European Journal of Epidemiology

, Volume 30, Issue 10, pp 1129–1135 | Cite as

Molecular pathological epidemiology gives clues to paradoxical findings

  • Reiko Nishihara
  • Tyler J. VanderWeele
  • Kenji Shibuya
  • Murray A. Mittleman
  • Molin Wang
  • Alison E. Field
  • Edward Giovannucci
  • Paul Lochhead
  • Shuji Ogino
PATHOLOGICAL EPIDEMIOLOGY

Abstract

A number of epidemiologic studies have described what appear to be paradoxical associations, where an incongruous relationship is observed between a certain well-established risk factor for disease incidence and favorable clinical outcome among patients with that disease. For example, the “obesity paradox” represents the association between obesity and better survival among patients with a certain disease such as coronary heart disease. Paradoxical observations cause vexing clinical and public health problems as they raise questions on causal relationships and hinder the development of effective interventions. Compelling evidence indicates that pathogenic processes encompass molecular alterations within cells and the microenvironment, influenced by various exogenous and endogenous exposures, and that interpersonal heterogeneity in molecular pathology and pathophysiology exists among patients with any given disease. In this article, we introduce methods of the emerging integrative interdisciplinary field of molecular pathological epidemiology (MPE), which is founded on the unique disease principle and disease continuum theory. We analyze and decipher apparent paradoxical findings, utilizing the MPE approach and available literature data on tumor somatic genetic and epigenetic characteristics. Through our analyses in colorectal cancer, renal cell carcinoma, and glioblastoma (malignant brain tumor), we can readily explain paradoxical associations between disease risk factors and better prognosis among disease patients. The MPE paradigm and approach can be applied to not only neoplasms but also various non-neoplastic diseases where there exists indisputable ubiquitous heterogeneity of pathogenesis and molecular pathology. The MPE paradigm including consideration of disease heterogeneity plays an essential role in advancements of precision medicine and public health.

Keywords

Bias Cardiovascular disease Molecular diagnostics Multifactorial diseases Personalized medicine 

