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Eur J Epidemiol. 2015 Oct;30(10):1129-35. doi: 10.1007/s10654-015-0088-4. Epub 2015 Oct 7.

Molecular pathological epidemiology gives clues to paradoxical findings.

Author information

1
Department of Nutrition, Harvard T.H. Chan School of Public Health, 655 Huntington Ave., Boston, MA, 02115, USA. rnishiha@hsph.harvard.edu.
2
Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Ave., Boston, MA, 02215, USA. rnishiha@hsph.harvard.edu.
3
Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan. rnishiha@hsph.harvard.edu.
4
Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02115, USA.
5
Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02115, USA.
6
Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan.
7
Cardiovascular Epidemiology Research Unit, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, 375 Longwood Ave., Boston, MA, USA.
8
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave., Boston, MA, 02115, USA.
9
Division of Adolescent Medicine, Boston Children's Hospital, 300 Longwood Ave., Boston, MA, 02115, USA.
10
Department of Epidemiology, Brown University, 121 South Main Street, Providence, RI, 02912, USA.
11
Department of Nutrition, Harvard T.H. Chan School of Public Health, 655 Huntington Ave., Boston, MA, 02115, USA.
12
Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA.
13
Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Ave., Boston, MA, 02215, USA. shuji_ogino@dfci.harvard.edu.
14
Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02115, USA. shuji_ogino@dfci.harvard.edu.
15
Department of Pathology, Brigham and Women's Hospital, Boston, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA. shuji_ogino@dfci.harvard.edu.

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

PMID:
26445996
PMCID:
PMC4639412
DOI:
10.1007/s10654-015-0088-4
[Indexed for MEDLINE]
Free PMC Article

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