Global breast cancer incidence varies considerably, particularly in comparisons of low- and high-income countries; rates may vary even within regions. Breast cancer rates for Caribbean countries are generally lower than for North America and Europe. Rates in Puerto Rico are in the middle of the range between the highest and the lowest Caribbean countries. Populations in transition, with greater variability in risk factor exposures, provide an important opportunity to better understand breast cancer etiology and as potential sources of variation in rates. Understanding of exposures across the life span can potentially contribute to understanding regional differences in rates. We describe here the design and implementation of a population-based, case-control study in the San Juan Metropolitan Area (SJMA) of Puerto Rico, the Atabey Epidemiology of Breast Cancer Study. We describe steps taken to ensure that the study was culturally appropriate, leveraging the Atabey researchers’ understanding of the culture, local health system, and other required resources to effectively recruit participants. A standardized, in-person interview was developed, with attention to life course events customized to the study population. In order to understand variation in global breast cancer rates, studies customized to the populations outside of North America and Europe are required. Cancer of the breast is the most frequently reported cancer among women globally . There iGlobally, many of the populations with lower breast cancer rates are in transition from a more traditional to a more westernized lifestyle, and are experiencing associated changes in breast cancer incidence and mortality over time ,11. AlthAlthough disparities in breast cancer incidence and prognosis by race, ethnicity and socioeconomic status in the USA have been documented , these dWhile there have been four analytical studies of breast cancer epidemiology in Puerto Rico ,19,20,21The Atabey Epidemiology of Breast Cancer Study is a population-based, case-control study focusing on the epidemiology of female breast cancer in Puerto Rico. This study is a collaboration between the University of Puerto Rico and the University at Buffalo, State University of New York. Study participants (30 to 79 years of age) were recruited between 2009 and 2014 from the Bayamón, Carolina, Guaynabo and San Juan municipalities in the San Juan Metropolitan Area (SJMA) . The stuBecause a population-based study of breast cancer had not previously been conducted in Puerto Rico, the study required the development of a research infrastructure as well as the maximization of existing resources. The knowledge and cultural competency of the Puerto Rico-based investigators was critical to the study development and implementation. Existing relationships with administrative and medical personnel, skilled potential staff, combined with understanding of local resources, local hospital procedures and local IRB requirements were essential for the effective implementation of the study.The study leveraged several important existing resources. These included the Puerto Rico Cancer Registry, which was used to assist in case ascertainment, the Puerto Rico Health Interview Survey (PRHIS), which was used as the model for the control ascertainment, and the Puerto Rico Clinical and Translational Research Consortium (PRCTRC), a University of Puerto Rico Medical Science Center facility where the blood draw, anthropometry and interviews were conducted, all described in detail below.The expertise of the local investigators was significant in hiring and training of study personnel. Their knowledge permitted the recruitment of interviewers and a Community Outreach (CO) worker who were able both to understand the study requirements and to interact appropriately with participants and potential participants to obtain the highest quality and most complete data. Study participants valued the fact that the Puerto Rican research was conducted by local investigators.Cases were women, 30 to 79 years of age, residents of the SJMA, with incident, primary, pathologically confirmed breast cancer and no history of previous cancer other than non-melanoma skin cancer. They were ascertained from the hospitals and clinics where breast cancer patients were diagnosed or treated: hospitals with oncology departments, cancer registries and private oncologist’s offices within the SJMA. A list of hospitals and clinics that report breast cancer cases was obtained from the Puerto Rico Central Cancer Registry (PRCCR). The PRCCR data were also used as a cross check to identify any potential cases who had not been ascertained from the other sources. The PRCCR gathers cancer data through an electronic reporting system and is a population-based registry that achieves 95% completeness of data collection from primary sources , with 92.8% of cancer cases having histologic confirmation of disease . The repControls were women aged 30–79, with no history of cancer, other than non-melanoma skin cancer, who were residents of the SJMA. They were selected and frequency-matched to cases by broad geographical residential area . The number of potential controls required for each municipality was based on the expected number of new breast cancer cases by municipality, informed by the PRCCR data.The sampling frame and the strategy for the selection of population-based controls was provided by Dr. Gilberto Ramos Valencia, Director of the Puerto Rico Health Interview Survey (PRHIS), a national cross-sectional health survey with a multistage sampling procedure of geo-political conglomerates  as determined by the USA Census from the year 2000 . The selCensus blocks were randomly selected from the municipalities of San Juan, Carolina, Bayamon and Guaynabo . The number of households in each selected census block was calculated and each household was considered a random point. The number of expected breast cancer cases from the municipalities in the target area (SJMA) was used to estimate the number of households to select in each block. From the randomly selected blocks, those that had the largest number of households were prioritized. The process was repeated until the total number of households needed to complete the identification of the expected number of controls from each municipality was achieved. The total number of households to be visited was calculated taking into consideration an expected refusal rate of 25%. The module “EpiTable” from EpiInfo 6, version 6.04d  was usedThe CO was trained to apply a systematic recruitment approach to reduce selection bias and to recruit a representative sample of population controls. On a weekly basis, the project coordinator met with the CO to discuss and plan the identification and recruitment of potential controls in the selected blocks. The CO received the precise address and description of the selected block , the address of the initial random point and the number of controls to recruit. The CO could not substitute the selected blocks or the randomly selected initial household assigned to the block.Once the initial random household was identified in the selected block, the CO visited the first household to recruit eligible controls. At each household, the CO obtained information regarding potential and eligible controls within the household. The CO asked if there was a woman living in the home who was between 30 and 79 years of age. If affirmative, the Atabey Study was described, and eligibility was confirmed. If an eligible woman was present, she was invited to participate. If more than one eligible woman lived in the same household, the CO invited the oldest eligible woman first. If she refused to participate then the CO could invite the second oldest woman.If there were no adults present in the household, a flyer describing the Atabey Study was left. The CO re-visited a household up to three times to determine if there were eligible controls in the household. The CO then visited the next house to the left, taking into consideration the number of potential controls to be recruited from that block. If the number of potential controls in the block was completed, the CO would visit the next assigned block, following the same process as previously described. A summary of the strategies used for the control identification and the recruitment process is shown in Once they agreed to participate, controls were assigned a unique identifying code number for tracking, an interview was scheduled and all data and samples, including a questionnaire and anthropometry data, and biological samples were collected.Careful attention to the Puerto Rican population and culture was woven into the questionnaire development. The instrument incorporated questions about known breast cancer risk factors, including sections on demographics, occupation, residential history, early life exposures, usual diet anchored to the year prior to the interview , adolescent diet, reproductive history, weight history, smoking history, exposure to environmental tobacco smoke, physical activity history, sun exposure history, personal and family history of diseases, environmental and occupational exposures and vitamin and medication use.While much of the questionnaire was similar to others used in other epidemiologic studies of breast cancer, many important culturally-sensitive differences were incorporated. For example, researchers discussed at length the acceptability of particular questions or procedures before including them. In particular, there was discussion regarding taking anthropometric measures and measuring skin pigmentation using colorimetry, as well as the development of questions regarding exposures that might help characterize transition among risk factors. All questionnaire and interviewer-related materials were translated to English for complete review by the investigative team at the University of Buffalo and then back translated to Spanish.To enhance cultural sensitivity, all staff interacting with study participants were local women with research experience and who spoke regional Spanish. They were trained extensively regarding study procedures. Training focused on prevention of bias in interactions with participants, on making participants feel comfortable and listening to them, but following the study protocol to keep the interview on track. During training, interviewers and investigators did role playing exercises to simulate appropriate conduct during the interview. Both nurses, who drew blood, did anthropometric and colorimetry measures, and interviewers were blinded to case-control status and to the study hypotheses. Quality control and re-training were conducted periodically to ensure compliance with study protocols by nurses and interviewers.To promote and solidify collaborative ties, the study investigators met by teleconference weekly to discuss the study development, implementation and data analyses. In addition, study investigators from the University of Puerto Rico travelled to Buffalo and University of Buffalo investigators travelled to Puerto Rico. The frequent communication was vital in the development of a strong collaboration, for sharing of expertise and for ongoing problem-solving of issues as they arose.Study nurses collected biological samples from each participant as well as anthropometric and skin pigmentation measurements following a detailed, standardized protocol. Fasting blood (27 mL of blood) was collected from study participants. Serum, plasma, buffy coat and red blood cells were aliquoted to 0.5 mL straws and