DNA Methylation Signature for JARID2-Neurodevelopmental Syndrome

The detection of a strong episignature for Chung-Jansen syndrome, partially overlapping with Börjeson-Forssman-Lehmann and White-Kernohan syndromes

Chung-Jansen syndrome is a neurodevelopmental disorder characterized by intellectual disability, behavioral problems, obesity and dysmorphic features. It is caused by pathogenic variants in the PHIP gene that encodes for the Pleckstrin homology domain-interacting protein, which is part of an epigenetic modifier protein complex. Therefore, we hypothesized that PHIP haploinsufficiency may impact genome-wide DNA methylation (DNAm). We assessed the DNAm profiles of affected individuals with pathogenic and likely pathogenic PHIP variants with Infinium Methylation EPIC arrays and report a specific and sensitive DNAm episignature biomarker for Chung-Jansen syndrome. In addition, we observed similarities between the methylation profile of Chung-Jansen syndrome and that of functionally related and clinically partially overlapping genetic disorders, White-Kernohan syndrome (caused by variants in DDB1 gene) and Börjeson-Forssman-Lehmann syndrome (caused by variants in PHF6 gene). Based on these observations we also proceeded to develop a common episignature biomarker for these disorders. These newly defined episignatures can be used as part of a multiclass episignature classifier for screening of affected individuals with rare disorders and interpretation of genetic variants of unknown clinical significance, and provide further insights into the common molecular pathophysiology of the clinically-related Chung-Jansen, Börjeson-Forssman-Lehmann and White-Kernohan syndromes.

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.

DNA methylation episignature, extension of the clinical features, and comparative epigenomic profiling of Hao-Fountain syndrome caused by variants in USP7

PURPOSE

Hao-Fountain syndrome (HAFOUS) is a neurodevelopmental disorder caused by pathogenic variants in USP7. HAFOUS is characterized by developmental delay, intellectual disability, speech delay, behavioral abnormalities, autism spectrum disorder, seizures, hypogonadism, and mild dysmorphic features. We investigated the phenotype of 18 participants with HAFOUS and performed DNA methylation (DNAm) analysis, aiming to generate a diagnostic biomarker. Furthermore, we performed comparative analysis with known episignatures to gain more insight into the molecular pathophysiology of HAFOUS.

METHODS

We assessed genomic DNAm profiles of 18 individuals with pathogenic variants and variants of uncertain significance (VUS) in USP7 to map and validate a specific episignature. The comparison between the USP7 cohort and 56 rare genetic disorders with earlier reported DNAm episignatures was performed with statistical and functional correlation.

RESULTS

We mapped a sensitive and specific DNAm episignature for pathogenic variants in USP7 and utilized this to reclassify the VUS. Comparative epigenomic analysis showed evidence of HAFOUS similarity to a number of other rare genetic episignature disorders.

CONCLUSION

We discovered a sensitive and specific DNAm episignature as a robust diagnostic biomarker for HAFOUS that enables VUS reclassification in USP7. We also expand the phenotypic spectrum of 9 new and 5 previously reported individuals with HAFOUS.

A Functional Single Nucleotide Polymorphism in the 3' Untranslated Region of the Porcine JARID2 Gene Is Associated with Aggressive Behavior of Weaned Pigs after Mixing

