk of pancreatic cancer . A 40% increased risk of pancreatic cancer was found among users of CCBs compared with users of any other anti-HT medications. The association became slightly attenuated when compared with non-users of any anti-HT medications. Non-statistically significant inverse associations were found for the use of ACEi, β-blocker, or diuretics with risk of pancreatic cancer . The assFurthermore, we found only the use of short-acting CCBs was associated with an increased risk of pancreatic cancer compared with the use of any other anti-HT medications. In addition, long-term use of short-acting CCBs (≥3 years) had a 107%  higher risk of pancreatic cancer . Furtherp = 0.021) and users of other anti-HT medications (p = 0.038) (p for interaction = 0.26) and non-users of any anti-HT medications (p for interaction = 0.12) (The average sRAGE levels were significantly lower in short-acting CCB users than non-users of any anti-HT medications (= 0.038) . The sRA= 0.038) . In the  = 0.12) . We obseNo statistically significant interaction was found for CCB use with BMI, WHR, cardiovascular disease or diabetes . In the In this large prospective cohort of postmenopausal women in the U.S., we hypothesized that the anti-HT medications that hamper RAGE inflammatory signaling would be associated with reduced risk of pancreatic cancer. Consistent with our hypothesis, we did observe a statistically non-significant inverse association between β-blockers use and risk of pancreatic cancer. However, contrary to our hypothesis, we found that short-acting CCBs use was associated with an increased risk of pancreatic cancer, especially among long-term users. Furthermore, we found that β-blockers use was associated with non-statistically significant higher levels of sRAGE and short-acting CCBs use was associated with statistically significant lower levels of sRAGE compared with the use of other anti-HT medications. The association between CCBs use and short-acting CCBs use and pancreatic cancer also differed by sRAGE levels. CCBs, also known as calcium antagonists, result in lower blood pressure by preventing calcium from entering vascular smooth muscle and thus relax and dilate blood vessels . PreviouHowever, we observed a positive association between short-acting and NDHP CCB use and risk of pancreatic cancer. A significantly lower sRAGE level was also found among short-acting CCB users, compared with women who used other anti-HT medications. sRAGE could mitigate the inflammatory response by blocking RAGE-ligand binding . Our preAlthough β-blocker has been shown to protect against pancreatic cancer development by arresting pancreatic cancer cell growth and inducing apoptosis as well as been shown to increase sRAGE levels , we did CCBs was approved as a first line treatment medication for hypertension by U. S. Food and Drug Administration (FDA) in 1989 ,31. At tThe strengths of this study included the long follow-up time among a large cohort of postmenopausal women, complete ascertainment of cases, comprehensive evaluation of confounding factors, detailed record of medication use before baseline, a robust research approach including the examination of CCBs by formulations and potential mechanistic insight into our observations. Nevertheless, our study had several limitations. The findings may not be generalizable to men, to pre-menopausal women, or to post-menopausal women that substantially differ from the U.S. in prevalence of underlying risk factors for pancreatic cancer like diabetes and obesity and with different rates of hypertension and use of CCBs. Also, the data on sRAGE were available only for a subset of participants, making this mechanistic insight novel but exploratory. The finding of the excess risk particularly in the subgroup of women using short-acting CCBs was based on a smaller sample size requiring qualified interpretation and need for replication in other larger studies. The time-varying analysis and propensity score analyses in general supported the positive association between CCB use and risk of pancreatic cancer. However, due to reduced use of CCBs in the study population , the HR generated from time varying analysis was not statistically significant. Because the monotherapy was uncommon, we were not able to examine the association by monotherapy due to smaller sample size. Likewise, the ARB use was uncommon in our study population (3.7%) and its association with pancreatic cancer was thus not evaluated. Lastly, the possibility of confounding effects related to prevalent use of CCBs, indication/contraindication to use of short-acting CCBs, and/or other unrecognized risk factors cannot be excluded . It is important to manage hypertension to prevent major adverse health consequences. We found that the use of commonly prescribed anti-HT medications was not significantly associated with risk of pancreatic cancer. Short-acting CCBs may potentially be a risk factor for pancreatic cancer in post-menopausal women. Further studies are needed to understand the common pathogenic mechanism shared by hypertension and pancreatic cancer such as RAGE signaling.