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Stampfer, M.

Publications and source records attributed to Stampfer, M..

2 recordsLinked to original sources

Experimental analysis of exome-scale mutational signature of glycidamide, the reactive metabolite of acrylamide

Acrylamide, a probable human carcinogen, is ubiquitously present in the human environment, with sources including heated starchy foods, coffee and cigarette smoke. Humans are also exposed to acrylamide occupationally. Acrylamide is genotoxic, inducing gene mutations and chromosomal aberrations in various experimental settings. Covalent haemoglobin adducts were reported in acrylamide-exposed humans and DNA adducts in experimental systems. The carcinogenicity of acrylamide has been attributed to the effects of glycidamide, its reactive and mutagenic metabolite capable of inducing rodent tumors at various anatomical sites. In order to characterize the pre-mutagenic DNA lesions and global mutation spectra induced by acrylamide and glycidamide, we combined DNA-adduct and whole-exome sequencing analyses in an established exposure-clonal immortalization system based on mouse embryonic fibroblasts. Sequencing and computational analysis revealed a unique mutational signature of glycidamide, characterized by predominant T:A>A:T transversions, followed by T:A>C:G and C:G>A:T mutations exhibiting specific trinucleotide contexts and significant transcription strand bias. Computational interrogation of human cancer genome sequencing data indicated that a combination of the glycidamide signature and an experimental benzo[a]pyrene signature are nearly equivalent to the COSMIC tobacco-smoking related signature 4 in lung adenocarcinomas and squamous cell carcinomas. We found a more variable relationship between the glycidamide- and benzo[a]pyrene-signatures and COSMIC signature 4 in liver cancer, indicating more complex exposures in the liver. Our study demonstrates that the controlled experimental characterization of specific genetic damage associated with glycidamide exposure facilitates identifying corresponding patterns in cancer genome data, thereby underscoring how mutation signature laboratory experimentation contributes to the elucidation of cancer causation.\n\nA 40-word summaryInnovative experimental approaches identify a novel mutational signature of glycidamide, a metabolite of the probable human carcinogen acrylamide. The results may elucidate the cancer risks associated with exposure to acrylamide, commonly found in tobacco smoke, thermally processed foods and beverages.

genomics

A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts

The Nurses Health Study (NHS), Nurses Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)).\n\nWe observed the strongest BMI association for the FTO SNP rs55872725 ({beta}=0.45, p=3.48x10-22), and using a significance level of p=0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR=2.17, 95% CI: 1.79-2.63, p=2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.

epidemiology