Muscle microRNAs in the cerebrospinal fluid predict clinical response to nusinersen therapy in type II and type III spinal muscular atrophy patients

270th ENMC International Workshop: Consensus for SMN2 genetic analysis in SMA patients 10-12 March, 2023, Hoofddorp, the Netherlands

The 270th ENMC workshop aimed to develop a common procedure to optimize the reliability of SMN2 gene copy number determination and to reinforce collaborative networks between molecular scientists and clinicians. The workshop involved neuromuscular and clinical experts and representatives of patient advocacy groups and industry. SMN2 copy number is currently one of the main determinants for therapeutic decision in SMA patients: participants discussed the issues that laboratories may encounter in this molecular test and the cruciality of the accurate determination, due the implications as prognostic factor in symptomatic patients and in individuals identified through newborn screening programmes. At the end of the workshop, the attendees defined a set of recommendations divided into four topics: SMA molecular prognosis assessment, newborn screening for SMA, SMN2 copies and treatments, and modifiers and biomarkers. Moreover, the group draw up a series of recommendations for the companies manufacturing laboratory kits, that will help to minimize the risk of errors, regardless of the laboratories' expertise.

Role of circulating biomarkers in spinal muscular atrophy: insights from a new treatment era

Spinal muscular atrophy (SMA) is a lower motor neuron disease due to biallelic mutations in the SMN1 gene on chromosome 5. It is characterized by progressive muscle weakness of limbs, bulbar and respiratory muscles. The disease is usually classified in four different phenotypes (1-4) according to age at symptoms onset and maximal motor milestones achieved. Recently, three disease modifying treatments have received approval from the Food and Drug Administration (FDA) and the European Medicines Agency (EMA), while several other innovative drugs are under study. New therapies have been game changing, improving survival and life quality for SMA patients. However, they have also intensified the need for accurate biomarkers to monitor disease progression and treatment efficacy. While clinical and neurophysiological biomarkers are well established and helpful in describing disease progression, there is a great need to develop more robust and sensitive circulating biomarkers, such as proteins, nucleic acids, and other small molecules. Used alone or in combination with clinical biomarkers, they will play a critical role in enhancing patients' stratification for clinical trials and access to approved treatments, as well as in tracking response to therapy, paving the way to the development of individualized therapeutic approaches. In this comprehensive review, we describe the foremost circulating biomarkers of current significance, analyzing existing literature on non-treated and treated patients with a special focus on neurofilaments and circulating miRNA, aiming to identify and examine their role in the follow-up of patients treated with innovative treatments, including gene therapy.

Cerebrospinal Fluid Proteomic Changes after Nusinersen in Patients with Spinal Muscular Atrophy

Disease-modifying treatments have transformed the natural history of spinal muscular atrophy (SMA), but the cellular pathways altered by SMN restoration remain undefined and biomarkers cannot yet precisely predict treatment response. We performed an exploratory cerebrospinal fluid (CSF) proteomic study in a diverse sample of SMA patients treated with nusinersen to elucidate therapeutic pathways and identify predictors of motor improvement. Proteomic analyses were performed on CSF samples collected before treatment (T0) and at 6 months (T6) using an Olink panel to quantify 1113 peptides. A supervised machine learning approach was used to identify proteins that discriminated patients who improved functionally from those who did not after 2 years of treatment. A total of 49 SMA patients were included (10 type 1, 18 type 2, and 21 type 3), ranging in age from 3 months to 65 years. Most proteins showed a decrease in CSF concentration at T6. The machine learning algorithm identified ARSB, ENTPD2, NEFL, and IFI30 as the proteins most predictive of improvement. The machine learning model was able to predict motor improvement at 2 years with 79.6% accuracy. The results highlight the potential application of CSF biomarkers to predict motor improvement following SMA treatment. Validation in larger datasets is needed.

microRNA-based predictor for diagnosis of frontotemporal dementia

AIMS

This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.

METHODS

We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).

RESULTS

On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases.

CONCLUSIONS

The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.

