{"paper_id":"f5453dc0-051e-4108-96e1-b409dd09e5b6","body_text":"Mitochondrial stress markers associate with phenotypic variability in Fabry disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mitochondrial stress markers associate with phenotypic variability in Fabry disease Lucia Lavalle, Hibba Kurdi, David Moreno Martinez, Vincent Muczynski, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9304477/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background: Fabry disease (FD) exhibits marked clinical heterogeneity that cannot be fully explained by residual α-galactosidase A activity. Mitochondrial dysfunction has been reported in FD, but the role of mitochondrial stress remains unexplored. Objective: To investigate whether mitochondrial unfolded protein response (mtUPR) related markers associate with phenotypic variability and correlates with disease severity. Methods: We measured intracellular heat-shock protein 60 (Hsp60) by western blotting in peripheral blood mononuclear cells from 27 FD patients (14 males, 13 females). Serum fibroblast growth-factor-21 and growth differentiation-factor-15 were measured in 35 patients. Clinical outcomes included Mainz Severity Score Index, Age-Adjusting Severity Score, estimated glomerular filtration rate, and left-ventricular mass index (LVMI). Results: Hsp60 showed variability, with sex-specific associations. In males, higher Hsp60 correlated with lower LVMI (r²=-0.82, p=0.01) and preserved renal function in late-onset patients (r²=0.89, p=0.006). In females, higher Hsp60 associated with higher LVMI (r²=0.66, p=0.045) and greater clinical severity. Male patients had elevated growth differentiation-factor-15 vs controls (935 vs 559 pg/ml, p=0.002). Both mitokines correlated with age and disease severity. Conclusions: mtUPR related markers exhibit sex- and genotype-specific patterns associated with disease severity, suggesting that mitochondrial stress contributes to phenotypic heterogeneity and may serve as biomarkers for treatment optimisation. Fabry disease mitochondrial unfolded protein response Hsp60 mitokines (FGF-21 GDF-15) and phenotypic heterogeneity Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Fabry disease (FD) is a progressive, X-linked lysosomal storage disorder caused by deficient α-galactosidase A activity, leading to globotriaosylceramide (Gb3) accumulation in multiple organ systems ( 1 ). The clinical heterogeneity of FD is striking, ranging from severe classical phenotypes manifesting in childhood to late-onset variants with organ-specific manifestations that may not appear until middle age ( 2 ). This phenotypic variability cannot be fully explained by residual enzyme activity alone, as patients with similar biochemical profiles often exhibit markedly different clinical courses ( 3 ). Understanding the molecular mechanisms underlying this heterogeneity is crucial for optimising therapeutic strategies and improving patient outcomes. Ageing and lysosomal storage disorders share common features of proteostatic stress, characterised by the accumulation of misfolded proteins and declining cellular quality control mechanisms ( 4 , 5 ). In Fabry disease, evidence suggests that cellular dysfunction extends beyond Gb3 accumulation, encompassing mitochondrial abnormalities, oxidative stress, and inflammatory responses ( 6 , 7 ). The progressive nature of FD manifestations with age suggests that cellular stress responses may become overwhelmed over time, contributing to organ dysfunction. The mitochondrial unfolded protein response (mtUPR) represents a conserved quality control mechanism activated by mitochondrial proteostatic stress ( 8 ). Upon detecting mitochondrial dysfunction, cells initiate a coordinated nuclear-mitochondrial signalling pathway that up-regulates protective factors, including mitochondrial chaperones such as heat shock protein 60 (Hsp60) ( 9 ). Additionally, mitochondrial stress triggers the cellular release of signalling molecules termed mitokines, including fibroblast growth factor 21 (FGF-21) and growth differentiation factor 15 (GDF-15), which coordinate systemic metabolic responses ( 10 , 11 ). While engagement of mitochondrial stress responses is generally cytoprotective, sustained signalling may become maladaptive and contribute to pathology ( 12 ). Several observations support a role for mitochondrial stress responses in the pathogenesis of Fabry disease. First, lysosomal dysfunction can impair mitochondrial function through disrupted calcium homeostasis and altered autophagy ( 13 ). Second, the accumulation of misfolded α-galactosidase A variants may create additional proteostatic stress ( 14 ). Third, the progressive, age-related nature of FD complications mirrors patterns seen in other conditions characterised by chronic mitochondrial stress signalling ( 15 ). These effects may vary by variant class, as missense and nonsense GLA variants are associated with different molecular consequences ( 16 ). We hypothesised that altered Hsp60 expression and mitokine levels are associated with phenotypic variability in Fabry disease and correlate with disease severity, particularly in cardiac and renal manifestations. Furthermore, we predicted that sex-specific differences in mitochondrial stress responses might help explain the different clinical patterns observed between male and female FD patients. 2. Methods 2.1 Study Design and Participants This cross-sectional study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC: 20/WM/0329) and the study was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent. We recruited 27 FD patients (14 males, 13 females) with confirmed GLA mutations and documented enzyme activity measurements before treatment initiation. Healthy controls for Hsp60 analyses included (n = 4; 3 males, 1 female). In contrast, the mitokine analyses included a larger cohort of age- and sex-matched volunteers without known genetic disorders (n = 25; 17 males, 8 females). 2.2 Clinical Assessments Clinical data were collected retrospectively from medical records. Disease severity was assessed using the Mainz Severity Score Index (MSSI) and Age-Adjusting Severity Score (AASS) ( 17 ). The cardiac evaluation included electrocardiogram and cardiac magnetic resonance imaging, with left ventricular mass index (LVMI) calculated using the Devereux formula ( 18 ). Left ventricular hypertrophy was defined as LVMI ≥ 78 g/m² (males) or ≥ 74 g/m² (females)( 19 ). Renal function was assessed by estimating glomerular filtration rate (eGFR) using the CKD-EPI Eq. (20). Patients were classified as classical or late-onset based on residual enzyme activity and characteristic symptoms ( 21 ). 2.3 Laboratory Methods 2.3.1 Cell Culture and Protein Analysis Peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation and cultured for 6 days in RPMI-1640 medium. Whole-cell lysates were prepared using mammalian cell lysis buffer with protease inhibitors. Hsp60 levels were measured by western blotting using an anti-Hsp60 monoclonal antibody (Bio-techne, NBP2-34670H) with Na+/K+-ATPase as loading control. Samples were analysed across multiple gels. For female samples, a consistent control sample was included across all gels. For male samples, one of three wild-type control samples was included within each gel. Densitometric quantification was normalised within each gel to the loading control. Fibroblast cell lines GM00302, GM00881, GM00882 (Coriell Institute) were grown in EMEM medium. 2.3.2 Serum Mitokine Analysis Based on manufacturer protocols, Serum FGF-21 and GDF-15 levels were measured using commercial ELISA kits (R&D Systems, DF2100 and DGD150). 2.4 Statistical Analysis Data analysis was performed using GraphPad Prism 8.0. Continuous variables are presented as median with interquartile range. Group comparisons used Mann-Whitney U tests or Kruskal-Wallis tests with Dunn's post-hoc correction. Correlations were assessed using Spearman's rank correlation. Multiple linear regression was employed to identify predictors of clinical outcomes. We applied Bonferroni correction for primary analyses (α = 0.01) to address multiple testing and reported effect sizes alongside p-values. Statistical significance was set at p < 0.05 for exploratory analyses. 