ArticleGenes2020
Ultra-Deep DNA Methylation Analysis of X-Linked Genes:
Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 11 citations in OpenAlex.
- Clinical variability of ATP11C-related hemolytic anemia: expanding the phenotypic and diagnostic spectrum.Blood advances · 2026Article
- Epigenetic Mechanisms in Fabry Disease: A Thematic Analysis Linking Differential Methylation Profiles and Genetic Modifiers to Disease Phenotype.Current issues in molecular biology · 2025Review
- A specific pluripotency-associated eRNA controls Nanog locus by shaping the epigenetic landscape and stabilizing enhancer-promoter interaction.Nucleic acids research · 2025Article
- Females with Fabry disease: an expert opinion on diagnosis, clinical management, current challenges and unmet needs.Frontiers in cardiovascular medicine · 2025Review
- Sex Differences in Anderson-Fabry Cardiomyopathy: Clinical, Genetic, and Imaging Analysis in Women.Genes · 2023Article
- Dysregulated DNA methylation in the pathogenesis of Fabry disease.Molecular genetics and metabolism reports · 2022Article
- Methylome Profiling in Fabry Disease in Clinical Practice: A Proof of Concept.International journal of molecular sciences · 2022Article
- Epigenetic remodelling of Fxyd1 promoters in developing heart and brain tissues.Scientific reports · 2022Article
- DNA methylation impact on Fabry disease.Clinical epigenetics · 2021Review
- DNA Methylation Profiles ofBiomolecules · 2021Article
- Modeling DNA Methylation Profiles through a Dynamic Equilibrium between Methylation and Demethylation.Biomolecules · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recessive X-linked disorders may occasionally evolve in clinical manifestations of variable severity also in female carriers. For some of such diseases, the frequency of the symptoms' appearance during women's life may be particularly relevant. This phenomenon has been largely attributed to the potential skewness of the X-inactivation process leading to variable phenotypes. Nonetheless, in many cases, no correlation with X-inactivation unbalance was demonstrated. However, methods for analyzing skewness have been mainly limited to Human Androgen Receptor methylation analysis (HUMARA). Recently, the X-inactivation process has been largely revisited, highlighting the heterogeneity existing among loci in the epigenetic state within inactive and, possibly, active X-chromosomes. We reasoned that gene-specific and ultra-deep DNA methylation analyses could greatly help to unravel details of the X-inactivation process and the roles of specific X genes inactivation in disease manifestations. We recently provided evidence that studying DNA methylation at specific autosomic loci at a single-molecule resolution (epiallele distribution analysis) allows one to analyze cell-to-cell methylation differences in a given cell population. We here apply the epiallele analysis at two X-linked loci to investigate whether females show allele-specific epiallelic patterns. Due to the high potential of this approach, the method allows us to obtain clearly distinct allele-specific epiallele profiles.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.