ReviewGenetic epidemiology2009
Ecogeographic genetic epidemiology.
Review in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis.Briefings in bioinformatics · 2022Article
- Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps.International journal of health geographics · 2016Review
- Genetic Geostatistical Framework for Spatial Analysis of Fine-Scale Genetic Heterogeneity in Modern Populations: Results from the KORA Study.International journal of genomics · 2015Article
- Genetics: A New Landscape for Medical Geography.Annals of the Association of American Geographers. Association of American Geographers · 2013Article
- Response to Condon et al. comments on "Cancer clusters in the USA: what do the last twenty years of state and federal investigations tell us?".Critical reviews in toxicology · 2013Article
- Analysis and visualization of H7 influenza using genomic, evolutionary and geographic information in a modular web service.Cladistics : the international journal of the Willi Hennig Society · 2012Article
- The spatial dimension in biological data mining.BioData mining · 2011Article
- Article
- Spatiotemporal dynamics in the early stages of the 2009 A/H1N1 influenza pandemic.PLoS currents · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial "clusters" of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic information systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.