Genetic GIScience: Toward a Place-Based Synthesis of the Genome, Exposome, and Behavome

Geoffrey Jacquez, Clive E Sabel, Chen Shi

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

The exposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic geographic information science (genetic GIScience), that is founded on the exposome, genome+, and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal, and behavioral determinants (the behavome). Genetic GIScience poses three key needs: first, a mathematical foundation for emergent theory; second, process-based models that bridge biological and geographic scales; third, biologically plausible estimates of space–time disease lags. Compartmental models are a possible solution; this article develops two models using pancreatic cancer as an exemplar. The first models carcinogenesis based on the cascade of mutations and cellular changes that lead to metastatic cancer. The second models cancer stages by diagnostic criteria. These provide empirical estimates of the distribution of latencies in cellular states and disease stages, and maps of the burden of yet to be diagnosed disease. This approach links our emerging knowledge of genomics to cancer progression at the cellular level, to individuals and their cancer stage at diagnosis, and to geographic distributions of cancer in extant populations. These methodological developments and exemplar provide the basis for a new synthesis in health geography: genetic GIScience.
Original languageEnglish
Pages (from-to)454-472
Number of pages19
JournalAnnals of the Association of American Geographers
Volume105
Issue number3
Publication statusPublished - May 2015

Keywords

  • cancer epidemiology
  • dynamical systems
  • genetic GIScience
  • health geography
  • space–time

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