stored in −80 °C freezers. Each biological sample was marked by a unique identifier using scannable bar codes. For those few participants who refused or were unable to provide a blood sample, a saliva sample was obtained for DNA extraction. All biological samples  were processed at the PRCTRC. Frozen straws were shipped overnight on dry ice to Buffalo, NY, for long-term specimen storage at the University at Buffalo; participant samples were divided into multiple shipments to avoid the possibility of total sample loss due to an unforeseen event. The Puerto Rican laboratory technician was trained in the processing and aliquoting protocol at the biospecimens laboratory at Roswell Park Comprehensive Cancer Institute in Buffalo, New York.Interviews were conducted in-person by trained personnel using a structured questionnaire. As noted above, the questionnaire was constructed specifically for this study. It utilized some questions regarding breast cancer risk factors based on questionnaires from other, similar studies, adapted to the particular needs of this population as well as other questions specific to Puerto Rican women. The data collection instrument included questions regarding demographic, occupation, residential history, early life exposures, reproductive factors, diet , vitamin use, sun exposure and medical history including use of some medications. At the end of the interview, once data relevant to both cases and controls were obtained, additional clinical information was collected from the breast cancer cases. These data included information regarding breast cancer treatment . Interviewers were blinded to case-control status up until questions from this section of the questionnaire were asked, when knowledge of case control status was required.Breast carcinoma is a heterogeneous disease comprised of different histopathological and clinical features. Classical immunohistochemical (IHC) markers such as estrogen receptors (ER), progesterone receptors (PR) and human epidermal growth factor receptor 2 (Her2) have important therapeutic prognostic implications.Study researchers obtained information on breast carcinoma pathology from hospital medical records or the Puerto Rico Central Cancer Registry. One investigator (CC), reviewed and cross-checked pathology data following the system described by Howlader et al. . Breast As shown in As shown in In total, in this population-based study, there were 315 cases and 348 controls who met eligibility requirements, completed the interview and provided biological samples. There were 41 participants for whom a saliva sample was obtained; the remainder provided a blood specimen. Pathological data were obtained from all breast cancer cases from hospital records or the Puerto Rico Central Cancer Registry.2) had lower body mass index (BMI) than controls [mean 31.2 kg/m2].Characteristics of Atabey participants are shown in With regard to reproductive factors, cases and controls were similar in age at menarche . Cases were more likely to be nulliparous than controls . Among parous participants, the mean number of births was somewhat higher for controls (2.9) than for cases (2.6). Among parous participants, the average age at first birth was higher for cases (24.3 years) than controls (22.8 years). Among post-menopausal participants, the age at menopause was 47.4 years for cases and 46.8 years for controls.Breast cancer cases had a higher likelihood of having a family history of breast cancer and a personal history of benign breast disease. Family history of breast cancer was reported by 21.0% of breast cancer cases and 8.6% of controls; 46.7% of cases and 25.6% of controls had a previous benign breast disease.Characteristics of the cases’ tumors are shown in To our knowledge, this is the first population-based, case-control study of incident breast cancer conducted in Puerto Rico. Previous studies in Puerto Rico focused on molecular factors associated with DNA repair among breast cancer women in Puerto Rico ,20,21. OThe Atabey study represents a long-lasting collaboration between the University of Puerto Rico (a minority institution) and the University at Buffalo (a recognized research institution) and Roswell Park Comprehensive Cancer Center (recognized for cancer research). Intercampus collaboration between the UPR at Río Piedras and UPR Medical Sciences Campus was obtained.There have been important lifestyle changes for known or suspected breast cancer risk factors in Puerto Rico. For example, median years of education of females in Puerto Rico increased from 3.3 school years in 1950 to 9.2 school years in 1980 . FertiliStudies of populations in transition provide the opportunity to examine factors related to changes in rates of cancer incidence and mortality. With greater variability in exposures, it may be possible to identify associations that are more difficult to determine in populations with greater uniformity in exposures. Furthermore, studies such as this one are important in capacity building, providing experience in research to all of those involved in the study design, implementation and analysis; further the study results are an important potential resource to other researchers and for training.The challenges of the study were considerable. Population-based studies such as this one with strict eligibility criteria impose an enormous burden. Without any population-based listing of the SJMA, the selection of appropriate population-based controls required a probabilistic sampling combined with verification of eligible households in the field. Having an experienced study coordinator and a CO with familiarity regarding the region were fundamental to the project. Case ascertainment required identification and enlisting cooperation of those providing care to breast cancer cases, as well as engaging administrators, other clinicians and institution-specific IRBs. While study participation was high, contacting and enrolling participants was challenging. For each identified participant, six to eight telephone calls were made to schedule an interview, remind them of their appointment, reschedule appointments and motivate them to participate. While response rates for both cases and controls were good relative to other case-control studies, there remains the possibility of selection bias, that is, that those participating differed systematically from those who did not participate and that those differences were not the same for cases and controls. Furthermore, as for any case-control study, there is the potential for recall bias. Every effort was made to reduce the likelihood of such biases in report by training the interviewers in the administration of the structured interview, providing context to the participants to assist them in recalling the past. There is evidence that recall bias in case control studies may be modest ,35. FinaThe population-based study design is a strength of this study. Furthermore, the relatively high response rates provide for external validity. The development of the study protocol and questionnaire, as well as the training of the staff, was tailored to the Puerto Rican culture and critical to the study’s success. Measurement and data collection procedures were standardized to minimize recall and interviewer bias. Interviewers were trained to follow standardized procedures and were of the same ethnicity as the Atabey study participants. Interviewers used visual aids to improve recall and minimize measurement error.This is the first population-based, case-control study of breast cancer conducted in Puerto Rico. Data were collected through a standardized in-person interview with special attention to life course events. This focus was novel for the study of breast cancer in a population with lower rates that is in transition. These results have the potential to benefit breast cancer prevention among other Hispanic women living in the U.S. who comprise nearly 16.2% of the U.S. female population  and sharStudies of populations in transition provide the opportunity to examine factors related to changes in rates of cancer incidence and mortality. With greater variability in exposures, it may be possible to identify associations that are more difficult to determine in populations with greater uniformity in exposures. In addition, recall of early life factors may be more possible with larger variation in exposures, with participants being able to recall at minimum whether they had or had not been exposed for example to foods part of a traditional diet. Furthermore, studies such as this one are important in capacity building, providing experience in research to all of those involved in the study design, implementation and analysis with study resources an important potential resource to other researchers and for training.


Background: Organophosphate pesticides (OPs) are one of the most commonly used classes of insecticides in the U.S., and metabolites of OPs have been detected in the urine of >75% of the U.S. population. While studies have shown that OP exposure is associated with risk of neurological diseases and some cancers, the relationship between OP exposure and breast cancer risk is not well understood. Methods: The aim of this rapid review was to systematically evaluate published literature on the relationship between OP exposure and breast cancer risk, including both epidemiologic and laboratory studies. Twenty-seven full-text articles were reviewed by searching on Pubmed, EMBASE, and Cochrane databases. Results: Some human studies showed that malathion, terbufos, and chlorpyrifos were positively associated with human breast cancer risk, and some laboratory studies demonstrated that malathion and chlorpyrifos have estrogenic potential and other cancer-promoting properties. However, the human studies were limited in number, mostly included agricultural settings in several geographical areas in the U.S., and did not address cumulative exposure. Conclusions: Given the mixed results found in both human and laboratory studies, more research is needed to further examine the relationship between OP exposure and breast cancer risk, especially in humans in non-agricultural settings. Breast cancer is the most common type of cancer among women worldwide after skin cancer, and approximately one in eight women will be diagnosed with invasive breast cancer in their lifetime . StudiesOrganophosphate pesticides (OPs) are currently one of the most commonly used classes of insecticides in the United States and are applied in agricultural, residential, and community settings. The global OP market is estimated to have a compound annual growth rate (CAGR) of 5.5% during the 2018–2023 period . OutsideOPs are classified as anticholinesterases and thus increase the concentration of acetylcholine (ACh) within the neuromuscular junction. With high doses, this can lead to acute neurotoxicity in humans . In the Several studies have demonstrated that OPs are also associated with cancer risk. For example, the Agricultural Health Study demonstrated that exposure to two other classes of OPs, malathion and terbufos, was significantly associated with risk for aggressive prostate cancer . A recenThis rapid review was designed and produced based on the PRISMA 2009 guidelines . In lighwww.prisma-statement.org) for published literature on organophosphates and breast cancer development until 24 April 2020. The following search terms were used: . These OP search terms were selected because they were listed as the top 10 most commonly used OPs in 2012 according to the U.S. EPA