DNA methylation impact on Fabry disease

Abstract

Background Fabry disease (FD) is a rare X-linked disease caused by mutations in GLA gene with consequent lysosomal accumulation of globotriaosylceramide (Gb3). Women with FD often show highly heterogeneous symptoms that can manifest from mild to severe phenotype. Main body The phenotypic variability of the clinical manifestations in heterozygous women with FD mainly depends on the degree and direction of inactivation of the X chromosome. Classical approaches to measure XCI skewness might be not sufficient to explain disease manifestation in women. In addition to unbalanced XCI, allele-specific DNA methylation at promoter of GLA gene may influence the expression levels of the mutated allele, thus impacting the onset and the outcome of FD. In this regard, analyses of DNA methylation at GLA promoter, performed by approaches allowing distinction between mutated and non-mutated allele, may be much more informative. The aim of this review is to critically evaluate recent literature articles addressing the potential role of DNA methylation in the context of FD. Although up to date relatively few works have addressed this point, reviewing all pertinent studies may help to evaluate the importance of DNA methylation analysis in FD and to develop new research and technologies aimed to predict whether the carrier females will develop symptoms. Conclusions Relatively few studies have addressed the complexity of DNA methylation landscape in FD that remains poorly investigated. The hope for the future is that ad hoc and ultradeep methylation analyses of GLA gene will provide epigenetic signatures able to predict whether pre-symptomatic female carriers will develop symptoms thus helping timely interventions.

The potential consequences of bidirectional promoter methylation on GLA and HNRNPH2 expression in Fabry disease phenotypes in a family of patients carrying a GLA deletion variant

“…Although few studies have dealt with the role of methylation in FD, for a review see Di Risi et al ( 24 ); the present study provided further evidence on the potential role of DNA methylation involvement in the clinical manifestation of FD. The GLA mutations can cause total or partial decreased activity of α-Gal A and accumulation of glycosphingolipids ( 3 , 4 ).…”

Dysregulated DNA methylation in the pathogenesis of Fabry disease

“…Hossain et al [ 14 , 15 ] directly analyzed methylation of the GLA gene in female Fabry patients, and showed that methylation of the non-mutated allele correlated with disease severity. These studies highlighted the potential effect of methylation of GLA gene on α-gal A activity and disease phenotype in heterozygous females (for a review on the role of DNA methylation in Fabry disease, see Di Risi et al [ 16 ]). However, the role of epigenetic modifications as a downstream mediator in disease pathogenesis has not been studied.…”

Regulatory pattern of abnormal promoter CpG island methylation in the glioblastoma multiforme classification

“…To investigate the DNA methylation of promoter CpG island (PCGI) associated with GBM disease progression, we established a richly computational strategy that maps the Infinium HumanMethylation450K microarray to gene PCGI methylation profiles and summarizes DNA methylation patterns at the gene level ( Zhao et al, 2021b ). First, based on the gene annotation derived from the GENCODE database and GPL13534 platform file containing the methylation probes information ( Li et al, 2020 ; Di Risi et al, 2021 ), we defined the promoter region as 2 kb located upstream of the transcription start site ( Hollstein et al, 2019 ). We extracted the relevant probes on the PCGI from the annotation file for subsequent analysis ( Carro et al, 2010 ).…”

“…Besides, we downloaded gene expression data from the Chinese Glioma Genome Atlas (CGGA, http://www.cgga.org.cn/ ) database as a supplementary dataset, which includes 282 GBM patients who possessed complete clinical information ( Zhao et al, 2021a ). The annotation file for mRNAs and promoter region was derived from the GENCODE database ( https://www.gencodegenes.org/ ) ( Di Risi et al, 2021 ). The single-cell sequencing data were obtained from GSE162631 in the GEO database, and cells derived from the tumor cores of three GBM patients in the dataset were selected ( Xie et al, 2021a ).…”