Epigenome-wide association study for transgenerational disease sperm epimutation biomarkers following ancestral exposure to jet fuel hydrocarbons

Maamar, Millissia Ben; Nilsson, Eric; Thorson, Jennifer L. M.; Beck, Daniel; Skinner, Michael K.

doi:10.1016/j.reprotox.2020.08.010

Cited by 8 publications

(15 citation statements)

References 71 publications

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“…A 1 kb DMR size was used instead of 100 bp to improve the bioinformatics, as described in the Methods. The updated histopathology procedure used three histologists blinded to the slide identity and the counting of larger tissue section regions than used previously 17 , 18 , 26 , 27 , 31 – 33 . The analysis of larger regions allowed more efficient detection of various abnormal histology and pathology.…”

Section: Resultsmentioning

confidence: 99%

“…Recently, a number of epigenome-wide association studies (EWAS) have been shown to identify epigenetic alterations (i.e., epimutations) associated with diseases. Sperm epimutations involved in the transgenerational inheritance of specific pathologies have been identified 21 – 27 . Transgenerational sperm epimutations associated with kidney, prostate, puberty, testis, obesity, and multiple pathologies have been identified for a variety of environmental toxicants including dioxin 21 , plastics 22 , pesticides 23 , glyphosate 24 , methoxychlor 25 , atrazine 26 , and jet fuel 27 in animal studies.…”

Section: Introductionmentioning

confidence: 99%

“…Sperm epimutations involved in the transgenerational inheritance of specific pathologies have been identified 21 – 27 . Transgenerational sperm epimutations associated with kidney, prostate, puberty, testis, obesity, and multiple pathologies have been identified for a variety of environmental toxicants including dioxin 21 , plastics 22 , pesticides 23 , glyphosate 24 , methoxychlor 25 , atrazine 26 , and jet fuel 27 in animal studies. The transgenerational sperm epimutations for exposure and disease-specific epimutations have been identified in these EWAS studies 21 – 27 and in EWAS human studies 28 , 29 .…”

Section: Introductionmentioning

confidence: 99%

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Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology

Beck

Nilsson

Maamar

et al. 2022

Sci Rep

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Environmental toxicants have been shown to promote the epigenetic transgenerational inheritance of disease through exposure specific epigenetic alterations in the germline. The current study examines the actions of hydrocarbon jet fuel, dioxin, pesticides (permethrin and methoxychlor), plastics, and herbicides (glyphosate and atrazine) in the promotion of transgenerational disease in the great grand-offspring rats that correlates with specific disease associated differential DNA methylation regions (DMRs). The transgenerational disease observed was similar for all exposures and includes pathologies of the kidney, prostate, and testis, pubertal abnormalities, and obesity. The disease specific DMRs in sperm were exposure specific for each pathology with negligible overlap. Therefore, for each disease the DMRs and associated genes were distinct for each exposure generational lineage. Observations suggest a large number of DMRs and associated genes are involved in a specific pathology, and various environmental exposures influence unique subsets of DMRs and genes to promote the transgenerational developmental origins of disease susceptibility later in life. A novel multiscale systems biology basis of disease etiology is proposed involving an integration of environmental epigenetics, genetics and generational toxicology.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology

Beck

Nilsson

Maamar

et al. 2022

Sci Rep

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“…The goal is to build a classification model that takes a region of the genome as input and predicts the region’s susceptibility to develop an environmentally induced transgenerational alteration in differential DNA methylation regions (DMRs) in the F3 generation from an ancestrally exposed F0 generation (great grandmother). The Skinner laboratory at Washington State University has produced several datasets based on the rat genome that identify DMRs in the F3 generation male sperm after exposing the F0 generation to one of nine toxicants: atrazine [ 15 ], dichloro-diphenyl-trichloroethane (DDT) [ 16 ], glyphosate [ 17 ], vinclozolin [ 18 ], pesticides [ 19 ], dioxin [ 20 ], jet fuel [ 21 ], methoxychlor [ 22 ], and plastics [ 23 ].…”

Section: Resultsmentioning

confidence: 99%

“…The Skinner laboratory at Washington State University has produced several datasets based on the rat genome that identify the differential DNA methylated regions (DMRs) in the F3 generation after exposure of the F0 generation to one of nine toxicants: atrazine [ 15 ], dichloro-diphenyl-trichloroethane (DDT) [ 16 ], glyphosate [ 17 ], vinclozolin [ 18 ], pesticides permethrin and N,N-Diethyl-meta-toluamide (DEET) [ 19 ], dioxin [ 20 ], jet fuel [ 21 ], methoxychlor [ 22 ], and plastics bisphenol A and phthalates [ 23 ]. Atrazine and glyphosate are commonly used herbicides.…”

Section: Introductionmentioning

confidence: 99%

Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach

et al. 2021

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Background Deep learning is an active bioinformatics artificial intelligence field that is useful in solving many biological problems, including predicting altered epigenetics such as DNA methylation regions. Deep learning (DL) can learn an informative representation that addresses the need for defining relevant features. However, deep learning models are computationally expensive, and they require large training datasets to achieve good classification performance. Results One approach to addressing these challenges is to use a less complex deep learning network for feature selection and Machine Learning (ML) for classification. In the current study, we introduce a hybrid DL-ML approach that uses a deep neural network for extracting molecular features and a non-DL classifier to predict environmentally responsive transgenerational differential DNA methylated regions (DMRs), termed epimutations, based on the extracted DL-based features. Various environmental toxicant induced epigenetic transgenerational inheritance sperm epimutations were used to train the model on the rat genome DNA sequence and use the model to predict transgenerational DMRs (epimutations) across the entire genome. Conclusion The approach was also used to predict potential DMRs in the human genome. Experimental results show that the hybrid DL-ML approach outperforms deep learning and traditional machine learning methods.

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A Review on Epigenetic Inheritance of Experiences in Humans

Ghai

Kader

2021

Biochem Genet

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Epigenome-wide association study for transgenerational disease sperm epimutation biomarkers following ancestral exposure to jet fuel hydrocarbons

Cited by 8 publications

References 71 publications

Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology

Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology

Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach

A Review on Epigenetic Inheritance of Experiences in Humans

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