In pig production, pigs often show more aggressive behavior after mixing, which adversely affects animal welfare and growth performance. The Jumonji and structural domain-rich AT interaction domain 2 (JARID2) gene plays an important role in neurodevelopment in mice and various psychiatric disorders in humans. The JARID2 gene may impact the aggressive behavior of pigs. By observing the behavior of 500 weaned pigs during the first 72 h after mixing, the ear tissue samples of the 12 most aggressive and 12 least aggressive pigs were selected for DNA resequencing based on the intensity of their aggressive behavior. Large group correlation analysis indicated that the rs3262221458 site located in the 3'-UTR region of the porcine JARID2 gene has a strong relationship with the aggressive behavior of weaned pigs. Pigs with the mutant TT genotype of rs3262221458 have more aggressive behavior than those pigs with the GG and GT genotypes. The dual luciferase assay indicated that the luciferase activity of the plasmids containing the G allele of rs326221458 was significantly less than that of plasmids containing the T allele of rs326221458 and control groups. The binding ability of miR-9828-3p to sequences containing the T allele was less than that of sequences containing the G allele. The overexpression of miR-9828-3p in porcine neuroglial cells (PNGCs) and PK15 cells significantly decreased the mRNA and protein levels of the JARID2 gene. In addition, miR-9828-3p inhibited the proliferation of PNGCs. After inhibiting miR-9828-3p, the mRNA and protein expression levels of JARID2 increased, and the proliferation of PNGCs showed an opposite trend to the cells that forced the expression of miR-9828-3p. In addition, interference with the JARID2 gene by siRNA can effectively inhibit the proliferation of PNGCs. In summary, we found that the rs326221458 locus regulates the expression of the JARID2 gene by affecting the binding of miR-9828-3p and the JARID2 gene, thereby affecting the aggressive behavior of weaned pigs after mixing.

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.

Functional Insight into and Refinement of the Genomic Boundaries of the JARID2-Neurodevelopmental Disorder Episignature

JARID2 (Jumonji, AT-rich interactive domain 2) haploinsufficiency is associated with a clinically distinct neurodevelopmental syndrome. It is characterized by intellectual disability, developmental delay, autistic features, behavior abnormalities, cognitive impairment, hypotonia, and dysmorphic features. JARID2 acts as a transcriptional repressor protein that is involved in the regulation of histone methyltransferase complexes. JARID2 plays a role in the epigenetic machinery, and the associated syndrome has an identified DNA methylation episignature derived from sequence variants and intragenic deletions involving JARID2. For this study, our aim was to determine whether patients with larger deletions spanning beyond JARID2 present a similar DNA methylation episignature and to define the critical region involved in aberrant DNA methylation in 6p22-p24 microdeletions. We examined the DNA methylation profiles of peripheral blood from 56 control subjects, 13 patients with (likely) pathogenic JARID2 variants or patients carrying copy number variants, and three patients with JARID2 VUS variants. The analysis showed a distinct and strong differentiation between patients with (likely) pathogenic variants, both sequence and copy number, and controls. Using the identified episignature, we developed a binary model to classify patients with the JARID2-neurodevelopmental syndrome. DNA methylation analysis indicated that JARID2 is the driver gene for aberrant DNA methylation observed in 6p22-p24 microdeletions. In addition, we performed analysis of functional correlation of the JARID2 genome-wide methylation profile with the DNA methylation profiles of 56 additional neurodevelopmental disorders. To conclude, we refined the critical region for the presence of the JARID2 episignature in 6p22-p24 microdeletions and provide insight into the functional changes in the epigenome observed when regulation by JARID2 is lost.

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.

Episignature Mapping of TRIP12 Provides Functional Insight into Clark-Baraitser Syndrome

Clark-Baraitser syndrome is a rare autosomal dominant intellectual disability syndrome caused by pathogenic variants in the TRIP12 (Thyroid Hormone Receptor Interactor 12) gene. TRIP12 encodes an E3 ligase in the ubiquitin pathway. The ubiquitin pathway includes activating E1, conjugating E2 and ligating E3 enzymes which regulate the breakdown and sorting of proteins. This enzymatic pathway is crucial for physiological processes. A significant proportion of TRIP12 variants are currently classified as variants of unknown significance (VUS). Episignatures have been shown to represent a powerful diagnostic tool to resolve inconclusive genetic findings for Mendelian disorders and to re-classify VUSs. Here, we show the results of DNA methylation episignature analysis in 32 individuals with pathogenic, likely pathogenic and VUS variants in TRIP12. We identified a specific and sensitive DNA methylation (DNAm) episignature associated with pathogenic TRIP12 variants, establishing its utility as a clinical biomarker for Clark-Baraitser syndrome. In addition, we performed analysis of differentially methylated regions as well as functional correlation of the TRIP12 genome-wide methylation profile with the profiles of 56 additional neurodevelopmental disorders.