Natural history of Type 2 and 3 spinal muscular atrophy: 2‐year NatHis‐SMA study

Mélanie Annoussamy; Andreea M Seferian; Aurore Daron; Yann Péréon; Claude Cances; Carole Vuillerot; Liesbeth De Waele; Vincent Laugel; Ulrike Schara; Teresa Gidaro; Charlotte Lilien; Jean‐Yves Hogrel; Pierre Carlier; Emmanuel Fournier; Linda Lowes; Ksenija Gorni; Myriam Ly‐Le Moal; Nicole Hellbach; Timothy Seabrook; Christian Czech; Ricardo Hermosilla; Laurent Servais; the NatHis‐SMA study group

doi:10.1002/acn3.51281

. 2020 Dec 24;8(2):359–373. doi: 10.1002/acn3.51281

Natural history of Type 2 and 3 spinal muscular atrophy: 2‐year NatHis‐SMA study

Mélanie Annoussamy ^1,², Andreea M Seferian ¹, Aurore Daron ³, Yann Péréon ⁴, Claude Cances ^5,⁶, Carole Vuillerot ^7,⁸, Liesbeth De Waele ^9,¹⁰, Vincent Laugel ¹¹, Ulrike Schara ¹², Teresa Gidaro ¹, Charlotte Lilien ^1,¹³, Jean‐Yves Hogrel ¹, Pierre Carlier ¹, Emmanuel Fournier ¹, Linda Lowes ¹⁴, Ksenija Gorni ¹⁵, Myriam Ly‐Le Moal ¹⁶, Nicole Hellbach ¹⁷, Timothy Seabrook ^17,^{^a}, Christian Czech ^17,^18,^{^a}, Ricardo Hermosilla ^17,^{^a}, Laurent Servais ^1,^13,^19,^✉; the NatHis‐SMA study group^{^b}

^¹Institute of Myology, GH Pitié Salpêtrière, Paris, France

^²Sysnav, Vernon, France

^³Centre de Référence des Maladies Neuromusculaires, CHU de Liège, Liege, Belgium

^⁴Centre de Référence Maladies Neuromusculaires Atlantique‐Occitanie‐Caraïbes, Hôpital Hôtel‐Dieu, Nantes, France

^⁵Centre de Référence des Maladies, Neuromusculaires, Hôpital des Enfants, Toulouse, France

^⁶Unité de Neurologie Pédiatrique, Hôpital des Enfants, Toulouse, France

^⁷Service de rééducation pédiatrique infantile L'Escale, Hôpital Mère Enfant, CHU‐Lyon, Bron, France

^⁸Neuromyogen Institute, CNRS, UMR 5310 INSERM U1217, Université de Lyon, Lyon, France

^⁹Department of Pediatric Neurology, University Hospitals Leuven, Leuven, Belgium

^¹⁰Department of Development and Regeneration, KU Leuven Kulak Kortrijk, Kortrijk, Belgium

^¹¹Neuropédiatrie, INSERM CIC 1434, CHU Strasbourg Hautepierre, Strasbourg, France

^¹²Paediatric neurology and Neuromuscular Center, University of Essen, Essen, Germany

^¹³Department of Paediatrics, MDUK Oxford Neuromuscular Centre, University of Oxford, Oxford, UK

^¹⁴Center for Gene Therapy, Nationwide Children's Hospital, Columbus, Ohio, USA

^¹⁵PDMA Neuroscience and Rare Disease, F. Hoffmann‐La Roche Ltd. Basel, Switzerland

^¹⁶Institut Roche, Boulogne‐Billancourt, France

^¹⁷Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland

^¹⁸Rare Disease Research Unit, Pfizer, Nice, France

^¹⁹Division of Child Neurology, Centre de Références des Maladies Neuromusculaires, Department of Pediatrics, University Hospital Liège & University of Liège, Liège, Belgium

Correspondence, Laurent Servais, MDUK Oxford Neuromuscular Centre, Department of Paediatrics, University of Oxford, Oxford, UK. Tel: +44742321337; Fax: +3243218266; E‐mail: laurent.servais@paediatrics.ox.ac.uk

^{^a}

No longer an employee of Roche at the time of publication.

^{^b}

Membership of the NatHis‐SMA study group is provided in the Acknowledgments.

^✉

Corresponding author.

PMCID: PMC7886049 PMID: 33369268

Abstract

Objective

To characterize the natural history of spinal muscular atrophy (SMA) over 24 months using innovative measures such as wearable devices, and to provide evidence for the sensitivity of these measures to determine their suitability as endpoints in clinical trials.

Methods

Patients with Type 2 and 3 SMA (N = 81) with varied functional abilities (sitters, nonsitters, nonambulant, and ambulant) who were not receiving disease‐modifying treatment were assessed over 24 months: motor function (Motor Function Measure [MFM]), upper limb strength (MyoGrip, MyoPinch), upper limb activity (ActiMyo^®), quantitative magnetic resonance imaging (fat fraction [FF_T2] mapping and contractile cross‐sectional area [C‐CSA]), pulmonary function (forced vital capacity [FVC], peak cough flow, maximum expiratory pressure, maximum inspiratory pressure, and sniff nasal inspiratory pressure), and survival of motor neuron (SMN) protein levels.

Results

MFM32 scores declined significantly over 24 months, but not 12 months. Changes in upper limb activity could be detected over 6 months and continued to decrease significantly over 12 months, but not 24 months. Upper limb strength decreased significantly over 12 and 24 months. FVC declined significantly over 12 months, but not 24 months. FF_T2 increased over 12 and 24 months, although not with statistical significance. A significant increase in C‐CSA was observed at 12 but not 24 months. Blood SMN protein levels were stable over 12 and 24 months.

Interpretation

These data demonstrate that the MFM32, MyoGrip, MyoPinch, and ActiMyo^® enable the detection of a significant decline in patients with Type 2 and 3 SMA over 12 or 24 months.

Introduction

Spinal muscular atrophy (SMA) is a severe, progressive neuromuscular disorder which leads to a progressive loss of motor function and reduced life expectancy. ¹ , ² , ³ , ⁴ SMA is caused by reduced levels of survival of motor neuron (SMN) protein due to deletions and/or mutations in the SMN1 gene. A second gene, SMN2, produces only low levels of functional SMN protein. ¹ , ² The pathophysiology resulting from reduced SMN protein levels is thought to affect multiple systems in the body. ³

SMA manifests as a broad spectrum of severities and is classified into clinical types based on the age of onset and the highest motor milestone achieved: ⁴ Type 1 (onset age < 6 months; patients are never able to sit independently), Type 2 (onset age < 18 months; patients acquire independent sitting but are unable to walk or stand independently), Type 3 (onset age > 18 months; patients achieve independent walking), and Type 4 (patients achieve motor milestones and symptoms develop in adulthood). However, while these classifications give some indication of expected survival and long‐term motor function, their predictive value is only moderate. ⁵ , ⁶ Therefore, the standard‐of‐care guidelines for SMA are now based on functional status (nonsitter, sitter, ambulant) instead of SMA type. ⁷

Three therapies are currently approved for the treatment of SMA: ⁸ nusinersen (SPINRAZA^® [Ionis Pharmaceuticals/Biogen]), an intrathecally administered SMN2‐targeting antisense oligonucleotide; ⁹ onasemnogene abeparvovec‐xioi (ZOLGENSMA^® [Novartis]), a gene‐transfer therapy that delivers a functional copy of an SMN1 gene by a single intravenous infusion in patients < 2 years old; ¹⁰ and risdiplam (EVRYSDI™ [Genentech, Inc.]), an orally administered SMN2 splicing modifier for adults and children ≥ 2 months old. ¹¹ These therapies have demonstrated improvements in survival and motor function; ¹² however, the long‐term efficacy of these treatments remains unknown, and access may be restricted by SMA type. ¹³ Therefore, there is a clear need to identify reliable outcome measures for different stages in SMA progression so that the full benefit or limitation of a potential therapy can be recognized, and patient burden reduced.

A key challenge with current clinical assessments relates to the slow progression of SMA. Unlike Type 1 SMA, in which rapid deterioration occurs, Type 2 and 3 SMA progress slowly, so decline can be challenging to detect over short periods using current measures such as the Revised Upper Limb Module (RULM), 6‐min walk test (6MWT), and Expanded Hammersmith Functional Motor Scale (HFMSE). ⁵ The inability of the HFMSE to capture some small functional changes in patients with Type 2 and 3 SMA was demonstrated in a natural history study which showed that pulmonary and motor function outcome measures remained relatively stable over 12 months, requiring longitudinal observational studies to extend beyond 12 months. ¹⁴ More recently, in two double‐blind, placebo‐controlled studies, the Motor Function Measure (MFM), ¹⁵ , ¹⁶ and RULM ¹⁶ captured a significant difference between treated and untreated patients, while the HFMSE failed to do this.

To reduce the number of patients included to adequately power clinical trials, the risk of false negatives, and the duration of clinical trials, more sensitive outcome measures are needed. This is true for all patients with Type 2 and 3 SMA, especially older patients with a longer disease duration, who have been shown to have a reduced response to disease‐modifying treatments. ¹⁷ Additionally, the increasing use of add‐on therapy in clinical trials, in which the effect of a second drug is smaller and more variable than a single drug compared with placebo, further highlights the need for more sensitive outcome measures to detect small functional changes.

Novel outcome measures aim to overcome some of the difficulties faced when using current clinical measures by capturing small functional changes over shorter periods. Recent studies have demonstrated the feasibility of wearable devices, such as ActiMyo^®, which generate digital measurements and allow patients to be monitored remotely in their daily lives. This enables real‐world longitudinal data to be captured in a way that is currently not possible in a clinical setting. ¹⁸ Furthermore, such measures facilitate a deeper understanding of the natural history of SMA, which may lead to better‐informed treatment decisions, such as those related to continuing or modifying treatment.

Here, we present data of a 24‐month observational natural history study, which may be one of the last in SMA due to an increasing number of patients receiving SMA treatment as a result of the recent approval of disease‐modifying treatments. Data from the MFM are presented to characterize the disease course over 24 months in patients with Type 2 and 3 SMA. Further assessments include muscle strength (digital measures assessed by performance in grip and pinch strength tests through wearable devices), fat fraction (FF_T2), and pulmonary function tests for the identification of (1) prognostic variables of SMA, (2) best‐outcome measures for future treatment studies, and (3) SMN biomarkers.

Methods

Study design and analysis population

The 2‐year NatHis‐SMA study was conducted between May 2015 and May 2018 in nine neuromuscular disease reference centers (located in Belgium, France, and Germany). Protocol approval was authorized in France by the regulatory health authority and the central Ethics committee and approved in Liège, Leuven, and Essen by the local Ethics Committees. Parental/legal guardian consent was obtained prior to inclusion in the study. The study is registered on ClinicalTrials.gov (NCT02391831).

Patient population

Baseline patient characteristics for this study have been published previously. ¹⁹ Patients included were aged 2–30 years, with Type 2 SMA (n = 53 [nonsitters, n = 19; sitters, n = 34]) or Type 3 SMA (n = 28 [nonambulant, n = 9; ambulant, n = 19]). Nonsitters are defined as patients with Type 2 SMA who scored 0 on Item 9 of the MFM, while sitters are patients with Type 2 SMA who scored ≥ 1 on Item 9 of the MFM. Ambulant is defined as patients able to walk 10 meters without assistance. Functional status was determined at baseline and was not changed regardless of whether a patient's status changed over time. Assessments were adjusted for each patient based on age (2–5 years old and 6–30 years old) and ambulant status. Exclusion criteria included patients exposed to disease‐modifying treatments within the 6 months prior to study recruitment, patients with comorbid conditions that could significantly interfere with disease outcome measures and pregnant or breastfeeding women.

Protocol

Outcomes assessed during the study include motor function (MFM), upper limb strength (MyoGrip, MyoPinch), upper limb activity (ActiMyo^®), quantitative magnetic resonance imaging (MRI) (FF_T2 mapping and muscle contractile cross‐sectional area [C‐CSA]), pulmonary tests (forced vital capacity [FVC], peak cough flow [PCF], maximum expiratory pressure [MEP], maximum inspiratory pressure [MIP], and sniff nasal inspiratory pressure [SNIP]), and measurement of blood SMN protein levels. These outcomes were evaluated at baseline and then every 6 months (±28 days) for the 24‐month duration of the study, except for the MRI assessment (performed annually in two French centers). The full protocol for this trial has been published previously. ¹⁹ One‐year ActiMyo^® data are only available for a limited number of patients due to lack of availability of ActiMyo^® devices at the time (Month 6, n = 25 [ambulant, n = 6; nonambulant, n = 19]; Month 12, n = 17 [ambulant, n = 4; nonambulant, n = 13]; Month 18, n = 7 [ambulant, n = 1; nonambulant, n = 6]; Month 24, n = 2 [ambulant, n = 1; nonambulant, n = 1]).

Other assessments measured during this study, including electrophysiological parameters, quality of life, and detailed MRI, are to be published separately.

Outcome measures

Motor function assessment

The MFM assesses motor function across three domains: standing position, ambulation, and transfers (D1), axial and proximal motor function (D2), and distal motor function (D3). A 4‐point Likert scale is used to rate the patient's maximal functional ability; higher scores indicate a higher level of function. MFM32, a 32‐item scale, was used for patients aged ≥ 6 years and the MFM20, a 20‐item scale, was used for children 2–5 years old. For patients 4–6 years old, the physiotherapist selected the most appropriate version based on the child's motor function abilities and overall development. The same scale was used throughout the study for each patient.

Upper limb strength assessment

Dominant and nondominant hand strength was assessed with the MyoGrip and MyoPinch devices (Ateliers Laumonier, Nesles‐la‐Vallée, France) in patients ≥ 6 years old, as previously described. ¹⁹ , ²⁰ , ²¹ MyoGrip measures handgrip forces from 0 to 90 kg, and MyoPinch measures key pinch with a nominal scale of 10 kg. ²² Patients were given at least three attempts on both arms to demonstrate maximal isometric grip and key pinch strength. If improvements between attempts were observed, patients were given up to two additional attempts. Results are expressed as a percentage of predicted values based on age ²³ with the maximal value used for analysis. Higher values reflect a higher level of upper arm strength.

Continuous movement recording

Upper arm activity was assessed with ActiMyo^® in a subset of nonambulant patients ≥ 6 years old, as previously described. ¹⁹ ActiMyo^® is a wearable device (Sysnav, Vernon, France) that measures patient movement in a real‐life setting. ²⁰ , ²⁴ The device was worn daily to longitudinally assess individualized changes in activity. One sensor was worn on the wrist, and the other was attached to the wheelchair. Five variables representing upper limb activity were generated: the wrist angular velocity (||Ω||), the wrist acceleration (||A||), the wrist vertical acceleration against gravity (vA), and the power and the percentage of activity time. Higher values reflect a higher level of upper limb activity.

In a limited number of ambulant patients, ActiMyo^® was also used to measure stride length and velocity. ²⁴ , ²⁵ The 95th percentile of the stride‐velocity distribution has been recently qualified by the European Medicines Agency and has a valid secondary outcome in Duchenne Muscular Dystrophy (DMD). ²⁵

MRI muscle assessment

FF_T2 maps were derived from quantitative water‐fat imaging obtained using a 3‐point Dixon 3D gradient echo sequence; the Dixon‐based regions of interest were used in combination with the FF_T2 mapping to provide the C‐CSA, as previously described. ¹⁹ These assessments were carried out in one study site with a limited number of patients. FF_T2 and C‐CSA were calculated separately for arms, forearms, legs, and thighs based on outputs for different muscle groups (see supplemental material for more detailed information).

Pulmonary function tests

Patients ≥ 6 years performed several assessments while in the sitting position: FVC, PCF, MEP, MIP, and SNIP. FVC and PCF were measured using the Vitalograph spirometer and software, while MEP, MIP, and SNIP were evaluated using the MicroRPM device. Assessment results are expressed as percentages of predicted values based on age, weight, and height; ²⁶ , ²⁷ , ²⁸ , ²⁹ , ³⁰ the best results of three measurements were selected for further analysis. (See supplemental material for more detailed information).

SMN protein levels

Blood SMN protein levels were measured by an optimized SMN protein assay (see supplemental material for detailed information). SMN1 and SMN2 copy numbers were determined, as previously described. ¹⁹

Statistical analyses

Four functional status groups were predefined for comparison analyses: ¹⁹ nonsitters with Type 2 SMA, sitters with Type 2 SMA, nonambulant patients with Type 3 SMA, and ambulant patients with Type 3 SMA. To determine whether outcome measures could differentiate between patients in different groups, proportions were compared using the Chi‐square test, and quantitative variables were compared using the Kruskal–Wallis one‐way analysis of variance; post hoc analyses based on the Dunn‐Bonferroni method were performed for significant results. The Wilcoxon signed‐rank test was used to assess changes over time. The relationships between variables were examined using Spearman's correlation coefficients. Standardized response means (SRM) were calculated for all assessments. All analyses were performed using SPSS Statistics 22 Statistical software (IBM Corp, Armonk, NY). The limit of statistical significance was set to 0.05.

Results

Participant disposition at Month 24

Eighty‐one patients were enrolled in this study (Fig. 1). A high number of these participants (n = 32) discontinued the study between Months 12 and 24 to pursue approved treatments or enroll in clinical trials. Baseline MFM scores increased with decreasing SMA severity; nonsitters with Type 2 SMA had the lowest scores, while ambulant patients with Type 3 SMA had the highest scores. Further baseline clinical and physical characteristics have been previously published. ¹⁹

CONSORT diagram. Reasons for premature withdrawal include: (A) loss of follow‐up; (B) consent withdrawal; (C) physician decision; (D) enrollment into other clinical trials; (E) initiation of nusinersen treatment; (F) other; and (G) missed visit. SMA, spinal muscular atrophy.

Motor function

Overall, the MFM total score discriminated between the four functional groups (Fig. 2 and Fig. S1). At Month 12 (n = 40), there was a decrease in MFM32 median total score from baseline by 1.05 points (range: −14.58 to 5.21; [Wilcoxon test P = 0.073]; SRM: 0.37) in all patients with Type 2 and 3 SMA. This decrease was not significant. At Month 24 (n = 27), MFM32 median total score decreased significantly from baseline scores by 2.08 points (range: –17.71 to 4.17; [P = 0.009]; SRM: 0.55) in all patients (Table S1).

MFM total scores from baseline to 24 months in individuals with SMA according to age and SMA type. MFM20 was used in patients < 6 years of age; MFM32 was used in patients ≥ 6 years of age. For patients aged 4–6 years old, the physiotherapist selected the most appropriate version based on the child's motor function abilities. Each line represents the trajectory of one patient over 24 months. Assessments were made at baseline, Month 6, 12, 18, and 24. MFM, motor function measure; MFM20, 20‐item MFM; MFM32, 32‐item MFM.

There was a significant decrease in MFM32 median total score of −3.13 points (range −8.33 to 4.17; P = 0.041; SRM: 0.80) over 24 months in nonsitters with Type 2 SMA (n = 11) (Fig. S1, Table S1); however, no significant decrease was found in patients in other functional groups (sitters with Type 2 SMA [−1.56 points; P = 0.285; SRM: 0.57]; nonambulant patients with Type 3 SMA [−1.04 points; P = 0.680; SRM: 0.39]; and ambulant patients with Type 3 SMA [0.00 points; P = 0.465; SRM: 0.36]) (Table S1).

There were no significant changes in MFM20 scores. At Month 12, median MFM20 scores increased by 1.67 points (n = 30; [range: −18.33 to −13.33]; P = 0.430) and decreased by 3.34 points (n = 10; [range: −11.66 to 10.00]; P = 0.313) at Month 24.

Upper limb strength

Overall, there was a significant decrease in median grip strength of 0.53% of predictive value at Month 12 (n = 38; [Wilcoxon test P = 0.003]; SRM: 0.42) and 0.95% at Month 24 (n = 27; [P = 0.002]; SRM: 0.49) independent of the SMA subtype (Fig. 3A, Table S2). Large interindividual variability in grip strength among participants with Type 3 SMA was observed, which decreased globally over time (Fig. 3B). There was also an overall significant decrease in median pinch strength of 0.79% of predictive value at Month 12 (n = 37; [P = 0.016]; SRM: 0.35) and a decrease of 1.21% at Month 24 (n = 27; [P = 0.037]; SRM: 0.38) (Fig. 4A, Table S3). There was no correlation between age and median pinch strength (Fig. 4B).

Change in grip strength over 24 months by (A) SMA type and (B) age. Grip strength was measured as a percentage of predictive values based on age using MyoGrip at baseline, Month 6, 12, 18, and 24 (Month 12, n = 38; Month 24, n = 27). Higher values reflect a higher level of upper arm strength. A) Closed circles represent outliers. B) Each line represents the trajectory of one patient over 24 months. SMA, spinal muscular atrophy.

Change in mean pinch strength over 24 months by (A) SMA type and (B) age. Pinch strength was measured as a percentage of predictive values based on age using MyoPinch at baseline, Month 6, 12, 18, and 24. (Month 12, n = 37; Month 24, n = 27). Higher values reflect a higher level of upper arm strength. A) Closed circles represent outliers and B) Each line represents the trajectory of one patient over 24 months. SMA, spinal muscular atrophy.