Detection of a DNA Methylation Signature for the Intellectual Developmental Disorder, X-Linked, Syndromic, Armfield Type

Episignatures in practice: independent evaluation of published episignatures for the molecular diagnostics of ten neurodevelopmental disorders

Variants of uncertain significance (VUS) are a significant issue for the molecular diagnosis of rare diseases. The publication of episignatures as effective biomarkers of certain Mendelian neurodevelopmental disorders has raised hopes to help classify VUS. However, prediction abilities of most published episignatures have not been independently investigated yet, which is a prerequisite for an informed and rigorous use in a diagnostic setting. We generated DNA methylation data from 101 carriers of (likely) pathogenic variants in ten different genes, 57 VUS carriers, and 25 healthy controls. Combining published episignature information and new validation data with a k-nearest-neighbour classifier within a leave-one-out scheme, we provide unbiased specificity and sensitivity estimates for each of the signatures. Our procedure reached 100% specificity, but the sensitivities unexpectedly spanned a very large spectrum. While ATRX, DNMT3A, KMT2D, and NSD1 signatures displayed a 100% sensitivity, CREBBP-RSTS and one of the CHD8 signatures reached <40% sensitivity on our dataset. Remaining Cornelia de Lange syndrome, KMT2A, KDM5C and CHD7 signatures reached 70-100% sensitivity at best with unstable performances, suffering from heterogeneous methylation profiles among cases and rare discordant samples. Our results call for cautiousness and demonstrate that episignatures do not perform equally well. Some signatures are ready for confident use in a diagnostic setting. Yet, it is imperative to characterise the actual validity perimeter and interpretation of each episignature with the help of larger validation sample sizes and in a broader set of episignatures.

Integrative omics approaches to advance rare disease diagnostics

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.

Identification of a DNA methylation signature for Renpenning syndrome (RENS1), a spliceopathy

The challenges and ambiguities in providing an accurate diagnosis for patients with neurodevelopmental disorders have led researchers to apply epigenetics as a technique to validate the diagnosis provided based on the clinical examination and genetic testing results. Genome-wide DNA methylation analysis has recently been adapted for clinical testing of patients with genetic neurodevelopmental disorders. In this paper, preliminary data demonstrating a DNA methylation signature for Renpenning syndrome (RENS1 - OMIM 309500), which is an X-linked recessive neurodevelopmental disorder caused by variants in polyglutamine-binding protein 1 (PQBP1) is reported. The identified episignature was then utilized to construct a highly sensitive and specific binary classification model. Besides providing evidence for the existence of a DNA methylation episignature for Renpenning syndrome, this study increases the knowledge of the molecular mechanisms related to the disease. Moreover, the availability of more subjects in future may facilitate the establishment of an episignature that can be utilized for diagnosis in a clinical setting and for reclassification of variants of unknown clinical significance.

Upregulation of FAM50A promotes cancer development

FAM50A encodes a nuclear protein involved in mRNA processing; however, its role in cancer development remains unclear. Herein, we conducted an integrative pan-cancer analysis using The Cancer Genome Atlas, Genotype-Tissue Expression, and the Clinical Proteomic Tumor Analysis Consortium databases. Based on the gene expression data from TCGA and GTEx databases, we compared FAM50A mRNA levels in 33 types of human cancer tissues to those in corresponding normal tissues and found that FAM50A mRNA level was upregulated in 20 of the 33 types of common cancer tissues. Then, we compared the DNA methylation status of the FAM50A promoter in tumor tissues to that in corresponding normal tissues. FAM50A upregulation was accompanied by promoter hypomethylation in 8 of the 20 types of tumor tissues, suggesting that promoter hypomethylation contributes to the upregulation of FAM50A in these cancer tissues. Elevated FAM50A expression in 10 types of cancer tissues was associated with poor prognosis in patients with cancer. FAM50A expression was positively correlated with CD4+ T-lymphocyte and dendritic cell infiltration in cancer tissues but was negatively correlated with CD8+ T-cell infiltration in cancer tissues. FAM50A knockdown caused DNA damage, induced interferon beta and interleukin-6 expression, and repressed the proliferation, invasion, and migration of cancer cells. Our findings indicate that FAM50A might be useful in cancer detection, reveal insights into its role in cancer development, and may contribute to the development of cancer diagnostics and treatments.

