Abstract
Background
Nociceptive pain is often recognized as a relevant symptom in late-onset Pompe disease (LOPD), yet its prevalence, distribution, and underlying determinants remain insufficiently characterized. We aimed to systematically assess nociceptive pain in LOPD and to explore its relationship with muscle function, structural muscle alterations, and potential modifiers.
Methods
In this multicenter cross-sectional study, 42 patients with LOPD and 61 disease controls (IBM, FSHD, SMA3) were evaluated. Pain was assessed using validated questionnaires and pain drawings. Motor function tests, pressure pain thresholds, muscle ultrasound, laboratory parameters, and genetic polymorphisms (ACE, ACTN3) were obtained. Associations between pain and clinical, structural, and biological variables were analyzed.
Results
Chronic nociceptive musculoskeletal pain was highly prevalent, particularly in LOPD (83.3%) compared to disease controls (p=0.005). However, pain reported on the assessment day was significantly lower in LOPD (30.9%, p<0.001) and SMA3 (25%, p=0.016). No significant associations were found between pain and muscle strength, motor function tests, ultrasound-detected muscle alterations, ACTN3 and ACE, and laboratory parameters.
Conclusion
Musculoskeletal pain is highly prevalent in LOPD but remains dissociated from objective measures of motor impairment, structural changes of muscle tissue, or genetic modifiers. The significant discrepancy between chronic pain history and acute pain reporting particularly in LOPD and SMA3 suggests that pain represents an independent clinical domain that is not fully captured by single-point assessments. Clinical management should focus on individualized pain assessment, as standard functional tests and snapshot pain assessments do not adequately reflect the patient’s pain burden.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1007/s00415-026-14071-x.
Keywords: Pain, Nociceptive, LOPD, Muskuloskelettal, FSHD, IBM
Introduction
Pompe disease (glycogen storage disorder type II) is a rare autosomal recessive disorder affecting some 5000 to 10,000 individuals globally caused by acid α-glucosidase deficiency in the GAA gene, leading to lysosomal glycogen accumulation and progressive multisystem involvement. Late-onset Pompe disease (LOPD) is clinically characterized by slowly progressive proximal and axial myopathy with variable respiratory impairment and marked clinical heterogeneity that is not fully explained by GAA genotype alone [10, 14, 20].
Beyond motor impairment, musculoskeletal pain is increasingly recognized as a relevant but underreported symptom in LOPD. It may occur early in the disease course and becomes more prevalent with disease progression, substantially impairing quality of life. Despite enzyme replacement therapy (ERT), which can stabilize or slow motor decline, pain frequently persists or worsens, indicating that its underlying mechanisms are insufficiently understood [12, 16, 21, 35]. In particular, it remains unclear whether pain in LOPD is directly related to measurable disease severity, such as muscle weakness or structural muscle alterations, or whether additional factors, including potential modulators, contribute to its manifestation. Previous studies investigating pain in Pompe disease are scarce and largely limited to questionnaire-based assessments and only one used objective clinical assessments, providing little insight into its relationship with objective measures of muscle function or structural muscle changes [12, 21]. Genetic polymorphisms affecting muscle structure and function, such as the angiotensin-converting enzyme (ACE) insertion/deletion polymorphism and the ACTN3 R577X variant, have been proposed as modifiers of muscle phenotype and disease severity in neuromuscular disorders [3, 6, 10, 18, 19, 22]. While the ACE insertion/deletion (I/D) polymorphism is associated with variations in muscle metabolic efficiency and fiber distribution, the ACTN3 R577X variant dictates the presence or absence of alpha-actinin-3 in fast-twitch fibers. Deficiency in this protein (the XX genotype) has been linked to altered muscle structural resilience and shifted metabolic profiles. While it is well recognized that these variants are not disease-causing, it has been postulated that they may influence muscle performance, susceptibility to structural damage, and possibly the perception of pain [3, 6, 10]. In addition to genetic factors, biochemical markers such as Vitamin D have been widely established as modulators of muscle function and nociceptive pain. Vitamin D deficiency is frequently linked to myalgia and increased pain sensitivity, yet its specific impact on the pain profile in LOPD has not been systematically investigated [11, 15, 28, 37]. However, the role of these genetic and biochemical factors in modulating pain in LOPD remains poorly understood.
