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Friday, May 8, 2009
Northwest Hall (Chicago Hilton)
10:00 AM
Background:
Although epidemiologists and toxicologists have started to investigate several chemicals as potential autism risk factors, it is still unclear what chemicals should be studied in this regard. A more objective and comprehensive approach to screening and prioritizing chemicals would be useful in designing future studies. This work should be informed by the most recent findings in the genetics of autism.
Objectives:
This analysis was an effort to find and demonstrate a way to cast a relatively wide net to identify chemicals that might merit further investigation as potential risk factors in autism, drawing upon the full range of genetic findings and a wide range of literature on gene-chemical interactions.
Methods:
The Comparative Toxicogenomics Database (CTD, http://ctd.mdibl.org) and AutDB (http://www.mindspec.org) were selected as relatively comprehensive, powerful tools for this type of analysis. The AutDB was used to identify 142 genes (as of late 2008) studied in autism, of which 122 genes were found to have reported chemical interaction data in the CTD. These interactions often consist of observed changes in gene expression in rodents exposed to various levels of the studied chemical substance. The chemical-gene interactions, GO terms, and pathways associated with these genes in the CTD were analyzed, and chemicals were manually classified as xenobiotics, medications, nutrients, and endogenous substances. Chemicals were prioritized based on number of reported interactions.
Results:
The genes MET, PTEN, ADRB2, and TH each had more than 30 interacting chemicals identified in the CTD, and 120 chemicals were reported to interact with PON1. Other genes, such as MECP2, TSC2, RELN, UBE3A, and GABRB3, showed interaction reports for only 4-14 chemicals each in the CTD. For many genes, such as EN2, SHANK3, FMR1, NLGN3, and NRXN1, the CTD contains interaction reports for only 1-2 chemicals so far.
Over 600 chemical substances were identified as interacting with any of the 122 autism candidate genes, of which 498 had unique CAS numbers.
Xenobiotics (or closely related substances) identified as interacting with autism candidate genes included the following (# of genes in parentheses): Carbon Tetrachloride (33), tert-Butylhydroperoxide (19), sodium arsenite (17), Lipopolysaccharides (11), Paraquat (10), nickel sulfate (9), Hydrogen Peroxide (9), arsenic trioxide (8), Benzene (7), Benzo(a)pyrene (7), Ethanol (7), Tobacco Smoke Pollution (4), Arsenic (4), Chlorpyrifos (4), Tetrachlorodibenzodioxin (4), and bisphenol A (4). Other chemicals previously implicated in autism or related conditions are also identified by this analysis, such as mercury compounds, lead, cocaine, fipronil, endosulfan, and phthalates.
Top substances related to dietary nutrients: Pirinixic acid (27 genes), Zinc, Resveratrol, Flavonoids, and Dietary Fats.
Top medications: Acetaminophen (49 genes), Tamoxifen, Diethylstilbestrol, Valproic Acid, and Celecoxib.
Top endogenous (or closely related) substances interacting with numerous autism candidate genes: Progesterone (37 genes), Estradiol, Ethinyl Estradiol, Corticosterone, and Thyroxine.
Conclusions:
As bioinformatics databases grow, they can inform prioritization of candidate environmental risk factors.
Although epidemiologists and toxicologists have started to investigate several chemicals as potential autism risk factors, it is still unclear what chemicals should be studied in this regard. A more objective and comprehensive approach to screening and prioritizing chemicals would be useful in designing future studies. This work should be informed by the most recent findings in the genetics of autism.
Objectives:
This analysis was an effort to find and demonstrate a way to cast a relatively wide net to identify chemicals that might merit further investigation as potential risk factors in autism, drawing upon the full range of genetic findings and a wide range of literature on gene-chemical interactions.
Methods:
The Comparative Toxicogenomics Database (CTD, http://ctd.mdibl.org) and AutDB (http://www.mindspec.org) were selected as relatively comprehensive, powerful tools for this type of analysis. The AutDB was used to identify 142 genes (as of late 2008) studied in autism, of which 122 genes were found to have reported chemical interaction data in the CTD. These interactions often consist of observed changes in gene expression in rodents exposed to various levels of the studied chemical substance. The chemical-gene interactions, GO terms, and pathways associated with these genes in the CTD were analyzed, and chemicals were manually classified as xenobiotics, medications, nutrients, and endogenous substances. Chemicals were prioritized based on number of reported interactions.
Results:
The genes MET, PTEN, ADRB2, and TH each had more than 30 interacting chemicals identified in the CTD, and 120 chemicals were reported to interact with PON1. Other genes, such as MECP2, TSC2, RELN, UBE3A, and GABRB3, showed interaction reports for only 4-14 chemicals each in the CTD. For many genes, such as EN2, SHANK3, FMR1, NLGN3, and NRXN1, the CTD contains interaction reports for only 1-2 chemicals so far.
Over 600 chemical substances were identified as interacting with any of the 122 autism candidate genes, of which 498 had unique CAS numbers.
Xenobiotics (or closely related substances) identified as interacting with autism candidate genes included the following (# of genes in parentheses): Carbon Tetrachloride (33), tert-Butylhydroperoxide (19), sodium arsenite (17), Lipopolysaccharides (11), Paraquat (10), nickel sulfate (9), Hydrogen Peroxide (9), arsenic trioxide (8), Benzene (7), Benzo(a)pyrene (7), Ethanol (7), Tobacco Smoke Pollution (4), Arsenic (4), Chlorpyrifos (4), Tetrachlorodibenzodioxin (4), and bisphenol A (4). Other chemicals previously implicated in autism or related conditions are also identified by this analysis, such as mercury compounds, lead, cocaine, fipronil, endosulfan, and phthalates.
Top substances related to dietary nutrients: Pirinixic acid (27 genes), Zinc, Resveratrol, Flavonoids, and Dietary Fats.
Top medications: Acetaminophen (49 genes), Tamoxifen, Diethylstilbestrol, Valproic Acid, and Celecoxib.
Top endogenous (or closely related) substances interacting with numerous autism candidate genes: Progesterone (37 genes), Estradiol, Ethinyl Estradiol, Corticosterone, and Thyroxine.
Conclusions:
As bioinformatics databases grow, they can inform prioritization of candidate environmental risk factors.