Pesticide Industry Sales and Usage 2008–2012 report [Pubmed, EMBASE, and Cochrane databases were used to conduct a systematic search based on the PRISMA guidelines  levels. The primary outcomes for the cell-based studies were measures or characteristics of mammary cell carcinogenic potential, for example, cell viability, anchorage independent growth, and cell invasion capabilities. Other outcome measures included levels of microsatellite instability (MSI) and loss of heterozygosity (LOH), estrogen receptor (ER) transactivation, changes in gene expression, reactive oxygen species (ROS) and reactive nitrogen species (RNS) production, and binding of OPs to sex hormones.Our search results identified only five human studies. In 2005, a study compared women diagnosed with breast cancer (cases) to healthy women (non-cases) among the United Farm Workers (UFW) in the state of California . Cases wThree studies were conducted using data from the Agricultural Health Study (AHS) in the states of Iowa and North Carolina. One of the primary goals of the AHS was to study the relationship between OP exposure and cancer risk among farmers and their spouses. In 2005, Engel and colleagues examined the association between OP exposure and breast cancer risk in spouses of pesticide applicators using data collected from an enrollment period between 1993–1997 and a follow-up period until 2000 . ChlorpyA more recent study in 2019 compared residential and occupational exposures to several pesticides, including the OPs chlorpyrifos and diazinon, between breast cancer cases and controls in three counties of California’s Central Valley with the highest reported pesticide use and agricultural density . Cases wOur search criteria resulted in eight animal studies analyzing the association between OP(s) and mammary carcinogenic potential. Malathion was shown to significantly increase the number of proliferative ducts , activelSome studies also suggested that chlorpyrifos and malathion may possess endocrine-disrupting potential. Chlorpyrifos and malathion significantly and non-significantly, respectively, decreased serum estradiol and progesterone levels ,35. ChloSuggested mechanisms for increasing mammary carcinogenic potential included acetylcholinesterase inhibition, endocrine disruption, increased oxidative stress, and decreased apoptotic signaling. A comprehensive summary of the results is shown in Our search criteria resulted in 14 cell-based studies analyzing the effects of OP exposure on mammary gland carcinogenesis. Two studies found that malathion, with or without estrogen, increased genomic instability, cell invasive capabilities and anchorage independent growth and altered the expression of cell cycle proteins in MCF-10F cells ,40. An aThere has been recent concern over the use of pesticides, including OPs, and their implications on public health ,55,56,57Some associations were found in human studies linking OP exposure to increased breast cancer risk. While most results indicate a trend towards increased risk, only some were statistically significant. One study found a significantly increased risk of breast cancer associated with malathion , while aNumerous animal and cell-based studies linked malathion and chlorpyrifos, and one study linked dimethoate, to mammary carcinogenesis. The results suggest that these OPs can potentially increase breast cancer risk through various mechanisms including increased oxidative stress, disruption of adhesion molecules, acetylcholinesterase inhibition, endocrine disruption, and induction of genomic instability. However, while treatment with malathion resulted in increased cell proliferation, treatment of chlorpyrifos resulted in either increased cell proliferation or cell cycle arrest and apoptosis, perhaps depending on the dosage administered.Since breast development is controlled by the endocrine system, endocrine disruption, defined as any disruption in the normal activity of the endocrine system , can leaStudies discussed in this review also observed increased cholinergic activity in OP-treated breast cancer cells and animal models ,32,39. WThere were several limitations among the current literature. Among the human studies, two had a case control study design ,28; thusMills and colleagues conducted an electronic record linkage recording ever use of OPs among members of the UFWA, which eliminated the issue of recall bias but introduced other limitations . By usinAmong all the studies, due to the nature of the collection method for exposure assessment, lifetime cumulative use of individual insecticides was not assessed. Studies involving the AHS cohort only collected information from a self-administered questionnaire about ever/never use during the pre-enrollment period ,26 and fThere are also likely some discrepancies in the true OP levels individuals were exposed to, as exposure can occur directly, through applying or mixing pesticides, or indirectly, through handling items, food, or water containing OP residues or through aerial drift. Exposure is also dependent on the type of protective equipment used during application and handling, as well as the pathway of exposure. For example, exposure can occur through dermal, inhalation, or ingestion routes , dermal Lastly, none of the human studies used biomonitoring collection methods as a way of measuring OP exposure. Environmental exposure to OPs occurs primarily via ingestion, inhalation, and dermal contact ,77,78. A−11 and 10−6 M, which represents the concentration range deemed safe by the National Institute of Environmental Research (NIER), while the latter administered a concentration of 10−5 M of malathion, which could potentially explain the discrepancies. Thus, some experimental doses of OPs may have limited applicability to real-life environmental exposure levels.There were also some limitations among the animal and cell-based studies. An inherent limitation of cell culture studies is that the pesticides would not be metabolized and cleared in the same manner as they would in a human. In addition, there is some evidence that cell lines show less sensitivity to their extracellular environment compared to cell cultures from tissue samples ; thus, tAnother limitation shared by both human and animal studies in this review is the lack of survival or mortality data. The animal studies’ measurement outcomes were limited to breast tumor growth and tissue histological changes and did not continue on to observe mammary cancer development, metastasis, or cancer-related death. In human studies, breast cancer cases were generally limited to surviving and lower-stage cancers. Future studies should incorporate longer follow-up and include mortality analyses.In this rapid review, we examined the current literature on human, animal, and cell-based studies that analyzed the potential association between OP exposure and breast cancer risk. To our knowledge, this is the first review on the relationship between OPs and breast cancer risk. One limitation on the review level is that the analyses may lack compatibility due to differences in study populations, cell lines, data collection methods, treatment methodologies, and follow-up times, making it difficult to compare the results among studies with similar endpoints. However, the advantage of such a review is the increased sample size and the ability to compare data and potential confounders among a diverse set of results, allowing us to draw novel inferences from many sources combined. Due to the nature of the study being a rapid review, another limitation is the absence of a quality assessment. Publication bias, the bias towards reporting positive associations, is also a possibility.The findings of this rapid review on human, animal, and cell-based studies suggest that certain OPs may be involved in increasing breast cancer risk. The results from the human studies demonstrated that malathion, chlorpyrifos, terbufos, and phorate may be associated with an increased risk of breast cancer. In addition to acting as acetylcholinesterase inhibitors, evidence suggests that malathion and chlorpyrifos have the potential to cause endocrine disruption, induce oxidative stress, and alter the expression of cell cycle proteins and cell adhesion molecules important for breast development. Taken together, given the prevalence of OPs and number of breast cancer cases, there is a need for further human research in non-occupational settings, potentially including the assessment of cumulative lifetime exposure to OPs, biomonitoring, mortality data, and a wider geographical assessment.


Consequently, there is a need to better understand the molecular signaling pathways that might be activated in individuals that are metabolically unhealthy and how these signaling pathways may drive biologically aggressive breast cancer. One key driver of both type-2 diabetes and cancer is insulin. Insulin is a potent hormone that activates many pathways that drive aggressive breast cancer biology. Here, we review (1) the controversial relationship between obesity and breast cancer, (2) the impact of insulin on organs, subcellular components, and cancer processes, (3) the potential link between insulin-signaling and cancer, and (4) consider time points during breast cancer prevention and treatment where insulin-signaling could be better controlled, with the ultimate goal of improving overall health, optimizing breast cancer prevention, and improving breast cancer survival.Studies investigating the potential link between adult pre-menopausal obesity [as measured by body mass index (BMI)] and triple-negative breast cancer have been inconsistent. Recent studies show that BMI is not an exact measure of metabolic health; individuals can be obese (BMI > 30 kg/m Along with the rise in obesity, there has been a rise in gestational diabetes and type-2 diabetes. Much research is focusing on the potential link between obesity, type-2 diabetes, and breast cancer, as increasingly women who are at risk for type-2 diabetes are also at risk for breast cancer. There has been much work investigating the potential link between obesity [as measured by body mass index (BMI)] and breast cancer. Results have been conflicting, likely reflecting the complex relationship between BMI and metabolic health. Recent studies show that BMI is not an exact measure of metabolic health. Individuals can be obese (BMI > 35 kg/m2) and metabolically healthy or lean (BMI < 25 kg/m2) and metabolically unhealthy. Consequently, there have been efforts to better understand the molecular signaling pathways that might be activated in individuals that are metabolically unhealthy. One key driver of both type-2 diabetes and cancer is insulin. Insulin is a potent hormone that activates many pathways that drive aggressive breast cancer biology. Here, we aim to review (1) the controversial relationship between obesity and breast cancer, (2) the impact of insulin on organs, subcellular components, and cancer processes, (3) the potential link between insulin-signaling and cancer, and (4) consider time points during breast cancer prevention and treatment where insulin-signaling could be better controlled, with the ultimate goal of improving overall health, optimizing breast cancer prevention, and improving breast cancer survival.Over the past 20 years, much of the world, has experienced a growing obesity epidemic. Once a disease of the wealthy, obesity now disproportionately effects women and the poor. Possible contributors include disparities in income that promote consumption of inexpensive high