Abbreviations

CIMP

CpG island methylator phenotype

MPE

Molecular pathological epidemiology

MSI

Microsatellite instability

RCC

Renal cell carcinoma

SNP

Single nucleotide polymorphism

References

  1. 1.
    Oreopoulos A, Padwal R, Kalantar-Zadeh K, Fonarow GC, Norris CM, McAlister FA. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J. 2008;156(1):13–22.CrossRefPubMedGoogle Scholar
  2. 2.
    Romero-Corral A, Montori VM, Somers VK, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies. Lancet. 2006;368(9536):666–78.CrossRefPubMedGoogle Scholar
  3. 3.
    Vemmos K, Ntaios G, Spengos K, et al. Association between obesity and mortality after acute first-ever stroke: the obesity-stroke paradox. Stroke. 2011;42(1):30–6.CrossRefPubMedGoogle Scholar
  4. 4.
    Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013;309(1):71–82.CrossRefPubMedGoogle Scholar
  5. 5.
    Ahima RS, Lazar MA. Physiology. The health risk of obesity—better metrics imperative. Science. 2013;341(6148):856–8.CrossRefPubMedGoogle Scholar
  6. 6.
    Lajous M, Bijon A, Fagherazzi G, et al. Body mass index, diabetes, and mortality in French women: explaining away a “paradox”. Epidemiology. 2014;25(1):10–4.PubMedCentralCrossRefPubMedGoogle Scholar
  7. 7.
    Nguyen US, Niu J, Choi HK, Zhang Y. Commentary: effect of obesity on mortality: comment on article by Banack and Kaufman. Epidemiology. 2014;25(1):2–3.PubMedCentralCrossRefPubMedGoogle Scholar
  8. 8.
    Flanders WD, Eldridge RC, McClellan W. A nearly unavoidable mechanism for collider bias with index-event studies. Epidemiology. 2014;25(5):762–4.CrossRefPubMedGoogle Scholar
  9. 9.
    Preston SH, Stokes A. Obesity paradox: conditioning on disease enhances biases in estimating the mortality risks of obesity. Epidemiology. 2014;25(3):454–61.PubMedCentralCrossRefPubMedGoogle Scholar
  10. 10.
    Banack HR, Kaufman JS. Does selection bias explain the obesity paradox among individuals with cardiovascular disease? Ann Epidemiol. 2015;25(5):342–9.CrossRefPubMedGoogle Scholar
  11. 11.
    Banack HR, Kaufman JS. The obesity paradox: understanding the effect of obesity on mortality among individuals with cardiovascular disease. Prev Med. 2014;62:96–102.CrossRefPubMedGoogle Scholar
  12. 12.
    VanderWeele TJ. Commentary: resolutions of the birthweight paradox: competing explanations and analytical insights. Int J Epidemiol. 2014;43(5):1368–73.PubMedCentralCrossRefPubMedGoogle Scholar
  13. 13.
    Ogino S, Giovannucci E. Commentary: lifestyle factors and colorectal cancer microsatellite instability—molecular pathological epidemiology science, based on unique tumour principle. Int J Epidemiol. 2012;41(4):1072–4.PubMedCentralCrossRefPubMedGoogle Scholar
  14. 14.
    Kuller LH, Bracken MB, Ogino S, Prentice RL, Tracy RP. The role of epidemiology in the era of molecular epidemiology and genomics: summary of the 2013 AJE-sponsored Society of Epidemiologic Research Symposium. Am J Epidemiol. 2013;178(9):1350–4.PubMedCentralCrossRefPubMedGoogle Scholar
  15. 15.
    Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–5.CrossRefPubMedGoogle Scholar
  16. 16.
    Ogino S, Nishihara R, VanderWeele TJ, et al. Molecular pathological epidemiology is essential in studying neoplastic and non-neoplastic diseases in the era of precision medicine. Epidemiology. (in press).Google Scholar
  17. 17.
    Ogino S, Lochhead P, Chan AT, et al. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol. 2013;26(4):465–84.PubMedCentralCrossRefPubMedGoogle Scholar
  18. 18.
    Ogino S, Stampfer M. Lifestyle factors and microsatellite instability in colorectal cancer: the evolving field of molecular pathological epidemiology. J Natl Cancer Inst. 2010;102(6):365–7.PubMedCentralCrossRefPubMedGoogle Scholar
  19. 19.
    Wang M, Kuchiba A, Ogino S. A meta-regression method for studying etiological heterogeneity across disease subtypes classified by multiple biomarkers. Am J Epidemiol. 2015;182(3):263–70.CrossRefPubMedGoogle Scholar
