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. 2021 Jan 19;16(1):e0236904. doi: 10.1371/journal.pone.0236904

Coffee consumption and risk of breast cancer: A Mendelian randomization study

Merete Ellingjord-Dale 1,*, Nikos Papadimitriou 2, Michail Katsoulis 3, Chew Yee 1, Niki Dimou 2, Dipender Gill 1, Dagfinn Aune 1,4,5, Jue-Sheng Ong 6,7, Stuart MacGregor 6, Benjamin Elsworth 7, Sarah J Lewis 7,8, Richard M Martin 7,8,9, Elio Riboli 1, Konstantinos K Tsilidis 1,10
Editor: Matteo Rota11
PMCID: PMC7815134  PMID: 33465101

Abstract

Background

Observational studies have reported either null or weak protective associations for coffee consumption and risk of breast cancer.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis to evaluate the relationship between coffee consumption and breast cancer risk using 33 single-nucleotide polymorphisms (SNPs) associated with coffee consumption from a genome-wide association (GWA) study on 212,119 female UK Biobank participants of White British ancestry. Risk estimates for breast cancer were retrieved from publicly available GWA summary statistics from the Breast Cancer Association Consortium (BCAC) on 122,977 cases (of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative) and 105,974 controls of European ancestry. Random-effects inverse variance weighted (IVW) MR analyses were performed along with several sensitivity analyses to assess the impact of potential MR assumption violations.

Results

One cup per day increase in genetically predicted coffee consumption in women was not associated with risk of total (IVW random-effects; odds ratio (OR): 0.91, 95% confidence intervals (CI): 0.80–1.02, P: 0.12, P for instrument heterogeneity: 7.17e-13), ER-positive (OR = 0.90, 95% CI: 0.79–1.02, P: 0.09) and ER-negative breast cancer (OR: 0.88, 95% CI: 0.75–1.03, P: 0.12). Null associations were also found in the sensitivity analyses using MR-Egger (total breast cancer; OR: 1.00, 95% CI: 0.80–1.25), weighted median (OR: 0.97, 95% CI: 0.89–1.05) and weighted mode (OR: 1.00, CI: 0.93–1.07).

Conclusions

The results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak association.

Background

Coffee contains biochemical compounds such as caffeine, polyphenols and diterpenes that may protect against breast cancer risk through their anticarcinogenic properties [1–3] or through their favorable alterations of levels of estradiol and SHBG [4–8]. Several observational studies have investigated the association between coffee consumption and breast cancer risk, but findings have been inconsistent with the majority of studies reporting null associations [9–25] and other studies reporting protective associations [26–30]. A recent meta-analysis including 21 prospective cohort studies reported a weak protective association for highest versus lowest category of coffee consumption with overall (RR = 0.96, 95% CI = 0.93–1.00) and postmenopausal (RR = 0.92, 95% CI = 0.88–0.98) breast cancer [31]. However, observational studies may be confounded by other dietary or lifestyle factors. Further, there are no clinical trials on the effect of coffee consumption on breast cancer risk, and it is still unclear whether an association exists and if so, whether it is causal.

Several genome-wide association studies (GWAS) on coffee or caffeine consumption have been previously published [32–37]. One of these GWAS was a meta-analysis conducted by the Coffee and Caffeine Genetics Consortium in 2015 incorporating summary statistics from 28 population-based studies of European ancestry, and reported six loci associated with coffee consumption that were involved either in the pharmacokinetics (cytochrome P4501A1 (CYP1A1)/cytochrome P4501A2 (CYP1A2), aryl hydrocarbon receptor (AHR)) or pharmacodynamics of caffeine (brain-derived neurotrophic factor (BDNF) and solute carrier family 6 member 4 (SLC6A4)) [35]. A more recent and larger GWAS was conducted among individuals (179,954 males and 212,119 females) of white British ancestry in the UK Biobank (UKB) cohort [37], and identified 35 genetic variants strongly associated with coffee intake.

Mendelian randomization (MR) is a method that uses genetic variation arising from meiosis as a natural experiment, to investigate the potential causal relationship between an exposure and an outcome [38, 39]. MR estimates are less susceptible to bias from potential reverse causality and confounding compared to estimates from observational studies, because genetic variants are randomly distributed at conception [40, 41]. A recent MR study assessed the potential causal association between coffee consumption and risk of several cancers, including breast cancer, and concluded that coffee consumption is unlikely to be associated with overall breast cancer susceptibility [37]. However, the latter study did not report associations by breast cancer subtypes. In the current MR study, we investigated the relationship between genetically predicted coffee consumption and risk of breast cancer overall as well as breast cancer subtypes incorporating several MR methods to assess the impact of potential MR assumption violations.

