( CAG ) n loci as genetic modifiers of age at onset in patients with spinocerebellar ataxia type 1 from mainland China

Integration of multi-omics technologies for molecular diagnosis in ataxia patients

Background: Episodic ataxias are rare neurological disorders characterized by recurring episodes of imbalance and coordination difficulties. Obtaining definitive molecular diagnoses poses challenges, as clinical presentation is highly heterogeneous, and literature on the underlying genetics is limited. While the advent of high-throughput sequencing technologies has significantly contributed to Mendelian disorders genetics, interpretation of variants of uncertain significance and other limitations inherent to individual methods still leaves many patients undiagnosed. This study aimed to investigate the utility of multi-omics for the identification and validation of molecular candidates in a cohort of complex cases of ataxia with episodic presentation. Methods: Eight patients lacking molecular diagnosis despite extensive clinical examination were recruited following standard genetic testing. Whole genome and RNA sequencing were performed on samples isolated from peripheral blood mononuclear cells. Integration of expression and splicing data facilitated genomic variants prioritization. Subsequently, long-read sequencing played a crucial role in the validation of those candidate variants. Results: Whole genome sequencing uncovered pathogenic variants in four genes (SPG7, ATXN2, ELOVL4, PMPCB). A missense and a nonsense variant, both previously reported as likely pathogenic, configured in trans in individual #1 (SPG7: c.2228T>C/p.I743T, c.1861C>T/p.Q621*). An ATXN2 microsatellite expansion (CAG32) in another late-onset case. In two separate individuals, intronic variants near splice sites (ELOVL4: c.541 + 5G>A; PMPCB: c.1154 + 5G>C) were predicted to induce loss-of-function splicing, but had never been reported as disease-causing. Long-read sequencing confirmed the compound heterozygous variants configuration, repeat expansion length, as well as splicing landscape for those pathogenic variants. A potential genetic modifier of the ATXN2 expansion was discovered in ZFYVE26 (c.3022C>T/p.R1008*). Conclusion: Despite failure to identify pathogenic variants through clinical genetic testing, the multi-omics approach enabled the molecular diagnosis in 50% of patients, also giving valuable insights for variant prioritization in remaining cases. The findings demonstrate the value of long-read sequencing for the validation of candidate variants in various scenarios. Our study demonstrates the effectiveness of leveraging complementary omics technologies to unravel the underlying genetics in patients with unresolved rare diseases such as ataxia. Molecular diagnoses not only hold significant promise in improving patient care management, but also alleviates the burden of diagnostic odysseys, more broadly enhancing quality of life.

Genetic modifiers of repeat expansion disorders

Repeat expansion disorders (REDs) are monogenic diseases caused by a sequence of repetitive DNA expanding above a pathogenic threshold. A common feature of the REDs is a strong genotype-phenotype correlation in which a major determinant of age at onset (AAO) and disease progression is the length of the inherited repeat tract. Over a disease-gene carrier's life, the length of the repeat can expand in somatic cells, through the process of somatic expansion which is hypothesised to drive disease progression. Despite being monogenic, individual REDs are phenotypically variable, and exploring what genetic modifying factors drive this phenotypic variability has illuminated key pathogenic mechanisms that are common to this group of diseases. Disease phenotypes are affected by the cognate gene in which the expansion is found, the location of the repeat sequence in coding or non-coding regions and by the presence of repeat sequence interruptions. Human genetic data, mouse models and in vitro models have implicated the disease-modifying effect of DNA repair pathways via the mechanisms of somatic mutation of the repeat tract. As such, developing an understanding of these pathways in the context of expanded repeats could lead to future disease-modifying therapies for REDs.

Explainable artificial intelligence based on feature optimization for age at onset prediction of spinocerebellar ataxia type 3

Existing treatments can only delay the progression of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) after onset, so the prediction of the age at onset (AAO) can facilitate early intervention and follow-up to improve treatment efficacy. The objective of this study was to develop an explainable artificial intelligence (XAI) based on feature optimization to provide an interpretable and more accurate AAO prediction. A total of 1,008 affected SCA3/MJD subjects from mainland China were analyzed. The expanded cytosine-adenine-guanine (CAG) trinucleotide repeats of 10 polyQ-related genes were genotyped and included in related models as potential AAO modifiers. The performance of 4 feature optimization methods and 10 machine learning (ML) algorithms were compared, followed by building the XAI based on the SHapley Additive exPlanations (SHAP). The model constructed with an artificial neural network (ANN) and feature optimization of Crossing-Correlation-StepSVM performed best and achieved a coefficient of determination (R2) of 0.653 and mean absolute error (MAE), root mean square error (RMSE), and median absolute error (MedianAE) of 4.544, 6.090, and 3.236 years, respectively. The XAI explained the predicted results, which suggests that the factors affecting the AAO were complex and associated with gene interactions. An XAI based on feature optimization can improve the accuracy of AAO prediction and provide interpretable and personalized prediction.

