The Comparative Toxicogenomics Database (CTD)

Mattingly, Carolyn J.; Colby, Glenn T.; Forrest, Jeffrey Yi‐Lin; Boyer, James L.

doi:10.1289/txg.6028

Cited by 38 publications

(46 citation statements)

References 9 publications

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“…Genes were also weighted for their ability to tolerate mutations (w g ), calculated as the fractional rank of the average EA score of mutations seen in the gnomAD data (Lek et al, ). The weighted loss of function of each gene (w g *LOF g ) was used as a starting value for diffusion across the CTD gene‐disease network (Mattingly, Colby, Forrest, & Boyer, ). Diffusion scores were calculated for each disease (Lin et al, ) and a collective burden was calculated for each of the seven disease categories (normalized between 0 and 1).…”

Section: Methodsmentioning

confidence: 99%

Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge

et al. 2019

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The Critical Assessment of Genome Interpretation‐5 intellectual disability challenge asked to use computational methods to predict patient clinical phenotypes and the causal variant(s) based on an analysis of their gene panel sequence data. Sequence data for 74 genes associated with intellectual disability (ID) and/or autism spectrum disorders (ASD) from a cohort of 150 patients with a range of neurodevelopmental manifestations (i.e. ID, autism, epilepsy, microcephaly, macrocephaly, hypotonia, ataxia) have been made available for this challenge. For each patient, predictors had to report the causative variants and which of the seven phenotypes were present. Since neurodevelopmental disorders are characterized by strong comorbidity, tested individuals often present more than one pathological condition. Considering the overall clinical manifestation of each patient, the correct phenotype has been predicted by at least one group for 93 individuals (62%). ID and ASD were the best predicted among the seven phenotypic traits. Also, causative or potentially pathogenic variants were predicted correctly by at least one group. However, the prediction of the correct causative variant seems to be insufficient to predict the correct phenotype. In some cases, the correct prediction has been supported by rare or common variants in genes different from the causative one.

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Section: Methodsmentioning

confidence: 99%

Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge

et al. 2019

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“…LOF g was weighted for the ability of each gene to tolerate mutations (w g ), which we calculated as the percentile rank of the average EA score of mutations seen in the gnomAD data (Lek et al, ) for that gene. Then, the weighted LOF g scores were used as starting values of the genes in a diffusion process (Lin et al, ) across an interaction network of genes and diseases (Davis et al, ; Gutierrez‐Sacristan et al, 2015; Mattingly, Colby, Forrest, & Boyer, ; Stark et al, ; Szklarczyk et al, ). After diffusion, we measured the signal on each disease class or on specific symptoms of the clinical descriptions.…”

Section: Resultsmentioning

confidence: 99%

CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation

Katsonis

Lichtarge

2019

Human Mutation

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Many computational approaches estimate the effect of coding variants, but their predictions often disagree with each other. These contradictions confound users and raise questions regarding reliability. Performance assessments can indicate the expected accuracy for each method and highlight advantages and limitations. The Critical Assessment of Genome Interpretation (CAGI) community aims to organize objective and systematic assessments: They challenge predictors on unpublished experimental and clinical data and assign independent assessors to evaluate the submissions. We participated in CAGI experiments as predictors, using the Evolutionary Action (EA) method to estimate the fitness effect of coding mutations. EA is untrained, uses homology information, and relies on a formal equation: The fitness effect equals the functional sensitivity to residue changes multiplied by the magnitude of the substitution. In previous CAGI experiments (between 2011 and 2016), our submissions aimed to predict the protein activity of single mutants. In 2018 (CAGI5), we also submitted predictions regarding clinical associations, folding stability, and matching genomic data with phenotype. For all these diverse challenges, we used EA to predict the fitness effect of variants, adjusted to specifically address each question. Our submissions had consistently good performance, suggesting that EA predicts reliably the effects of genetic variants.