calorie foods with low nutritional value , lack ofIncreased adiposity in childhood has been consistently associated with a decreased risk of pre- and post-menopausal breast cancer. Conversely, increased adiposity after menopause is associated with increase of risk –26. Howe2 (5.0-U) difference, 0.77; 95%CI, 0.73–0.80] than for BMI age 45–54 years . The investigators observed a 4.2-fold risk gradient between the highest and lowest BMI categories (BMI ≥35.0 vs. <17.0) at ages 18–24 years. Associations between BMI and breast cancer were stronger for estrogen receptor–positive (ER+) and/or progesterone receptor–positive (PR+) than for hormone receptor–negative (ER–) breast cancers.The Premenopausal Breast Cancer Collaborative group recently published a multicenter analysis used pooled individual-level data from 758,592 premenopausal women from 19 prospective cohorts to estimate hazard ratios (HRs) of premenopausal breast cancer in association with BMI from ages 18 through 54 years . ResultsThe potential association between obesity and TNBC has been a subject of intense research study. As outlined below, studies investigating the potential relationship between obesity and TNBC have been inconsistent. This is a summary of some of the key studies that have been recently published.2) and basal-type TNBC.The Carolina Breast Cancer Study is a North Carolina population-based case-controlled study of breast cancer, conducted in three phases . The cur2) and TNBC in 620 predominantly non-Hispanic White women in rural Appalachia. This study reported a significant association between obesity and the incidence of TNBC  an inverse association between a woman's BMI at age 18 and premenopausal ER–/PR– breast cancer and (2) a positive association between current BMI and post-menopausal ER+/PR+ breast cancer .The Black Women's Health Study (BWHS) is a prospective study among African-American/Black women across the United States . The stuThe Women's Circle of Health Study is a multi-site case–control study in New York City and New Jersey that aims to identify risk factors for early aggressive breast cancers in African-American/Black and non-Hispanic European-American women , 33. RecThe Premenopausal Breast Cancer Collaborative group (as described above) observed an inverse association between premenopausal obesity and ER+/PR+ breast cancer . In cont2) and with a decreased risk of TNBC . Adult premenopausal women with increased BMI had a decreased incidence of (1) premenopausal ER+ breast cancer and (2) all subsequent post-menopausal breast cancer  (The African-American Breast Cancer Epidemiology and Risk (AMBER) Consortium was formed, in part, to investigate the inconsistent and confusing results generated in individual studies testing for the potential association between obesity (measured by BMI and/or WHR) and TNBC. The AMBER Consortium  brings tubtypes) . In adulubtypes) . The invubtypes) .Insulin is a peptide hormone that is produced by the pancreatic islet beta cells in response to an increase in serum glucose . InsuliThe majority of mammalian cell types express the insulin receptor and, consequently, are impacted by insulin-signaling . In addiInsulin binds to the insulin receptor and activates cell signaling pathways that are key regulators of cellular homeostasis. These signaling pathways are dysregulated in the majority of biologically aggressive cancers . Under nChronic high caloric intake (overeating) disrupts the balance between energy storage and consumption resulting in pre-diabetes (insulin resistance) and, ultimately, type-2 diabetes . OvereatThe increasing demands on the pancreatic islet beta cells that occur during hyperinsulinemia (insulin-resistance) contribute to the subsequent development of type-2 diabetes . ObesityInsulin-resistance is diagnosed when an individual has impaired fasting glucose and/or impaired glucose tolerance that does not meet the threshold for diabetes . Insulinhttps://extranet.who.int/rhl/topics/preconception-pregnancy-childbirth-and-postpartum-care/antenatal-care/who-recommendation-diagnosis-gestational-diabetes-pregnancy-0). Long-term, women with gestational diabetes are at risk for the subsequent development of type-2 diabetes    study reported in 2014 that 40.4% of adult women were obese (Body Mass Index (BMI) ≥30 kg/m2) , 61. Bet2) , 61 but 2) , 61. Obe2) –62.https://www.cdc.gov/diabetes/data/statistics/statistics-report.html); this total included 7.2 million  who were not aware. Compared to non-Hispanic whites, the age-adjusted prevalence of diagnosed and undiagnosed diabetes was higher among Asians, non-Hispanic Blacks, and Hispanics during 2011–2014. The world-wide incidence of diabetes, insulin-resistance, and gestational diabetes is difficult to estimate as many cases are undiagnosed and unreported [see Ogurtsova et al., 2017 for a full review (According to the United States Center for Disease Control (CDC), in 2015, 30.3 million people  across the United States are estimated to have type-2 diabetes . The threat of violence strongly affects the willingness of mothers to let their children play outdoors (http://www.nrpa.org/publications-research/research-papers/archive/) (https://theblackdetour.com/the-obesity-crisis-in-black-america/).Social inequities have contributed to a decrease in exercise in African-Americans/Blacks and Hispanic/Latinos. Access to public parks, public pools, and green space is much lower in African-American/Black and Latino/Hispanic neighborhoods. Sidewalks in African-American/Black neighborhoods are likely to be in poor condition (rchive/) . Africanhttps://www.cdc.gov/diabetes/data/statistics/statistics-report.html). The incidence of insulin-resistance was highest in Asians (35.7%) followed by non-Hispanic Blacks (36.3%), Hispanics (31.7%), and non-Hispanic Whites (31.5%) (https://www.cdc.gov/diabetes/data/statistics/statistics-report.html).As the incidence of obesity and type-2 diabetes continues to rise, women of childbearing age are at increased risk for insulin-resistance and gestational diabetes. The CDC reported in 2014 that 29.3% of women in the United States had insulin-resistance; only 13.3% were aware of having insulin-resistance  . This asAfter insulin binds to the insulin receptor, the insulin receptor is activated and then internalized within clathrin-coated vesicles , 7978, 7For a comprehensive review, see Gastaldelli et al. . As discThe liver is a key target of insulin and plays an important role in the development of insulin-resistance and type-2 diabetes. Chronic overeating results in the liver (1) losing its ability to regulate and suppress gluconeogenesis but (2) retaining its ability to drive lipogenesis. This dual dysregulation/overproduction of glucose and lipids is characteristic of the hyperglycemia and hyperlipidemia observed in metabolic syndrome and type-2 diabetes –98. ChroAlthough the pathophysiology of selective insulin/insulin-receptor signaling remains unclear, it is generally acknowledged that the pathways to insulin regulation of glucose vs. triglyceride production diverge downstream of AKT , 102. HoIn the liver, a key morphologic feature of chronic nutrient overload, hyperinsulinemia, and lipogenesis is steatosis. Steatosis, or fatty change, is the abnormal retention of lipids within cells. Excess lipid accumulates in hepatocyte vesicles, these vesicles displace the cytoplasm (microvesicular steatosis). When the vesicles are large enough to distort the nucleus, this is called macrovesicular steatosis. Macrovesicular steatosis is important for the development of hepatic fatty liver disease.Wound healing is impaired in individuals with type-2 diabetes and insulin resistance. Multiple components of wound healing are impaired including (1) neutrophil activation, (2) fibroblast migration and replication, and (3) abnormal angiogenesis. Insulin regulates VEGF expression and hyperinsulinemia is linked to decreased VEGF production –108. RedThe PI3K/AKT/mTOR-signaling pathway is a well-established regulator of central glucose metabolism and aerobic glycolysis  115–117117. AggrMitochondria are the major sites of cellular reactive oxygen species (ROS) production  45). Mi. Mi45). High ROS production plays an important role in cancer initiation and progression . ROS actInsulin activates both MAPK (RAS/RAF/mitogen activated protein kinase) and PI3K/AKT-signaling . This duMAPK-signaling plays a key role in motility and invasion. Under nutrient-rich circumstances, IGF-1 binds to the IGF-1 receptor (IGF-1R) leading to downstream phosphorylation-cascades that activates RAS, RAF, ERK, and MAPK  124)..124).Insulin activates AKT. AKT exhibits differential cellular localization in stationary vs. motile cells. Stationary epithelial cells display apical–basal polarity and exhibit an even distribution of basal level of phosphorylated AKT on the plasma membrane, overlapping with cortical actin filaments . Twist pThere is emerging evidence that AKT activation promotes cell motility through direct modulation of cytoskeleton-proteins, including actin and vimentin. Cell motility requires the dynamic remodeling of the cytoskeleton resulting in changes in cell morphology and polarity. Actin has been shown to preferentially bind to phosphorylated AKT at pseudopodia with enhanced bundles , 128. ThRho GTPases regulate cell cytoskeleton organization, migration, transcription, and proliferation . Rho proEMT is a cellular process critical for normal embryonic organogenesis. Dysregulation of EMT is frequently observed in biologically aggressive cancers, including breast cancer, and promotes invasion, metastasis, and poor survival . Key traCDH1 (E-cadherin gene) promoter through direct protein–protein interaction  inflammatory cytokines including interleukin-1 (IL-1), IL-2, IL-6, IL-8, IL-12, and TNF-α and (2) chemokines MCP-1, MCP-2, CXCL1, CXCL10, and RANTES . TogetheHyperinsulinemia also promotes macrophage switching and macrophage-mediated inflammation . ActivatAs early as the 1800's, physicians discovered that high dose (now known to be anti-inflammatory) salicylates (5.0–7.5 g/d) reduced glycosuria in diabetic patients , 146. SuLeptin and adiponectin are true adipokines that appear to be produced exclusively by adipocytes; leptin expression increases with increased adiposity; adiponectin expression decreases with increased adiposity , 157. ThHyperinsulinemia and tissue inflammation is also closely linked to atherosclerosis . In obesAngiogenesis is a key process in cancer initiation and metastasis. Endothelial cells and pericytes are two key cell types that participate in vessel formation and maturation and both endothelial cells and pericytes express the insulin receptor . Insulin2 . While BMI is a commonly used measure, the appropriateness of BMI as a phenotypic marker of adiposity across populations differing in race and ethnicity is highly controversial. BMI is an inexact measure of metabolic dysfunction; comparing BMI between individuals of different races and ethnicities has inherent problems  per area  can have normal metabolic profiles, “metabolically healthy obese”  who have abnormal metabolic profiles and increased cardiovascular risk. These individuals were first described by Ruderman et al. as hyperinsulinemic, insulin resistant, hypertriglyceridemic, and predisposed to subsequent development of type 2 diabetes mellitus and coronary artery disease  metabolic abnormalities that include insulin resistance, hypertriglyceridemia, (3) abdominal fat distribution, and (4) elevated blood pressure . Western influences on lifestyle including diet and