Methods

Genetic data on coffee consumption

We used 35 single nucleotide polymorphisms (SNPs) that were associated with coffee consumption at genome-wide significance (p<5e-8) level in the combined population of men and women in UKB [37], but their beta estimates (SNP-coffee) were derived from analyses only among the female population. In a sensitivity analysis, we combined beta estimates (SNP-coffee) for both men and women to increase statistical power. The UKB is a population-based cohort study of more than 500,000 participants aged 38 to 73 years, who enrolled in the study between 2006 and 2010 from across the UK [42]. Coffee consumption was measured via self-administered questionnaires and was defined as cups of decaffeinated coffee, instant coffee, ground coffee and any other type of coffee (UKB Data field ID: 1508) consumed per day [37]. Briefly, the UKB participants were genotyped using Affymetrix UK Biobank Axiom array and imputed against the UK10K, 1000 Genomes Phase 3 and Haplotype Reference Consortium panels [37]. The GWAS was conducted using the BOLT-LMM software [43] to model the genetic association accounting for cryptic relatedness in the UKB sample. SNPs were clumped at r2 <0.01 using a 10-mb window [37].

Genetic data on breast cancer

Out of the 35 genome-wide significant SNPs [37], we extracted 33 SNPs from the publicly available breast cancer GWAS from the Breast Cancer Association Consortium (BCAC). BCAC has data on 122,977 breast cancer cases of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative, and 105,974 controls of European ancestry (http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/gwas-icogs-and-oncoarray-summary-results/). BCAC was initiated in 2005 and is an international collaboration that studies genetic susceptibility to breast cancer. The breast cancer GWAS was performed in females of European ancestry from 68 studies collaborating in BCAC, the Discovery, Biology and Risk of Inherited Variants in Breast Cancer Consortium (DRIVE; 61,282 cases and 45,494 controls), the Illumina iSelect genotyping Collaborative Oncological Gene-Environment Study (iCOGS; 46,785 cases and 42,892 controls), and 11 other breast cancer GWAS (14,910 cases and 17,588 controls) [44]. Genotyping in the BCAC and DRIVE studies was done using OncoArray1, whereas iCOGS used Illumina iSelect array (http://ccge.medschl.cam.ac.uk/research/consortia/icogs/). Using the 1000 Genomes Project (Phase 3) reference panel, genotypes were imputed for approximately 21M variants [44].

Statistical power

Statistical power calculations were conducted using the online mRnd calculator (available at http://cnsgenomics.com/shiny/mRnd/). Using an estimated 1% variance of coffee consumption explained by the instruments [37], the study had 80% power with a type I error rate of 0.05 to detect associations of odds ratios of 0.89, 0.87 and 0.80 per one cup of coffee per day and risk of overall, ER-positive and ER-negative breast cancer, respectively.

Statistical analysis

Main MR analysis

We conducted a two-sample MR using summary association data for 33 coffee-associated SNPs. We ran both fixed- and random-effects inverse-variance weighted (IVW) models, but the random-effects IVW model was considered the main analysis due to the large number of SNPs and the substantive observed heterogeneity [45, 46]. The IVW MR approach combines individual MR estimates across SNPs to derive an overall weighted estimate of the potential causal effect. We calculated the MR-derived odds ratio (OR) of breast cancer risk for a one cup per day increase in genetically predicted coffee consumption. This study used publicly available data.

Sensitivity analyses

The IVW MR approach assumes that all genetic variants must satisfy the instrumental variable assumptions, namely the genetic variants must be: 1) associated with coffee consumption, 2) not associated with confounders of the association between coffee consumption and breast cancer, and 3) only associated with breast cancer via their association with coffee consumption [45, 47, 48]. We tested for potential violation of the first MR assumption by measuring the strength of the genetic instruments using F-statistics. The F-statistic is the ratio of the mean square of the model to the mean square of error [49]. The Cochran’s Q test and the I2 statistic were used to quantify the heterogeneity in effect sizes between the genetic instruments [50], which may indicate horizontal pleiotropy that could violate the third MR assumption. To further test and attempt to correct for potential violation of the second and third MR assumptions, we used several approaches such as the MR-Egger regression [51], the weighted median [52] and mode [53] methods, and the MR pleiotropy residual sum and outlier test (MR-PRESSO) [54].

