Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures

Suvorov, Alexander; Salemme, Victoria; McGaunn, Joseph; Poluyanoff, Anthony; Amir, Saira

doi:10.1016/j.dib.2020.106398

Cited by 5 publications

(9 citation statements)

References 13 publications

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“…According to our hypothesis, specific immune response mechanisms may be synergistically affected by chemical exposures and SARS-CoV-2, resulting in increased severity of the disease. To test this hypothesis, we first used data on the sensitivity of mammalian genes to chemical exposures identified in our previous research [15,27] by overlaying transcriptomic datasets from many individual toxicological genomic studies. This allowed the identification of genes that respond most often to a variety of chemical exposures (Figure 1).…”

Section: Resultsmentioning

confidence: 99%

“…The unbiased approach for the identification of genes sensitive to chemical exposures was developed in our previous studies [15,27]. A database was created by extracting data on chemical-gene interactions from the Comparative Toxicogenomics Database (CTD) [39] (Figure 1A) using the following filtering criteria.…”

Section: Sensitivity Of Genes To Chemical Exposuresmentioning

confidence: 99%

“…Data Availability Statement: All data used in this study are available from published sources and public databases. Information on genes' sensitivity to chemical exposures was published previously [15,27]. Normalized gene expression (NGE) values for human immune cells are available from the Human Protein Atlas [40].…”

Section: Conflicts Of Interestmentioning

confidence: 99%

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Chemical Exposures Affect Innate Immune Response to SARS-CoV-2

Arowolo

Pobezinsky

Suvorov

2021

IJMS

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Severe outcomes of COVID-19 are associated with pathological response of the immune system to the SARS-CoV-2 infection. Emerging evidence suggests that an interaction may exist between COVID-19 pathogenesis and a broad range of xenobiotics, resulting in significant increases in death rates in highly exposed populations. Therefore, a better understanding of the molecular basis of the interaction between SARS-CoV-2 infection and chemical exposures may open opportunities for better preventive and therapeutic interventions. We attempted to gain mechanistic knowledge on the interaction between SARS-CoV-2 infection and chemical exposures using an in silico approach, where we identified genes and molecular pathways affected by both chemical exposures and SARS-CoV-2 in human immune cells (T-cells, B-cells, NK-cells, dendritic, and monocyte cells). Our findings demonstrate for the first time that overlapping molecular mechanisms affected by a broad range of chemical exposures and COVID-19 are linked to IFN type I/II signaling pathways and the process of antigen presentation. Based on our data, we also predict that exposures to various chemical compounds will predominantly impact the population of monocytes during the response against COVID-19.

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Section: Resultsmentioning

confidence: 99%

Section: Sensitivity Of Genes To Chemical Exposuresmentioning

confidence: 99%

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Chemical Exposures Affect Innate Immune Response to SARS-CoV-2

Arowolo

Pobezinsky

Suvorov

2021

IJMS

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“…Our previous studies developed an unbiased approach to identify genes sensitive to chemical exposures [4,69,70].…”

Section: Identification Of Genes Sensitive To Chemical Exposuresmentioning

confidence: 99%

“…For this analysis, the list of genes with their corresponding CGI numbers was analyzed against two independent openaccess databases for pathway curation: KEGG [71] and Reactome [72,73]. The details of this analysis are described elsewhere [70]. GSEA is an efficient method for the identification of changes in biological pathways as it captures cumulative changes of multiple members of a pathway [74].…”

Section: Identification Of Molecular Pathways Enriched With Chemicall...mentioning

confidence: 99%

Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures

Arowolo¹,

Salemme²,

Suvorov³

2022

Preprint

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Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multichemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer's disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.

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Underexplored Molecular Mechanisms of Toxicity

Arowolo,

Suvorov

2024

Preprint

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Social biases may concentrate attention of researchers on a small number of well-known molecules/mechanisms leaving others underexplored. In accordance with this view, central to mechanistic toxicology is a narrow range of molecular pathways that are assumed to be involved in significant part of responses to toxicity. It is unclear, however, if there are other molecular mechanisms which play important role in toxicity events but are overlooked by toxicology. To identify overlooked genes sensitive to chemical exposures we used publicly available databases. First, we used data on published chemical-gene interactions for 17,338 genes to estimate their sensitivity to chemical exposures. Next, we extracted data on publication numbers per gene for 19,243 human genes from Find My Understudied Genes database. Threshold were applied to both datasets using our algorithm to identify chemically sensitive and chemically insensitive genes and well-studied and underexplored genes. 1,110 underexplored genes highly sensitive to chemical exposures were used in GSEA and Shiny GO analyses to identify enriched biological categories. Metabolism of fatty acids, amino acids, and glucose were identified as underexplored molecular mechanisms sensitive to chemical exposures. These findings suggest that future effort is needed to uncover the role of xenobiotics in the current epidemics of metabolic diseases.

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Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures

Cited by 5 publications

References 13 publications

Chemical Exposures Affect Innate Immune Response to SARS-CoV-2

Chemical Exposures Affect Innate Immune Response to SARS-CoV-2

Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures

Underexplored Molecular Mechanisms of Toxicity

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