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Molecular pathological epidemiology

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Molecular pathological epidemiology (abbreviated as MPE, also called "molecular pathologic epidemiology") is a specific discipline of epidemiology, and also that of pathology. It is defined as "epidemiology of molecular pathology and heterogeneity of disease". [1] MPE represents an integrative interdisciplinary (transdisciplinary or multidisciplinary) science of molecular pathology and epidemiology. Pathology and epidemiology share the same goal of elucidating etiology of disease, and integrative MPE approach aims to achieve this goal simultaneously at molecular, individual, and population levels. Researchers who conduct MPE research are referred to as molecular pathological epidemiologist (or molecular pathologic epidemiologist). Typically, MPE refers to research which utilizes tissue pathology resource and data within existing epidemiology studies. MPE started as analysis of disease patients with data of risk factors (such as smoking) and molecular pathologic findings (such as KRAS oncogene mutation in lung cancer). As advancement of technology and molecular pathology has become rapid, application of molecular pathology to epidemiology is increasingly widespread.

Accumulating evidence including data from The Cancer Genome Atlas projects indicates that disease evolution represents inherently heterogeneous process. Essentially, each individual has a unique disease process different from any other individual (“the unique disease principle”), considering uniqueness of the exposome and its unique influence on molecular pathologic process in each individual.[2] In clinical medicine, this concept has been adopted along with the terms of precision medicine and personalized medicine. Studies to examine the relationship between an exposure and molecular pathologic signature of disease (particularly, cancer) became increasingly common throughout the 1990s and early 2000s.[3] However, the use of molecular pathology in epidemiology posed unique challenges including lack of standardized methodologies and guidelines as well as paucity of interdisciplinary experts and training programs.[4] MPE research necessitates new conceptual framework and methodologies (epidemiological method) because MPE examines heterogeneity in an outcome variable.

In this context, the field of MPE gradually formed. The term "molecular pathological epidemiology" was used by Shuji Ogino and Meir Stampfer in 2010.[5] Specific principles of MPE have developed since 2010. The MPE paradigm has been globally adopted and in widespread use,[6][7][8][9][10][11][12][13][14][15][16][17] and has been a subject in international conferences.[18][19] [20] Molecular epidemiology broadly encompasses MPE and conventional-type molecular epidemiology with the use of traditional disease designation system.

In MPE, investigators dissect interrelationships between exposures (e.g., environmental, dietary, lifestyle and genetic factors); alterations in cellular or extracellular molecules (disease molecular signatures); and evolution and progression of disease. As disease molecular signatures, investigators can analyze genome, methylome, epigenome, metabolome, transcriptome, proteome, microbiome, immunity, and interactome. In particular, a putative risk factor can be linked to specific molecular signatures of a disease to support a causal association. Thus, MPE can advance the area of causal inference. The MPE research enables identification of a new biomarker for potential clinical utility, using a large-scale population based data (e.g., PIK3CA mutation in colorectal cancer to select patients for aspirin therapy).[21] The MPE approach can be used as one of next steps from genome-wide association study (GWAS), which is termed “GWAS-MPE approach”.[22] Detailed disease endpoint phenotyping can be conducted by means of molecular pathology or surrogate histopathology or immunohistochemistry analysis of diseased tissues and cells within GWAS.[23][24] As an alternative approach, potential risk variants identified by GWAS can be examined in combination with molecular pathology analysis on diseased tissues.[25][26][27][28] This GWAS-MPE approach can give not only more precise effect estimates, even larger effects, for specific molecular subtypes of the disease, but also insights into pathogenesis by linking genetic variants to molecular pathologic signatures of disease. Since molecular diagnostics is becoming routine clinical practice in the era of precision medicine, routine molecular pathology data can be utilized in a wide spectrum of epidemiologic research.

See also

References

  1. ^ Ogino S, Lochhead P, Giovannucci E, Meyerhardt JA, Fuchs CS, Chan AT. Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology. Oncogene 2014;33:2949-2955.
  2. ^ Ogino S, Lochhead P, Chan AT, Nishihara R, Cho E, Wolpin BM, Meyerhardt JA, Meissner A, Schernhammer ES, Fuchs CS, Giovannucci E (April 2013). "Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease". Modern Pathology. 26 (4): 465–84. doi:10.1038/modpathol.2012.214. PMC 3637979. PMID 23307060.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  3. ^ Slattery ML (October 2002). "The science and art of molecular epidemiology". Journal of Epidemiology and Community Health (Comment). 56 (10): 728–9. doi:10.1136/jech.56.10.728. PMC 1732025. PMID 12239192.
  4. ^ Sherman ME, Howatt W, Blows FM, Pharoah P, Hewitt SM, Garcia-Closas M (April 2010). "Molecular pathology in epidemiologic studies: a primer on key considerations". Cancer Epidemiology, Biomarkers & Prevention. 19 (4): 966–72. doi:10.1158/1055-9965.EPI-10-0056. PMC 2852464. PMID 20332257.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  5. ^ Ogino S, Stampfer M (March 2010). "Lifestyle factors and microsatellite instability in colorectal cancer: the evolving field of molecular pathological epidemiology". Journal of the National Cancer Institute (Comment). 102 (6): 365–7. doi:10.1093/jnci/djq031. PMC 2841039. PMID 20208016.
  6. ^ Curtin K, Slattery ML, Samowitz WS (2011). "CpG island methylation in colorectal cancer: past, present and future". Pathology Research International. 2011: 902674. doi:10.4061/2011/902674. PMC 3090226. PMID 21559209.{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: unflagged free DOI (link)
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  18. ^ Kuller LH, Bracken MB, Ogino S, Prentice RL, Tracy RP (November 2013). "The role of epidemiology in the era of molecular epidemiology and genomics: Summary of the 2013 AJE-sponsored Society of Epidemiologic Research Symposium". American Journal of Epidemiology. 178 (9): 1350–4. doi:10.1093/aje/kwt239. PMID 24105654.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  19. ^ Epplein M, Bostick RM, Mu L, Ogino S, Braithwaite D, Kanetsky PA. Challenges and opportunities in international molecular cancer prevention research: A report from the ASPO Molecular Epidemiology and the Environment and International Issues in Cancer Interest Group. Cancer Epidemiol Biomarkers Prev 2014;23:2613-2617.
  20. ^ Ogino S, Campbell PT, Nishihara R, Phipps AI, Beck AH, Sherman ME, Chan AT, Troester MA, Bass AJ, Fitzgerald KC, Irizarry RA, Kelsey KT, Nan H, Peters U, Poole EM, Qian ZR, Tamimi RM, Tchetgen Tchetgen EJ, Tworoger SS, Zhang X, Giovannucci EL, van den Brandt PA, Rosner BA, Wang M, Chatterjee N, Begg CB. Proceedings of The Second International Molecular Pathological Epidemiology (MPE) Meeting. Cancer Causes Control. 2015 May 9. PMID 25956270.
  21. ^ Ogino S, Lochhead P, Giovannucci E, Meyerhardt JA, Fuchs CS, Chan AT (June 2014). "Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology". Oncogene. 33 (23): 2949–55. doi:10.1038/onc.2013.244. PMID 23792451.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  22. ^ Ogino S, Chan AT, Fuchs CS, Giovannucci E (March 2011). "Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field". Gut. 60 (3): 397–411. doi:10.1136/gut.2010.217182. PMC 3040598. PMID 21036793.{{cite journal}}: CS1 maint: multiple names: authors list (link)
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