physical activity likely contribute this burgeoning problem in China, India, and other parts of Asia as well as in the United States for Asian-Americans.Asians have a disproportionately increased incidence of diabetes mellitus relative to other racial and ethnic groups, in the United States and worldwide. By the International Diabetes Federation estimates for 2017, China and India have the largest number of people 20–79 years old with diabetes at 114.4 and 72.9 million, respectively, compared to the next highest in the United States at 30.2 million . For a given BMI, Asian-Americans have a higher likelihood of developing diabetes compared to non-Hispanic whites . BMI doemericans . For ideicans  compared with that of the lower quartiles  vs. women BMI <25 kg/m2 and no metabolic abnormality  had increased risk of post-menopausal breast cancer (As discussed above (section Complex Relationship Between Obesity and Breast Cancer) BMI and obesity have not been consistently associated with increased risk with premenopausal TNBC. However, as also discussed above , BMI and obesity do not consistently predict metabolic health; individuals can be normal weight and metabolically unhealthy; conversely individuals can be obese and metabolically healthy. Recent studies provide evidence that metabolic health (rather than BMI) may be a better predictor of breast cancer risk . Combinet cancer . In a tht cancer . In the t cancer . These sAs detailed above, insulin signaling activates PI3K/AKT/mTOR; PI3K/AKT/mTOR signaling promotes proliferation, apoptosis-resistance, and invasion , 190–194Biologically aggressive breast cancers, particularly TNBC and poor prognosis luminal B breast cancers  frequently exhibit high glucose consumption and aerobic glycolysis , 196. AgH1 cytokines ; M1 macrophages possess enhanced cytotoxic activity and are anti-tumorigenic  are regulated by Torigenic , howeverorigenic , 201. Inorigenic , 202. M2origenic , 204. TaTreatment of obesity-related end-organ failure (type-2 diabetes) is expensive. However, much of our efforts in preventing diabetes through diet and exercise have not been successful and type-2 diabetes is frequently not diagnosed until complications occur. This has led to a call for early screening and treatment of individuals at high-risk for type-2 diabetes.https://www.drugs.com/monograph/metformin-hydrochloride.html). Metformin is prescribed for first-line treatment of type-2 diabetes (https://www.drugs.com/monograph/metformin-hydrochloride.html) (https://www.drugs.com/monograph/metformin-hydrochloride.html) (https://www.drugs.com/monograph/metformin-hydrochloride.html). Metformin inhibits hepatic gluconeogenesis and decreases intestinal absorption of glucose, secondarily decreasing circulating insulin (https://www.accessdata.fda.gov/drugsatfda_docs/label/2006/021748s002lbl.pdf). Metformin is also thought to indirectly increase insulin sensitivity by increasing peripheral glucose uptake and utilization (https://www.accessdata.fda.gov/drugsatfda_docs/label/2006/021748s002lbl.pdf). Given its efficacy and excellent safety profile, metformin is on the World Health's Organization list of essential medicines and has been used for glucose control since the 1960's .Metformin  is a well-tolerated oral biguanide hypoglycemic agent that is prescribed to over 120 million type-2 diabetic patients worldwide (de.html) , 205–207de.html) . Common Despite its long history of clinical use, the precise molecular mechanism(s) underlying metformin's insulin-lowering effects, as well as its potential anti-neoplastic potential, are not completely understood. It is well-established that metformin inhibits hepatic gluconeogenesis and secondarily lowers circulating insulin levels  209). T. T209). There is increasing evidence that metformin, with or without lifestyle modification, in young, high-risk individuals can reverse and prevent type-2 diabetes. In the Diabetes Prevention Study (DPS), metformin was as effective as lifestyle modification in participants <60 years of age  and in wn = 1,082), (2) metformin  850 mg twice daily, or (3) intensive lifestyle intervention   of the cohort elected to be evaluated in the DPPOS follow-up trial  is the largest and longest clinical trial of metformin for the prevention of type-2 diabetes , 216. Th= 1,079) , 216. Th= 1,079) . The priup trial , 216.2), metformin was as effective a lifestyle modification , and effective. Despite the fact that metformin prevention of type-2 diabetes in high-risk individuals is now standard of care in the United States, many clinicians continue to focus on exclusively on treatment of type-2 diabetes and not its prevention.Based on findings from the DPP/DPPOS study, in 2014, the American Association of Diabetes published formal recommendations for prevention of type-2 diabetes  56). Re. Re56). As discussed above, insulin activates many key-signaling pathways and cancer processes that are key for cancer initiation and progression including: EMT, cell migration and mobility, tissue inflammation, ROS production, glycolysis and, perhaps, angiogenesis . MetformBRCA1 mutations. Given that PI3K/AKT/mTOR is a key driver of the aggressive biology of TNBC and metformin inhibits PI3K/AKT/mTOR, there has been interest in testing whether metformin maybe effective for prevention of TNBC in BRCA1 germline mutation carriers. In addition to targeting PI3K/AKT/mTOR, metformin targets additional signaling networks regulated by AMPK. Metformin-targeting of AMPK for prevention of TNBC in BRCA1 mutation carriers has good rationale because of the dual signaling networks regulated by both AMPK and BRCA1, include acetyl coenzyme A carboxylase alpha (ACCA), p53, and PTEN . The primary endpoint is invasive disease-free survival. Studies testing the impact of metformin in the unaffected breast include a study in women scheduled for a reduction mammoplasty that compares changes in LKB1 and AMPK signaling in women treated with metformin 500 mg twice a day  vs. no treatment . There are two ongoing larger primary prevention studies one in overweight and obese premenopausal women with high breast density  database 2010–2015, diabetic patients undergoing partial, total, or subcutaneous mastectomy were at greater risk of early post-operative surgical site infection—both superficial  and deep  tissue infections . For diaGiven the high prevalence of undiagnosed pre-diabetes and diabetes in the United States and worldwide, preoperative screening to identify such patients prior to surgical intervention is warranted. Numerous studies have investigated the utility of preoperative testing via HgbA1c in addition to the usual practice of random or fasting blood glucose levels. An observational cohort study of inpatient gastrointestinal surgical procedures at Veterans Affairs hospitals from 2007 to 2014 suggested that knowledge of elevated preoperative HgbA1c led to greater perioperative vigilance in monitoring and treating hyperglycemia and improved clinical outcome . Using HIn a review of 20 studies regarding perioperative glycemic control in diabetic patients and post-operative complications, elevated preoperative HgbA1c was not associated with increased post-operative morbidity and mortality in 20 selected studies; the authors, however, noted the need for good quality evidence in view of the heterogeneous, retrospective studies, and small patient numbers . To evalWomen receiving breast cancer chemotherapy are extensively monitored for electrolyte and liver function abnormalities and neutropenia. While serum glucose is routinely tested, there is minimal attention to development of insulin-resistance during breast cancer treatment. This is a missed opportunity and represents an important opportunity for improving cancer care. Given the key role that insulin signaling plays in cancer processes, it is logical to ensure that women who are treated for breast cancer do not develop insulin-resistance.Women who are treated for breast cancer experience stress, abnormal sleep patterns, overeating, administration of steroids, loss of body image, gastrointestinal disturbances, and immune suppression . Breast p < 0.01) (p < 0.01)  . Body we < 0.01) . Taken tWhile diabetes/insulin-resistance and breast cancer are distinct diseases, insulin-signaling plays a central role in both illnesses. Insulin activates key cancer processes including EMT, tissue inflammation, motility, and angiogenesis. There are key opportunities to impact and prevent hyperinsulinemia during breast cancer prevention, surgical assessment, and chemotherapy. While it is not standard of care to test for insulin-resistance during the course of breast cancer screening and treatment, it is standard of care to screen and test high risk women for insulin-resistance as part of whole woman care. Given the important role insulin signaling plays in driving signaling pathways that promote aggressive cancer biology, more attention should be paid by cancer physicians to screening and treating insulin resistance.VS organized the manuscript and wrote many of the sections. JM wrote the section on breast cancer medical oncology treatment and insulin resistance. LY wrote the sections on Asians and surgical complications and insulin resistance. RN cowrote the section on type 2 diabetes, progressive beta-cell failure, and decline in insulin production. ED cowrote the section on type 2 diabetes and progressive beta-cell failure.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies. One of the most important discoveries of modern genetics following the release of the complete sequence of the human genome and mapping of all genes is the role of genetic variation in disease incidence. To date, there are 88 million genetic variants that have been characterized. A genetic variant is an umbrella term referring to different types of alterations in a sequence within a certain region of the genome. Although the majority of these variants are unlikely to impact human health, there are some that have been associated with disease. These associations have provided valuable information about human diseases. Such genetic variants include indels (“insertions” or “deletions”), copy number variations (CNVs), translocations, transversions, and single nucleotide polymorphisms (SNPs). For the purpose of simplicity and coherence, we will solely focus on SNPs in the present review.SNPs are nucleotide variations occurring at a specific location within a genome, and with a frequency greater than 1% in a population. However, it should be noted that these variations do not necessarily cause disease. SNPs at low frequencies are usually referred to as mutations and, in combination with other genetic or epigenetic factors, may be responsible for causing disease. Of the aforementioned 88 million variants characterized in the human genome, 84.7 million are SNPs . SNPs arIt is known that GWAS assess and analyze differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent in a population under investigation. The ultimate goal of GWAS is to predict either disease risk or disease progression by utilizing genetic risk factors to define the biological basis of disease susceptibility. This also enables the development of innovative and preventative therapeutic strategies . There aTherefore, GWAS serve as a tool to identify associations between genetic regions and specific traits of interest. A basic GWAS will evaluate the genetic profiles of hundreds of patients of a well-defined phenotype to those of hundreds of control subjects. In this review, we will present and discuss the most