4.7 Review

Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis

Journal

JOURNAL OF GASTROENTEROLOGY
Volume 52, Issue 3, Pages 265-275

Publisher

SPRINGER JAPAN KK
DOI: 10.1007/s00535-016-1272-3

Keywords

Colorectal neoplasms; Drug therapy; Immunology; Microbiology; Personalized therapy

Funding

  1. U.S. National Institutes of Health (NIH) [R01 CA151993, R35 CA197735, K07 CA190673]
  2. Nodal Award from the Dana-Farber Harvard Cancer Center
  3. Friends of the Dana-Farber Cancer Institute
  4. Uehara Memorial Foundation
  5. Mochida Memorial Foundation for Medical and Pharmaceutical Research

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Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on the unique disease principle, the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.

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