Taken together, there is a relevant gap in understanding the prevalence, distribution, and determinants of musculoskeletal pain in LOPD, particularly with respect to its relationship to objective measures of muscle function, structural muscle integrity, and potential biological modifiers.
The primary aim of this study was to systematically characterize the prevalence, severity, and spatial distribution of nociceptive musculoskeletal pain in adults with LOPD. Secondary objectives were to investigate associations between pain and muscle function, pressure pain sensitivity, structural muscle alterations assessed by ultrasound, as well as biochemical and genetic factors. To contextualize these findings, patients with other slowly progressive neuromuscular diseases (IBM, FSHD, and SMA3) and sharing a phenotype of slowly progressive, predominantly proximal and axial muscle weakness, but different in their underlying disease mechanisms, were included as disease controls.
Methods
This nationwide, exploratory cross-sectional study was conducted at primary neuromuscular centers in Germany (Munich, Hamburg, Bremen). Adults (≥ 18 years) with genetically confirmed late-onset Pompe disease (LOPD) were eligible. Disease controls included patients with inclusion body myositis (IBM, confirmed by muscle biopsy), facioscapulohumeral muscular dystrophy (FSHD, genetically confirmed), and spinal muscular atrophy type 3 (SMA3, genetically confirmed), selected due to comparable patterns of proximal muscle involvement but different pathophysiology (muscular dystrophy, degenerative myopathy, neurogenic atrophy). Key exclusion criteria were current participation in interventional trials and clinically relevant depression, defined as a Beck Depression Inventory Fast Screen (BDI-FS) score ≥4 as well as continuous ventilation. As pain assessment focused on nociceptive musculoskeletal pain, participants with neuropathic pain and other extra-muscular pain entities in their current symptoms or medical history were not included in the primary analysis. Missing data were not imputed; analyses were performed on available cases. The study was registered at ClinicalTrials.gov (NCT05272969). The study protocol was approved by the Ethics Committee of the Faculty of Medicine, Ludwig Maximilian University (LMU) Munich, Germany (approval number 20–0977), and was conducted in accordance with the Declaration of Helsinki and applicable local regulations. All participants provided written informed consent prior to study participation.
Clinical and functional assessment
Muscle strength was assessed using the Medical Research Council (MRC) scale. Functional endurance was evaluated using the six-minute walk test (6MWT) [1, 7, 9].
Pressure pain sensitivity
Pressure pain threshold (PPT) was measured using pressure algometry at predefined muscle sites (trapezius, deltoid, supraspinatus, rectus femoris, and tibialis anterior). The mean of three measurements per site was recorded as kg/cm2 and used for analysis [8, 23].
Muscle imaging
Muscle ultrasound was performed to assess structural muscle alterations, including muscle thickness and echogenicity, using the Heckmatt grading scale 1–4 across proximal, axial, and limb muscles [13, 24, 25, 33]. Although originally developed for dystrophic muscle disease, the Heckmatt score is a robust semiquantitative marker of muscle echogenicity and can also be applied in neurogenic and other neuromuscular disorders, including SMA and IBM [2, 26, 34, 36].
Laboratory and genetic analyses
Blood samples were analyzed for creatine kinase, vitamin D, calcium, phosphate, and magnesium levels. Genotyping for ACE (I/D) and ACTN3 (R577X) polymorphisms was performed. Genomic DNA was isolated from peripheral blood samples using a standard extraction kit according to the manufacturer’s instructions (Chemagic DNA Blood Kit H24 (Perkin Elmer, Waltham, MA, USA), Flexigene DNA Kit (Qiagen, Hilden, Germany)). Exome sequencing based on the Twist Human Comprehensive Exome (Twist Bioscience, San Francisco, CA, USA) was performed. As a first step, genotyping for the ACE (I/D, rs4646994) and ACTN3 (R577X, rs1815739) polymorphisms was carried out using the megSAP pipeline (https://github.com/imgag/megSAP) followed by visual inspection with the Integrated Genomics Viewer [29].