significant findings obtained thus far in GWAS for the triple negative breast cancer (TNBC) disease. We have elected to focus on the TNBC subtype mainly owing to its aggressiveness, young age of diagnosis, and limited treatment options.As mentioned above, there are two fundamental concepts underlying GWAS. These are linkage disequilibrium (LD) and the common disease–common variant (CD–CV) hypothesis.LD is defined as a non-random association of two alleles at two or more loci . In turnIn general, closely linked polymorphic SNPs have strong LD between them. The International HapMap consortium has demonstrated that the human genome contains haplotype blocks, within which either most or all are high LD SNPs. Thus, there is a fine-scale pattern of LD present in human populations. Subsequently, it has been assumed that high LD levels detected among SNPs are for those alleles that exhibit increased risks of complex inherited diseases . InteresThe CD–CV hypothesis  has beenWhile discussing genetic heterogeneity and the potential role of rare genetic variants in complex human diseases, McClellan and King  have poiOne of these noted issues pertains to the fact that some of the genetic variants lack biological functions, and thereby their relative importance is highly diminished. In fact, it has been observed that GWAS are populated by risk variants of no known functions. Thus, the utility and reliability of GWAS have been questioned as most detected SNPs in GWAS are from intergenic regions . FurtherIn another claim, it has been reported that it is population stratification that results in GWAS hits . Althougp-values, fixed effects, random effects, Bayesian statistics, and multivariate analysis [As with all studies, sample size significantly impacts interpretations of data. Single GWAS analyses are relatively underpowered owing to the fact that they have a limited number of samples, which drastically increases the probability of false-positive findings. Given this, implementing meta-analysis of several GWAS can overcome these small-sample numbers and study-specific limitations, thus providing a more robust statistical analysis and reduced false-positive results. To date, there are many published articles describing the meta-analysis of GWAS ,13,14. Hanalysis . Using sanalysis ,17,18,19analysis , ISC [21analysis .The use of GWAS for cancer research studies has encountered several challenges, including the following: sample size; high numbers (430) of significant SNPs for cancer; association of several SNPs with multiple cancer localizations; implications of identified genes in several key signaling pathways involved in cancer; modulation of some pathways by lifestyle and environment; and, lastly, the fact that most studies are conducted using European populations, thus limiting extrapolation of these findings to other populations .Breast cancer remains a highly serious disease with the highest female incidence and mortality, as determined by age-standardized rate (ASR) per 100,000, of 46.3 and 13.0 worldwide, 54.5 and 15.5 for Eastern Europe , and 51.BRCA1/2 mutations, Her2 negative, locally advanced, or metastatic cancer that have been previously treated by chemotherapy (OlympiAD) [BRCA1/2 pathogenic mutations with either locally advanced or metastatic cancers (EMBRACA) [The above-mentioned receptor-based molecular classification undertaken by staining for estrogen, progesterone, and Her2 protein receptors has led to the identification of the breast cancer subtype triple negative breast cancer (TNBC). This subtype is the most aggressive and lethal form of all breast cancer subtypes, and is based on its elevated metastatic rate, reoccurrence, and drug resistance. Furthermore, as the nomenclature suggests, TNBC is characterized by a lack of ER, PR, and HER2/Neu expression ,34,35. TlympiAD) . The secEMBRACA) . In 2018Most GWAS related to cancer have evaluated either relationships of SNPs to risk of disease ,44,45,46LSP1), TOX high mobility group box family member 3 (TOX3), transition protein 1 (TNP1), carbohydrate sulfotransferase 9 (CHST9), aquaporin 4 (AQP4), BRCA1 DNA repair associated (BRCA1), and fibroblast growth factor receptor 2 (FGFR2) (MAP3K1), RAD51 paralog B (RAD51L1), BRCA1, BRCA2, estrogen receptor 1 (ESR1), MDM5, transforming growth factor beta 1 (TGFB1), telomerase reverse transcriptase (TERT), carbohydrate sulfotransferase 9 (CHST9), or REV1 DNA directed polymerase (REV1). Although there is some overlap with BRCA1/2 genes, for the most part, these associated genes are distinct. Moreover, the majority of SNPs identified in TNBC studies are associated with the risk of developing this disease, while only six SNPs are associated with either survival or prognosis of TNBC.On the basis of the literature, the following genes are associated with patient prognosis: lymphocyte-specific protein 1 ( (FGFR2) . MoreoveThe most common SNPs associated with TNBC are located within introns of protein-coding genes , thus coIn the second instance, if an intronic variant generates either long non-coding RNAs or circular RNAs , with eiTGFB1 is a tumor suppressor that, upon acquisition of oncogenic mutations, begins to stimulate malignant cell invasion and metastasis through epithelial-to-mesenchymal transition [Caspase-8 (Casp-8) is another interesting case, with specific effects in TNBC. In addition to its involvement in extrinsic apoptosis, Casp-8 stimulates cell cycle progression, while it inhibits cell invasion and migration through modulation of multiple genes; thus, this Caspase may play a more profound role in TNBC than in other malignant pathologies [Caspase 8, it is the C allele that offers a protective role over BC development [The third most common TNBC-associated SNPs are located in exons, yielding missense transcripts . This obansition . The trahologies . Intereselopment .KRAS variant rs61764370 (A > C) containing TNBC tumors, there is a decrease in let-7 miRNA level [BABAM1 rs8170 (G > A) and ALS2CR12 rs17468277 (C > T) are two synonymous genetic variants associated with an increased risk of breast cancer. Following a frameshift mutation of the BRCA1 gene, it is detected that rs80357794 (delC) is strongly correlated with hereditary ovarian and aggressive forms of breast cancer, including TNBC  to search for SNPs associated with TNBC. A total of five SNPs have been identified, and these are presented in Using the GWAS catalogue from EMBL-EBI, two SNPs (rs3803662 and rs8170) were selected, based on their identification in several studies, and patterns adjacent to these two SNPs were analyzed. For rs3803662, we observed that two additional SNPs were associated with breast cancer, and a single SNP was associated with both breast cancer and Parkinson’s disease. Meanwhile, for rs8170, we identified a single SNP that was associated with ovarian cancer; three SNPs that were associated with breast cancer; and a single SNP, rs2363956, that was associated with TNBC . It is iOn the basis of frequencies of different types of functional consequences generated by SNPs exhibited in TNBC, it is revealed that intronic variants are the most common functional consequence described in 42 different studies investigating SNPs in TNBC  are relevant to our discussion of SNPs, as they contribute to cancer risk ; moreoveBRCA1 and BRCA2 [ITGB4. However, it should be noted that the status of HER2 is not included in this study; therefore, associations with TNBC could not be determined [PAPD4  [p = 0.005) [Altering miRNA functions has an effect on the regulation of gene expression. Moreover, this form of polymorphism influences gene function and contributes to variability in disease susceptibility and severity in patients . There ind BRCA2 . It is rtermined . Further33–0.72) . In addi= 0.005) .MDM4, creating a novel site for miR-191 [MDM4, is also associated with an increased risk of triple negative breast cancer [Polymorphisms in miRNAs have been linked to increased risks of several cancers, such as colon ,77, brea miR-191 , is spec miR-191 . This ist cancer . Accordit cancer , a singlUsing the same GWAS concepts as in the case of general identification of SNPs, we can direct the observed miRNA-associated mutation frequencies towards four molecular consequences.Firstly, modifications in miRNA promoter/enhancer regions can influence specific miRNA expression. As these forms of mutations have only been recently investigated, data are scarce. For instance, in lung cancer, the G > C SNP in −617 site and the A > G SNP in −604 site in the promoter region of miR-7 decrease the levels of expression of this miRNA, and lead to a worse prognosis of the disease .Secondly, mutations in the primary miRNA processing proteins influence their function, and thus their processed miRNA availability. This was exemplified in a study of stage I and stage II breast cancer patients of African ancestry. Incidence of a higher frequency of the A allele in rs78393591, belonging to the Drosha gene, resulted in a higher risk for developing breast cancer .Thirdly, mutations in miRNA sequences, especially in the miRNA seed region, would affect its binding preferences. For instance, a higher frequency of the C allele in the rs72631820 locus of miR-339-3p was associated with a higher risk of having ER-tumors in patients of African ancestry with stage I or stage II BC . MeanwhiITGB4 [MDM4 gene, which provides a binding site for miR-191 and miR-877-3p. It should be noted that this gain in miRNA binding site is primarily reported for small cell lung cancer and prostate cancer [MDM4 is an oncoprotein that negatively regulates the p53 tumor suppressor protein, and its overexpression can lead to cancer progression [Lastly, mutations in the 3′UTR of one or a few miRNA targets would indirectly influence miRNAs targeting profiles of a diseased cell. For instance, women of GA or AA genotypes at the rs743554 locus have higher probabilities of developing ER-breast cancer and worse survival rates. Such a mutation in the 3′UTR of integrin β4 mRNA results in loss of tumor suppressor miRNA; that is, miR-34a ability to bind to ITGB4 . It is pITGB4 . One suce cancer . Despitee cancer , excludie cancer ,88,91. Mgression .In recent years, miRNAs, small non-coding RNAs that can regulate gene expression, have garnered interest owing to their capacity to act as biomarkers for both diagnosis and prognosis of diseases . InteresFuture studies should be more focused on mutations found in intronic regions, as these might be the origins of non-coding RNA species other than those of major protein-coding mRNA. This would have a major impact on how we interpret findings from future GWAS, particularly when considering that a single miRNA mutation has a major downstream effect owing to the ability of miRNAs to interact with hundreds of mRNAs at a time.The association of disease with particular alleles remains unclear, as it should. With the availability of large numbers of published GWAS identifying disease susceptibility loci, the following studies are specifically related to breast cancer ,104,105.The following section will discuss predictive models used in some GWAS related to breast cancer, although not specifically related to TNBC, but still correlated to receptors of specific subtypes.BRCA1 and BRCA2 genes, that confer the highest risks of developing breast cancer. GWAS have discovered multiple common breast cancer susceptibility variants, which individually present small risks, but their combined effects can be substantial. One method to quantify the combined effects of common variants is to use polygenic