3. Results 3.1 Patient Characteristics Twenty-seven FD patients were included: 14 males (9 with N215S variant, 5 with other variants) and 13 females. Patient demographics are summarised in Table 1 . Males with the N215S variant showed predominantly cardiac phenotypes, while non-N215S males exhibited more classical, multisystem disease. Female patients exhibited variable phenotypes, independent of their genotype. Table 1 Patient demographics Parameters Males Females Overall N = 19 N = 17 N215S non-N215S N (%) 9 (47.4) 10 (52.6) Age (years) at diagnosis Mean (SD) 48.9 (19.1) 24.5 (17.9) 37 (17.9) Median (range) 54 (13 to 71) 26 (1 to 53) 37.5 (5 to 69) Currently on treatment, n (%) 9 (100) 10 (100) 12 (70.6) Enzyme replacement therapy, n (%) 1 (11.1) 6 (60) 6 (50) Pharmacological chaperone therapy, n (%) 8 (88.9) 4 ( 40 ) 6 (50) Age (years) at treatment commencement Mean (SD) 50.8 (18.7) 29.5 ( 18 ) 36.9 (15.7) Median (range) 57 (15 to 71) 31.5 (2 to 53) 39 (12 to 63) Classic Fabry disease cardinal features Acroparesthesias, n (%) 1 (11.1) 8 (80) 8 (47.1) Fabry crisis, n (%) 0 (0) 4 ( 40 ) 4 (23.5) Angiokeratoma, n (%) 1 (11.1) 3 ( 30 ) 3 (17.7) Decreased sweating, n (%) 4 (44.4) 7 (70) 6 (35.3) Cornea verticillata*, n (%) 0 (0) 2 ( 20 ) 2 (11.8) Abnormal pure tone audiometry, n (missing) 4 ( 1 ) 6 (0) 11 (0) Mean age (SD) 67 (6.4) 42.3 (6.9) 46.6 (21.7) Median age (range) 65 (62 to 76) 41.5 (35 to 55) 57 (4 to 69) LVH on image, n (%) 7 (77.8) 7 (70) 7 (41.2) Mean age (SD) 57.4 (8.5) 42.2 (8.8) 54.7 (9.3) Median age (range) 57 (45 to 71) 41 (29 to 53) 52 (42–69) CKD stages (mL/min/1.73m2) 1 (> 90) 4 4 8 2 (60 ± 89) 3 4 6 3A (45 ± 59) 1 1 3 3B (30 ± 44) 0 0 0 4 (> 15 ± 29) 1 0 0 5 (< 15 or on dialysis) 0 1 0 GI symptoms during childhood 1 (11.1) 5 (50) 4 (30.8) Serious clinical outcomes**, n (%) 6 (66.7) 5 (50) 6 (46.2) Overall severity at sampling Mild (MSSI < 20), n (%) 4 (44.4) 3 ( 30 ) 10 (5.9) Moderate (MSSI = 20–40), n (%) 3 (33.3) 5 (50) 6 (35.3) Severe (MSSI > 40), n (%) 2 (22.2) 2 ( 20 ) 1 (5.9) Age adjusting score Mean (SD) -5.7 (6.8) 8.7 (9.5) 5.8 (10.1) Median (range) -6.9 (-15.8 to 6.1) 7 (-9.6 to 22.2) 5.1 (-14.3 to 24.6) * Cornea verticillata was not assessed for all patients. **Serious clinical outcomes include myocardial infarction, stroke, transient ischaemic attack, implantation of pacemaker or of implantable cardiovascular defibrillator, the development of atrial fibrillation, and chronic kidney disease (CKD) 3A (GFR < 59ml/min/1.73m2).N: number, SD: standard deviation, LVH: left ventricular hypertrophy, GI: gastrointestinal. 3.2 Mitochondrial Stress Response in Fabry Fibroblasts Initial characterisation using immortalised fibroblast cell lines revealed fundamental differences in cellular stress responses between variant types (Fig. 1 ). The missense R301Q variant exhibited a marked elevation of both Hsp60 (187% of the wild-type level) and Hsp10 (127% of the wild-type level), consistent with mitochondrial stress responses involving the mtUPR pathway. In contrast, the nonsense R220X variant exhibited substantially reduced levels (Hsp60: 45%, Hsp10: 18% of wild-type). These findings suggest distinct pathogenic mechanisms: missense variants create a \"protein misfolding burden\" that triggers compensatory stress responses. In contrast, nonsense variants result in \"protein absence\" without the additional proteostatic stress of misfolded protein accumulation. This distinction has implications for understanding why patients with similar residual enzyme activities can exhibit different clinical trajectories and treatment responses. 3.3 Hsp60 Levels in Fabry Disease Patients Western blot analysis of PBMCs revealed substantial variability in Hsp60 levels among FD patients, with some individuals showing > 2-fold elevation and others < 50% of healthy control levels (Fig. 2 ). No significant overall difference was observed between FD patients and controls when analysed as a group (males: 254% vs 100%, p = NS; females: 89% vs 100%, p = NS). However, the relationship between Hsp60 and ageing differed markedly between patients and controls. While healthy controls showed the expected positive correlation between Hsp60 and age (r²=1.0, p = 0.04, Fig. 3 A), this relationship was absent in FD patients (Fig. 3 C), suggesting altered mitochondrial stress response independent of chronological ageing. 