MR-Egger

The MR-Egger is an adaption of Egger regression, which allows for directional pleiotropy by introducing an intercept in the weighted regression model. Values away from zero for the intercept term are an indication of horizontal pleiotropy [51]. The MR-Egger approach provides unbiased results in the presence of pleiotropic instruments assuming that the magnitude of pleiotropic effects is independent of the size of the SNP-coffee consumption effects, which is called the Instrument Strength Independent of Direct Effects (InSIDE) assumption [51].

Weighted median

We used the weighted median method that orders the MR estimates obtained using each instrument weighted for the inverse of their variance. Selecting the median result provides a single MR estimate with confidence intervals estimated using a parametric bootstrap method [52]. The weighted median does not require that the size of any pleiotropic effects on the instruments are uncorrelated to their effects on the intermediate phenotype, but assumes that at least half of the instruments are valid [55].

Weighted mode

The mode based causal estimate consistently estimates the true causal effect when the largest group of instruments with consistent MR estimates is valid [53].

MR-PRESSO

We used the MR-PRESSO outlier test to identify outlier SNPs, which could have pleiotropic effects [54]. This method regresses SNP-outcome on SNP-exposure and uses square of residuals to identify outliers.

To further determine whether pleiotropy could have influenced our results, we collected information on published associations of the genetic instruments for coffee consumption with other phenotypes from the Phenoscanner webpage [56]. Genetic instruments associated at genome-wide significance with potentially important confounders of the coffee and breast cancer association, namely BMI [57–61], age at menarche [62, 63], alcohol [64–68], smoking [67, 69–71] and age at menopause [72] were iteratively excluded from the analyses.

In addition, we repeated the analysis after excluding SNPs that had p-values in their associations with coffee consumption among women larger than 1e-05 to avoid weak instrument bias. We also used beta estimates from a previous GWAS as an alternative instrument of eight SNPs (rs1260326, rs1481012, rs17685, rs7800944, rs6265, rs9902453, rs2472297 and rs4410790) associated with coffee consumption [35] to ensure that our results were robust against different choices of instrument selection and because these eight SNPs are linked to caffeine metabolism and may reflect less likelihood for pleiotropic actions. All the analyses were performed using the MR robust package in Stata [73] and the Mendelian randomization package in R [74].

Results

The associations between the genetic instruments with coffee consumption and breast cancer are shown in the S1 Table. One variant (rs17817964 in FTO) was strongly associated with overall (P = 4.67E-20), ER-positive (P = 2.48E-13) and ER-negative breast cancer (P = 1.56E-09).

Main MR analyses

The fixed-effects IVW method yielded inverse associations for genetically predicted coffee intake and risk of total, ER-positive and ER-negative breast cancer (Figs 1–3 and S2 Table), but there was substantial heterogeneity in the individual SNPs instrumenting coffee and risk of disease (Cochran’s Q test P-value = 10−5–10−13, I2 = 57–74%, S1–S6 Figs). Therefore, the random-effects IVW model was preferentially adopted for the main analysis, where the association between coffee consumption (per cup of coffee per day) and total (OR = 0.91, 95% CI = 0.80–1.02, P = 0.12), ER-positive (OR = 0.90, 95% CI = 0.79–1.02, P = 0.09) and ER-negative breast cancer (OR = 0.88, 95% CI = 0.75–1.03, P = 0.12) resulted in wider confidence intervals overlapping the null (Figs 1–3 and S2 Table).

Fig 1. Association between 1 cup/day increase of coffee consumption and breast cancer risk overall.

Fig 1

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MR-analyses are derived using random effect IVW, MR-Egger, weighted median and mode.

Fig 3. Association between 1 cup/day increase of coffee consumption and risk of ER-negative breast cancer.

Fig 3

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MR-analyses are derived using random effect IVW, MR-Egger, weighted median and mode.

MR-Egger

Results based on the MR-Egger regression did not show any association for genetically predicted coffee consumption and risk of total breast cancer or subtypes (Figs 1–3, S2 Table).

Weighted median and mode

Similarly, results from the weighted median analysis showed little evidence of an association per one cup of coffee per day and overall (OR = 0.97, 95% CI = 0.89–1.05, P = 0.45, Fig 1), ER-positive (OR = 0.94, 95% CI = 0.86–1.04, P = 0.24, Fig 2) and ER-negative breast cancer (OR = 1.02, 95% CI = 0.90–1.17, P = 0.72, Fig 3). The weighted mode model also yielded little evidence for an association (Overall breast cancer; OR = 1.00, 95% CI = 0.93–1.07, Figs 1–3 and S2 Table).

Fig 2. Association between 1 cup/day increase of coffee consumption and risk of ER-positive breast cancer.

Fig 2

Open in a new tab

MR-analyses are derived using random effect IVW, MR-Egger, weighted median and mode.

MR-PRESSO

The MR-PRESSO outlier test detected six SNPs as potential outliers for total breast cancer (i.e. rs13387939, rs17817964, rs34060476, rs2472297, rs2521501 and rs539515), three SNPs for ER-positive breast cancer (i.e. rs17817964, rs2472297 and rs2521501) and three SNPs for ER-negative breast cancer (i.e. rs13387939, rs3810291 and rs17817964). After excluding these SNPs outliers, there was an inverse association between genetically predicted coffee intake (per one cup of coffee per day) and risk of overall (OR = 0.90, 95% CI = 0.83–0.98, P = 0.03) and ER-positive breast cancer (OR = 0.87, 95% CI = 0.78–0.97, P = 0.02), but no association for ER-negative breast cancer (OR = 0.97, 95% CI = 0.87–1.08, P = 0.62, S2 Table). However, the rs2472297 is located between CYP1A1 and CYP1A2 and is involved in the pharmacokinetics of caffeine, and has the strongest association with coffee consumption amongst all genetic instruments (P< 1e-168). Many of the other outlying SNPs had genome-wide significant associations with age at menarche (rs17817964, rs13387939, rs539515 and rs3810291), body mass index (rs17817964, rs13387939, rs2472297, rs539515 and rs3810291) and alcohol intake (rs17817964 and rs34060476, S3 Table).

Sensitivity analyses

We performed several sensitivity analyses and there was little evidence of any association between genetically predicted coffee consumption and breast cancer risk (S2 Table). We performed MR-analyses after excluding genetic instruments known to be associated at genome-wide significance with 1) body mass index (i.e. rs4357572, rs539515, rs62106258, rs13387939, rs142219, rs2465054, rs4410790, rs2472297, rs17817964, rs66723169 and rs3810291), 2) age at menarche (i.e. rs539515, rs62106258, rs13387939, rs2236955, rs17817964 and rs381029), 3) alcohol consumption (i.e. rs1260326, rs34060476, rs17817964 and rs66723169), 4) smoking (i.e. rs56113850), and 5) age at menopause (i.e. rs1260326) (S2 and S3 Tables). When we reran the analyses after excluding 13 genetic instruments (i.e.rs117968677, rs1260326, rs1422191, rs16966903, rs2236955, rs2465054, rs2667773, rs34190000, rs3810291, rs395815, rs4092465, rs55754437 and rs62064918) with p-values with coffee consumption among women larger than 10−5, the results remained largely the same (Overall; OR = 0.90, 95% CI 0.77–1.06, ER-positive; OR = 0.99, 95% CI 0.77–1.05 and ER-negative; OR = 0.88, 95% CI 0.72–1.07, S2 Table). In another sensitivity analysis, we used as genetic instruments eight SNPs (i.e. rs1260326, rs1481012, rs17685, rs7800944, rs6265, rs9902453, rs4410790 and rs2472297) from a GWAS for coffee consumption among consumers conducted by the Coffee and Caffeine Genetics Consortium [35], and there was again no evidence of an association (Overall; OR = 1.10, 95% CI 0.97–1.24, ER-positive; OR = 1.07, 95% CI 0.96–1.21 and ER-negative; OR = 1.16, 95% CI 0.97–1.38). To increase statistical power, we used the 33 genetic instruments from UK Biobank but with beta estimates (SNP-coffee) from females and males combined, but the results remained largely the same (Overall; OR = 0.92, 95% CI 0.82–1.04, P = 0.20, ER-positive; OR = 0.92, 95% CI 0.81–1.04, P = 0.16, ER-negative; OR = 0.90, 95% CI 0.77–1.05, P = 0.17, S2 Table).