risk scores, as these genomic profiles permit stratification of women based on their risks of developing breast cancer [In the general population, it is only a small proportion of breast cancer patients who actually exhibit rare mutations in certain genes, such as t cancer . Currentt cancer ,108. AccMavaddat et al.  developeThese findings highlight the potential for combining PRS and other known risk factors for risk stratification. Moreover, the risk strata defined by PRS have allowed for the evaluation of risk reduction strategies. There are various other studies that have used similar approaches by combining PRS with environmental, modifiable, or non-modifiable risk factors. For example, Garcia-Closas et al.  have usep-interaction = 0.009), adult height (p-interaction = 0.025), and the combined MHT (p-interaction = 0.038) specific to an ER-positive status [Rudolph et al.  specifice status .More recently, Mavaddat et al.  have enhEven though GWAS are not disease-specific, they provide important and new knowledge for both research and clinical studies. GWAS catalogues or databases offer valuable SNP libraries that assist in gaining a better understanding of a target human disease in correlation with other diseases, and also facilitate in developing new research strategies that could aid clinicians. Although most GWAS focus on European populations, these methodologies could easily be transferred to studies of other population subtypes.As for TNBC patients, there are large numbers of identified SNPs that correlate with cancer risk, but very few SNPs that correlate with either survival or prognosis. In addition, developing a better understanding of how these alterations relate to gene and protein expression in TNBC will help in translating these findings in specific tests that could aid clinicians either in screening patients at risk for TNBC or in identifying new drugs that could improve patient outcomes by using personalized medicine.The use of high throughput technologies would bring significant advantages to GWAS and databases, as these would correlate SNPs with other biological relevant data, and subsequently translate this complex information to patient care. Furthermore, GWAS can be used for TNBC by identifying correlations of different identified SNPs with miRNA sites useful for targeting to determine their influence on either prognosis or progression of TNBC in patients. Additionally, a functional consequence of miRNA-associated polymorphisms is variability in disease susceptibility. Furthermore, PRS can potentially improve stratification for screening, especially when combining family history, other risk factors, and risk prediction models.In conclusion, interpretations of GWAS findings remain challenging; however, identifying and using SNPs specific for TNBC, we may be able to elucidate and better contextualize these types of studies. However, further studies should be undertaken on various other population subgroups, as well as pursuing analysis of general or healthy populations in order to overcome the limitations of our current knowledge.


Other risk factors including age at menarche, menopause, hormone replacement therapy after menopause, oral contraceptive use, and alcohol consumption did not show a heterogeneous association with breast cancer across the BI-RADS categories. Several known risk factors of breast cancer had a heterogeneous effect on breast cancer development across breast density categories, especially in postmenopausal women.We evaluated the heterogeneity of the effect of known risk factors on breast cancer development based on breast density by using the Breast Imaging-Reporting and Data System (BI-RADS). In total, 4,898,880 women, aged 40–74 years, who participated in the national breast cancer screening program in 2009–2010 were followed up to December 2018. Increased age showed a heterogeneous association with breast cancer (1-year hazard ratio (HR) = 0.92, 1.00 (reference), 1.03, and 1.03 in women with BI-RADS density category 1, 2, 3, and 4, respectively; P-heterogeneity < 0.001). More advanced age at menopause increased breast cancer risk in all BI-RADS categories. This was more prominent in women with BI-RADS density category 1 but less prominent in women in other BI-RADS categories (P-heterogeneity = 0.009). In postmenopausal women, a family history of breast cancer, body mass index ≥ 25 kg/m Breast cancer is the most common cancer in women worldwide, accounting for 24.4% of all types of cancer; moreover, breast cancer is the leading cause of cancer death in women . In AsiaBreast density is a non-modifiable risk factor for breast cancer and can be identified through breast cancer screening using a mammogram. High mammographic density increases the risk of breast cancer; women with a breast tissue density ≥ 75% have a 4–5 times higher risk compared with those with a density < 5% ,4. The eMost previous studies that investigated the interaction effect between breast density and other risk factors on breast cancer development considered other risk factors as effect modifiers and breast density as an independent variable of interest ,11,12,13In Asian countries, known breast cancer risk factors are less prevalent; however, the prevalence of dense breasts is high  and screThe associations between risk factors and the development of breast cancer stratified by breast density, and heterogeneity of the association between BI-RADS categories are presented in When stratified by menopausal status, a heterogeneous effect of each risk factor on breast cancer based on the four density categories was not observed in premenopausal participants . Despite2, and smoking history showed a heterogeneous association with BI-RADS density categories , 2.36 (95% CI = 1.80–3.09), 1.64 (95% CI = 1.35–1.98), and 1.79 (95% CI = 1.40–2.29) for those in BI-RADS categories 1, 2, 3, and 4, respectively (P-heterogeneity = 0.008). Smoking increased the risk of breast cancer significantly in participants with BI-RADS density category 3 ; however, smoking did not show an association in other categories (P-heterogeneity = 0.001).In postmenopausal participants, in addition to age at menopause  showed a heterogeneous association with breast cancer across density categories. Among the participants who underwent menopause, a family history of breast cancer, BMI ≥ 25 kg/mIn the Korean population, age-specific breast cancer incidence increases up to the age of 45–49 years, and then decreases with further increases in age . In the A previous study suggested that menopause is more strongly associated with breast density than age . Several2, has not increased in women. Especially in women aged 20–39 and 40–59 years old, the prevalence of obesity has decreased [BMI is a well-known risk factor for the development of breast cancer in postmenopausal women because of the aromatization of androgens into estrogens, but not premenopausal breast cancer where increased BMI may have a protective effect . Howeverecreased , which iecreased . The uniSeveral studies have shown that the association between breast density and the risk of breast cancer is stronger in women with a family history of breast cancer than those without a family history ,11,34. TDespite the well-known carcinogenic effect of smoking, there has been a debate on the association between smoking and breast cancer. However, recent studies demonstrated that smoking increased the risk of breast cancer , as wellThe effect of the decrease in risk with increased age at menarche and a non-significant association of oral contraceptive use irrespective of the breast density category were comparable with findings in previous studies ,44. LoweThere are several limitations of this study. First, the study population comprised cancer screening examinees and their baseline characteristics may not be comparable with those of non-examinees. Considering that breast cancer screening participation rate in 2009–2010 was approximately 45%  and we iDespite these limitations, our study has a number of strengths including the large sample size and prospective design. The follow-up period was > 8 years and enabled us to study the short- and intermediate-term effects of risk factors and breast density on breast cancer. In addition, the study population covers a large proportion of the female population in Korea and various risk factors interacting with breast density were considered together.The NHIS in Korea supports biennial health examinations for individuals aged ≥ 40 years. It also supports the screening of stomach, liver, colon, breast, and cervical cancer in the eligible population. Participants of health examinations and cancer screening are asked to complete self-reported questionnaires, which collect information on lifestyle factors, family history of chronic diseases and cancer, and reproductive factors. The information in the questionnaires and results of health examinations and cancer screening are collected through the NHIS screening database. All participants provided consent that allowed the transfer of information to the NHIS database.For breast cancer, NHIS supports biennial mammographic screening for women aged ≥ 40 years. Approximately 40% of women who are eligible participate in the screening; approximately 3 million mammographic screenings are performed each year. During screening, data on the BI-RADS density assessment and BI-RADS assessment categories were collected. Breast cancer incidence was defined via linking the database with the NHIS medical usage database to obtain the information related to either invasive breast cancer (C50) or ductal carcinoma in situ (D05) and catastrophic illness codes up to December 2018. Upon reviewing the study proposal and request to the National Health Insurance Sharing Service, the NHIS database was made available for research. The study proposal was approved by the Institutional Review Board of the Hanyang University College of Medicine (IRB no. HYI-18-175-1).n = 278,461) were excluded. The remaining 5,038,851 were included in the analysis as subjects. Women who newly acquired medical usage record for breast cancer (C50 and D05) with a catastrophic illness code  by December 2018 were defined as incident breast cancer cases. In addition, 141,345 women with missing information on breast density or with breast implants were excluded; the remaining 4,897,506 women including 54,164 breast cancer cases were included in the analysis for the analysis stratified by BI-RADS density categories.We identified 5,317,312 women who participated in health examinations and breast cancer screenings between 2009 and 2010. Among these, women aged ≥ 75 and women who had a medical usage record for any type of cancer with catastrophic illnesses code before the date of breast cancer screening or within 3 months from the date of breast cancer screening  and R software (version 3.5.0) during March–December 2019.The distribution of breast cancer risk factors as a whole and according to the BI-RADS density categories was presented as numbers and percentages. The effect of each risk factor on breast cancer was analyzed using the Cox proportional-hazard regression model adjusted for other risk factors. The results are presented as hazard ratio (HR) and 95% confidence intervals (CIs) for the total number of participants and stratified by BI-RADS density categories. The follow-up was considered from the date of breast cancer screening during the year of 2009–2010 up to December 31, 2018, date of death, or date of any cancer incidence (based on which date came first). Incident breast cancer was considered as an event; death, incidence of other types of cancer, and no incidence of cancer were censored. Additionally, the effect of each risk factor on breast cancer and the stratification by BI-RADS breast density categories were evaluated according to the menopausal status. Heterogeneity of the effect of each risk factor across the BI-RADS density categories was assessed using IIn summary, some known risk factors of breast cancer showed a heterogeneous effect on breast cancer across breast density categories, especially in postmenopausal women. The association of genetic risk factors or family history, known breast cancer risk factors, especially reproductive factors with breast density is under investigation. Among various hypotheses regarding the mechanism of effect of breast density on breast cancer risk, this research focused on the interaction effect. However, studies have suggested the mediation effect of breast density on the association between known risk factors and breast cancer ,59. The