Patient-reported outcomes
Participants completed validated questionnaires assessing pain, function, and fatigue, including the Brief Pain Inventory (BPI), Fatigue Severity Scale (FSS), Rasch-built Pompe-specific Activity scale (RPAct), and the German Pain Questionnaire [4, 5, 17, 27, 31, 32]. Pain distribution was captured using body maps and digitally analyzed in Python to generate spatial pain patterns. Data quality checks and cleaning were performed prior to analysis to ensure consistent, valid records. The Pain drawings were available as binary image data with 850×600 pixel values. For spatial characterization, pixel-wise prevalence (“mean heat-maps”) was computed as the average value of each pixel across all binary drawings. Extra-muscular pain types (e.g., joint pain or neuropathic pain) were excluded.
Outcomes
The primary outcome was the prevalence, severity, and spatial distribution of musculoskeletal pain in LOPD compared with disease controls. Secondary outcomes included associations between pain and muscle function, pressure pain sensitivity, muscle ultrasound findings, patient-reported outcomes, and biochemical and genetic variables.
Statistical analysis
Given the exploratory design in rare diseases, analyses were primarily descriptive and inferential analyses should be interpreted as exploratory and hypothesis-generating. Continuous variables are reported as mean (SD) or median (IQR), as appropriate. Group comparisons were performed using one-way ANOVA or Kruskal–Wallis tests (depending on distribution), with Bonferroni-adjusted post hoc analyses where applicable. Assumptions for ANOVA were verified by visual inspection of normality and Levene’s test confirmed homogeneity of variances for all dependent variables (all p>0.05). Associations were explored using correlation and regression analyses. Multivariate logistic regression models were adjusted for age, sex, and disease group. A two-sided p value ≤0.05 was considered statistically significant. Given multiple secondary analyses, findings should be interpreted with caution due to potential type I error inflation.
Results
Study population and clinical baseline characteristics
Between May 2022 and October 2024, 103 patients were enrolled, exceeding the planned total sample size (n=95). Of these, 42 had LOPD, 20 had inclusion body myositis (IBM), 21 had facioscapulohumeral muscular dystrophy (FSHD), and 20 had spinal muscular atrophy type 3 (SMA3) (Table S1 and Fig S1). Disease confirmation results are summarized in supplements Table S2. Nineteen patients were excluded during screening due to depressive symptoms (Beck Depression Index-Fast Screen >=4) or inability to perform functional assessments. Demographic characteristics differed significantly across groups, particularly for age, age at symptom onset, and disease duration (Table 1). Baseline clinical characteristics are summarized in Table 2. Overall, no significant differences were observed between the four disease groups regarding functional assessment, as measured by the 6MWT %predicted (p = 0.169), or fatigue levels (FSS, p = 0.149). Similarly, depressive symptoms (BDI) and physical activity levels (RPAct) did not differ significantly across groups (p > 0.05). A significant intergroup difference was identified for the MRC-Score %predicted (p = 0.029), with FSHD and SMA3 patients showing numerically lower median scores compared to the LOPD and IBM groups. However, subsequent post hoc pairwise comparisons with the Bonferroni correction did not reveal any significant differences among specific groups.
Table 1.
Baseline participant demographics
| Total (n=103) | LOPD (n=42) | IBM (n=20) | FSHD (n=21) | SMA3 (n=20) | p valuea | |
|---|---|---|---|---|---|---|
| Female n (%) | 49 (48) | 23 (55) | 6 (30) | 13 (62) | 7 (35) | – |
| Age | 51 (20−85) | 48 (22−85) | 70 (51−82) | 41 (22−67) | 42 (20−66) | <0.01 |
| Age at symptom onset | 33 (0−72) | 27 (0−57) | 61 (44−72) | 27 (10−46) | 15 (0−45) | <0.01 |
|
Disease duration [years] |
18.9 (2−57) | 19.2 (2−38) | 8.8 (2−33) | 19.9 (6−55) | 28.3 (11−57) | <0.001 |
| BMI [kg/cm2] | 24 (12−36) | 23 (12−36) | 25 (15−33) | 25 (16−33) | 24 (14−33) | 0.601 |
Baseline demographics by disease group. Data are presented as median (IQR) for non-normally distributed variables and aanalyzed via Kruskal–Wallis test
Table 2.
Baseline clinical characteristics
| LOPD (n=42) | IBM (n=20) | FSHD (n=21) | SMA3 (n=20) | p value | |
|---|---|---|---|---|---|
| 6MWT, [%predicted]a | 69.55 ± 27.10 | 65.97 ± 23.37 | 61.89 ± 25.35 | 52.05 ± 27.02 | 0.169 |
| MRC-Score, [%predicted]b | 84.21 (71.84–91.84) | 86.85 (74.99–92.10) | 71.58 (58.95–85.26) | 70.53 (65.26–84.21) | 0.029c |
| FSSa | 33.31 ± 12.95 | 37.05 ± 18.32 | 42.35 ± 13.96 | 37.10 ± 13.15 | 0.149 |
| BDIb | 8.50 (7.00–11.00) | 9.00 (7.00–14.50) | 9.00 (7.25–12.00) | 8.00 (7.00–12.00) | 0.650 |
| RPActa | 21.23 ± 2.15 | 20.33 ±5.46 | 12.89 ± 2.67 | 22.2 ± 3.25 | 0.088 |
Clinical baseline characteristics by disease group. Data are presented as mean ± standard deviation (SD) for normally distributed variables and median (IQR) for non-normally distributed variables. Group comparisons were performed using one-way ANOVA or the Kruskal–Wallis test, as appropriate. aVariables with normal distribution analyzed via ANOVA. bVariables with non-normal distribution analyzed via Kruskal–Wallis test. cAlthough the overall Kruskal–Wallis test for MRC Scale % predicted was significant, post hoc pairwise comparisons with Bonferroni correction showed no significant differences between individual groups
Primary outcome
Overall, 64.1% of all participants reported chronic nociceptive musculoskeletal pain. Within the LOPD group, 35 out of 42 patients (83.3%) were affected, with significantly higher prevalence compared to the other groups (p=0.005) and significantly more females reporting pain (Table 3 and supplements Table 3). Heatmaps of pain drawings illustrate the distribution of perceived musculoskeletal pain across disease groups. Patients were instructed to indicate the location of their pain on a body map, categorized by the following qualities: burning, pressing, pulling, or undefined (up to four pain qualities per patient). This resulted in a total of 144 pain drawings (LOPD n=76; FSHD n=34; SMA3 n=22; IBM n=12). Pain drawings were digitized and analyzed at a pixel-wise level using Pain2D-Software® to determine spatial prevalence (Fig. 1 and supplements Fig S2). Pain distribution patterns corresponded closely to disease-specific muscle involvement. In LOPD, pain was predominantly localized to proximal lower limbs and axial muscles. In contrast, pain on the day of the visit, captured by the BPI, was reported significantly lower than compared to the reported chronic pain. Subgroup analysis using the McNemar test revealed that this discrepancy was significant within the LOPD group (p<0.001) and the SMA3 group (p=0.016), whereas no significant differences between chronic and current pain were found for IBM (p=0.180) and FSHD (p=0.375). Due to BPI, pain intensity and interference scores were low across all groups on the day of the visit, with no significant differences between disease entities or sex (see Table S3). Pain characteristics and BPI scores are detailed in Table 3.
Table 3.