3.4 Sex-Specific Associations with Clinical Severity Hsp60 levels showed sex-specific associations with disease severity. In females, higher Hsp60 levels correlated significantly with greater age-adjusted clinical severity (AASS: r²=0.54, p = 0.03, Fig. 3 E) and inversely with younger age at sampling (r²= -0.57, p = 0.02, Fig. 3 C), contrasting with the positive age correlation in healthy controls (Fig. 3 A). The relationship between Hsp60 and cardiac outcomes revealed opposite patterns in males and females. In males, higher Hsp60 levels strongly correlated with lower LVMI (r²=-0.82, p = 0.01), suggesting a cardioprotective effect (Fig. 3 D). This relationship was most pronounced in the N215S subgroup. Conversely, in females, higher Hsp60 levels are associated with higher LVMI (r²=0.66, p = 0.045), indicating a potential maladaptive response (Fig. 3 E). Association with renal function also differed by sex and genotype. In N215S males, again higher Hsp60 levels correlated with better preserved GFR (r²=0.89, p = 0.006), while non-N215S males showed the opposite relationship (r²=-0.89, p = 0.006). Females showed a weak positive trend that did not reach statistical significance. 3.5 Serum Mitokine Levels Analysis of serum mitokines revealed significantly elevated GDF-15 levels in male FD patients compared to healthy controls (935 vs 559 pg/ml, p = 0.002). These levels also exceed published population medians for healthy males, including younger adults (< 30 years: 483 pg/mL) and those aged 50–59 (931 pg/mL)( 22 ) FGF-21 levels showed no significant difference (Figure S4). Both mitokines correlated positively with age in FD patients, with stronger correlations than observed in healthy controls (Fig. 4 ), suggesting accelerated mitochondrial ageing. In males, Hsp60 levels showed a strong inverse correlation with FGF-21 (r²=-0.75, p = 0.004), while females showed a weaker negative correlation with GDF-15 (r²=-0.57, p = 0.047) (Fig. 4 ). These relationships suggest coordinated but sex-specific mitochondrial stress responses. 3.6 Association with Disease Severity and Outcomes Both mitokines correlated positively with disease severity scores in males, with particularly strong associations in the N215S subgroup (MSSI vs FGF-21: r²=0.87, p = 0.005; MSSI vs GDF-15: r²=0.73, p = 0.03). No significant correlations were observed in females. Patients with documented cardiomyopathy had significantly higher GDF-15 levels (935 vs 610 pg/ml, p = 0.02), and both mitokines were elevated in patients with left ventricular hypertrophy (FGF-21: 160 vs 98 pg/ml, p = 0.04; GDF-15: 975 vs 656 pg/ml, p = 0.01). Similar patterns were observed for clinically significant renal events, with GDF-15 showing the strongest associations (Fig. 4 ). 3.7 Impact of Treatment Timing An important finding was the strong correlation between age at treatment initiation and serum mitokine levels. Males who started treatment at older ages had significantly elevated FGF-21 (r²=0.43, p = 0.04) and GDF-15 (r²=0.58, p = 0.006) levels, with similar patterns in females for GDF-15 (r²=0.70, p = 0.007). This relationship was independent of the current treatment type, suggesting a degree of irreversibility of mitochondrial dysfunction beyond a critical age threshold. 3.8 Predictive Modelling Multiple linear regression analysis identified key predictors of clinical outcomes. For MSSI in males, the best model (r²=0.76, p = 0.004) included GDF-15 (β = 0.01, p = 0.009), GLA protein levels (β = 37.3, p = 0.006), and Hsp60 (β=-52.2, p = 0.003), explaining 76% of severity score variance. In the N215S male subgroup, FGF-21 alone explained 92% of MSSI variance (β = 0.12, p = 0.01). 