Although a number of studies explain the association between dietary patterns, which take into account that foods are eaten in combination, and breast cancer risk, the findings are inconsistent. We examined the association between dietary patterns and multi-grain rice intake, and the risk of breast cancer in a large-scale prospective cohort study in Korean women. A total of 93,306 women aged 40–69 years from the Health Examinees-Gem (HEXA-G) study (2004 and 2013) were included. We obtained Information on cancer diagnosis via linkage to the Korea Central Cancer Registry. Factor analysis was conducted to obtain dietary patterns, and Cox proportional models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CI) for breast cancer risk. For 494,490 person-years, 359 new cases of breast cancer occurred. We identified three major dietary patterns, that explained 23.9% of the total variance based on daily total food intake (g/day) from 37 food groups: the meat dietary pattern (higher intake of bread and red meat), the white rice dietary pattern (higher intake of white rice and lower intake of multi-grain rice), and the other pattern. Women who had higher white rice dietary pattern scores had a 35% higher risk of breast cancer, than did women with lower white rice dietary pattern scores . We found that women who consumed three or more servings of multi-grain rice per day had 33% lower risk of breast cancer than did those who consumed one or less multi-grain rice serving per day among women under 50 years of age . Our study suggests that a multi-grain rice diet may be associated with lower risk of breast cancer in Korean women. The incidence rate of breast cancer varies widely worldwide . In KoreSeveral epidemiologic studies have linked the risk of breast cancer with individual foods and nutrients such as fruits and vegetables , fats 44, red meSeveral epidemiological studies have investigated the association between dietary patterns and breast cancer risk. Previous cohort studies indicated that those who had dietary patterns, characterized by high intake of fruit and vegetables ,13, fishAsian dietary habit differ from those of western populations; Asian populations consume much less meat and more carbohydrate compared to the western populations ,19. HoweIn this study, we aim to estimate the effect of dietary patterns and multi-grain rice intake on the risk of breast cancer development by using a large-scale prospective cohort study of Korean women between 2004 and 2013.This study used baseline data from the Health Examinees-Gem (HEXA-G) study, which was derived from the HEXA study ,24. The n = 8,531). Participants were also excluded if they did not answer the Food Frequency Questionnaires (FFQs)  and had insufficient values  for total energy intake ; 4000 participants who already had any type of cancer at baseline were excluded. We also excluded women who were diagnosed with breast cancer during the first 2 years of the follow-up period to lessen the impact of reverse causality (n = 221). Finally, we considered 78,320 women in this analysis.Updated from the previously published HEXA studies ,24, the The HEXA study is a component of the Korean Genome and Epidemiology Study (KoGES). The study protocol was approved by the Institutional Review Board (IRB) of the Seoul National University Hospital (IRB number 0608-018-179) and the Ethics Committee of the KoGES of the Korea National Institute of Health (IRB number 2014-08-02-3C-A).Usual dietary intake was assessed using a validated semi-quantitative FFQ during the previous one year . InterviInformation on the date of initial diagnosis and cause of cancer was ascertained by linkages to the Korea Central Cancer Registry, until 31 December 2014. Participants gave written informed consent for secondary data linkages, such as the Korean Central Cancer Registry. Cancer incidence was defined based on the 10th revision of International Classification of Disease (ICD-10) as follows: cancer incidence (C), and breast cancer incidence (C50).2) was calculated by dividing body weight (in kilograms) by the square of height (in metres).Each participant’s age, educational level , regular exercise , alcohol intake , smoking status , marital status , menopausal status , the number of parity, age at first birth, age at menarche, oral contraceptive use , and the presence of family history of cancer  were obtained using the structured questionnaire. We obtained information on the participant’s height (cm) and weight (kg) directly measured by the medical staff. Body mass index  was used to derive dietary patterns based on the 37 food groups in our analysis. The factors were rotated using an orthogonal transformation to simplify the factor structure for easier interpretation. The more involved a variable was, the higher the weight. Variables unrelated to a dietary pattern would be weighted close to zero. The factor score for each dietary pattern was calculated by summing the intakes of all the food groups weighted by their factor loadings, and each participant was assigned a factor score for each dietary pattern . A higheCox proportional hazards models were fit to assess the relationship between each dietary pattern and the incidence of breast cancer; age was used as the time scale in Cox proportional hazard models. Age at baseline was used as the entry time to reflect the left-truncation time of the data and age at cancer diagnosis or final follow-up was the exit time. Person-years of follow-up were estimated from the date of study entry until the date of breast cancer diagnosis, date of any cancer diagnosis, or the end of the follow-up period . In separate analyses, we also assessed the relationship between each individual component of the white rice dietary pattern and the risk of breast cancer. Participants were classified into three categories based on the distribution of their reported daily intake of each component of the dietary pattern. Because the number of participants who never or rarely consumed white rice (83%) were more than those who never or rarely consumed multi-grain rice (43%), we categorized these women into <1 serving/day, 1–2 serving/day, or ≥3 servings/day for white rice consumption and ≤1 serving/day, 2 serving/day, or ≥3 servings/day for multi-grain rice consumption groups.2, continuous), total energy intake , educational level , parity , age at first birth , age at menarche , regular exercise , alcohol intake , and the presence of a family history of breast cancer . Tests of linear trend were calculated by assigning the medians to each category and evaluated by the Wald test.Multivariable hazard ratios (HRs) were adjusted for BMI (kg/mp ≤ 0.05.If we had missing variables (less than 3% of each variable), we assigned the median value or most common category to missing variables in this study. SAS software version 9.4  was used for all analyses. All p-values were two-sided tests, and statistical significance was set at We identified three major dietary patterns in the final models, ‘meat dietary pattern’, and ‘white rice dietary pattern’, and the ‘other pattern. Three dietary patterns, which explained 23.9% of the variance in the 37 food groups in our factor analysis. The factor loading matrix for the three patterns, for which a positive loading indicates a positive association between the dietary pattern and the food group and a negative loading indicates an inverse association, is shown in 2), and 1981.0 , respectively. We compared the general characteristics of the participants across quartiles of the factor score for each dietary pattern  for 78,320 women, a total of 359 breast cancer cases were newly diagnosed, and these cases were included in this analysis. The participants’ mean age, BMI, and total energy intake were 52.3 (years), 23.6 . In contrast, the meat dietary pattern and the other pattern were not associated with the risk of breast cancer.Multivariable HRs of breast cancer according to quartile category of each dietary pattern score are shown in p for trend = 0.0204). However, we observed women who consumed three or more servings of white rice per day had no significantly increased risk of breast cancer  compared with women who almost never consumed white rice.In this large prospective cohort study, we identified three dietary patterns: the ‘meat dietary pattern’, the ‘white rice dietary pattern’, and the ‘other pattern’. We found that higher white rice dietary pattern scores were significantly associated with increased risk of breast cancer. However, there were no associations between the meat dietary pattern or the other pattern and breast cancer risk among women.Previous prospective cohort studies on the association between dietary pattern and breast cancer risk conducted in western populations ,15,17,32In our study, we identified the white rice dietary pattern, which is characterized by high intake of white rice and low intake of multi-grain rice, in Korean women. Similarly, previous studies identified the white rice pattern, characterized by very high consumption of white rice and very low consumption of whole grain  and the This study found that the white rice dietary pattern was significantly associated with the risk of breast cancer. White rice is classified as a refined grain because during the refining process the outer layer of the grain containing bran and germ is striped out, and white rice that only contains the endosperm is produced . A case-In this study, the main components of the white rice dietary pattern were white rice and multi-grain rice. Our results showed that higher consumption of multi-grain rice was associated with a lower risk of breast cancer among women under 50 years of age. In agreement with our findings, a cohort study  and caseWhole grains have more nutritional value than refined grains ,45 becauThe strength of our study is that it is a prospective cohort study that eliminated potential for recall biases that can occur in either case-control studies or retrospective cohort studies. To the best of our knowledge, this is the first prospective study to examine the association between dietary patterns and breast cancer risk in Korean women. In addition, we used cancer diagnosis data that had high completeness approximately 97.8% in 2014  and highNevertheless, our study had some limitations. First, we assessed dietary intake only at baseline and could not control the possibility that some changes may have occurred in participants’ dietary habits may have occured during follow-up . More ac