Pain characteristics and BPI scores stratified by diagnostic group
| LOPD (n=42) | IBM (n=20) | FSHD (n=21) | SMA3 (n=20) | p value | |
|---|---|---|---|---|---|
| Pain n (%) chronic pain | 35 (83.3%) | 8 (40%) | 12 (57.1%) | 11 (55%) | 0.0051 |
| BPI Pain today yes | 13 (30.9%) | 3 (15%) | 9 (42.9%) | 5 (25%) | 0.2552 |
| BPI pain intensity today | 1.75 (1.32–3.07) | 2.00 (0.60–3.89) | 2.00 (1.34–3.11) | 2.25 (1.89–2.70) | 0.5263 |
| BPI pain interference today | 1.86 (1.13–2.96) | 3.00 (1.58–7.30) | 2.86 (1.57–5.26) | 5.29 (1.24–7.22) | 0.2423 |
Values are presented as n (%) or median (IQR). p values derived from 1Chi-square tests (Pain n), 2Fisher´s exact test (BPI Pain n) due to small cell counts (≤ 5 in 50% of cells) and 3Kruskal–Wallis test (BPI scores). BPI Brief Pain Inventory
Fig. 1.
Heatmap of nociceptive pain drawings across the four disease groups. Heatmaps of pain distribution
Secondary outcomes
Pain management
Pain was primarily managed with non-opioid analgesics, particularly NSAIDs, while opioid use was rare. Non-pharmacological approaches, especially thermotherapy, were frequently reported (supplements Table S4 and S5).
Pain in association with functional and structural parameters and laboratory tests
Pressure pain thresholds differed across disease groups, with LOPD patients showing consistently higher thresholds than other groups, indicating reduced sensitivity to mechanical stimuli (Fig. 2 and supplemental Table S6 and Figure S3). However, these differences were not statistically robust after correction for multiple testing. No significant association was observed between the presence of pain and muscle strength (MRC), functional capacity (6MWT), or structural muscle alterations assessed by ultrasound. Similarly, biochemical parameters, including vitamin D and creatine kinase levels, were not associated with pain (supplements Table S7, S8, S9, 10 and Fig S4).
Fig. 2.
Heatmap of pressure pain threshold and Heckmatt score. Left: Anatomical heatmap of mean PPT values in kg/cm2. Right: mean Heckmatt scores across assessed muscles. Mean values are used for visualization purposes to illustrate trends across the ordinal 1–4 Heckmatt scale. Values for left and right figures are displayed in supplements Tables S6 and S10
Genetic analyses
Genotype distributions for both ACTN3 and ACE polymorphisms were comparable across all four disease groups, with no statistically significant differences observed (p=0.653 and p=0.485, respectively; Table 4). In all groups, the heterozygous variants (RX and ID) represented the most frequent genotypes.
Table 4.
ACTN3- and ACE-polymorphisms per disease group
| Genotype | LOPD (n=42) | SMA3 (n=19) | IBM (n=20) | FSHD (n=20) | Total (n=101) | p value1 |
|---|---|---|---|---|---|---|
| ACTN3 | 0.653 | |||||
| RX (het) | 30 (71.4%) | 15 (78.9%) | 10 (50.0%) | 10 (50.0%) | 65 (64.4%) | |
| XX (hom) | 5 (11.9%) | 0 (0.0%) | 3 (15.0%) | 8 (40.0%) | 16 (15.8%) | |
| RR (wt) | 7 (16.7%) | 4 (21.1%) | 7 (35.0%) | 2 (10.0%) | 20 (19.8%) | |
| ACE | 0.485 | |||||
| ID (het) | 27 (64.3%) | 9 (45.0%) | 13 (65.0%) | 9 (42.9%) | 58 (56.3%) | |
| DD (hom) | 5 (11.9%) | 3 (15.0%) | 2 (10.0%) | 9 (42.9%) | 19 (18.4%) | |
| II (wt) | 10 (23.8%) | 8 (40.0%) | 5 (25.0%) | 3 (14.3%) | 26 (25.2%) |
Data are presented as absolute numbers and column percentages n (%). 1Fisher’s Exact test was used due small expected cell counts (< 5 in 50% of cells). ACTN3 alpha-actinin-3 gene; ACE angiotensin-converting enzyme gene; het heterogenous; hom homozygous; wt wild type
Correlation and association analyses
Statistical analysis revealed no significant association between the ACE or ACTN3 genotype and the reported chronic nociceptive pain (p=0.653) (Table 5).
