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.[2] 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.[3] 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.[4] 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.[5] MPE research necessitates new conceptual framework and methodologies (epidemiological method) because MPE examines heterogeneity in an outcome variable.[6]

In this context, the field of MPE gradually formed. The term "molecular pathological epidemiology" was used by Shuji Ogino and Meir Stampfer in 2010.[7] Specific principles of MPE have developed since 2010. The MPE paradigm has been globally adopted and in widespread use,[8][9][10][11][12][13][14][15][16][17][18][19] and has been a subject in international conferences.[20][21][22] 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.[23] 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).[24] The MPE approach can be used as one of next steps from genome-wide association study (GWAS), which is termed “GWAS-MPE approach”.[25] 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.[26][27] As an alternative approach, potential risk variants identified by GWAS can be examined in combination with molecular pathology analysis on diseased tissues.[28][29][30][31] 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.[32] 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. Ogino S, Fuchs CS, Giovannucci E. How many molecular subtypes? Implications of the unique tumor principle in personalized medicine. Expert Rev Mol Diagn 2012;12:621-628.
  3. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  4. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  5. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  6. ↑ 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 Oct 15;176(8):672-4. doi: 10.1093/aje/kws229. Epub 2012 Aug 30. No abstract available. PMID 22935516
  7. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  8. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  9. ↑ Lua error in package.lua at line 80: module 'strict' not found.
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  20. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  21. ↑ 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.
  22. ↑ 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.
  23. ↑ Ogino S, Lochhead P, Chan AT, Nishihara R, Cho E, Wolpin BM, Meyerhardt JA, Meissner A, Schernhammer ES, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol. 2013 Apr;26(4):465-84. doi: 10.1038/modpathol.2012.214. Epub 2013 Jan 11. Review. PMID 23307060
  24. ↑ Lua error in package.lua at line 80: module 'strict' not found.
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  27. ↑ Lua error in package.lua at line 80: module 'strict' not found.
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  31. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  32. ↑ Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut. 2011 Mar;60(3):397-411. doi: 10.1136/gut.2010.217182. Epub 2010 Oct 29. Review. PMID 2103679
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