4. Discussion 4.1 Overall Findings This study provides the first systematic investigation of mtUPR related markers in Fabry disease, revealing complex sex- and genotype-specific patterns that may contribute to phenotypic heterogeneity. Hsp60 is induced as part of the mtUPR but is not specific to this pathway, while circulating mitokines reflect broader mitochondrial stress responses. Their coordinated alteration is consistent with engagement of mitochondrial stress pathways at both cellular and systemic levels ( 23 , 24 ). The most striking finding was the opposite relationship between Hsp60 levels and cardiac outcomes in males versus females. In males, higher Hsp60 levels were associated with better preserved cardiac architecture, while the relationship was reversed in females. This sex dimorphism may reflect fundamental differences in X-linked inheritance patterns, hormonal influences on mitochondrial function, and cellular stress responses. 4.2 Sex-Specific Mitochondrial Stress Responses The contrasting relationships between Hsp60 levels and cardiac outcomes in males versus females likely reflect X-linked inheritance patterns and hormonal influences on mitochondrial function ( 25 ). In males who carry only one X chromosome, uniform GLA expression patterns may allow for more predictable mitochondrial stress responses. The protective association of higher Hsp60 with lower LVMI in males aligns with studies showing cardioprotective effects of moderate Hsp60 upregulation ( 26 , 27 ). Conversely, the positive correlation between Hsp60 and LVMI in females may reflect X-inactivation mosaicism leading to variable cellular stress responses ( 28 ). Females with higher Hsp60 levels were paradoxically younger, suggesting early-onset, severe disease rather than a protective stress response. This pattern may indicate that in severely affected female patients, mitochondrial stress responses may become maladaptive in contexts of overwhelming cellular stress. The observation that females showed a negative correlation between Hsp60 and age, contrasting with the positive correlation in healthy controls, suggests that normal ageing patterns are disrupted. This may be related to the modulatory effects of oestrogen on mitochondrial function and stress responses ( 29 ). 4.3 Mitokine Elevation and Clinical Implications Elevated GDF-15 levels in male FD patients align with its established role as a stress-responsive mitokine in cardiovascular and renal disease ( 30 ). GDF-15 has emerged as a biomarker of mitochondrial dysfunction and is elevated in various cardiovascular conditions ( 31 ). Comparative biomarker studies suggest that GDF-15 provides a more global signal across mitochondrial disease phenotypes, while FGF-21 is more influenced by muscle involvement ( 32 ). Consistent with this, mechanistic studies indicate that mitochondrial stress in skeletal muscle is a major driver of FGF-21 secretion, whereas GDF-15 integrates mitochondrial stress signals across tissues ( 33 ). The strong relationship between treatment timing and mitokine levels has important clinical implications. Patients initiating therapy after age 40 showed markedly elevated mitokine levels, suggesting a greater burden of mitochondrial stress at the time of intervention. This observation supports current discussions supporting early therapeutic intervention, even in asymptomatic patients ( 34 ). Is late treatment just a surrogate for late onset patients? 4.4 Genotype-Specific Responses: Implications for Disease Mechanisms The striking differences in mitochondrial stress marker patterns between N215S and non-N215S patients suggest fundamentally distinct pathogenic mechanisms underlying these Fabry disease subtypes. These findings challenge the traditional view of FD as a uniform lysosomal storage disorder and point toward genotype-specific therapeutic requirements. 4.4.1 Protein Misfolding vs. Protein Absence Paradigms The N215S variant exemplifies the later-onset missense mutation with cellular trafficking abnormalities within Fabry disease. This missense mutation results in a thermolabile enzyme that misfolds in the endoplasmic reticulum (ER), triggering ER-associated degradation (ERAD) and subsequently activating downstream stress responses ( 35 ). Our fibroblast data demonstrate that missense variants, such as R301Q, produce robust Hsp60 upregulation (187% of wild-type), consistent with a pronounced mitochondrial stress response in response to proteostatic stress. This misfolded protein burden creates a dual pathology: ( 1 ) enzyme deficiency leading to substrate accumulation and ( 2 ) continuous proteostatic stress