Table 5.
Association between ACTN3-/ACE genotype and the presence of chronic pain
| Genotype | Pain + n (%) |
Pain - n (%) |
Total | p value | Adjusted residual |
|---|---|---|---|---|---|
| ACTN3 | p=0.6531 | ||||
| Homozygous (XX) | 12 (75.0%) | 4 (25.0%) | 16 | 0.9 | |
| Heterozygous (RX) | 42 (64.6%) | 23 (35.4%) | 65 | −0.2 | |
| Wild-type (RR) | 12 (60.0%) | 8 (40.0%) | 20 | −0.6 | |
| ACE | p=0.4851 | ||||
| Homozygous (DD) | 13 (68.4%) | 6 (31.6%) | 19 | 0.3 | |
| Heterozygous (ID) | 35 (60.3%) | 23 (39.7%) | 58 | −1.2 | |
| Wild-type (II) | 18 (75%) | 6 (25.0%) | 24 | 1.1 |
Data are presented as absolute numbers (n (%)). 1 Fisher’s exact test. Adjusted residuals > 1.96 indicate cells contributing significantly to the overall association. ACTN3 alpha-actinin-3 gene; ACE angiotensin-converting enzyme gene; het heterogeneous; hom homozygous; wt wild type.
Further association analyses revealed no significant relationship between the presence or intensity of pain and any biochemical, demographic, or functional parameters, including vitamin D levels, disease duration, age, BMI, and motor function scores (6MWT, MRC) (supplements Tables S11 and S12). Specifically, within the LOPD group, no correlation was found between vitamin D levels and pain severity (rs=0.03, p=0.892). Consequently, as no trends were observed in the total cohort or in Vitamin D levels, no further subgroup-specific analyses were performed for the LOPD group. In multivariate logistic regression analysis, higher global PPT were independently associated with the presence of musculoskeletal pain (odds ratio 1.15, 95% CI 1.00–1.32; p=0.046), after adjustment for disease group, age, and sex.
The ACE and ACTN3 polymorphisms showed no significant association with the age of symptom onset, muscle strength (MRC), or functional capacity (6MWT) in either the total cohort or the LOPD subgroup. Although ACE genotypes were significantly associated with differences in creatine kinase (CK) levels (p=0.014), with the II-genotype exhibiting higher values, this biochemical variation did not translate into detectable differences in clinical motor performance (supplements Table S12).
A significant moderate-to-strong negative correlation was found between 6MWT performance and a lower-limb composite Heckmatt score (Spearman´s rs=− 0.574; p<0.001), indicating that an increased echogenicity and structural degeneration of the lower extremities are strongly linked to reduced submaximal functional capacity (supplements Fig S5). In multivariate logistic regression analyses adjusted for age, sex, and disease group, neither 6MWT % predicted, MRC sum score nor global mean Heckmatt score was associated with musculoskeletal pain (see Table S8). Regarding patient-reported outcomes, no significant difference in FSS score was observed between patients with and without nociceptive pain (p = 0.116). However, fatigue severity showed a weak positive correlation with pain intensity (Spearman’s rₛ = 0.220, p = 0.026) (see Table S11).
Discussion
This is the first multicentre cross-sectional study to systematically evaluate nociceptive pain in patients with late-onset Pompe disease (LOPD) by integrating patient-reported outcomes with clinical assessments of muscle function, structure, and pain perception, alongside laboratory modifiers. To better contextualize the pain profile of LOPD, these findings were compared with other neuromuscular disorders sharing a phenotype of slowly progressive, predominantly proximal and axial muscle weakness, but differing in their underlying pathology.
