DNA methylation episignature for Witteveen-Kolk syndrome due to SIN3A haploinsufficiency

Diagnostic utility and reporting recommendations for clinical DNA methylation episignature testing in genetically undiagnosed rare diseases

PURPOSE

This study aims to assess the diagnostic utility and provide reporting recommendations for clinical DNA methylation episignature testing based on the cohort of patients tested through the EpiSign Clinical Testing Network.

METHODS

The EpiSign assay utilized unsupervised clustering techniques and a support vector machine-based classification algorithm to compare each patient's genome-wide DNA methylation profile with the EpiSign Knowledge Database, yielding the result that was reported. An international working group, representing distinct EpiSign Clinical Testing Network health jurisdictions, collaborated to establish recommendations for interpretation and reporting of episignature testing.

RESULTS

Among 2399 cases analyzed, 1667 cases underwent a comprehensive screen of validated episignatures, imprinting, and promoter regions, resulting in 18.7% (312/1667) positive reports. The remaining 732 referrals underwent targeted episignature analysis for assessment of sequence or copy-number variants (CNVs) of uncertain significance or for assessment of clinical diagnoses without confirmed molecular findings, and 32.4% (237/732) were positive. Cases with detailed clinical information were highlighted to describe various utility scenarios for episignature testing.

CONCLUSION

Clinical DNA methylation testing including episignatures, imprinting, and promoter analysis provided by an integrated network of clinical laboratories enables test standardization and demonstrates significant diagnostic yield and clinical utility beyond DNA sequence analysis in rare diseases.

Mitotic Block and Epigenetic Repression Underlie Neurodevelopmental Defects and Neurobehavioral Deficits in Congenital Heart Disease

Poor neurodevelopment is often observed with congenital heart disease (CHD), especially with mutations in chromatin modifiers. Here analysis of mice with hypoplastic left heart syndrome (HLHS) arising from mutations in Sin3A associated chromatin modifier Sap130 , and adhesion protein Pcdha9, revealed neurodevelopmental and neurobehavioral deficits reminiscent of those in HLHS patients. Microcephaly was associated with impaired cortical neurogenesis, mitotic block, and increased apoptosis. Transcriptional profiling indicated dysregulated neurogenesis by REST, altered CREB signaling regulating memory and synaptic plasticity, and impaired neurovascular coupling modulating cerebral blood flow. Many neurodevelopmental/neurobehavioral disease pathways were recovered, including autism and cognitive impairment. These same pathways emerged from genome-wide DNA methylation and Sap130 chromatin immunoprecipitation sequencing analyses, suggesting epigenetic perturbation. Mice with Pcdha9 mutation or forebrain-specific Sap130 deletion without CHD showed learning/memory deficits and autism-like behavior. These novel findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation and suggest new avenues for therapy.

Rescuing lung development through embryonic inhibition of histone acetylation

A major barrier to the impact of genomic diagnosis in patients with congenital malformations is the lack of understanding regarding how sequence variants contribute to disease pathogenesis and whether this information could be used to generate patient-specific therapies. Congenital diaphragmatic hernia (CDH) is among the most common and severe of all structural malformations; however, its underlying mechanisms are unclear. We identified loss-of-function sequence variants in the epigenomic regulator gene SIN3A in two patients with complex CDH. Tissue-specific deletion of Sin3a in mice resulted in defects in diaphragm development, lung hypoplasia, and pulmonary hypertension, the cardinal features of CDH and major causes of CDH-associated mortality. Loss of SIN3A in the lung mesenchyme resulted in reduced cellular differentiation, impaired cell proliferation, and increased DNA damage. Treatment of embryonic Sin3a mutant mice with anacardic acid, an inhibitor of histone acetyltransferase, reduced DNA damage, increased cell proliferation and differentiation, improved lung and pulmonary vascular development, and reduced pulmonary hypertension. These findings demonstrate that restoring the balance of histone acetylation can improve lung development in the Sin3a mouse model of CDH.

Comprehensive evaluation of the implementation of episignatures for diagnosis of neurodevelopmental disorders (NDDs)

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.