Molecular Biomarkers for the Diagnosis, Prognosis, and Pharmacodynamics of Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is a progressive degenerative illness that affects 1 in every 6 to 11,000 live births. This autosomal recessive disorder is caused by homozygous deletion or mutation of the SMN1 gene (survival motor neuron). As a backup, the SMN1 gene has the SMN2 gene, which produces only 10% of the functional SMN protein. Nusinersen and risdiplam, the first FDA-approved medications, act as SMN2 pre-mRNA splicing modifiers and enhance the quantity of SMN protein produced by this gene. The emergence of new therapies for SMA has increased the demand for good prognostic and pharmacodynamic (response) biomarkers in SMA. This article discusses current molecular diagnostic, prognostic, and pharmacodynamic biomarkers that could be assessed in SMA patients' body fluids. Although various proteomic, genetic, and epigenetic biomarkers have been explored in SMA patients, more research is needed to uncover new prognostic and pharmacodynamic biomarkers (or a combination of biomarkers).

Identifying Biomarkers of Spinal Muscular Atrophy for Further Development

BACKGROUND

Spinal muscular atrophy (SMA) is caused by bi-allelic, recessive mutations of the survival motor neuron 1 (SMN1) gene and reduced expression levels of the survival motor neuron (SMN) protein. Degeneration of alpha motor neurons in the spinal cord causes progressive skeletal muscle weakness. The wide range of disease severities, variable rates of decline, and heterogenous clinical responses to approved disease-modifying treatment remain poorly understood and limit the ability to optimize treatment for patients. Validation of a reliable biomarker(s) with the potential to support early diagnosis, inform disease prognosis and therapeutic suitability, and/or confirm response to treatment(s) represents a significant unmet need in SMA.

OBJECTIVES

The SMA Multidisciplinary Biomarkers Working Group, comprising 11 experts in a variety of relevant fields, sought to determine the most promising candidate biomarker currently available, determine key knowledge gaps, and recommend next steps toward validating that biomarker for SMA.

METHODS

The Working Group engaged in a modified Delphi process to answer questions about candidate SMA biomarkers. Members participated in six rounds of reiterative surveys that were designed to build upon previous discussions.

RESULTS

The Working Group reached a consensus that neurofilament (NF) is the candidate biomarker best poised for further development. Several important knowledge gaps were identified, and the next steps toward filling these gaps were proposed.

CONCLUSIONS

NF is a promising SMA biomarker with the potential for prognostic, predictive, and pharmacodynamic capabilities. The Working Group has identified needed information to continue efforts toward the validation of NF as a biomarker for SMA.

Response of plasma microRNAs to nusinersen treatment in patients with SMA

OBJECTIVE

Spinal muscular atrophy (SMA) is a common genetic cause of infant mortality. Nusinersen treatment ameliorates the clinical outcome of SMA, however, some patients respond well, while others have limited response. We investigated microRNAs in blood samples from SMA patients and their response to nusinersen treatment evaluating the potential of circulating microRNAs as biomarkers for SMA.

METHODS

In a discovery cohort study, microRNA next-generation sequencing was performed in blood samples from SMA patients (SMA type 2, n = 10; SMA type 3, n = 10) and controls (n = 7). The dysregulated microRNAs were further analysed in the therapeutic response cohort comprised of SMA type 1 patients (n = 22) who had received nusinersen treatment, at three time points along the treatment course (baseline, 2 and 6 months of treatment). The levels of the studied microRNAs were correlated to the SMA clinical outcome measures.

RESULTS

In the discovery cohort, 69 microRNAs were dysregulated between SMA patients and controls. In the therapeutic response cohort, the baseline plasma levels of miR-107, miR-142-5p, miR-335-5p, miR-423-3p, miR-660-5p, miR-378a-3p and miR-23a-3p were associated with the 2 and 6 months response to nusinersen treatment. Furthermore, the levels of miR-107, miR-142-5p, miR-335-5p, miR-423-3p, miR-660-5p and miR-378-3p at 2 months of treatment were associated with the response after 6 months of nusinersen treatment.

INTERPRETATION

Blood microRNAs could be used as biomarkers to indicate SMA patients' response to nusinersen and to monitor the efficacy of the therapeutic intervention. In addition, some of these microRNAs provide insight into processes involved in SMA that could be exploited as novel therapeutic targets.