  20. 20.
    Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut. 2011;60(3):397–411.PubMedCentralCrossRefPubMedGoogle Scholar
  21. 21.
    Begg CB, Orlow I, Zabor EC, et al. Identifying etiologically distinct sub-types of cancer: a demonstration project involving breast cancer. Cancer Med. 2015;4(9):1432–9.PubMedCentralCrossRefPubMedGoogle Scholar
  22. 22.
    Abbenhardt C, Poole EM, Kulmacz RJ, et al. Phospholipase A2G1B polymorphisms and risk of colorectal neoplasia. Int J Mol Epidemiol Genet. 2013;4(3):140–9.PubMedCentralPubMedGoogle Scholar
  23. 23.
    Amirian ES, Petrosino JF, Ajami NJ, Liu Y, Mims MP, Scheurer ME. Potential role of gastrointestinal microbiota composition in prostate cancer risk. Infect Agents Cancer. 2013;8(1):42.PubMedCentralCrossRefPubMedGoogle Scholar
  24. 24.
    Araujo RF Jr, Lira GA, Guedes HG, et al. Lifestyle and family history influence cancer prognosis in Brazilian individuals. Pathol Res Pract. 2013;209(12):753–7.CrossRefPubMedGoogle Scholar
  25. 25.
    Bae JM, Kim JH, Cho NY, Kim TY, Kang GH. Prognostic implication of the CpG island methylator phenotype in colorectal cancers depends on tumour location. Br J Cancer. 2013;109(4):1004–12.PubMedCentralCrossRefPubMedGoogle Scholar
  26. 26.
    Bishehsari F, Mahdavinia M, Vacca M, Malekzadeh R, Mariani-Costantini R. Epidemiological transition of colorectal cancer in developing countries: environmental factors, molecular pathways, and opportunities for prevention. World J Gastroenterol. 2014;20(20):6055–72.PubMedCentralCrossRefPubMedGoogle Scholar
  27. 27.
    Brandstedt J, Wangefjord S, Nodin B, Eberhard J, Jirstrom K, Manjer J. Associations of hormone replacement therapy and oral contraceptives with risk of colorectal cancer defined by clinicopathological factors, beta-catenin alterations, expression of cyclin D1, p53, and microsatellite-instability. BMC Cancer. 2014;14:371.PubMedCentralCrossRefPubMedGoogle Scholar
  28. 28.
    Coppede F. The role of epigenetics in colorectal cancer. Expert Rev Gastroenterol Hepatol. 2014;8(8):935–48.CrossRefPubMedGoogle Scholar
  29. 29.
    Cross AJ, Moore SC, Boca S, et al. A prospective study of serum metabolites and colorectal cancer risk. Cancer. 2014;120(19):3049–57.CrossRefPubMedGoogle Scholar
  30. 30.
    Hagland HR, Soreide K. Cellular metabolism in colorectal carcinogenesis: influence of lifestyle, gut microbiome and metabolic pathways. Cancer Lett. 2015;356(2 Pt A):273–80.CrossRefPubMedGoogle Scholar
  31. 31.
    Hoffmeister M, Blaker H, Kloor M, et al. Body mass index and microsatellite instability in colorectal cancer: a population-based study. Cancer Epidemiol Biomarkers Prev. 2013;22(12):2303–11.CrossRefPubMedGoogle Scholar
  32. 32.
    Hughes LA, Khalid-de Bakker CA, Smits KM, et al. The CpG island methylator phenotype in colorectal cancer: progress and problems. Biochim Biophys Acta. 2012;1825(1):77–85.PubMedGoogle Scholar
  33. 33.
    Hughes LA, Simons CC, van den Brandt PA, et al. Body size, physical activity and risk of colorectal cancer with or without the CpG island methylator phenotype (CIMP). PLoS One. 2011;6(4):e18571.PubMedCentralCrossRefPubMedGoogle Scholar
  34. 34.
    Hughes LA, Williamson EJ, van Engeland M, et al. Body size and risk for colorectal cancers showing BRAF mutation or microsatellite instability: a pooled analysis. Int J Epidemiol. 2012;41(4):1060–72.CrossRefPubMedGoogle Scholar
  35. 35.
    Ku CS, Cooper DN, Wu M, et al. Gene discovery in familial cancer syndromes by exome sequencing: prospects for the elucidation of familial colorectal cancer type X. Mod Pathol. 2012;25(8):1055–68.CrossRefPubMedGoogle Scholar
  36. 36.
    Shaheen NJ. Editorial: what is behind the remarkable increase in esophageal adenocarcinoma? Am J Gastroenterol. 2014;109(3):345–7.CrossRefPubMedGoogle Scholar
  37. 37.