Discussion

In this comprehensive MR analysis of coffee consumption with risk of breast cancer, we observed that in the majority of analyses genetically predicted consumption of coffee was not associated with overall, ER-positive and ER-negative breast cancer. In line with our results, a recent large MR-study on the association between coffee consumption and risk of being diagnosed with or dying from cancer overall and by anatomical subsite reported no evidence for an association with risk of breast cancer [37]. Compared to the previous study, our study added results by ER-status and presented detailed sensitivity analyses to fully assess potential violations of MR assumptions.

Coffee is among the most commonly consumed beverages worldwide, and its drinking provides exposure to a range of biologically active compounds [75]. Higher coffee consumption has been associated with decreased risk of all-cause, cardiovascular and cancer mortality among non-smokers [76]. Several observational studies have investigated the association between coffee consumption and risk of breast cancer development, but findings have been inconsistent [31, 77, 78]. The most recent meta-analysis synthesized evidence from 21 prospective cohort studies [31], and reported a weak inverse association between coffee consumption and risk of total (OR higher vs. lower = 0.96, 95% CI = 0.93–1.00) and postmenopausal breast cancer (OR = 0.92, 95% CI = 0.88–0.98). Null associations were reported by estrogen or progesterone receptor status [31]. When a dose-response meta-analysis was conducted among 13 prospective studies [31], the association per one cup of coffee per day was nominally significant (OR for postmenopausal disease = 0.97, 95% CI = 0.95–1.00), which was consistent with the finding of the current MR study (OR = 0.90, 95% CI 0.79–1.02). In agreement, the World Cancer Research Fund Third Expert Report graded the evidence of coffee consumption and breast cancer risk as limited-no conclusion [79].

MR studies can be useful in nutritional epidemiology, as they are less susceptible to biases that are commonly present in traditional observational literature [80], namely exposure measurement error, residual confounding and reverse causation. MR estimates warrant a causal interpretation only if the assumptions of the instrumental variable approach hold. Though it is not possible to prove the validity of the assumptions in entirety, we performed several sensitivity analyses to detect potential violations and derived estimates that are potentially robust against violations of these assumptions. The majority of the sensitivity analyses supported our main analysis finding.

Several limitations should be considered when interpreting our findings. Our MR-analysis had appropriate statistical power to detect an OR of 0.89 per cup of coffee per day and risk of overall breast cancer. Observational studies have detected smaller associations of coffee consumption and breast cancer risk than this [31]. We were unable to rule out the possibility that coffee consumption may have a weaker association that we were not powered to detect. A weakness of using summary level data in two-sample MR is that stratified analyses by covariates of interest (e.g. smoking, alcohol, obesity, physical activity) are not possible which would have allowed us to investigate potential interactions between risk factors, but previous observational studies have in general not identified interactions with these variables [31]. Although we have involved clinically meaningful disease subtypes such as ER+ /− breast cancer, we could not examine breast cancer based on menopause status but 85% of breast cancer cases in our sample are postmenopausal. Although our genetic instruments are robustly associated with coffee consumption, coffee consumption itself is a heterogeneous phenotype that may potentially limit the generalizability of our findings on specific coffee type or preparation procedure. In addition, we are currently unable to isolate and classify genetic variants into caffeine and non-caffeine aspects of coffee given that the genetic loci heavily overlap, and future research into the biological mechanisms of the genetic instruments is warranted when more data becomes available; until then, a potential role of micronutrients attained through coffee consumption on reduction of breast cancer risk cannot be ruled out. Another limitation was that two-sample MR assumes linearity, so we could not evaluate potential existence of non-linear associations.

Conclusions

In summary, the results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak association.

Supporting information

S1 Fig

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S2 Fig

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S3 Fig

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S4 Fig

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S5 Fig

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S6 Fig

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S1 Table. Univariate mendelian randomization analyses of coffee consumption genetic variants and breast cancer.

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S2 Table. Characteristics of genetic variants associated with coffee consumption and breast cancer overall and subtypes.

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S3 Table. SNPs associated with secondary traits using Phenoscanner (http://www.phenoscanner.medschl.cam.ac.uk/upload/).

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Click here for additional data file. (10.9KB, xlsx)

Acknowledgments

Disclaimer: Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.

