Exposure of Greenlandic Inuit and South African VhaVenda men to the persistent DDT metabolite is associated with an altered sperm epigenome at regions implicated in paternal epigenetic transmission and developmental disease – a cross-sectional study
Bibliographic record
Abstract
Abstract Background The persistent organochlorine dichlorodiphenyltrichloroethane (DDT) is banned world-wide due to its negative health effects and persistence in the environment. It is exceptionally used as an insecticide for malaria control. Exposure occurs in regions where DDT is applied, as well as in the arctic where it’s endocrine disrupting metabolite, p,p’- dichlorodiphenyldichloroethylene ( p,p’- DDE) accumulates in marine mammals and fish. DDT and p,p’- DDE exposures are linked to birth defects, infertility, cancer, and neurodevelopmental delays. Of particular concern is the potential of DDT use to impact the health of generations to come. Generational effects of toxicant exposures have been described in animal models and implicated germline epigenetic factors. Similar generational effects have been shown in epidemiological studies. Although advances in understanding the molecular mechanisms mediating this epigenetic inheritance have been made, there remain major knowledge gaps in how this occurs in humans. In animal and human models, DNA methylation (DNAme) has been implicated in paternal epigenetic effects. In animal models, histone H3K4 trimethylation (H3K4me3) has been shown to be responsive to the paternal environment and linked with epigenetic transmission to the embryo. Our objectives were to define the associations between p,p’- DDE serum levels and alterations in the sperm methylome and H3K4me3 enrichment using next generation sequencing. We aimed to compare regions of epigenomic sensitivity between geographically diverse populations with different routes and levels of exposures, and to identify interactions between altered DNAme and H3K4me3 regions. The potential for p,p’- DDE to impact the health of the next generation was explored by examining the functions of the genomic regions impacted, their roles during embryo development, and in health and disease. Methods In the Limpopo Province of South Africa, we recruited 247 VhaVenda South African men from 12 villages that either used indoor residual spraying with DDT for malaria control or not. We selected 49 paired blood and semen samples, from men that ranged from 18 to 32 years of age (mean 25 years). Sample inclusion was based on normal sperm counts (> 15 million/ml), normal sperm DNA fragmentation index, and testing a range of p,p’- DDE exposure levels (mean 10,462.228 ± 1,792.298 ng/ml). From a total of 193 samples, 47 Greenlandic Inuit blood and semen paired samples were selected from the biobank of the INUENDO cohort. The subjects ranged from 20 to 44 years of age (mean 31 years), were born in Greenland, and all had proven fertility. Sample selection was based on obtaining a range of p,p’ -DDE exposure levels (mean 870.734 ± 134.030 ng/ml). Here we determined the molecular responses at the level of the sperm epigenome to serum p,p’ -DDE levels using MethylC-Capture-seq (MCC-seq) and chromatin-immunoprecipitation followed by sequencing (ChIP-seq). We identified genomic regions with altered DNA methylation (DNAme) and differential enrichment of histone H3 lysine 4 trimethylation (H3K4me3) in sperm. We used in silico analyses to discover regions of differential methylation associated with p,p’- DDE levels that were predicted to be transmitted and persist in the embryo. Results Alterations in DNAme and H3K4me3 enrichment followed dose response-like trends, and we identified overlapping genomic regions with DNAme sensitivities in both populations. Altered DNAme and H3K4me3 in sperm occurred at transposable elements and regulatory regions involved in fertility, disease, development, and neurofunction. A subset of regions with altered sperm DNAme and H3K4me3 were predicted to persist in the pre-implantation embryo and were associated with embryonic gene expression. Limitations The samples were collected from remote areas of the world thus sample size is relatively small. The populations differed in the routes of exposure, timing of collection, mean age (mean of 25 versus 31 years of age in South African and Greenlandic populations respectively) and in the timing of p,p’- DDE measurement. Moreover, the Greenlandic Inuit men were proven fertile whereas the fertility status of the South African men was unknown. Confounding factors such as other environmental exposures and selection bias cannot be ruled out. Conclusions These findings suggest that in men, DDT and p,p’- DDE exposure impacts the sperm epigenome in a dose-responsive manner and may negatively impact the health of future generations through epigenetic mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".