from attempted protein folding and degradation. The ER-mitochondria contact sites (mitochondrial-associated membranes) serve as critical communication hubs where ER stress can contribute to mitochondrial stress signalling ( 36 ). In N215S patients, this creates a chronic state of integrated stress response activation that may fundamentally alter cellular metabolism and stress tolerance. Conversely, nonsense variants like R220X represent a \"protein absence disorder,\" where mRNA degradation via nonsense-mediated decay prevents the accumulation of misfolded proteins ( 37 ). Our data show minimal Hsp60 upregulation (45% of wild-type) in these variants, suggesting that the absence of misfolded protein reduces proteostatic stress despite equivalent or greater substrate accumulation. This suggests the relevant pathology is primarily lysosomal dysfunction without the added burden of protein misfolding stress. 4.4.2 Therapeutic Implications of Mechanistic Differences These mechanistic distinctions have therapeutic implications. N215S patients showed that 92% of MSSI variance was explained by FGF-21 levels alone, indicating a tight coupling between mitochondrial stress and clinical severity. This suggests that therapies targeting proteostasis (such as pharmacological chaperones) may be particularly beneficial for missense variants by reducing the protein misfolding burden and consequently decreasing proteostatic and mitochondrial stress ( 38 ). In addition, our treatment analysis revealed that patients receiving pharmacological chaperone therapy showed different mitokine patterns compared to enzyme replacement therapy, with stronger correlations between treatment initiation age and FGF-21 levels (r²=0.65, p = 0.002). This suggests that successful protein rescue by chaperones may specifically ameliorate the proteostatic stress component of disease pathogenesis. For nonsense variants, the primary pathology stems from substrate accumulation rather than protein misfolding stress. These patients may benefit more from substrate reduction or enzyme replacement if their cellular stress responses are less overwhelmed by proteostatic burden ( 39 ). 4.4.3 Sex-Specific Interactions with Genotype The interaction between genotype and sex adds another layer of complexity. In N215S males, higher Hsp60 levels strongly correlated with better renal function (r²=0.89, p = 0.006), suggesting that a more effective mitochondrial stress response may be associated with cytoprotection when proteostatic stress is manageable. However, even high Hsp60 levels are associated with worse outcomes in females with severe phenotypes, possibly reflecting X-inactivation mosaicism creating cellular populations with varying stress tolerance ( 40 ). This sex-genotype interaction may explain why some female N215S patients develop severe phenotypes despite this variant's \"late-onset\" classification. Cellular mosaicism may create focal areas of high misfolded protein burden that overwhelm local stress responses, leading to tissue-specific pathology despite overall preserved enzyme activity. These observations highlight the need for future work that clarifies the cellular basis of these sex- and genotype-specific responses, including how mitochondrial stress responses are modulated across different tissues. 4.4.4 Evolutionary and Clinical Perspectives From an evolutionary perspective, preserving missense variants like N215S in the population, despite their pathogenic potential, may reflect residual protein function under optimal conditions. The amenability of many missense variants to pharmacological chaperone therapy supports this concept³⁶. However, chronic proteostatic stress may accelerate cellular ageing processes, explaining the delayed but progressive nature of complications in these patients. Clinically, these findings suggest that Fabry disease represents at least two distinct disorders: a \"protein misfolding lysosomal disease\" (exemplified by N215S and similar variants) and a \"classical lysosomal storage disease\" (exemplified by nonsense variants). This distinction may require different monitoring strategies, with mitokine levels being potentaillyuseful for the former group, and traditional biomarkers (lyso-Gb3, clinical symptoms) being more relevant for the latter. The therapeutic window concept also differs between groups. Missense variant patients may have a narrower therapeutic window due to cumulative proteostatic damage, explaining why early intervention is particularly relevant for preventing irreversible mitochondrial dysfunction. Nonsense variant patients may have more predictable progression patterns based primarily on substrate accumulation kinetics and so while early therapy is not less relevant it is more obviously prompted by the onset of clinical features. 