Human environmental disease network: A computational model to assess toxicology of contaminants

Taboureau, Olivier; Audouze, Karine

doi:10.14573/altex.1607201

Cited by 20 publications

(17 citation statements)

References 27 publications

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“…In an exposome context, network science enables organization of high dimensional omics data for visualization and information summary purpose such as to identify hubs of correlated exposures and to interpret systemic biological changes that associate with multiple exposures and health effects [73][74][75][76]. Networks can be used to study the relationships between exposures based on their correlation in a population or based on their chemical or toxicological properties, and therefore reveal grouping of exposures [77,78]. This structure may be interpreted a posteriori through previous knowledge on the exposure sources (e.g., occupational exposure, consumer goods, diet), or in a biological context using KEGG pathways or mummichog for pathway enrichment analysis or adverse outcome pathway (AOPs).…”

Section: Incorporating Omics Into Exposome Researchmentioning

confidence: 99%

Applying the exposome concept in birth cohort research: a review of statistical approaches

et al. 2020

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The exposome represents the totality of life course environmental exposures (including lifestyle and other non-genetic factors), from the prenatal period onwards. This holistic concept of exposure provides a new framework to advance the understanding of complex and multifactorial diseases. Prospective pregnancy and birth cohort studies provide a unique opportunity for exposome research as they are able to capture, from prenatal life onwards, both the external (including lifestyle, chemical, social and wider community-level exposures) and the internal (including inflammation, metabolism, epigenetics, and gut microbiota) domains of the exposome. In this paper, we describe the steps required for applying an exposome approach, describe the main strengths and limitations of different statistical approaches and discuss their challenges, with the aim to provide guidance for methodological choices in the analysis of exposome data in birth cohort studies. An exposome approach implies selecting, pre-processing, describing and analyzing a large set of exposures. Several statistical methods are currently available to assess exposome-health associations, which differ in terms of research question that can be answered, of balance between sensitivity and false discovery proportion, and between computational complexity and simplicity (parsimony). Assessing the association between many exposures and health still raises many exposure assessment issues and statistical challenges. The exposome favors a holistic approach of environmental influences on health, which is likely to allow a more complete understanding of disease etiology.

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Section: Incorporating Omics Into Exposome Researchmentioning

confidence: 99%

Applying the exposome concept in birth cohort research: a review of statistical approaches

et al. 2020

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“…In recent years, across the globe, new diseases secondary to environmental exposures have been described, and it was also found that existing diseases have been modified by exposure to environmental chemicals or an environmental factor that has been found in their pathogenesis [1].…”

Section: Introductionmentioning

confidence: 99%

“…Contemporary imaging methods in the last 15 years started reporting alterations in different human systems such as the central nervous system [4], cardiovascular system [5] and pulmonary system [6] among others; evidence suggests the existence of human being environmental disease network [1].…”

Section: Introductionmentioning

confidence: 99%

Imaging methods used in the assessment of environmental disease networks: a brief review for clinicians

2020

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Background: Across the globe, diseases secondary to environmental exposures have been described, and it was also found that existing diseases have been modified by exposure to environmental chemicals or an environmental factor that has been found in their pathogenesis. The Institute of Medicine has shared a permanent concern related to the nations environmental health capacity since 1988.Main body: Contemporary imaging methods in the last 15 years started reporting alterations in different human systems such as the central nervous system, cardiovascular system and pulmonary system among others; evidence suggests the existence of a human environmental disease network. The primary anatomic regions, affected by environmental diseases, recently assessed with imaging methods include Brain (lead exposure, cerebral stroke, pesticide neurotoxicity), uses MRI, DTI, carotid ultrasonography and MRS; Lungs (smoke inhalation, organophosphates poisoning) are mainly assessed with radiography; Gastrointestinal system (chronic inflammatory bowel disease), recent studies have reported the use of aortic ultrasound; Heart (myocardial infarction), its link to environmental diseased has been proved with carotid ultrasound; and Arteries (artery hypertension), the impairment of aortic mechanical properties has been revealed with the use of aortic and brachial ultrasound. Conclusions:Environmental epidemiology has revealed that several organs and systems in the human body are targets of air pollutants. Current imaging methods that can assess the deleterious effects of pollutants includes a whole spectrum: radiography, US, CT and MRI. Future studies will help to reveal additional links among environmental disease networks.

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“…Currently, the human disease networks based on single biological related factors include: the genetic human disease network [6,7,8], the metabolic disease network [9], the microRNA-related disease network [10,11], the phenotypic disease network [12,13,14], the symptom disease network [15], the differential co-expression-based disease network [16,17], the environment-based disease network [18], the human pathway disease network [19], etc. The networks based on multiple biological related factors include: the disease network based on genetic and environmental factors [20], and the disease network constructed by combining genetic, morbidity and co-morbidity information from clinical outcomes, and metabolic pathways [21], etc.…”

Section: Introductionmentioning

confidence: 99%

Constructing and analyzing a disease network based on proteins

Liu

Huang

2019

E3S Web Conf.

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Protein is the specific executor of life activities, but there is no protein-based disease network and the current disease networks cannot show that a disease group share the same factors. We propose a method to construct a protein-based network by assigning disease pairs to different intervals according to their similarities and searching for disease groups in each interval. Statistical methods are used to analyze the disease network, and the result indicates that : in the case where a disease belongs to only one disease group, most diseases have their own protein characteristics, but the common protein of them is not obvious; the more diseases a protein is related to, the more likely the protein becomes common protein; diseases grouping at protein level in this study are different from traditional disease classification; there is a certain relationship between disease symptoms and underlying proteins, but not one-to-one correspondence.

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Human environmental disease network: A computational model to assess toxicology of contaminants

Cited by 20 publications

References 27 publications

Applying the exposome concept in birth cohort research: a review of statistical approaches

Applying the exposome concept in birth cohort research: a review of statistical approaches

Imaging methods used in the assessment of environmental disease networks: a brief review for clinicians

Constructing and analyzing a disease network based on proteins

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