Abbreviations

BMI

body mass index

BCAC

the Breast Cancer Association Consortium

CI

Confidence interval

ER

estrogen receptor

GWA

Genome-wide association

IVW

Inverse variance weighted

MR

Mendelian randomization

OR

Odds ratio

SNP

single-nucleotide polymorphism

UKB

UK Biobank

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This work was supported by the World Cancer Research Fund International Regular Grant Programme (WCRF 2014/1180 to Konstantinos K. Tsilidis). RMM was supported by a Cancer Research UK (C18281/A19169) programme grant (the Integrative Cancer Epidemiology Programme) and is part of the Medical Research Council Integrative Epidemiology Unit at the University of Bristol supported by the Medical Research Council (MC_UU_12013/1, MC_UU_12013/2, and MC_UU_12013/3) and the University of Bristol. RMM is also supported by the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre which is funded by the National Institute for Health Research (NIHR) and is a partnership between University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Matteo Rota

6 Nov 2020

PONE-D-20-21709

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

PLOS ONE

Dear Dr. Ellingjord-Dale,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

First of all I want to apologize with the authors as the peer review process takes a long time. One of the reviewer who initially accepted to review the manuscript did not eventually do the review. The manuscript has now been reviewed by two external evaluable referees, who suggested minor revisions. I am agree to, this is a well written and as per state of the art conducted investigation. The reviewers’ comments are attached below. In addition to such comments, I would ask to the authors to specify all the parameters involved in the computation of the study power (page 7), including the type I error. It’s also not clear to the reader what parameters 0.89, 0.87 and 0.80 represent, i.e. regression coefficients? Or what else?

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[The

breast cancer genome-wide association analyses were supported by the Government of

Canada through Genome Canada and the Canadian Institutes of Health Research, the

‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome

Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065,

18

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: I think this is an interesting research with large genetic data in Europe.

#1 What kinds of subtypes did you assess? I understand that you investigated the relationship between genetically predicted coffee consumption and risk of breast cancer overall as well as breast cancer subtypes incorporating several MR methods to assess the impact of potential MR assumption violations. However, there were no information about subtypes you assessed in method. There are several subtypes in breast cancer, so please state which subtypes you assessed in method section.

#2 Have you considered the dose-response analysis, especially for the postmenopausal women? There is a dose-response meta-analysis regarding the association between coffee intake and breast cancer risk. (Nutrients. 2018 Jan 23;10(2):112) The result showed that consumption of four cups of coffee per day was associated with a 10% reduction in postmenopausal cancer risk. If you have done, please include it in the results.

#3 You mentioned that you have considered some potentially important confounders of coffee and breast cancer association (BMI, age at menarche, alcohol, smoking, and age at menopause). How did you choose these factors? There are more factors potentially associated with breast cancer, as parity, age at first birth, family history of breast cancer, and use of menopausal hormone therapy. (Biochim Biophys Acta. 2015 Aug;1856(1):73-85) Is it possible to consider these factors in the analysis?

Reviewer #2: Ellingjord-Dale, M. et al performed a 2-sample Mendelian randomization analysis, accompanied by comprehensive sensitivity analyses to investigate the association between coffee intake and risk of breast cancer. Authors observed null associations in both primary and sensitivity analyses. The manuscript is well written and easy to follow. Below are my suggestions/concerns that need to be addressed in the revision.

• Given substantial heterogeneity in ratio estimates between variants, it is misleading to present results from the fixed IVW analyses. I suggest to remove “IVW fixed” results from figure 1, 2 and 3.

• In the conclusion, authors state “…, but we cannot rule out existence of weak inverse association”. I agree with authors that there could be a weak association which was not picked up by the study, but I do not think it is appropriate to infer directionality of such association.

• In the discussion, authors should also acknowledge linearity assumption with their MR analyses. If there is a threshold adverse effect, this could have been masked by fitting a linear model.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Jan 19;16(1):e0236904. doi: 10.1371/journal.pone.0236904.r002

Author response to Decision Letter 0

13 Dec 2020

RESPONSES TO REVIEWERS -PONE-D-20-21709

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

Editor:

#1 I would ask to the authors to specify all the parameters involved in the computation of the study power (page 7), including the type I error. It’s also not clear to the reader what parameters 0.89, 0.87 and 0.80 represent, i.e. regression coefficients? Or what else?

Response: We have specified the parameters in the computation of the study power under the heading Statistical power page 7, including the type I error rate.

