Hypothesis and Theory: Roles of Arginine Methylation in C9orf72-Mediated ALS and FTD

Genome-Wide DNA Methylation in Early-Onset-Dementia Patients Brain Tissue and Lymphoblastoid Cell Lines

Epigenetics, a potential underlying pathogenic mechanism of neurodegenerative diseases, has been in the scope of several studies performed so far. However, there is a gap in regard to analyzing different forms of early-onset dementia and the use of Lymphoblastoid cell lines (LCLs). We performed a genome-wide DNA methylation analysis on sixty-four samples (from the prefrontal cortex and LCLs) including those taken from patients with early-onset forms of Alzheimer's disease (AD) and frontotemporal dementia (FTD) and healthy controls. A beta regression model and adjusted p-values were used to obtain differentially methylated positions (DMPs) via pairwise comparisons. A correlation analysis of DMP levels with Clariom D array gene expression data from the same cohort was also performed. The results showed hypermethylation as the most frequent finding in both tissues studied in the patient groups. Biological significance analysis revealed common pathways altered in AD and FTD patients, affecting neuron development, metabolism, signal transduction, and immune system pathways. These alterations were also found in LCL samples, suggesting the epigenetic changes might not be limited to the central nervous system. In the brain, CpG methylation presented an inverse correlation with gene expression, while in LCLs, we observed mainly a positive correlation. This study enhances our understanding of the biological pathways that are associated with neurodegeneration, describes differential methylation patterns, and suggests LCLs are a potential cell model for studying neurodegenerative diseases in earlier clinical phases than brain tissue.

Differential cortical gray matter changes in early- and late-onset patients with amyotrophic lateral sclerosis

Age at onset may be an important feature associated with distinct subtypes of amyotrophic lateral sclerosis (ALS). Little is known about the neuropathological mechanism of early-onset ALS (EO-ALS) and late-onset ALS (LO-ALS). Ninety ALS patients were divided into EO-ALS and LO-ALS group, and 128 healthy controls were matched into young controls(YCs) and old controls (OCs). A voxel-based morphometry approach was employed to investigate differences in gray matter volume (GMV). Significant age at onset-by-diagnosis interactions were found in the left parietal operculum, left precentral gyrus, bilateral postcentral gyrus, right occipital gyrus, and right orbitofrontal cortex. Post hoc analysis revealed a significant decrease in GMV in all affected regions of EO-ALS patients compared with YCs, with increased GMV in 5 of the 6 brain regions, except for the right orbitofrontal cortex, in LO-ALS patients compared with OCs. LO-ALS patients had a significantly increased GMV than EO-ALS patients after removing the aging effect. Correspondingly, GMV of the left postcentral gyrus correlated with disease severity in the 2 ALS groups. Our findings suggested that the pathological mechanisms in ALS patients with different ages at onset might differ. These findings provide unique insight into the clinical and biological heterogeneity of the 2 ALS subtypes.

The role of long noncoding RNAs in liquid-liquid phase separation

Long noncoding RNAs (lncRNAs), which are among the most well-characterized noncoding RNAs, have attracted much attention due to their regulatory functions and potential therapeutic options in many types of disease. Liquid-liquid phase separation (LLPS), the formation of droplet condensates, is involved in various cellular processes, but the molecular interactions of lncRNAs in LLPS are unclear. In this review, we describe the research development on LLPS, including descriptions of various methods established to identify LLPS, summarize the physiological and pathological functions of LLPS, identify the molecular interactions of lncRNAs in LLPS, and present the potential applications of leveraging LLPS in the clinic. The aim of this review is to update the knowledge on the association between LLPS and lncRNAs, which might provide a new direction for the treatment of LLPS-mediated disease.

Reduced C9orf72 expression exacerbates polyGR toxicity in patient iPSC-derived motor neurons and a Type I protein arginine methyltransferase inhibitor reduces that toxicity

Introduction

Intronic repeat expansions in the C9orf72 gene are the most frequent known single genetic causes of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). These repeat expansions are believed to result in both loss-of-function and toxic gain-of-function. Gain-of-function results in the production of toxic arginine-rich dipeptide repeat proteins (DPRs), namely polyGR and polyPR. Small-molecule inhibition of Type I protein arginine methyltransferases (PRMTs) has been shown to protect against toxicity resulting from polyGR and polyPR challenge in NSC-34 cells and primary mouse-derived spinal neurons, but the effect in human motor neurons (MNs) has not yet been explored.

Methods

To study this, we generated a panel of C9orf72 homozygous and hemizygous knockout iPSCs to examine the contribution of C9orf72 loss-of-function toward disease pathogenesis. We differentiated these iPSCs into spinal motor neurons (sMNs).

Results

We found that reduced levels of C9orf72 exacerbate polyGR15 toxicity in a dose-dependent manner. Type I PRMT inhibition was able to partially rescue polyGR15 toxicity in both wild-type and C9orf72-expanded sMNs.

Discussion

This study explores the interplay of loss-of-function and gain-of-function toxicity in C9orf72 ALS. It also implicates type I PRMT inhibitors as a possible modulator of polyGR toxicity.

Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis

OBJECTIVE

There is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.

METHODS

Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.

RESULTS

Compared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small-worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.

CONCLUSION

Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.