Musculoskeletal pain was highly prevalent in LOPD and occurred significantly more frequently than in comparable neuromuscular diseases. However, pain was not associated with objective measures of muscle strength, structural muscle alterations assessed by ultrasound, or biochemical parameters.
Our observed prevalence of nociceptive pain in LOPD is consistent with the previous reports highlighting pain as a relevant but underrecognized symptom in Pompe disease [12, 20, 21, 30, 35]. The spatial distribution of pain, predominantly affecting the proximal lower limbs and axial musculature, reflects the typical pattern of muscle involvement in LOPD. A key finding of this study is the absence of a significant relationship between pain and objective markers of disease severity, including muscle strength (MRC), functional capacity (6MWT), and muscle ultrasound findings. Notably, the lack of association between perceived pain and Heckmatt scores argues against a direct link between structural muscle degeneration and nociceptive pain generation. Similarly, biochemical parameters, including creatine kinase and vitamin D levels, were not associated with pain. These findings suggest that commonly assumed contributors to musculoskeletal pain, such as muscle damage or metabolic alterations, do not sufficiently explain pain perception in LOPD.
LOPD patients exhibited comparatively higher pressure pain thresholds across multiple muscle groups, indicating reduced sensitivity to mechanical stimuli. This may reflect altered central pain processing in the context of chronic, slowly progressive neuromuscular disease. In contrast to preliminary observations, we found no association between ACTN3 or ACE polymorphisms and chronic nociceptive musculoskeletal pain. While ACTN3 XX may influence muscle resilience, our data suggest that in diseases like LOPD, the primary pathology and mechanical factors overshadow these genetic modifiers [10]. Although ACE genotype was associated with creatine kinase levels, this did not translate into differences in motor performance, and its clinical relevance remains uncertain.
The inclusion of disease control groups (IBM, FSHD, SMA3) provides important context for interpreting these findings in LOPD. Despite different pathophysiological mechanisms, pain quality and severity were broadly comparable across groups. The lack of a clear association between pain and disease duration or functional impairment across all groups suggests that chronic neuromuscular disease per se does not inevitably lead to increased pain burden. These findings further support the concept that pain in neuromuscular disorders is multifactorial and not solely determined by the degree of muscle pathology but may arise from predominantly regional muscle and musculoskeletal imbalances rather than structural muscle tissue alteration. Although muscle biopsy was not performed in this study, future studies incorporating histopathological analyses, including muscle fiber distribution, may help clarify whether specific structural muscle alterations contribute to pain in LOPD.
A key finding in our study is the discrepancy between the high prevalence of reported chronic musculoskeletal pain and the significantly lower frequency of pain on the day of assessment in LOPD and SMA3. This indicates that single-point assessments such as the BPI may underestimate the true pain burden. Pain in these patients appears to be fluctuating and activity-dependent, which may not be captured during single clinical visits. This temporal dissociation may also explain the lack of correlation between pain intensity and objective functional measures. Consequently, from a clinical perspective, the dissociation between pain and objective disease severity highlights the need for independent assessment and management of pain in LOPD, as well as repeated clinical reassessment over time. Standard neuromuscular evaluations focusing on strength and function do not adequately reflect the patient’s pain burden, supporting the routine use of dedicated pain assessment tools.
Fatigue may represent a relevant factor influencing pain perception in patients with neuromuscular disorders. Although fatigue severity was not associated with the presence of nociceptive pain, higher FSS scores were weakly associated with greater pain intensity, suggesting that fatigue may contribute to the subjective burden of pain rather than its occurrence.
This study has several limitations. The sample size, although exceeding initial targets, remains limited for subgroup analyses. The cross-sectional design precludes conclusions on causality or longitudinal progression. While adjustments for multiple testing were applied in primary analyses, the exploratory nature of secondary outcomes increases the risk of type I error. Finally, pain remains a subjective construct, and psychosocial factors beyond depression were not systematically assessed.