#2 Revised financial disclosure

Response: This work was supported by the World Cancer Research Fund International Regular Grant Programme (WCRF 2014/1180 to Konstantinos K. Tsilidis). RMM was supported by a Cancer Research UK (C18281/A19169) programme grant (the Integrative Cancer Epidemiology Programme) and is part of the Medical Research Council Integrative Epidemiology Unit at the University of Bristol supported by the Medical Research Council (MC_UU_12013/1, MC_UU_12013/2, and MC_UU_12013/3) and the University of Bristol. RMM is also supported by the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre which is funded by the National Institute for Health Research (NIHR) and is a partnership between University Hospitals Bristol NHS Foundation Trust and the University of Bristol.

We would be grateful if you could change the relevant online submission form on our behalf.

#3 Revised ethics statement

Response: Not applicable, as only publicly available summary association data were used.

Reviewer #1:

#1 What kinds of subtypes did you assess? I understand that you investigated the relationship between genetically predicted coffee consumption and risk of breast cancer overall as well as breast cancer subtypes incorporating several MR methods to assess the impact of potential MR assumption violations. However, there were no information about subtypes you assessed in method. There are several subtypes in breast cancer, so please state which subtypes you assessed in method section.

Response: Thank you. We have added more information about the estrogen receptor positive and negative breast cancer in the Methods section (Genetic data on breast cancer).

#2 Have you considered the dose-response analysis, especially for the postmenopausal women? There is a dose-response meta-analysis regarding the association between coffee intake and breast cancer risk. (Nutrients. 2018 Jan 23;10(2):112) The result showed that consumption of four cups of coffee per day was associated with a 10% reduction in postmenopausal cancer risk. If you have done, please include it in the results.

Response: We have already performed analyses per 1 cup per day of genetically predicted coffee consumption. We are not able to run analyses only on postmenopausal women since the available GWA studies on breast cancer presented information on overall breast cancer, but the majority (85%) of the included women were postmenopausal. We have acknowledged this issue in the limitation section of the Discussion.

#3 You mentioned that you have considered some potentially important confounders of coffee and breast cancer association (BMI, age at menarche, alcohol, smoking, and age at menopause). How did you choose these factors? There are more factors potentially associated with breast cancer, as parity, age at first birth, family history of breast cancer, and use of menopausal hormone therapy. (Biochim Biophys Acta. 2015 Aug;1856(1):73-85) Is it possible to consider these factors in the analysis?

Response: We ran sensitivity analyses excluding SNPs in our genetic instrument associated with risk factors for breast cancer to probe into potential horizontal pleiotropy. The reason for not excluding SNPs associated with parity, age at first birth or HRT use was that relevant GWA studies have not been performed or the SNPs in our instrument were not associated with these risk factors.

Reviewer #2:

#1 Given substantial heterogeneity in ratio estimates between variants, it is misleading to present results from the fixed IVW analyses. I suggest to remove “IVW fixed” results from figure 1, 2 and 3.

Response: We have removed the fixed IVW results from figures 1, 2 and 3.

#2 In the conclusion, authors state “…, but we cannot rule out existence of weak inverse association”. I agree with authors that there could be a weak association which was not picked up by the study, but I do not think it is appropriate to infer directionality of such association.

Response: We have removed the direction of the weak association both in the conclusion in the Abstract (page 3) and in the Conclusion of the manuscript (page 16). Thank you.

#3 In the discussion, authors should also acknowledge linearity assumption with their MR analyses. If there is a threshold adverse effect, this could have been masked by fitting a linear model.

Response: We have acknowledged the linearity assumption issue in the limitation section of the Discussion.

Attachment

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Decision Letter 1

Matteo Rota

4 Jan 2021

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

PONE-D-20-21709R1

Dear Dr. Ellingjord-Dale,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Matteo Rota, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

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Reviewer #2: Yes

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Reviewer #2: Yes

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Acceptance letter

Matteo Rota

8 Jan 2021

PONE-D-20-21709R1

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

Dear Dr. Ellingjord-Dale:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Matteo Rota

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig

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    S2 Fig

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    S3 Fig

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    S4 Fig

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    S5 Fig

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    S6 Fig

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    S1 Table. Univariate mendelian randomization analyses of coffee consumption genetic variants and breast cancer.

    (XLSX)

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    S2 Table. Characteristics of genetic variants associated with coffee consumption and breast cancer overall and subtypes.

    (XLSX)

    Click here for additional data file. (14.5KB, xlsx)
    S3 Table. SNPs associated with secondary traits using Phenoscanner (http://www.phenoscanner.medschl.cam.ac.uk/upload/).

    (XLSX)

    Click here for additional data file. (10.9KB, xlsx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (16.7KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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