Pediatric developmental syndromes present with systemic, complex, and often overlapping clinical features that are not infrequently a consequence of Mendelian inheritance of mutations in genes involved in DNA methylation, establishment of histone modifications, and chromatin remodeling (the ''epigenetic machinery''). The mechanistic cross-talk between histone modification and DNA methylation suggests that these syndromes might be expected to display specific DNA methylation signatures that are a reflection of those primary errors associated with chromatin dysregulation. Given the interrelated functions of these chromatin regulatory proteins, we sought to identify DNA methylation epi-signatures that could provide syndrome-specific biomarkers to complement standard clinical diagnostics. In the present study, we examined peripheral blood samples from a large cohort of individuals encompassing 14 Mendelian disorders displaying mutations in the genes encoding proteins of the epigenetic machinery. We demonstrated that specific but partially overlapping DNA methylation signatures are associated with many of these conditions. The degree of overlap among these epi-signatures is minimal, further suggesting that, consistent with the initial event, the downstream changes are unique to every syndrome. In addition, by combining these epi-signatures, we have demonstrated that a machine learning tool can be built to concurrently screen for multiple syndromes with high sensitivity and specificity, and we highlight the utility of this tool in solving ambiguous case subjects presenting with variants of unknown significance, along with its ability to generate accurate predictions for subjects presenting with the overlapping clinical and molecular features associated with the disruption of the epigenetic machinery.

Purpose We 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. Methods We 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). Results Among 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. Conclusion This 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.

Coffin–Siris and Nicolaides–Baraitser syndromes (CSS and NCBRS) are Mendelian disorders caused by mutations in subunits of the BAF chromatin remodeling complex. We report overlapping peripheral blood DNA methylation epi-signatures in individuals with various subtypes of CSS (ARID1B, SMARCB1, and SMARCA4) and NCBRS (SMARCA2). We demonstrate that the degree of similarity in the epi-signatures of some CSS subtypes and NCBRS can be greater than that within CSS, indicating a link in the functional basis of the two syndromes. We show that chromosome 6q25 microdeletion syndrome, harboring ARID1B deletions, exhibits a similar CSS/NCBRS methylation profile. Specificity of this epi-signature was confirmed across a wide range of neurodevelopmental conditions including other chromatin remodeling and epigenetic machinery disorders. We demonstrate that a machine-learning model trained on this DNA methylation profile can resolve ambiguous clinical cases, reclassify those with variants of unknown significance, and identify previously undiagnosed subjects through targeted population screening.

Mitochondrial membrane phospholipids are essential for the mitochondrial architecture, the activity of respiratory proteins, and the transport of proteins into the mitochondria. The accumulation of phospholipids within mitochondria depends on a coordinate synthesis, degradation, and trafficking of phospholipids between the endoplasmic reticulum (ER) and mitochondria as well as intramitochondrial lipid trafficking. Several studies highlight the contribution of dietary fatty acids to the remodeling of phospholipids and mitochondrial membrane homeostasis. Understanding the role of phospholipids in the mitochondrial membrane and their metabolism will shed light on the molecular mechanisms involved in the regulation of mitochondrial function and in the mitochondrial-related diseases.

Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89%-100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation-dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection.

Kabuki syndrome (KS) is caused by mutations in KMT2D, which is a histone methyltransferase involved in methylation of H3K4, a histone marker associated with DNA methylation. Analysis of >450,000 CpGs in 24 KS patients with pathogenic mutations in KMT2D and 216 controls, identified 24 genomic regions, along with 1,504 CpG sites with significant DNA methylation changes including a number of Hox genes and the MYO1F gene. Using the most differentiating and significant probes and regions we developed a "methylation variant pathogenicity (MVP) score," which enables 100% sensitive and specific identification of individuals with KS, which was confirmed using multiple public and internal patient DNA methylation databases. We also demonstrated the ability of the MVP score to accurately reclassify variants of unknown significance in subjects with apparent clinical features of KS, enabling its potential use in molecular diagnostics. These findings provide novel insights into the molecular etiology of KS and illustrate that DNA methylation patterns can be interpreted as 'epigenetic echoes' in certain clinical disorders.

BackgroundDNA methylation is an essential epigenetic mark, controlled by DNA methyltransferase (DNMT) proteins, which regulates chromatin structure and gene expression throughout the genome. In this study, we describe a family with adult-onset autosomal dominant cerebellar ataxia with deafness and narcolepsy (ADCA-DN) caused by mutations in the maintenance methyltransferase DNMT1 and assess the DNA methylation profile of these individuals.ResultsWe report a family with six individuals affected with ADCA-DN; specifically, patients first developed hearing loss and ataxia, followed by narcolepsy, and cognitive decline. We identified a heterozygous DNMT1 variant, c.1709C>T [p.Ala570Val] by Sanger sequencing, which had been previously reported as pathogenic for ADCA-DN and segregated with disease in the family. DNA methylation analysis by high-resolution genome-wide DNA methylation array identified a decrease in CpGs with 0–10 % methylation and 80–95 % methylation and a concomitant increase in sites with 10–30 % methylation and >95 % methylation. This pattern suggests an increase in methylation of normally unmethylated regions, such as promoters and CpG islands, as well as further methylation of highly methylated gene bodies and intergenic regions. Furthermore, a regional analysis identified 82 hypermethylated loci with consistent robust differences across ≥5 consecutive probes compared to our large reference cohort.ConclusionsThis report identifies robust changes in the DNA methylation patterns in ADCA-DN patients, which is an important step towards elucidating disease pathogenesis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-016-0254-x) contains supplementary material, which is available to authorized users.

BackgroundClaes-Jensen syndrome is an X-linked inherited intellectual disability caused by mutations in the KDM5C gene. Kdm5c is a histone lysine demethylase involved in histone modifications and chromatin remodeling. Males with hemizygous mutations in KDM5C present with intellectual disability and facial dysmorphism, while most heterozygous female carriers are asymptomatic. We hypothesized that loss of Kdm5c function may influence other components of the epigenomic machinery including DNA methylation in affected patients.ResultsGenome-wide DNA methylation analysis of 7 male patients affected with Claes-Jensen syndrome and 56 age- and sex-matched controls identified a specific DNA methylation defect (epi-signature) in the peripheral blood of these patients, including 1769 individual CpGs and 9 genomic regions. Six healthy female carriers showed less pronounced but distinctive changes in the same regions enabling their differentiation from both patients and controls. Highly specific computational model using the most significant methylation changes demonstrated 100% accuracy in differentiating patients, carriers, and controls in the training cohort, which was confirmed on a separate cohort of patients and carriers. The 100% specificity of this unique epi-signature was further confirmed on additional 500 unaffected controls and 600 patients with intellectual disability and developmental delay, including other patient cohorts with previously described epi-signatures.ConclusionPeripheral blood epi-signature in Claes-Jensen syndrome can be used for molecular diagnosis and carrier identification and assist with interpretation of genetic variants of unknown clinical significance in the KDM5C gene.Electronic supplementary materialThe online version of this article (10.1186/s13148-018-0453-8) contains supplementary material, which is available to authorized users.