    Simons CC, van den Brandt PA, Stehouwer CD, van Engeland M, Weijenberg MP. Body size, physical activity, early-life energy restriction, and associations with methylated insulin-like growth factor-binding protein genes in colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2014;23(9):1852–62.CrossRefPubMedGoogle Scholar
  38. 38.
    Zaidi N, Lupien L, Kuemmerle NB, Kinlaw WB, Swinnen JV, Smans K. Lipogenesis and lipolysis: The pathways exploited by the cancer cells to acquire fatty acids. Prog Lipid Res. 2013;52(4):585–9.PubMedCentralCrossRefPubMedGoogle Scholar
  39. 39.
    Zhu Y, Yang SR, Wang PP, et al. Influence of pre-diagnostic cigarette smoking on colorectal cancer survival: overall and by tumour molecular phenotype. Br J Cancer. 2014;110(5):1359–66.PubMedCentralCrossRefPubMedGoogle Scholar
  40. 40.
    Weisenberger DJ, Levine AJ, Long TI, et al. Association of the colorectal CpG island methylator phenotype with molecular features, risk factors, and family history. Cancer Epidemiol Biomarkers Prev. 2015;24(3):512–9.CrossRefPubMedGoogle Scholar
  41. 41.
    Phipps AI, Limburg PJ, Baron JA, et al. Association between molecular subtypes of colorectal cancer and patient survival. Gastroenterology. 2015;148(1):77–87 e2.CrossRefPubMedGoogle Scholar
  42. 42.
    Curtin K, Slattery ML, Samowitz WS. CpG island methylation in colorectal cancer: past, present and future. Pathol Res Int. 2011;2011:902674.CrossRefGoogle Scholar
  43. 43.
    Campbell PT, Deka A, Briggs P, et al. Establishment of the cancer prevention study II nutrition cohort colorectal tissue repository. Cancer Epidemiol Biomarkers Prev. 2014;23(12):2694–702.CrossRefPubMedGoogle Scholar
  44. 44.
    Ng JM, Yu J. Promoter hypermethylation of tumour suppressor genes as potential biomarkers in colorectal cancer. Int J Mol Sci. 2015;16(2):2472–96.PubMedCentralCrossRefPubMedGoogle Scholar
  45. 45.
    Caiazza F, Ryan EJ, Doherty G, Winter DC, Sheahan K. Estrogen receptors and their implications in colorectal carcinogenesis. Front Oncol. 2015;5:19.PubMedCentralCrossRefPubMedGoogle Scholar
  46. 46.
    Campbell PT, Newton CC, Newcomb PA, et al. Association between body mass index and mortality for colorectal cancer survivors: overall and by tumor molecular phenotype. Cancer Epidemiol Biomarkers Prev. 2015;24(8):1229–38.CrossRefPubMedGoogle Scholar
  47. 47.
    Li P, Wu H, Zhang H, et al. Aspirin use after diagnosis but not prediagnosis improves established colorectal cancer survival: a meta-analysis. Gut. 2015;64(9):1419–25.CrossRefPubMedGoogle Scholar
  48. 48.
    Epplein M, Bostick RM, Mu L, Ogino S, Braithwaite D, Kanetsky PA. Challenges and opportunities in international molecular cancer prevention research: An ASPO Molecular Epidemiology and the Environment and International Cancer Prevention Interest Groups Report. Cancer Epidemiol Biomarkers Prev. 2014;23(11):2613–7.PubMedCentralCrossRefPubMedGoogle Scholar
  49. 49.
    Ogino S. Molecular pathological epidemiology (MPE): overview of its paradigm and wide applicability even without tumor tissue [abstract]. In: Proceedings of the twelfth annual AACR international conference on frontiers in cancer prevention research; 2013 Oct 27–30. National Harbor, MD: Cancer Prev Res (Phila); 2013;6:CN06-01.Google Scholar
  50. 50.
    Ogino S, Campbell PT, Nishihara R, et al. Proceedings of the second international molecular pathological epidemiology (MPE) meeting. Cancer Causes Control. 2015;26(7):959–72.CrossRefPubMedGoogle Scholar
  51. 51.
    Colussi D, Brandi G, Bazzoli F, Ricciardiello L. Molecular pathways involved in colorectal cancer: implications for disease behavior and prevention. Int J Mol Sci. 2013;14(8):16365–85.PubMedCentralCrossRefPubMedGoogle Scholar
  52. 52.
    Ogino S, Goel A. Molecular classification and correlates in colorectal cancer. J Mol Diagn. 2008;10(1):13–27.PubMedCentralCrossRefPubMedGoogle Scholar
  53. 53.
    Bardhan K, Liu K. Epigenetics and colorectal cancer pathogenesis. Cancers (Basel). 2013;5(2):676–713.CrossRefGoogle Scholar
  54. 54.