4.5 Therapeutic Implications These findings have several potential therapeutic implications. First, mitokine levels, particularly GDF-15, may serve as biomarkers for monitoring treatment response and disease progression. Second, the relationship between treatment initiation age and mitochondrial dysfunction markers supports aggressive early treatment strategies. Third, sex-specific differences in mitochondrial stress responses may require tailored treatment approaches. The observation that pharmacological chaperone therapy (PCT) showed different associations with mitokine levels compared to enzyme replacement therapy suggests that treatment modalities targeting protein folding may have distinct effects on mitochondrial stress responses. Mitochondrial stress markers may also help refine treatment stratification by identifying patients with greater vulnerability to mitochondrial dysfunction or differential responses to specific therapies 4.6 Study Limitations Several limitations warrant consideration. The cross-sectional design precludes the determination of causality between mtUPR related markers and clinical outcomes. In addition, the markers used here do not provide definitive evidence of mtUPR activation. The relatively small sample size, particularly for subgroup analyses, limits statistical power and generalisability. Given the modest numbers within sex- and genotype-stratified analyses, these findings should be regarded as exploratory and hypothesis-generating and may be susceptible to statistical artefact. The study design also does not allow full adjustment for potential confounders, including age, treatment status, genotype, co-morbidities, and other clinical variables. We measured Hsp60 in PBMCs, which may not accurately reflect organ-specific mitochondrial stress. PBMCs also represent a heterogeneous cell population, and inter-individual variation in cellular composition may influence Hsp60 levels independently of disease-related stress responses. Tissue-specific markers would provide more direct evidence of organ-level mitochondrial stress. Furthermore, PBMCs were cultured before analysis, and ex vivo culture conditions may themselves influence stress protein expression. Another important limitation relates to Hsp60 quantification, which was performed by western blotting. This is a semi-quantitative technique and is subject to technical and inter-experimental variability despite normalisation to a loading control. Samples were analysed across multiple gels; a consistent reference control sample was used across gels for female experiments. However, in male experiments different control samples were used across gels, and inter-gel variability therefore cannot be fully excluded. We cannot exclude the influence of co-morbidities, medications, or environmental factors on the mitochondrial stress markers assessed. Future studies should include a comprehensive assessment of potential confounders. Finally, the mechanistic basis for sex-specific differences remains unclear. Functional studies examining patterns of X-inactivation, hormonal influences, and cellular stress responses are required to elucidate the underlying mechanisms. 