In conclusion, musculoskeletal pain is a frequent but largely independent clinical feature in LOPD that is not explained by muscle strength, structural damage, biochemical parameters, or common genetic modifiers. These findings support the concept of pain as a distinct clinical domain requiring dedicated assessment and management.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank all study participants for participation and their consent to analyze their data in this study.
Author contributions
Stephan Wenninger: study conceptualization, statistical analysis and interpretation of data, discussion of results, critical revision of the manuscript for intellectual content, and first and final manuscript draft. A guarantor who accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. Marcela Arndt: data acquisition, statistical analysis and interpretation of data, discussion of results, and critical revision of the manuscript for intellectual content. Corinna Wirner-Piotrowski: data acquisition and critical revision of the manuscript for intellectual content. Marko Mijic: discussion of results and critical revision of the manuscript for intellectual content. Natalia Garcia-Angarita: discussion of results and critical revision of the manuscript for intellectual content. Kristina Gutschmidt: discussion of results and critical revision of the manuscript for intellectual content. Daniel H. Mendelsohn: statistical analysis, discussion of results, and critical revision of the manuscript for intellectual content. Karl Christian Knop: data acquisition, discussion of results, and critical revision of the manuscript for intellectual content. Matthias Spranger: data acquisition, discussion of results, and critical revision of the manuscript for intellectual content. Frank Klawonn: statistical analysis, discussion of results, and critical revision of the manuscript for intellectual content. Lea Eileen Brauner: statistical analysis, discussion of results, and critical revision of the manuscript for intellectual content. Christoph Schmidt: genetic analysis, discussion of results, and critical revision of the manuscript for intellectual content. Lisa Winkler: genetic analysis, discussion of results, and critical revision of the manuscript for intellectual content. Dieter Gläser: genetic analysis, discussion of results, and critical revision of the manuscript for intellectual content. Benedikt Schoser: discussion of results and critical revision of the manuscript for intellectual content. Stephan Wenninger and Marcela Arndt have contributed equally to this paper.
Funding
Open Access funding enabled and organized by Projekt DEAL. The study received financial grant from Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Brüningstraße 50, 65926 Frankfurt am Main. SGZ-2020-13334.
Data availability
The anonymized participant data presented here are available upon request from the correspondent author (stephan.wenninger@med.uni-muenchen.de).
Declarations
Conflicts of interest
SW has received research grant by Sanofi-Aventis Deutschland GmbH and DGM—Deutsche Gesellschaft für Muskelkranke e.V. He has served on advisory boards for Alexion Pharma, CSL Behring, and Sanofi Genzyme GmbH. He received funding for travel or speaker Honoraria from Sanofi-Aventis Germany GmbH; SH Glykogenose Gesellschaft; AbbVie Germany GmbH; Recordati Pharma GmbH; CSLBehring GmbH; Alexion Pharma GmbH; Desitin Germany; Akcea GmbH. Outside of this context, BS has served on advisory boards for Alexion, Argenex, Amicus, Astellas, Spark, and Sanofi; he has undertaken contracted unrestricted research for Sanofi and Amicus; and has received honoraria from Kedrion. DG: received funding for travel and speaker Honoraria from Hormosan and received funding for travel and speaker Honoraria from Amicus. BS: has received research grants from AMDA Foundation, EU Horizon 2022 programs ComPaSS and PaLaDIn, Entry-DM, Marigold Foundation, and Roche Diagnostics; received speaker’s honoraria from Alexion, Amicus, Argenx, Astellas, Kedrion, and Sanofi; been a scientific advisor for Amicus, Alexion, Astellas, Avidity, Denali, Dyne, Souffle, and Sanofi; and declares no stocks or shares. The other authors have no conflicts of interest to declare (NGA, MM, KG, CWP, MA, DHM, CS, LW, KCK, MS, FK, and LEB).
Study registration
This study was registered at clinicaltrials.gov, number NCT05272969.
Footnotes
Stephan Wenninger and Marcela Arndt have contributed equally to this paper.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The anonymized participant data presented here are available upon request from the correspondent author (stephan.wenninger@med.uni-muenchen.de).