    Lochhead P, Chan AT, Nishihara R, et al. Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod Pathol. 2015;28(1):14–29.PubMedCentralCrossRefPubMedGoogle Scholar
  55. 55.
    Funkhouser WK Jr, Lubin IM, Monzon FA, et al. Relevance, pathogenesis, and testing algorithm for mismatch repair-defective colorectal carcinomas: a report of the association for molecular pathology. J Mol Diagn. 2012;14(2):91–103.CrossRefPubMedGoogle Scholar
  56. 56.
    Samowitz WS, Albertsen H, Sweeney C, et al. Association of smoking, CpG island methylator phenotype, and V600E BRAF mutations in colon cancer. J Natl Cancer Inst. 2006;98(23):1731–8.CrossRefPubMedGoogle Scholar
  57. 57.
    Limsui D, Vierkant RA, Tillmans LS, et al. Cigarette smoking and colorectal cancer risk by molecularly defined subtypes. J Natl Cancer Inst. 2010;102(14):1012–22.PubMedCentralCrossRefPubMedGoogle Scholar
  58. 58.
    Nishihara R, Morikawa T, Kuchiba A, et al. A prospective study of duration of smoking cessation and colorectal cancer risk by epigenetics-related tumor classification. Am J Epidemiol. 2013;178(1):84–100.PubMedCentralCrossRefPubMedGoogle Scholar
  59. 59.
    Nishihara R, Wu K, Lochhead P, et al. Long-term colorectal-cancer incidence and mortality after lower endoscopy. N Engl J Med. 2013;369(12):1095–105.CrossRefPubMedGoogle Scholar
  60. 60.
    Brixen LM, Bernstein IT, Bulow S, Ehrnrooth E. Survival of patients with Stage III colon cancer is improved in hereditary non-polyposis colorectal cancer compared with sporadic cases. A Danish registry based study. Colorectal Dis. 2013;15(7):816–23.CrossRefPubMedGoogle Scholar
  61. 61.
    Levin B. Why hereditary nonpolyposis colorectal carcinoma patients appear to have better survival than patients with sporadic colorectal carcinoma. Cancer. 1998;83(2):201–3.CrossRefPubMedGoogle Scholar
  62. 62.
    Peters U, Hutter CM, Hsu L, et al. Meta-analysis of new genome-wide association studies of colorectal cancer risk. Hum Genet. 2012;131(2):217–34.PubMedCentralCrossRefPubMedGoogle Scholar
  63. 63.
    Phipps AI, Newcomb PA, Garcia-Albeniz X, et al. Association between colorectal cancer susceptibility loci and survival time after diagnosis with colorectal cancer. Gastroenterology. 2012;143(1):51–54 e4.PubMedCentralCrossRefPubMedGoogle Scholar
  64. 64.
    Garcia-Albeniz X, Nan H, Valeri L, et al. Phenotypic and tumor molecular characterization of colorectal cancer in relation to a susceptibility SMAD7 variant associated with survival. Carcinogenesis. 2013;34(2):292–8.PubMedCentralCrossRefPubMedGoogle Scholar
  65. 65.
    Choi Y, Park B, Jeong BC, et al. Body mass index and survival in patients with renal cell carcinoma: a clinical-based cohort and meta-analysis. Int J Cancer. 2013;132(3):625–34.CrossRefPubMedGoogle Scholar
  66. 66.
    Hakimi AA, Furberg H, Zabor EC, et al. An epidemiologic and genomic investigation into the obesity paradox in renal cell carcinoma. J Natl Cancer Inst. 2013;105(24):1862–70.PubMedCentralCrossRefPubMedGoogle Scholar
  67. 67.
    Menendez JA, Lupu R. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat Rev Cancer. 2007;7(10):763–77.CrossRefPubMedGoogle Scholar
  68. 68.
    Esteller M, Garcia-Foncillas J, Andion E, et al. Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N Engl J Med. 2000;343(19):1350–4.CrossRefPubMedGoogle Scholar
  69. 69.
    McDonald KL, Rapkins RW, Olivier J, et al. The T genotype of the MGMT C > T (rs16906252) enhancer single-nucleotide polymorphism (SNP) is associated with promoter methylation and longer survival in glioblastoma patients. Eur J Cancer. 2013;49(2):360–8.CrossRefPubMedGoogle Scholar
  70. 70.
    Ogino S, Hazra A, Tranah GJ, et al. MGMT germline polymorphism is associated with somatic MGMT promoter methylation and gene silencing in colorectal cancer. Carcinogenesis. 2007;28(9):1985–90.CrossRefPubMedGoogle Scholar
  71. 71.
