X-linked myotubular myopathy is associated with epigenetic alterations and is ameliorated by HDAC inhibition

X-linked myotubular myopathy (XLMTM) is a fatal neuromuscular disorder caused by loss of function mutations in MTM1. At present, there are no directed therapies for XLMTM, and incomplete understanding of disease pathomechanisms. To address these knowledge gaps, we performed a drug screen in mtm1 mutant zebrafish and identified four positive hits, including valproic acid, which functions as a potent suppressor of the mtm1 zebrafish phenotype via HDAC inhibition. We translated these findings to a mouse XLMTM model, and showed that valproic acid ameliorates the murine phenotype. These observations led us to interrogate the epigenome in Mtm1 knockout mice; we found increased DNA methylation, which is normalized with valproic acid, and likely mediated through aberrant 1-carbon metabolism. Finally, we made the unexpected observation that XLMTM patients share a distinct DNA methylation signature, suggesting that epigenetic alteration is a conserved disease feature amenable to therapeutic intervention

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes.

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD.'' All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations.Genetics of disease, diagnosis and treatmen

DNA methylation signature associated with Bohring-Opitz syndrome: a new tool for functional classification of variants in ASXL genes

The additional sex combs-like (ASXL) gene family-encoded by ASXL1, ASXL2, and ASXL3-is crucial for mammalian development. Pathogenic variants in the ASXL gene family are associated with three phenotypically distinct neurodevelopmental syndromes. Our previous work has shown that syndromic conditions caused by pathogenic variants in epigenetic regulatory genes show consistent patterns of genome-wide DNA methylation (DNAm) alterations, i.e., DNAm signatures in peripheral blood. Given the role of ASXL1 in chromatin modification, we hypothesized that pathogenic ASXL1 variants underlying Bohring-Opitz syndrome (BOS) have a unique DNAm signature. We profiled whole-blood DNAm for 17 ASXL1 variants, and 35 sex- and age-matched typically developing individuals, using Illumina's Infinium EPIC array. We identified 763 differentially methylated CpG sites in individuals with BOS. Differentially methylated sites overlapped 323 unique genes, including HOXA5 and HOXB4, supporting the functional relevance of DNAm signatures. We used a machine-learning classification model based on the BOS DNAm signature to classify variants of uncertain significance in ASXL1, as well as pathogenic ASXL2 and ASXL3 variants. The DNAm profile of one individual with the ASXL2 variant was BOS-like, whereas the DNAm profiles of three individuals with ASXL3 variants were control-like. We also used Horvath's epigenetic clock, which showed acceleration in DNAm age in individuals with pathogenic ASXL1 variants, and the individual with the pathogenic ASXL2 variant, but not in individuals with ASXL3 variants. These studies enhance our understanding of the epigenetic dysregulation underpinning ASXL gene family-associated syndromes

DNA methylation as a predictor of fetal alcohol spectrum disorder

Abstract Background Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2–5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5–18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD." All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations