Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders.
Ontology highlight
ABSTRACT:
SUBMITTER: Aref-Eshghi E
PROVIDER: S-EPMC8206389 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders.
Aref-Eshghi Erfan E Kerkhof Jennifer J Pedro Victor P VP France Groupe DI GD Barat-Houari Mouna M Ruiz-Pallares Nathalie N Andrau Jean-Christophe JC Lacombe Didier D Van-Gils Julien J Fergelot Patricia P Dubourg Christéle C Cormier-Daire Valerie V Rondeau Sophie S Lecoquierre François F Saugier-Veber Pascale P Nicolas Gaël G Lesca Gaetan G Chatron Nicolas N Sanlaville Damien D Vitobello Antonio A Faivre Laurence L Thauvin-Robinet Christel C Laumonnier Frederic F Raynaud Martine M Alders Mariëlle M Mannens Marcel M Henneman Peter P Hennekam Raoul C RC Velasco Guillaume G Francastel Claire C Ulveling Damien D Ciolfi Andrea A Pizzi Simone S Tartaglia Marco M Heide Solveig S Héron Delphine D Mignot Cyril C Keren Boris B Whalen Sandra S Afenjar Alexandra A Bienvenu Thierry T Campeau Philippe M PM Rousseau Justine J Levy Michael A MA Brick Lauren L Kozenko Mariya M Balci Tugce B TB Siu Victoria Mok VM Stuart Alan A Kadour Mike M Masters Jennifer J Takano Kyoko K Kleefstra Tjitske T de Leeuw Nicole N Field Michael M Shaw Marie M Gecz Jozef J Ainsworth Peter J PJ Lin Hanxin H Rodenhiser David I DI Friez Michael J MJ Tedder Matt M Lee Jennifer A JA DuPont Barbara R BR Stevenson Roger E RE Skinner Steven A SA Schwartz Charles E CE Genevieve David D Sadikovic Bekim B
American journal of human genetics 20210601 6
Similar Datasets
Project description:Genetic syndromes frequently present with overlapping clinical features and inconclusive or ambiguous genetic findings which can confound accurate diagnosis and clinical management. An expanding number of genetic syndromes have been shown to have unique genomic DNA methylation patterns (called "episignatures"). Peripheral blood episignatures can be used for diagnostic testing as well as for the interpretation of ambiguous genetic test results. We present here an approach to episignature mapping in 42 genetic syndromes, which has allowed the identification of 34 robust disease-specific episignatures. We examine emerging patterns of overlap, as well as similarities and hierarchical relationships across these episignatures, to highlight their key features as they are related to genetic heterogeneity, dosage effect, unaffected carrier status, and incomplete penetrance. We demonstrate the necessity of multiclass modeling for accurate genetic variant classification and show how disease classification using a single episignature at a time can sometimes lead to classification errors in closely related episignatures. We demonstrate the utility of this tool in resolving ambiguous clinical cases and identification of previously undiagnosed cases through mass screening of a large cohort of subjects with developmental delays and congenital anomalies. This study more than doubles the number of published syndromes with DNA methylation episignatures and, most significantly, opens new avenues for accurate diagnosis and clinical assessment in individuals affected by these disorders.
