Evidence map›Paper›PMID 28068484›Full record

ReviewAnnual review of public health2017

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

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 and 3 more

Abstract readReview
In one paragraph

Review in Annual review of public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

60 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

13 authors.

Arjun K ManraiDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115; email: chirag_patel@hms.harvard.edu.
Yuxia CuiNational Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709; email: balshaw@niehs.nih.gov.
Pierre R BushelNational Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709; email: balshaw@niehs.nih.gov.
Molly HallCenter for Systems Genomics, The Pennsylvania State University, College Station, Pennsylvania 16802.
Spyros KarakitsiosEnvironmental Engineering Laboratory, Department of Chemical Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece.
Carolyn J MattinglyDepartment of Biological Sciences, College of Sciences, North Carolina State University, Raleigh, North Carolina 27695.
Marylyn RitchieCenter for Systems Genomics, The Pennsylvania State University, College Station, Pennsylvania 16802.
Charles SchmittRenaissance Computing Institute, Chapel Hill, North Carolina 27517.
Denis A SarigiannisEnvironmental Engineering Laboratory, Department of Chemical Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece.
Duncan C ThomasDivision of Biostatistics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90089-9011.
David WishartDepartments of Biological Sciences and Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.
David M BalshawNational Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709; email: balshaw@niehs.nih.gov.
Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115; email: chirag_patel@hms.harvard.edu.

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MYLES G COCKBURN · 1985 to 2026
$181.4M
Translational Research Support CoreP30ES007048 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROB S MCCONNELL · 1996 to 2026
$46.4M
Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David V Conti · 2016 to 2026
$25.5M
TrainingU54HG007963 · NHGRI · HARVARD MEDICAL SCHOOL · PI KOHANE, ISAAC S. · 2014 to 2018
$18.3M
Microarray and Genome InformaticsZIAES102345 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI BUSHEL, ROBERT · 2009 to 2021
$10.8M
The Comparative Toxicogenomics Database (CTD)R01ES014065 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI DAVIS, ALLAN PETER, MATTINGLY, CAROLYN J. · 2006 to 2021
$10.5M
Methods for Pathway Modeling with Application to FolateR01ES019876 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, DUNCAN C. · 2010 to 2014
$2.9M
Generation of a centralized and integrated resource for exposure dataR01ES019604 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI MATTINGLY, CAROLYN J. · 2011 to 2015
$1.3M
Data-driven identification of environmental factors in cardiovascular diseaseR00ES023504 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2016 to 2018
$728k
Increasing the power of GxE detection by using multi-locus genome-wide predictorsR21ES025052 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2015 to 2017
$434k
Data-driven identification of environmental factors in cardiovascular diseaseK99ES023504 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2014 to 2015
$245k
Novel methods to identify and replicate complex interactions in common diseaseF31HG008588 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI HALL, MOLLY ANN · 2015 to 2015
$9k
NCI NIH HHS P01 CA196569NCI NIH HHS P30 CA014089NHGRI NIH HHS F31 HG008588NHGRI NIH HHS U54 HG007963NIEHS NIH HHS K99 ES023504NIEHS NIH HHS P30 ES007048NIEHS NIH HHS R00 ES023504NIEHS NIH HHS R01 ES014065NIEHS NIH HHS R01 ES019604NIEHS NIH HHS R01 ES019876NIEHS NIH HHS R21 ES025052
6 · The paper itself

Abstract

The complexity of the human exposome-the totality of environmental exposures encountered from birth to death-motivates systematic, high-throughput approaches to discover new environmental determinants of disease. In this review, we describe the state of science in analyzing the human exposome and provide recommendations for the public health community to consider in dealing with analytic challenges of exposome-based biomedical research. We describe extant and novel analytic methods needed to associate the exposome with critical health outcomes and contextualize the data-centered challenges by drawing parallels to other research endeavors such as human genomics research. We discuss efforts for training scientists who can bridge public health, genomics, and biomedicine in informatics and statistics. If an exposome data ecosystem is brought to fruition, it will likely play a role as central as genomic science has had in molding the current and new generations of biomedical researchers, computational scientists, and public health research programs.

Indexed as

Biomedical ResearchComputational BiologyPublic HealthEcosystemEnvironmental ExposureHumansRisk Factorsbioinformaticsdata standardsenvironment-wide association studiesexposuresgenomics

Identifiers

PMID28068484
PMCPMC5774331

What OpenQuestion holds

Textmetadata
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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.