Literature DB >> 25592584

Development of exposome correlation globes to map out environment-wide associations.

Chirag J Patel1, Arjun K Manrai.   

Abstract

The environment plays a major role in influencing diseases and health. The phenomenon of environmental exposure is complex and humans are not exposed to one or a handful factors but potentially hundreds factors throughout their lives. The exposome, the totality of exposures encountered from birth, is hypothesized to consist of multiple inter-dependencies, or correlations, between individual exposures. These correlations may reflect how individuals are exposed. Currently, we lack methods to comprehensively identify robust and replicated correlations between environmental exposures of the exposome. Further, we have not mapped how exposures associated with disease identified by environment-wide association studies (EWAS) are correlated with other exposures. To this end, we implement methods to describe a first "exposome globe", a comprehensive display of replicated correlations between individual exposures of the exposome. First, we describe overall characteristics of the dense correlations between exposures, showing that we are able to replicate 2,656 correlations between individual exposures of 81,937 total considered (3%). We document the correlation within and between broad a priori defined categories of exposures (e.g., pollutants and nutrient exposures). We also demonstrate utility of the exposome globe to contextualize exposures found through two EWASs in type 2 diabetes and all-cause mortality, such as exposure clusters putatively related to smoking behaviors and persistent pollutant exposure. The exposome globe construct is a useful tool for the display and communication of the complex relationships between exposure factors and between exposure factors related to disease status.

Entities:  

Mesh:

Year:  2015        PMID: 25592584      PMCID: PMC4299925     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  21 in total

1.  Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements.

Authors:  A J Butte; I S Kohane
Journal:  Pac Symp Biocomput       Date:  2000

2.  Epidemiology. Environment and disease risks.

Authors:  Stephen M Rappaport; Martyn T Smith
Journal:  Science       Date:  2010-10-22       Impact factor: 47.728

3.  Environment-wide association study (EWAS) for type 2 diabetes in the Marshfield Personalized Medicine Research Project Biobank.

Authors:  Molly A Hall; Scott M Dudek; Robert Goodloe; Dana C Crawford; Sarah A Pendergrass; Peggy Peissig; Murray Brilliant; Catherine A McCarty; Marylyn D Ritchie
Journal:  Pac Symp Biocomput       Date:  2014

4.  Studying the elusive environment in large scale.

Authors:  Chirag J Patel; John P A Ioannidis
Journal:  JAMA       Date:  2014-06-04       Impact factor: 56.272

5.  Systematic evaluation of environmental and behavioural factors associated with all-cause mortality in the United States national health and nutrition examination survey.

Authors:  Chirag J Patel; David H Rehkopf; John T Leppert; Walter M Bortz; Mark R Cullen; Glenn M Chertow; John Pa Ioannidis
Journal:  Int J Epidemiol       Date:  2013-12-16       Impact factor: 7.196

6.  Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits.

Authors:  Jian Yang; Teresa Ferreira; Andrew P Morris; Sarah E Medland; Pamela A F Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael N Weedon; Ruth J Loos; Timothy M Frayling; Mark I McCarthy; Joel N Hirschhorn; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2012-03-18       Impact factor: 38.330

7.  Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease.

Authors:  Chirag J Patel; Rong Chen; Atul J Butte
Journal:  Bioinformatics       Date:  2012-06-15       Impact factor: 6.937

8.  Environmental risk score as a new tool to examine multi-pollutants in epidemiologic research: an example from the NHANES study using serum lipid levels.

Authors:  Sung Kyun Park; Yebin Tao; John D Meeker; Siobán D Harlow; Bhramar Mukherjee
Journal:  PLoS One       Date:  2014-06-05       Impact factor: 3.240

9.  Unraveling the health effects of environmental mixtures: an NIEHS priority.

Authors:  Danielle J Carlin; Cynthia V Rider; Rick Woychik; Linda S Birnbaum
Journal:  Environ Health Perspect       Date:  2013-01       Impact factor: 9.031

10.  Estimating genomic coexpression networks using first-order conditional independence.

Authors:  Paul M Magwene; Junhyong Kim
Journal:  Genome Biol       Date:  2004-11-30       Impact factor: 13.583

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  31 in total

Review 1.  Unravelling the human genome-phenome relationship using phenome-wide association studies.