SRSF1 haploinsufficiency is responsible for a syndromic developmental disorder associated with intellectual disability

SRSF1 (also known as ASF/SF2) is a non-small nuclear ribonucleoprotein (non-snRNP) that belongs to the arginine/serine (R/S) domain family. It recognizes and binds to mRNA, regulating both constitutive and alternative splicing. The complete loss of this proto-oncogene in mice is embryonically lethal. Through international data sharing, we identified 17 individuals (10 females and 7 males) with a neurodevelopmental disorder (NDD) with heterozygous germline SRSF1 variants, mostly de novo, including three frameshift variants, three nonsense variants, seven missense variants, and two microdeletions within region 17q22 encompassing SRSF1. Only in one family, the de novo origin could not be established. All individuals featured a recurrent phenotype including developmental delay and intellectual disability (DD/ID), hypotonia, neurobehavioral problems, with variable skeletal (66.7%) and cardiac (46%) anomalies. To investigate the functional consequences of SRSF1 variants, we performed in silico structural modeling, developed an in vivo splicing assay in Drosophila, and carried out episignature analysis in blood-derived DNA from affected individuals. We found that all loss-of-function and 5 out of 7 missense variants were pathogenic, leading to a loss of SRSF1 splicing activity in Drosophila, correlating with a detectable and specific DNA methylation episignature. In addition, our orthogonal in silico, in vivo, and epigenetics analyses enabled the separation of clearly pathogenic missense variants from those with uncertain significance. Overall, these results indicated that haploinsufficiency of SRSF1 is responsible for a syndromic NDD with ID due to a partial loss of SRSF1-mediated splicing activity.

Functional correlation of genome-wide DNA methylation profiles in genetic neurodevelopmental disorders

An expanding range of genetic syndromes are characterized by genome-wide disruptions in DNA methylation profiles referred to as episignatures. Episignatures are distinct, highly sensitive and specific biomarkers that have recently been applied in clinical diagnosis of genetic syndromes. Episignatures are contained within the broader disorder-specific genome-wide DNA methylation changes which can share significant overlap amongst different conditions. In this study we performed functional genomic assessment and comparison of disorder-specific and overlapping genome-wide DNA methylation changes related to 65 genetic syndromes with previously described episignatures. We demonstrate evidence of disorder-specific and recurring genome-wide differentially methylated probes (DMPs) and regions (DMRs). The overall distribution of DMPs and DMRs across the majority of the neurodevelopmental genetic syndromes analyzed showed substantial enrichment in gene promoters and CpG islands, and under-representation of the more variable intergenic regions. Analysis showed significant enrichment of the DMPs and DMRs in gene pathways and processes related to neurodevelopment, including neurogenesis, synaptic signaling and synaptic transmission. This study expands beyond the diagnostic utility of DNA methylation episignatures by demonstrating correlation between the function of the mutated genes and the consequent genomic DNA methylation profiles as a key functional element in the molecular etiology of genetic neurodevelopmental disorders. This article is protected by copyright. All rights reserved.

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders

Overlapping clinical phenotypes and an expanding breadth and complexity of genomic associations are a growing challenge in the diagnosis and clinical management of Mendelian disorders. The functional consequences and clinical impacts of genomic variation may involve unique, disorder-specific, genomic DNA methylation episignatures. In this study, we describe 19 novel episignature disorders and compare the findings alongside 38 previously established episignatures for a total of 57 episignatures associated with 65 genetic syndromes. We demonstrate increasing resolution and specificity ranging from protein complex, gene, sub-gene, protein domain, and even single nucleotide-level Mendelian episignatures. We show the power of multiclass modeling to develop highly accurate and disease-specific diagnostic classifiers. This study significantly expands the number and spectrum of disorders with detectable DNA methylation episignatures, improves the clinical diagnostic capabilities through the resolution of unsolved cases and the reclassification of variants of unknown clinical significance, and provides further insight into the molecular etiology of Mendelian conditions.