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“…The expression of seven genes was negatively associated with MNBN (none with MNMONO), namely SMC1A , LATS2 , TRIM13 , PDCD11 , CD28 , IL7R , and NIPBL . The expression of these particular genes has previously been shown to be affected by one or more genotoxic carcinogens in experimental models (Mattingly et al 2003). However, because detailed exposure data were absent, we could not further substantiate the involvement of specific chemicals.…”

Section: Discussionmentioning

confidence: 99%

Micronuclei in Cord Blood Lymphocytes and Associations with Biomarkers of Exposure to Carcinogens and Hormonally Active Factors, Gene Polymorphisms, and Gene Expression: The NewGeneris Cohort

Merlo

Agramunt

Anna

et al. 2014

Environ Health Perspect

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Background: Leukemia incidence has increased in recent decades among European children, suggesting that early-life environmental exposures play an important role in disease development.Objectives: We investigated the hypothesis that childhood susceptibility may increase as a result of in utero exposure to carcinogens and hormonally acting factors. Using cord blood samples from the NewGeneris cohort, we examined associations between a range of biomarkers of carcinogen exposure and hormonally acting factors with micronuclei (MN) frequency as a proxy measure of cancer risk. Associations with gene expression and genotype were also explored.Methods: DNA and protein adducts, gene expression profiles, circulating hormonally acting factors, and GWAS (genome-wide association study) data were investigated in relation to genomic damage measured by MN frequency in lymphocytes from 623 newborns enrolled between 2006 and 2010 across Europe.Results: Malondialdehyde DNA adducts (M1dG) were associated with increased MN frequency in binucleated lymphocytes (MNBN), and exposure to androgenic, estrogenic, and dioxin-like compounds was associated with MN frequency in mononucleated lymphocytes (MNMONO), although no monotonic exposure–outcome relationship was observed. Lower frequencies of MNBN were associated with a 1-unit increase expression of PDCD11, LATS2, TRIM13, CD28, SMC1A, IL7R, and NIPBL genes. Gene expression was significantly higher in association with the highest versus lowest category of bulky and M1dG–DNA adducts for five and six genes, respectively. Gene expression levels were significantly lower for 11 genes in association with the highest versus lowest category of plasma AR CALUX® (chemically activated luciferase expression for androgens) (8 genes), ERα CALUX® (for estrogens) (2 genes), and DR CALUX® (for dioxins). Several SNPs (single-nucleotide polymorphisms) on chromosome 11 near FOLH1 significantly modified associations between androgen activity and MNBN frequency. Polymorphisms in EPHX1/2 and CYP2E1 were associated with MNBN.Conclusion: We measured in utero exposure to selected environmental carcinogens and circulating hormonally acting factors and detected associations with MN frequency in newborns circulating T lymphocytes. The results highlight mechanisms that may contribute to carcinogen-induced leukemia and require further research.Citation: Merlo DF, Agramunt S, Anna L, Besselink H, Botsivali M, Brady NJ, Ceppi M, Chatzi L, Chen B, Decordier I, Farmer PB, Fleming S, Fontana V, Försti A, Fthenou E, Gallo F, Georgiadis P, Gmuender H, Godschalk RW, Granum B, Hardie LJ, Hemminki K, Hochstenbach K, Knudsen LE, Kogevinas M, Kovács K, Kyrtopoulos SA, Løvik M, Nielsen JK, Nygaard UC, Pedersen M, Rydberg P, Schoket B, Segerbäck D, Singh R, Sunyer J, Törnqvist M, van Loveren H, van Schooten FJ, Vande Loock K, von Stedingk H, Wright J, Kleinjans JC, Kirsch-Volders M, van Delft JHM, NewGeneris Consortium. 2014. Micronuclei in cord blood lymphocytes and associations with biomarkers of exposure to carcinogens and hormona...

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The Comparative Toxicogenomics Database (CTD)

Cited by 38 publications

References 9 publications

Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge

Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge

CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation

Micronuclei in Cord Blood Lymphocytes and Associations with Biomarkers of Exposure to Carcinogens and Hormonally Active Factors, Gene Polymorphisms, and Gene Expression: The NewGeneris Cohort

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