| S-EPMC7058829 | biostudies-literature
Project description:Episignatures are popular tools for the diagnosis of rare neurodevelopmental disorders. They are commonly based on a set of differentially methylated CpGs used in combination with a support vector machine model. DNA methylation (DNAm) data often include missing values due to changes in data generation technology and batch effects. While many normalization methods exist for DNAm data, their impact on episignature performance have never been assessed. In addition, technologies to quantify DNAm evolve quickly and this may lead to poor transposition of existing episignatures generated on deprecated array versions to new ones. Indeed, probe removal between array versions, technologies or during preprocessing leads to missing values. Thus, the effect of missing data on episignature performance must also be carefully evaluated and addressed through imputation or an innovative approach to episignatures design. In this paper, we used data from patients suffering from Kabuki and Sotos syndrome to evaluate the influence of normalization methods, classification models and missing data on the prediction performances of two existing episignatures. We compare how six popular normalization methods for methylarray data affect episignature classification performances in Kabuki and Sotos syndromes and provide best practice suggestions when building new episignatures. In this setting, we show that Illumina, Noob or Funnorm normalization methods achieved higher classification performances on the testing sets compared to Quantile, Raw and Swan normalization methods. We further show that penalized logistic regression and support vector machines perform best in the classification of Kabuki and Sotos syndrome patients. Then, we describe a new paradigm to build episignatures based on the detection of differentially methylated regions (DMRs) and evaluate their performance compared to classical differentially methylated cytosines (DMCs)-based episignatures in the presence of missing data. We show that the performance of classical DMC-based episignatures suffers from the presence of missing data more than the DMR-based approach. We present a comprehensive evaluation of how the normalization of DNA methylation data affects episignature performance, using three popular classification models. We further evaluate how missing data affect those models' predictions. Finally, we propose a novel methodology to develop episignatures based on differentially methylated regions identification and show how this method slightly outperforms classical episignatures in the presence of missing data.
| S-EPMC10676303 | biostudies-literature
Project description: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.
| S-EPMC10853222 | biostudies-literature
Project description: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.
| S-EPMC8756545 | biostudies-literature
Project description:Large structural chromosomal deletions and duplications, referred to as copy number variants (CNVs), play a role in the pathogenesis of neurodevelopmental disorders (NDDs) through effects on gene dosage. This review focuses on our current understanding of genomic disorders that arise from large structural chromosome rearrangements in patients with NDDs, as well as difficulties in overlap of clinical presentation and molecular diagnosis. We discuss the implications of epigenetics, specifically DNA methylation (DNAm), in NDDs and genomic disorders, and consider the implications and clinical impact of copy number and genomic DNAm testing in patients with suspected genetic NDDs. We summarize evidence of global methylation episignatures in CNV-associated disorders that can be used in the diagnostic pathway and may provide insights into the molecular pathogenesis of genomic disorders. Finally, we discuss the potential for combining CNV and DNAm assessment into a single diagnostic assay.
| S-EPMC9324454 | biostudies-literature
Project description:BackgroundWe aimed to define the clinical and variant spectrum and to provide novel molecular insights into the DHX30-associated neurodevelopmental disorder.MethodsClinical and genetic data from affected individuals were collected through Facebook-based family support group, GeneMatcher, and our network of collaborators. We investigated the impact of novel missense variants with respect to ATPase and helicase activity, stress granule (SG) formation, global translation, and their effect on embryonic development in zebrafish. SG formation was additionally analyzed in CRISPR/Cas9-mediated DHX30-deficient HEK293T and zebrafish models, along with in vivo behavioral assays.ResultsWe identified 25 previously unreported individuals, ten of whom carry novel variants, two of which are recurrent, and provide evidence of gonadal mosaicism in one family. All 19 individuals harboring heterozygous missense variants within helicase core motifs (HCMs) have global developmental delay, intellectual disability, severe speech impairment, and gait abnormalities. These variants impair the ATPase and helicase activity of DHX30, trigger SG formation, interfere with global translation, and cause developmental defects in a zebrafish model. Notably, 4 individuals harboring heterozygous variants resulting either in haploinsufficiency or truncated proteins presented with a milder clinical course, similar to an individual harboring a de novo mosaic HCM missense variant. Functionally, we established DHX30 as an ATP-dependent RNA helicase and as an evolutionary conserved factor in SG assembly. Based on the clinical course, the variant location, and type we establish two distinct clinical subtypes. DHX30 loss-of-function variants cause a milder phenotype whereas a severe phenotype is caused by HCM missense variants that, in addition to the loss of ATPase and helicase activity, lead to a detrimental gain-of-function with respect to SG formation. Behavioral characterization of dhx30-deficient zebrafish revealed altered sleep-wake activity and social interaction, partially resembling the human phenotype.ConclusionsOur study highlights the usefulness of social media to define novel Mendelian disorders and exemplifies how functional analyses accompanied by clinical and genetic findings can define clinically distinct subtypes for ultra-rare disorders. Such approaches require close interdisciplinary collaboration between families/legal representatives of the affected individuals, clinicians, molecular genetics diagnostic laboratories, and research laboratories.