Anxiety and depression in spinocerebellar ataxia patients during the COVID-19 pandemic in China: A cross-sectional study

Coronavirus disease 2019 (COVID-19) is currently a global concern, and the psychological impact cannot be overlooked. Our purpose was to evaluate the anxiety and depression in spinocerebellar ataxia (SCA) patients during the pandemic and to analyse the influencing factors. We conducted an online questionnaire survey among 307 SCA patients from China and selected 319 healthy people matched by sex and age as the control group. The questionnaire included general information, the self-rating anxiety scale (SAS), and the self-rating depression scale (SDS). The relevant factors included COVID-19 risk factors, age, sex, body mass index (BMI), educational background, disease course, score on the scale for the assessment and rating of ataxia (SARA), Mini-mental State Examination (MMSE) and International Cooperative Ataxia Rating Scale (ICARS). The proportion of SCA patients with anxiety was 34.9%, and the proportion with depression was 56.7%. The SAS and SDS scores of the SCA patients were significantly higher than those of the control group (SAS: 45.8 ± 10.1 vs. 40.6 ± 8.9, P < 0.01; SDS: 55.1 ± 12.2 vs. 43.6 ± 11.9, P < 0.01). In SCA3, the risk of exposure to COVID-19, educational level, disease course and the severity of ataxia may be factors affecting patients' mental health. More attention should be paid to the mental health of SCA patients during the COVID-19 pandemic.

Human stem cell models of polyglutamine diseases: Sources for disease models and cell therapy

Polyglutamine (polyQ) diseases are a group of neurodegenerative disorders involving expanded CAG repeats in pathogenic genes that are translated into extended polyQ tracts and lead to progressive neuronal degeneration in the affected brain. To date, there is no effective therapy for these diseases. Due to the complex pathologic mechanisms of these diseases, intensive research on the pathogenesis of their progression and potential treatment strategies is being conducted. However, animal models cannot recapitulate all aspects of neuronal degeneration. Pluripotent stem cells (PSCs), such as induced pluripotent stem cells (iPSCs) and embryonic stem cells (ESCs), can be used to study the pathological mechanisms of polyQ diseases, and the ability of autologous stem cell transplantation to treat these diseases. Differentiated PSCs, neuronal precursor cells/neural progenitor cells (NPCs) and mesenchymal stem cells (MSCs) are valuable resources for preclinical and clinical cell transplantation therapies. Here, we discuss diverse stem cell models and their ability to generate neurons involved in polyQ diseases, such as medium spiny neurons (MSNs), cortical neurons, cerebellar Purkinje cells (PCs) and motor neurons. In addition, we discuss potential therapeutic approaches, including stem cell replacement therapy and gene therapy.

Age is an important independent modifier of SCA3 phenotype severity

OBJECTIVE

This study aimed to investigate factors modulating spinocerebellar ataxia type 3 (SCA3) phenotype severity besides the expanded CAG repeats (ExpCAG) of ATXN3.

METHODS

Data regarding CAG trinucleotide repeats, age at onset (AO), duration, age, sex, transmitting parent, and scale scores of SCA3 patients were collected. Multiple linear regression analysis was performed to identify influential independent variables. Age, AO, ExpCAG, and duration were considered control variables to analyze the correlation between independent variables and scale scores.

RESULTS

Duration, age, and ExpCAG were screened as influential independent variables (P = 0.000). Age had the greatest impact on multiple linear regression models (P<5E-8). ExpCAG and SARA/ICARS/INAS/Barthel index were not correlated (P > 0.05); considering only age as the control, ExpCAG was slightly-to-moderately correlated with all aforementioned scores except INAS (P < 0.05). Age and all scores, except INAS, were positively correlated (P < 0.05); considering duration, AO, or ExpCAG as controls, their correlations did not change significantly. On controlling age, AO was negatively correlated with all scores (P < 0.05), except for the Barthel index (P > 0.05). Furthermore, the interaction model revealed that the interaction between age, duration, and ExpCAG was significantly associated with SCA3 disease severity (P < 0.05).

CONCLUSION

Age is a potentially important modifier of SCA3 phenotype severity, through the interaction between ExpCAG and aging factors.

PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation

From clinical observations to large-scale sequencing studies, the phenotypic impact of genetic modifiers is evident. To better understand the full spectrum of the genetic contribution to human disease, concerted efforts are needed to construct a useful modifier resource for interpreting the information from sequencing data. Here, we present the PhenoModifier (https://www.biosino.org/PhenoModifier), a manually curated database that provides a comprehensive overview of human genetic modifiers. By manually curating over ten thousand published articles, 3078 records of modifier information were entered into the current version of PhenoModifier, related to 288 different disorders, 2126 genetic modifier variants and 843 distinct modifier genes. To help users probe further into the mechanism of their interested modifier genes, we extended the yeast genetic interaction data and yeast quantitative trait loci to the human and we also integrated GWAS data into the PhenoModifier to assist users in evaluating all possible phenotypes associated with a modifier allele. As the first comprehensive resource of human genetic modifiers, PhenoModifier provides a more complete spectrum of genetic factors contributing to human phenotypic variation. The portal has a broad scientific and clinical scope, spanning activities relevant to variant interpretation for research purposes as well as clinical decision making.