    Hawkins NJ, Lee JH, Wong JJ, Kwok CT, Ward RL, Hitchins MP. MGMT methylation is associated primarily with the germline C > T SNP (rs16906252) in colorectal cancer and normal colonic mucosa. Mod Pathol. 2009;22(12):1588–99.CrossRefPubMedGoogle Scholar
  72. 72.
    Gao Q, Tsoi KK, Hirai HW, et al. Serrated polyps and the risk of synchronous colorectal advanced neoplasia: a systematic review and meta-analysis. Am J Gastroenterol. 2015;110(4):501–9 (quiz 10).CrossRefPubMedGoogle Scholar
  73. 73.
    Field AE, Camargo CA Jr, Ogino S. The merits of subtyping obesity: one size does not fit all. JAMA. 2013;310(20):2147–8.CrossRefPubMedGoogle Scholar
  74. 74.
    Ikramuddin S, Livingston EH. New insights on bariatric surgery outcomes. JAMA. 2013;310(22):2401–2.CrossRefPubMedGoogle Scholar
  75. 75.
    van Winkel R. Aetiological stratification as a conceptual framework for gene-by-environment interaction research in psychiatry. Epidemiol Psychiatr Sci. 2015;24(1):6–11.CrossRefPubMedGoogle Scholar
  76. 76.
    Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2013;128(16):e240–319.CrossRefPubMedGoogle Scholar
  77. 77.
    Febbo PG, Ladanyi M, Aldape KD, et al. NCCN Task Force report: evaluating the clinical utility of tumor markers in oncology. J Natl Compr Cancer Netw. 2011;9(Suppl 5):S1–32 (quiz S3).Google Scholar
  78. 78.
    Reimers MS, Zeestraten EC, Kuppen PJ, Liefers GJ, van de Velde CJ. Biomarkers in precision therapy in colorectal cancer. Gastroenterol Rep (Oxf). 2013;1(3):166–83.CrossRefGoogle Scholar
  79. 79.
    Bayer R, Galea S. Public health in the precision-medicine era. N Engl J Med. 2015;373(6):499–501.CrossRefPubMedGoogle Scholar
  80. 80.
    Ogino S, King EE, Beck AH, Sherman ME, Milner DA, Giovannucci E. Interdisciplinary education to integrate pathology and epidemiology: towards molecular and population-level health science. Am J Epidemiol. 2012;176(8):659–67.PubMedCentralCrossRefPubMedGoogle Scholar
  81. 81.
    Kuller LH. Invited commentary: the 21st century epidemiologist—a need for different training? Am J Epidemiol. 2012;176(8):668–71.CrossRefPubMedGoogle Scholar
  82. 82.
    VanderWeele TJ, Knol MJ. Interactions and complexity: goals and limitations. Epidemiol Method. 2014;3(1):79–81.Google Scholar
  83. 83.
    Song M, Nishihara R, Wang M, et al. Plasma 25-hydroxyvitamin D and colorectal cancer risk according to tumour immunity status. Gut. 2015. doi:10.1136/gutjnl-2014-308852.
  84. 84.
    Ogino S, Beck AH, King EE, Sherman ME, Milner DA, Giovannucci E. Ogino et al. Respond to “The 21st century epidemiologist”. Am J Epidemiol. 2012;176(8):672–4.PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Reiko Nishihara
    • 1
    • 2
    • 3
  • Tyler J. VanderWeele
    • 4
    • 5
  • Kenji Shibuya
    • 3
  • Murray A. Mittleman
    • 4
    • 6
  • Molin Wang
    • 4
    • 5
    • 7
  • Alison E. Field
    • 4
    • 7
    • 8
    • 9
  • Edward Giovannucci
    • 1
    • 4
    • 7
  • Paul Lochhead
    • 10
  • Shuji Ogino
    • 2
    • 4
    • 11
  1. 1.Department of NutritionHarvard T.H. Chan School of Public HealthBostonUSA
  2. 2.Department of Medical OncologyDana-Farber Cancer Institute, Harvard Medical SchoolBostonUSA
  3. 3.Department of Global Health Policy, Graduate School of MedicineThe University of TokyoTokyoJapan
  4. 4.Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonUSA
  5. 5.Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonUSA
  6. 6.Cardiovascular Epidemiology Research Unit, Department of MedicineBeth Israel Deaconess Medical Center, Harvard Medical SchoolBostonUSA
  7. 7.Channing Division of Network Medicine, Department of MedicineBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  8. 8.Division of Adolescent MedicineBoston Children’s HospitalBostonUSA
  9. 9.Department of EpidemiologyBrown UniversityProvidenceUSA
  10. 10.Division of GastroenterologyMassachusetts General HospitalBostonUSA
  11. 11.Department of PathologyBrigham and Women’s Hospital, Boston, Harvard Medical SchoolBostonUSA

Personalised recommendations