| S-EPMC8140440 | biostudies-literature
Project description:Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.
| S-EPMC7730976 | biostudies-literature
Project description:PurposeWe describe the clinical implementation of genome-wide DNA methylation analysis in rare disorders across the EpiSign diagnostic laboratory network and the assessment of results and clinical impact in the first subjects tested.MethodsWe outline the logistics and data flow between an integrated network of clinical diagnostics laboratories in Europe, the United States, and Canada. We describe the clinical validation of EpiSign using 211 specimens and assess the test performance and diagnostic yield in the first 207 subjects tested involving two patient subgroups: the targeted cohort (subjects with previous ambiguous/inconclusive genetic findings including genetic variants of unknown clinical significance) and the screening cohort (subjects with clinical findings consistent with hereditary neurodevelopmental syndromes and no previous conclusive genetic findings).ResultsAmong the 207 subjects tested, 57 (27.6%) were positive for a diagnostic episignature including 48/136 (35.3%) in the targeted cohort and 8/71 (11.3%) in the screening cohort, with 4/207 (1.9%) remaining inconclusive after EpiSign analysis.ConclusionThis study describes the implementation of diagnostic clinical genomic DNA methylation testing in patients with rare disorders. It provides strong evidence of clinical utility of EpiSign analysis, including the ability to provide conclusive findings in the majority of subjects tested.
| S-EPMC8187150 | biostudies-literature
Project description:Methylation of several lysine residues of histones is a crucial mechanism for relatively long-term regulation of genomic activity. Recent molecular biological studies have demonstrated that the function of histone methylation is more diverse and complex than previously thought. Moreover, studies using newly available genomics techniques, such as exome sequencing, have identified an increasing number of histone lysine methylation-related genes as intellectual disability-associated genes, which highlights the importance of accurate control of histone methylation during neurogenesis. However, given the functional diversity and complexity of histone methylation within the cell, the study of the molecular basis of histone methylation-related neurodevelopmental disorders is currently still in its infancy. Here, we review the latest studies that revealed the pathological implications of alterations in histone methylation status in the context of various neurodevelopmental disorders and propose possible therapeutic application of epigenetic compounds regulating histone methylation status for the treatment of these diseases.
| S-EPMC5535897 | biostudies-literature
Project description:PURA-related neurodevelopmental disorders (PURA-NDDs) include 5q31.3 microdeletion syndrome and PURA syndrome. PURA has been proposed as a candidate gene responsible for 5q31.3 microdeletion syndrome. Phenotype comparisons between patients with PURA mutations and 5q31.3 microdeletions encompassing more than PURA gene are lacking. A total of 25 previously undescribed Mainland China patients were evaluated. Clinical data were obtained from medical record review and standardized medical history questionnaire. Clinical profile and genetic spectrum of the patients with PURA syndrome and genotype-phenotype correlations between PURA mutations group and 5q31.3 microdeletions group were analyzed. Our identified seventeen de nove PURA variants were novel, and two recurrent frameshift variants, c.697_699del (p.F233del) and c.159dup (p.L54Afs*147) were detected in the four independent pedigrees. One patient with 5q31.3 microdeletion further supported the shortest overlapping region only contains PURA and IGIP gene. Developmental delay/intellectual disability, neonatal hypotonia, neonatal feeding difficulties, hypersomnolence and dysmorphic features were prominent clinical features in PURA syndrome. There was no significant difference between two groups in incidence of neonatal problems, developmental delay and common medical comorbidities. We observed a higher frequency of abnormal brain MRI and specific facial dysmorphism in 5q31.3 microdeletion group. This is the first work describing a largest cohort of Mainland China patients broaden the clinical and molecular spectrum of PURA-NDDs. Our findings not only demonstrated that PURA haploinsufficiency was a major contributor to the important phenotypes of 5q31.3 microdeletion, but also implied that additional genes still played a role in the 5q31.3 microdeletion.
| S-EPMC9822978 | biostudies-literature