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.

Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature

Sequence-based genetic testing currently identifies causative genetic variants in ∼50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. Rare epigenetic variations ("epivariants") can drive disease by modulating gene expression at single loci, whereas genome-wide DNA methylation changes can result in distinct "episignature" biomarkers for monogenic disorders in a growing number of rare diseases. Here, we interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 516 individuals with genetically unsolved DEEs who had previously undergone extensive genetic testing. We identified rare differentially methylated regions (DMRs) and explanatory episignatures to discover causative and candidate genetic etiologies in 10 individuals. We then used long-read sequencing to identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and two copy number variants. We also identify pathogenic sequence variants associated with episignatures; some had been missed by previous exome sequencing. Although most DEE genes lack known episignatures, the increase in diagnostic yield for DNA methylation analysis in DEEs is comparable to the added yield of genome sequencing. Finally, we refine an episignature for CHD2 using an 850K methylation array which was further refined at higher CpG resolution using bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate genetic causes as ∼2% (10/516) for unsolved DEE cases.

Complexity in Genetic Epilepsies: A Comprehensive Review

Epilepsy is a highly prevalent neurological disorder, affecting between 5-8 per 1000 individuals and is associated with a lifetime risk of up to 3%. In addition to high incidence, epilepsy is a highly heterogeneous disorder, with variation including, but not limited to the following: severity, age of onset, type of seizure, developmental delay, drug responsiveness, and other comorbidities. Variable phenotypes are reflected in a range of etiologies including genetic, infectious, metabolic, immune, acquired/structural (resulting from, for example, a severe head injury or stroke), or idiopathic. This review will focus specifically on epilepsies with a genetic cause, genetic testing, and biomarkers in epilepsy.

Clinical validation of a single NGS targeted panel pipeline using the KAPA HyperChoice system for detection of germline, somatic and mitochondrial sequence and copy number variants

BACKGROUND

Comprehensive molecular diagnostics are highly dependent on the technical performance of next-generation sequencing (NGS) pipelines, which are assessed by data quality, cost, turnaround time, and accuracy of detecting a range of sequence and copy number variants.

METHODS

A dataset of 285 clinically validated cases (205 retrospective and 80 prospective), carrying complex sequence and copy number variants and thousands of genetic polymorphisms underwent a clinical validation of the KAPA HyperChoice target enrichment system with parallel sample fidelity assessment across a number of NGS panels. The analysis included assessment of peripheral blood, urine, muscle and FFPE tissues.

RESULTS

High-quality and exceptionally uniform data with 100% coverage of all targeted panels were obtained, resulting in complete sensitivity and specificity for all variant types across nearly all panels and tissue types. Overall reduction in cost and turnaround times was obtained with the implementation of a parallel genotyping sample fidelity system.

CONCLUSION

Results of the laboratory quality improvement study focused on a single NGS pipeline that includes both nuclear and mitochondrial genomes demonstrated utility in the clinical setting to assess a range of referral reasons, necessary due to the complex molecular etiology of human genetic disorders, while reducing costs and turnaround times.