Authors:  William S Bush; Matthew T Oetjens; Dana C Crawford
Journal:  Nat Rev Genet       Date:  2016-02-15       Impact factor: 53.242

Review 2.  Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.

Authors:  Chirag J Patel; Jacqueline Kerr; Duncan C Thomas; Bhramar Mukherjee; Beate Ritz; Nilanjan Chatterjee; Marta Jankowska; Juliette Madan; Margaret R Karagas; Kimberly A McAllister; Leah E Mechanic; M Daniele Fallin; Christine Ladd-Acosta; Ian A Blair; Susan L Teitelbaum; Christopher I Amos
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-07-14       Impact factor: 4.254

Review 3.  The Exposome Research Paradigm: an Opportunity to Understand the Environmental Basis for Human Health and Disease.

Authors:  Germaine M Buck Louis; Melissa M Smarr; Chirag J Patel
Journal:  Curr Environ Health Rep       Date:  2017-03

4.  Demographic Inequities in Health Outcomes and Air Pollution Exposure in the Atlanta Area and its Relationship to Urban Infrastructure.

Authors:  Joseph L Servadio; Abiola S Lawal; Tate Davis; Josephine Bates; Armistead G Russell; Anu Ramaswami; Matteo Convertino; Nisha Botchwey
Journal:  J Urban Health       Date:  2019-04       Impact factor: 3.671

5.  Using exposomics to assess cumulative risks and promote health.

Authors:  Martyn T Smith; Rosemarie de la Rosa; Sarah I Daniels
Journal:  Environ Mol Mutagen       Date:  2015-10-17       Impact factor: 3.216

Review 6.  Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health.

Authors:  Arjun K Manrai; Yuxia Cui; Pierre R Bushel; Molly Hall; Spyros Karakitsios; Carolyn J Mattingly; Marylyn Ritchie; Charles Schmitt; Denis A Sarigiannis; Duncan C Thomas; David Wishart; David M Balshaw; Chirag J Patel
Journal:  Annu Rev Public Health       Date:  2016-12-23       Impact factor: 21.981

7.  Exposure to multiple chemicals in a cohort of reproductive-aged Danish women.

Authors:  Anna Rosofsky; Patricia Janulewicz; Kristina A Thayer; Michael McClean; Lauren A Wise; Antonia M Calafat; Ellen M Mikkelsen; Kyla W Taylor; Elizabeth E Hatch
Journal:  Environ Res       Date:  2016-12-29       Impact factor: 6.498

8.  Perspective: Limiting Dependence on Nonrandomized Studies and Improving Randomized Trials in Human Nutrition Research: Why and How.

Authors:  John F Trepanowski; John P A Ioannidis
Journal:  Adv Nutr       Date:  2018-07-01       Impact factor: 8.701

Review 9.  Assessing health risks from multiple environmental stressors: Moving from G×E to I×E.

Authors:  Cliona M McHale; Gwendolyn Osborne; Rachel Morello-Frosch; Andrew G Salmon; Martha S Sandy; Gina Solomon; Luoping Zhang; Martyn T Smith; Lauren Zeise
Journal:  Mutat Res Rev Mutat Res       Date:  2017-11-24       Impact factor: 5.657

10.  Field-wide meta-analyses of observational associations can map selective availability of risk factors and the impact of model specifications.

Authors:  Stylianos Serghiou; Chirag J Patel; Yan Yu Tan; Peter Koay; John P A Ioannidis
Journal:  J Clin Epidemiol       Date:  2015-09-28       Impact factor: 6.437

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