Clinical Study of 8 Cases of CHD2 Gene Mutation–Related Neurological Diseases and Their Mechanisms

IGF1R and FLT1 in female endothelial cells and CHD2 in male microglia play important roles in Alzheimer's disease based on gender difference analysis

OBJECTIVE

This study investigated sex-specific pathogenesis mechanisms in Alzheimer's disease (AD) using single-nucleus RNA sequencing (snRNA-seq) data.

METHODS

Data from the Gene Expression Omnibus (GEO) were searched using terms "Alzheimer's Disease", "single cell", and "Homo sapiens". Studies excluding APOE E4 and including comprehensive gender information with 10× sequencing methods were selected, resulting in GSE157827 and GSE174367 datasets from human prefrontal cortex samples. Sex-stratified analyses were conducted on these datasets, and the outcomes of the analysis for GSE157827 were compared with those of GSE174367. The findings were validated using expression profiling from the mouse dataset GSE85162. Furthermore, real-time PCR experiments in mice further confirmed these findings. The Seurat R package was used to identify cell types, and batch effects were mitigated using the Harmony R package. Cell proportions by sex were compared using the Mann-Whitney-Wilcoxon test, and gene expression variability was displayed with an empirical cumulative distribution plot. Differentially expressed genes were identified using the FindMarkers function with the MAST test. Transcription factors were analyzed using the RcisTarget R package.

RESULTS

Seven cell types were identified: astrocytes, endothelial cells, excitatory neurons, inhibitory neurons, microglia, oligodendrocytes, and oligodendrocyte progenitor cells. Additionally, five distinct subpopulations of both endothelial and microglial cells were also identified, respectively. Key findings included: (1) In endothelial cells, genes involved in synapse organization, such as Insulin Like Growth Factor 1 Receptor (IGF1R) and Fms Related Receptor Tyrosine Kinase 1(FLT1), showed higher expression in females with AD. (2) In microglial cells, genes in the ribosome pathway exhibited higher expression in males without AD compared to females (with or without AD) and males with AD. (3) Chromodomain Helicase DNA Binding Protein 2 (CHD2) negatively regulated gene expression in the ribosome pathway in male microglia, suppressing AD, this finding was further validated in mice. (4) Differences between Asians and Caucasians were observed based on sex and disease status stratification.

CONCLUSIONS

IGF1R and FLT1 in endothelial cells contribute to AD in females, while CHD2 negatively regulates ribosome pathway gene expression in male microglia, suppressing AD in humans and mice.

Expanding the Mutational Landscape and Clinical Phenotype of CHD2-Related Encephalopathy

Objectives

To present a case series of novel CHD2 variants in patients presenting with genetic epileptic and developmental encephalopathy.

Background

CHD2 gene encodes an ATP-dependent enzyme, chromodomain helicase DNA-binding protein 2, involved in chromatin remodeling. Pathogenic variants in CHD2 are linked to early-onset conditions such as developmental and epileptic encephalopathy, drug-resistant epilepsies, and neurodevelopmental disorders. Approximately 225 diagnosed patients from 28 countries exhibit various allelic variants in CHD2, including small intragenic deletions/insertions and missense, nonsense, and splice site variants.

Results

We present the molecular and clinical characteristics of 17 unreported individuals from 17 families with novel pathogenic or likely pathogenic variants in CHD2. All individuals presented with severe global developmental delay, childhood-onset myoclonic epilepsy, and additional neuropsychiatric features, such as behavioral including autism, ADHD, and hyperactivity. Additional findings include abnormal reflexes, hypotonia and hypertonia, motor impairment, gastrointestinal problems, and kyphoscoliosis. Neuroimaging features included hippocampal signal alterations (4/10), with additional volume loss in 2 cases, inferior vermis hypoplasia (7/10), mild cerebellar atrophy (4/10), and cerebral atrophy (1/10).

Discussion

Our study broadens the geographic scope of CHD2-related phenotypes, providing valuable insights into the prevalence and clinical characteristics of this genetic disorder in previously underrepresented populations.

Clinical analysis of five CHD2 gene mutations in Chinese children with epilepsy

INTRODUCTION

Increasing evidence reveals critical roles for CHD2 in children with developmental and epileptic encephalopathy.

OBJECTIVES

The aim was to present clinical analysis results of five cases with CHD2 mutations and 157 reported cases with non-copy number variations (non-CNV) of CHD2.

METHODS

This study recruited pediatric epilepsy patients with CHD2 mutations and clinical data from November 2016 to October 2023 in the Linyi People's Hospital, China. Whole-exome and gene panel sequencing were employed to find mutations. The HGMD and PubMed databases were examined for documented cases that had CHD2 mutations.

RESULTS

This study reports five cases with CHD2 mutations: c.3543T > A, c.1850A > G, c.2536C > T, c.4233_4236del, c.3782G > C. Three novel mutations (c.3543T > A, c.1850A > G, c.2536C > T) have never been reported. c.4233_4236del has been reported in three cases, indicating that this locus may be a mutation hotspot. c.3782G > C has been reported in one case. All five patients had seizures before the age of four. Three patients had varying degrees of developmental delay, and four patients had varying degrees of intellectual disability. All of them had controlled seizures after Valproic acid (VPA) monotherapy or VPA in combination with other medications. Furthermore, we reviewed 157 reported cases having non-CNV mutations of CHD2. Most mutations of these cases were de novo. Epilepsy, developmental delay, and intellectual disability were the typical clinical phenotypes. We also found a significant clustering of the mutations near the C-terminus of the CHD2 protein (P < 0.001).

CONCLUSION

This study reports new CHD2 genotypes and analyzes reported CHD2 mutation cases. Given its significance in epileptic encephalopathies, research on the CHD2 gene may provide new insights into epileptogenesis.

Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment.