Due to the limited amount of information, modeling longitudinal rare-disease data can benefit from integrating clinical knowledge. Yet, elicitation of expert knowledge and formalization for model fitting is challenging, in particular due to limited time of clinical experts. To nevertheless make domain knowledge accessible during model fitting, we use large language models (LLMs) as synthetic clinical experts to supervise a variational-autoencoder-based approach that learns low-dimensional latent summaries of visit-level observations. Specifically, LLMs are queried offline on textual descriptions of patient observations to obtain judgments, e.g., the suspected clinical category. To improve the variational autoencoder fit, we train a differentiable surrogate model on these judgments and augment the loss function to encourage reconstructions that preserve the clinical-label distribution of their corresponding input profile. In an application to longitudinal motor-function assessments from children with spinal muscular atrophy, we map visit-level clinical profiles to low-dimensional representations that are linked by a multivariate mixed-effects model. The synthetic expert loss discourages reconstructions that remain numerically close in data space but alter the clinical interpretation of the reconstructed motor function profile, such as by crossing a disease-type boundary. We thus reduced disagreement between original and reconstructed SMA type labels from about 11 to 7 percent. Furthermore, informing the latent representation by the synthetic expert improved prediction of motor function milestones compared with unsupervised latent representations and a data-level baseline. These results suggest that incorporating LLMs into model fitting can make clinical knowledge available to representation learning and improve clinical faithfulness for longitudinal rare-disease data.

Newborn screening (NBS) and its genetic version, genetic NBS (gNBS), are now used to identify a broad range of conditions, including metabolic, endocrine, and genetic disorders, leading to significant reductions in infant mortality and long-term complications. Advances in genomic technologies, particularly next-generation sequencing, have enhanced the ability to detect rare diseases early, using gNBS, improving long-term outcomes. The availability and scope of gNBS vary across countries, influenced by national policies and technological advancements. This systematic literature review aims to clarify the specific barriers, opportunities, and more general attitudes that stakeholders express about gNBS for rare diseases. We extracted articles from 2010 to 2022. We followed the PRISMA guidelines and registered the review via PROSPERO (CRD42022297678). From an initial retrieval of 4519 records, two selection rounds resulted in a final list of 112 articles, which were assessed across different categories exploring various aspects of gNBS. The most important perceived opportunities in gNBS were the benefits of early intervention to reduce the burden of the diagnostic odyssey. The main identified barriers included three key codes: the stress and risk associated with false results and dealing with uncertainty (n = 25), the psychosocial implications (n = 26), and misunderstandings due to lack of education or communication. The majority of respondents expressed positive views, particularly regarding actionability. The results indicate a generally favourable attitude toward newborn screening, with subtle variations in viewpoints. Our findings on these themes can specifically inform how final attitudes are shaped based on particular aspects.

Background:Spinal Muscular Atrophy (SMA) is a phenotypically heterogenous disease. The Survival Motor Neuron 2 (SMN2) gene copy number can partially predict the clinical severity of SMA, with a single SMN2 copy generally associated with the most severe phenotypes. The aim of this retrospective observational study was to explore the spectrum of phenotypes associated with one SMN2 copy and the possible association with genotype and outcome. Methods:We conducted a retrospective observational study of individuals with genetically confirmed SMA (biallelic Survival Motor Neuron 1 [SMN1] variants) and one SMN2 copy, recruited from 36 Italian neuromuscular centres and additional 28 centres from nine other countries (Austria, Belgium, Brazil, Chile, Germany, Netherlands, Spain, United Kingdom and United States) between January 2015 and November 2025.Individuals were included irrespective of age or phenotype; those with incomplete genetic data or confounding diagnoses were excluded. The primary outcome was the phenotypic spectrum associated with a single SMN2 copy, including clinical severity, genotype, treatment exposure, and survival at last follow-up. Findings:Sixty-five individuals with one SMN2 copy were included. Neonatal onset was observed in 50/65 (77%). The predominant phenotype was type 0 (39/50, 78%), followed by type 1.1 (6/50, 12%). Five individuals with neonatal onset had prenatal signs (reduced foetal movements and cardiac malformation), but no contractures reported. All individuals with neonatal onset had homozygous deletions of SMN1. The remaining 15/65 (23%) had later onset, with milder phenotypes and all but two presented either with an heterozygous SMN1 deletion associated with a point mutation, or with c.859G>C(p.Gly287Arg) variant in SMN2. Interpretation:Our findings confirm that type 0 is the most frequent phenotype associated with one SMN2 copy, but the boundaries between neonatal-onset phenotypes appear to be fluid. The individuals with one SMN2 copy with milder phenotypes carried variants known to mitigate disease severity. Further prospective studies are needed to better define genotype-phenotype correlations and inform treatment decisions in this population. Funding:Some of the data in this study originate from disease registries at least partially funded by Biogen, Novartis and Roche.

Real-world treatments for 5q-spinal muscular atrophy (SMA) have evolved rapidly following the sequential approval of three disease-modifying treatments (DMTs): nusinersen, onasemnogene abeparvovec and risdiplam. The aim of this study was to map the sequence and timing of SMA treatments accurately using the SMArtCARE registry, a disease-specific registry for patients with SMA across 84 participating centres in Germany, Austria and Switzerland. All patients registered in SMArtCARE were included in the analysis. Patients were grouped based on their treatment regimen: those who remained on the first DMT versus those who switched DMT. The impacts of clinical and genetic factors on treatment decisions were evaluated, including age at initiation of treatment, SMN2 copy number, motor function status, the need for ventilator support or tube feeding, and the presence of scoliosis. A total of 2140 patients were included. Of these, 1294 patients (60.5%) initiated treatment with nusinersen, 514 patients (24.0%) with risdiplam and 243 patients (11.4%) with onasemnogene abeparvovec. Overall, 1366 patients (63.8%) remained on the first DMT. Most treatment switches occurred shortly after approval of a new DMT. Notably, most patients who switched showed no change in motor milestone status between the start of the first and the second DMT. In this large real-world cohort, we present the first comprehensive analysis of SMA treatment patterns across all age groups and disease severities. Although most patients remained on the first DMT, switches were observed, mainly after DMT approvals. Decisions to switch appear multifactorial and are not related directly to motor function effectiveness.

BACKGROUND:Systematic protocols for long-term surveillance of children with spinal muscular atrophy treated with onasemnogene abeparvovec are lacking. Together with best practice recommendations for safety monitoring and management, such recommendations should increase patient safety and confidence levels of healthcare providers. OBJECTIVE:Based on systematic literature review and evidence grading from part 1, this initiative aims to develop a structured treatment plan applicable across all treatment centers in Germany, Austria and Switzerland. Additionally, it seeks to establish consensus recommendations for the clinical management of safety alerts. METHODS:Part 2 describes the methodology used to formulate Delphi consensus statements, the development of a structured treatment plan for OA treatment, and the anonymous consensus voting process with standardized follow-up in case of disagreement. RESULTS:A total of 12 consensus statements were developed, addressing diagnostic work-up, safety evaluation, and best practice management of common adverse drug reactions associated with OA gene therapy. All statements achieved >95% consensus in the anonymous Delphi voting. Additionally, two consensus recommendations for handling of positive newborn screening result achieved consensus of 97% and 87%, respectively. A structured treatment plan for gene therapy was consented with 100% agreement, as were standardized recommendations for laboratory testing and a consensus-based algorithm for management of liver transaminase elevations. CONCLUSIONS:Delphi-based expert recommendations, developed in co-creation with patient representatives, provide a framework to minimize complications associated with gene therapy and establish the basis for standardized post-marketing data collections. The methodology used in this Delphi-consensus-group can serve as a blueprint for future gene therapy approvals.

Collagen VI-related dystrophies manifest with a spectrum of clinical phenotypes, ranging from Ullrich congenital muscular dystrophy (UCMD), presenting with prominent congenital symptoms and characterized by progressive muscle weakness, joint contractures and respiratory insufficiency, to Bethlem muscular dystrophy, with milder symptoms typically recognized later and at times resembling a limb girdle muscular dystrophy, and intermediate phenotypes falling between UCMD and Bethlem muscular dystrophy. Despite clinical and muscle pathology features highly suggestive of collagen VI-related dystrophy, some patients had remained without an identified causative variant in COL6A1, COL6A2 or COL6A3. With combined muscle RNA sequencing and whole-genome sequencing, we uncovered a recurrent, de novo deep intronic variant in intron 11 of COL6A1 (c.930+189C>T) that leads to a dominantly acting in-frame pseudoexon insertion. We subsequently identified and have characterized an international cohort of 44 patients with this COL6A1 intron 11 causative variant, one of the most common recurrent causative variants in the collagen VI genes. Patients manifest a consistently severe phenotype characterized by a paucity of early symptoms followed by an accelerated progression to a severe form of UCMD, except for one patient with somatic mosaicism for this COL6A1 intron 11 variant who manifests a milder phenotype consistent with Bethlem muscular dystrophy. Partial amelioration of the disease phenotype in this individual provides a strong rationale for the development of our pseudoexon skipping therapy to successfully suppress the pseudoexon insertion, resulting in normal COL6A1 transcripts. We have previously shown that splice-modulating antisense oligomers applied in vitro effectively decreased the abundance of the mutant pseudoexon-containing COL6A1 transcripts to levels comparable to the in vivo scenario of the somatic mosaicism shown here, indicating that this therapeutic approach carries significant translational promise for ameliorating the severe form of UCMD caused by this common recurrent COL6A1 variant.

Background and objectivesThe severity of the phenotype of spinal muscular atrophy (SMA) is highly variable, yet little is known about the phenotypic variation among siblings. We systematically investigated the phenotypic variability of therapy-naïve 5q-SMA siblings leveraging a large multicentre cohort from the SMArtCARE registry.ResultsClinical information was available from 132 siblings of 65 families. There were 24 (18.2%) type 1, 38 (28.7%) type 2, 54 (40.9%) type 3 patients, and 16 (12.1%) presymptomatic individuals. In 17 families (32.1%), there was discordance in the type of SMA among symptomatic siblings. We found no influence of gender on discordance in SMA type among siblings (p = 0.528). The median age at disease onset within all sibships varied by 6 months (interquartile range (IQR) = 1-30). There was no correlation in age of onset among siblings (r = 0.405; p = 0.052). Among siblings who lost ambulation, the median interval between the start of wheelchair use was 12 months, but the maximal interval was 18 years. In one pair of siblings, one sibling lost the ability to walk at the age of 13, whereas the other sibling was still ambulatory at the age of 54. In 6 sibling pairs (9.5%), only one of both siblings had a history of scoliosis surgery. Analysing SMN2 copy numbers, in one sibling pair (1.8%) 1 SMN2 gene copy was detected, while 10 (17.5%) had 2 copies, 23 (40.4%) had 3 copies, and 17 (29.8%) had 4 copies. Concordance in SMN2 copy numbers across siblings was observed in 90% of families. With increasing SMN2 copy number, the median differences in age of onset among siblings increased without reaching statistical significance.ConclusionThis study reports considerable phenotypic variability in therapy-naïve SMA sibships that cannot solely be explained by differences in SMN2 copy numbers.

In a longitudinal clinical registry, different measurement instruments might have been used for assessing individuals at different time points. To combine them, we investigate deep learning techniques for obtaining a joint latent representation, to which the items of different measurement instruments are mapped. This corresponds to domain adaptation, an established concept in computer science for image data. Using the proposed approach as an example, we evaluate the potential of domain adaptation in a longitudinal cohort setting with a rather small number of time points, motivated by an application with different motor function measurement instruments in a registry of spinal muscular atrophy (SMA) patients. There, we model trajectories in the latent representation by ordinary differential equations (ODEs), where person-specific ODE parameters are inferred from baseline characteristics. The goodness of fit and complexity of the ODE solutions then allows to judge the measurement instrument mappings. We subsequently explore how alignment can be improved by incorporating corresponding penalty terms into model fitting. To systematically investigate the effect of differences between measurement instruments, we consider several scenarios based on modified SMA data, including scenarios where a mapping should be feasible in principle and scenarios where no perfect mapping is available. While misalignment increases in more complex scenarios, some structure is still recovered, even if the availability of measurement instruments depends on patient state. A reasonable mapping is feasible also in the more complex real SMA dataset. These results indicate that domain adaptation might be more generally useful in statistical modeling for longitudinal registry data.

Pooled risdiplam (EVRYSDI®) safety data were analysed from 465 symptomatic patients with Types 1–3 SMA in the FIREFISH (NCT02913482), SUNFISH (NCT02908685) and JEWELFISH (NCT03032172) studies (overall exposure: 1,292 patient-years [PY]). Data were also collected from 18 presymptomatic patients in RAIN- BOWFISH (NCT03779334). At the clinical cut-off dates, most treatment-related adverse events (AEs) were mild; none led to treatment withdrawal in any trial (N=483). In presymptomatic patients, the most common AEs per 100PY were vomiting (48.24), teething and pyrexia (41.35 each), nasal congestion (34.46) and diarrhoea and viral infection (27.57 each). In symptomatic patients, the overall rate of AEs decreased with continued treatment; there was decline in the rate of gastrointestinal AEs during the first 4 weeks of treatment and no observable trend in the rate of infection AEs in the first 6 months. In symptomatic patients, serious AEs (SAEs) were more frequent in Type 1 SMA. The rate of SAEs declined in Type 1 SMA but remained stable in Types 2/3 SMA. No SAEs were observed in presymptomatic patients. These data will add to the understanding of the long-term safety profile of risdiplam. Studies are ongoing; safety data will be published annually until patients complete 5 years of treatment.

Natural history data show that respiratory function is impaired in SMA patients. Observational studies have shown stabilization of respiratory function in adult SMA patients treated with nusinersen. However, long-term studies investigating the effect of nusinersen on respiratory function in adult SMA patients are rare. We examined respiratory function using forced vital capacity of predicted normal (FVC

An increasing number of adults with spinal muscular atrophy (SMA) wish to become parents. New disease-modifying therapies (DMT) have improved health outcomes and are expected to reduce disability in adults with SMA, but their current label prevents their use in pregnancy. While there is some information on pregnancy outcomes in the pre-DMT era, little has been published recently, and no ubiquitously accepted guidelines exist. Nonetheless, it is crucial to provide knowledgeable and open counselling, ideally in the context of treatments. Counseling for both adolescent and adult patients should include the subject of 'reproductive choices' when discussing the selection of DMTs for those considering parenthood. A multi-disciplinary team, including gynecologists and neurologists with expertise in neuromuscular disorders must closely monitor pregnant patients with SMA, preferably within disease registries, to detect potential complications early and ensure optimal treatment options are available. Real-world data in so far three patients with SMA showed a beneficial pregnancy outcome with nusinersen. It is anticipated that forthcoming real-world data will finally clarify the safety of administering Nusinersen during pregnancy, particularly in relation to child health and for preserving muscle function and preventing motor deterioration in the affected mother.

Background and objectives: Disease-modifying treatments (DMT) have dramatically changed phenotypes in patients with spinal muscular atrophy (SMA). Because publications regarding standards of care were published before DMTs emerged, detailed recommendations and guidelines for physiotherapeutic management are still lacking. The objective of this study was to map the physiotherapeutic management of patients with SMA within the SMArtCARE network, a disease-specific registry for patients with 5q-SMA with 83 participating centers in Germany, Switzerland, and Austria.Methods: An online survey using a modified Delphi approach was conducted among physiotherapists with two questionnaire rounds between June 2022 and June 2023. Seven physiotherapeutic experts developed and revised the questionnaires focusing on the main topics of stretching, positioning, mobility and exercise, and chest physiotherapy. The second questionnaire was based on eight different case studies.Results: The second questionnaire was sent to 148 participants with a response rate of 28%. Most of the physiotherapists were well experienced in treating SMA patients. There was a strong consensus that home-based stretching should be used in pediatric patients with contractures regardless of their motor function. Muscle strengthening training was considered to be essential for all sitters and for walkers with moderate motor function restriction by a strong consensus. For all patients with respiratory involvement there was a consensus for prophylactic respiratory therapy.Conclusion: Our results describe the current physiotherapeutic management and recommendations within the SMArtCARE network. These findings highlight the need for an individualized approach, and the necessity of developing and adjusting existing guidelines.

Ordinary differential equations (ODEs) can provide mechanistic models of temporally local changes of processes, where parameters are often informed by external knowledge. While ODEs are popular in systems modeling, they are less established for statistical modeling of longitudinal cohort data, e.g., in a clinical setting. Yet, modeling of local changes could also be attractive for assessing the trajectory of an individual in a cohort in the immediate future given its current status, where ODE parameters could be informed by further characteristics of the individual. However, several hurdles so far limit such use of ODEs, as compared to regression-based function fitting approaches. The potentially higher level of noise in cohort data might be detrimental to ODEs, as the shape of the ODE solution heavily depends on the initial value. In addition, larger numbers of variables multiply such problems and might be difficult to handle for ODEs. To address this, we propose to use each observation in the course of time as the initial value to obtain multiple local ODE solutions and build a combined estimator of the underlying dynamics. Neural networks are used for obtaining a low-dimensional latent space for dynamic modeling from a potentially large number of variables, and for obtaining patient-specific ODE parameters from baseline variables. Simultaneous identification of dynamic models and of a latent space is enabled by recently developed differentiable programming techniques. We illustrate the proposed approach in an application with spinal muscular atrophy patients and a corresponding simulation study. In particular, modeling of local changes in health status at any point in time is contrasted to the interpretation of functions obtained from a global regression. This more generally highlights how different application settings might demand different modeling strategies.

PURPOSE:Over 30 international studies are exploring newborn sequencing (NBSeq) to expand the range of genetic disorders included in newborn screening. Substantial variability in gene selection across programs exists, highlighting the need for a systematic approach to prioritize genes. METHODS:We assembled a data set comprising 25 characteristics about each of the 4390 genes included in 27 NBSeq programs. We used regression analysis to identify several predictors of inclusion and developed a machine learning model to rank genes for public health consideration. RESULTS:Among 27 NBSeq programs, the number of genes analyzed ranged from 134 to 4299, with only 74 (1.7%) genes included by over 80% of programs. The most significant associations with gene inclusion across programs were presence on the US Recommended Uniform Screening Panel (inclusion increase of 74.7%, CI: 71.0%-78.4%), robust evidence on the natural history (29.5%, CI: 24.6%-34.4%), and treatment efficacy (17.0%, CI: 12.3%-21.7%) of the associated genetic disease. A boosted trees machine learning model using 13 predictors achieved high accuracy in predicting gene inclusion across programs (area under the curve = 0.915, R2 = 84%). CONCLUSION:The machine learning model developed here provides a ranked list of genes that can adapt to emerging evidence and regional needs, enabling more consistent and informed gene selection in NBSeq initiatives.

Spinal muscular atrophy (SMA) is a severe neuromuscular disease, leading to progressive muscle weakness and potentially early mortality if untreated. Onasemnogene abeparvovec is a recombinant adeno-associated virus serotype 9 (rAAV9)-based gene therapy that has demonstrated improvements in survival and motor function for SMA patients. Here, we present a case of a patient diagnosed with a grade 1 pilocytic astrocytoma at the age of 2 years, approximately 8 months after onasemnogene abeparvovec treatment. Although vector genomes delivered by rAAVs persist primarily as episomes, rare integration events have been linked to tumor formation in neonate murine models. Therefore, we investigated the presence and possible integration of onasemnogene abeparvovec in formalin-fixed paraffin embedded (FFPE) and frozen tumor samples. In situ hybridization demonstrated variable transduction levels in individual tumor cells, while droplet digital PCR measured an average vector copy number ranging from 0.7 to 4.9 vector genomes/diploid genome. Integration site analysis identified a low number of integration sites that were not conserved between technical replicates, nor between FFPE and frozen samples, indicating that cells hosting integrating vector genomes represented a minority in the overall cell population. Thus, molecular analysis of the tumor tissue suggests that tumorigenesis was causally independent of the administration of onasemnogene abeparvovec.

Background Since the approval of onasemnogen abeparvovec (OA) for gene addition therapy in children with spinal muscular atrophy (SMA), there has been a considerable increase of evidence regarding its effectiveness and safety. Consequently, the previous recommendations needed to be revised. Objective The primary objective was to develop an evidence- and expert-based best practice protocol ensuring optimal patient safety and comprehensive support for affected families. The harmonization of treatment algorithms is expected to facilitate the collection of standardized real-world data, laying the foundation for future evidence-based adjustments. Methods A modified, two-part Delphi process was selected as a standardized methodology. Experts specializing in SMA from all 31 neuromuscular treatment centers within Germany, Austria and Switzerland, and patient advocacy groups participated in an industry-independent Delphi panel. Existing evidence concerning effectiveness, safety, and guidelines of OA was analyzed in a systematic literature followed by development of consensus statements regarding its effectiveness. Results Strong consensus was reached regarding the following statements on effectiveness: (1) OA gene addition therapy for SMA demonstrates a clear advantage compared to the natural progression of the disease. (2) Superiority of any of the three approved disease-modifying therapies has not been proven. (3) Earlier initiation of therapy with fewer symptoms and shorter disease duration leads to better outcomes. (4) There is no clinical evidence supporting the superiority of combining two treatments over monotherapy. Conclusions: The systematic literature analysis constitutes the basis for the subsequent part 2, which involves the generation of expert-based recommendations for the surveillance of SMA gene addition therapy.