Evidence map›Paper›PMID 26339073›Full record

ArticleAnnals of the Association of American Geographers. Association of American Geographers

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

Geoffrey M Jacquez, Clive E Sabel, Chen Shi

Open access · greenAbstract read
In one paragraph

Article in Annals of the Association of American Geographers. Association of American Geographers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 26 citations in OpenAlex.

  1. Review
  2. Allostatic Load and Exposure Histories of Disadvantage.International journal of environmental research and public health · 2021
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. How Sensors Might Help Define the External Exposome.International journal of environmental research and public health · 2017
    Review
  8. The Social Determinants of Health Core: Taking a Place-Based Approach.American journal of preventive medicine · 2017
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Geoffrey M JacquezDepartment of Geography, University at Buffalo-State University of New York ; BioMedware.
Clive E SabelSchool of Geographical Sciences, University of Bristol.
Chen ShiDepartment of Geography, University at Buffalo-State University of New York.
University at Buffalo, State University of New York · USUniversity of Bristol · GB

Funding

Cancer Clustering for Residential HistoriesR44CA117171 · NCI · BIOMEDWARE · PI JACQUEZ, GEOFFREY M. · 2007 to 2008
$750k
Model Transition Sensitivity AnalysisR44AI049007 · NIAID · BIOMEDWARE · PI JACQUEZ, GEOFFREY M. · 2003 to 2004
$748k
Exploratory evaluation of homomorphic cryptography for confidentiality protectionR21LM011132 · NLM · BIOMEDWARE · PI JACQUEZ, GEOFFREY M. · 2012 to 2013
$371k
NCI NIH HHS R44 CA117171NIAID NIH HHS R44 AI049007NLM NIH HHS R21 LM011132
6 · The paper itself

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 GISc) 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 GISc 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, to geographic distributions of cancer in extant populations. These methodological developments and exemplar provide the basis for a new synthesis in health geography: genetic geographic information science.

Indexed as

Cancer epidemiologydynamical systemsgenetic GISchealth geographyspace-time

Identifiers

PMID26339073
PMCPMC4554694
OpenAlexW2140753801

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.