5. Conclusions This study shows that mtUPR related markers exhibits sex- and genotype-specific patterns in Fabry disease that are associated with cardiac and renal disease severity. Higher intracellular Hsp60 levels are associated with lower LVMI in males but higher in females, while elevated serum mitokines, particularly GDF-15, are associated with disease severity and late treatment initiation. These findings suggest that mitochondrial stress responses may contribute significantly to phenotypic heterogeneity in Fabry disease and may have potential as biomarkers for disease monitoring and optimisation of treatment timing. The strong association between treatment initiation age and mitokine levels supports early therapeutic intervention and suggests that mitochondrial dysfunction may become irreversible beyond a critical age threshold. Future longitudinal studies are needed to validate these markers for clinical use and to elucidate the mechanistic basis for sex-specific differences in mitochondrial stress responses. Understanding these pathways may lead to new therapeutic targets and personalised treatment approaches for Fabry disease. Declarations Ethics approval and consent to participate This study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC: 20/WM/0329). All participants provided written informed consent. Consent for publication Not applicable. Availability of data and materials The datasets generated and analysed during the current study are available from the corresponding author on reasonable request. Competing interests Derralynn Hughes has received consulting and speaking fees from Sanofi, Takeda, Chiesi and Amicus, and consulting fees from Ultragenyx, Sangamo, Idorsia, Spur Therapeutics and Relay Therapeutics, administered through UCL Consultants and used in part to support research in lysosomal storage disorders. David Moreno Martinez has received honoraria for speaking engagements, advisory board participation and travel grants from Sanofi, Takeda, Chiesi and Amicus. The remaining authors declare that they have no competing interests. Funding This work was supported by the Royal Free Charity. Authors’ contributions Lucia Lavalle designed the study, performed experiments, analysed the data, and drafted the manuscript. Derralynn Hughes conceived and supervised the study and contributed to data interpretation and manuscript revision. Hibba Kudri contributed to acquisition of cardiac data. David Moreno Martinez contributed to patient recruitment and clinical data collection. Vincent Muczynski contributed to laboratory experiments, including mitokine measurements. Simon Heales contributed to study oversight and critical revision of the manuscript. All authors read and approved the final manuscript. References Germain DP. Fabry disease. Orphanet J Rare Dis. 2010 Nov 22;5:30. doi:10.1186/1750-1172-5-30 PubMed PMID: 21092187. Nowak A, Huynh-Do U, Krayenbuehl PA, Beuschlein F, Schiffmann R, Barbey F. Fabry disease genotype, phenotype, and migalastat amenability: Insights from a national cohort. J Inherit Metab Dis. 2020 Mar;43(2):326–33. doi:10.1002/jimd.12167 PubMed PMID: 31449323. Ortiz A, Germain DP, Desnick RJ, Politei J, Mauer M, Burlina A, et al. 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EBioMedicine. 2025 May;115:105733. doi:10.1016/j.ebiom.2025.105733 Hughes DA, Ramaswami U, Barba Romero MÁ, Deegan P. Age adjusting severity scores for Anderson–Fabry Disease. Mol Genet Metab. 2010;101(2):219–27. doi:https://doi.org/10.1016/j.ymgme.2010.06.002 Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol. 1986 Feb 15;57(6):450–8. doi:10.1016/0002-9149(86)90771-x PubMed PMID: 2936235. Chuang ML, Gona P, Hautvast GLTF, Salton CJ, Breeuwer M, O’Donnell CJ, et al. CMR reference values for left ventricular volumes, mass, and ejection fraction using computer-aided analysis: the Framingham Heart Study. J Magn Reson Imaging. 2014 Apr;39(4):895–900. doi:10.1002/jmri.24239 PubMed PMID: 24123369. Lamb EJ, Levey AS, Stevens PE. The Kidney Disease Improving Global Outcomes (KDIGO) guideline update for chronic kidney disease: evolution not revolution. Clin Chem. 2013 Mar;59(3):462–5. doi:10.1373/clinchem.2012.184259 PubMed PMID: 23449698. Smid BE, van der Tol L, Cecchi F, Elliott PM, Hughes DA, Linthorst GE, et al. Uncertain diagnosis of Fabry disease: consensus recommendation on diagnosis in adults with left ventricular hypertrophy and genetic variants of unknown significance. Int J Cardiol. 2014 Dec 15;177(2):400–8. doi:10.1016/j.ijcard.2014.09.001 PubMed PMID: 25442977. Welsh P, Kimenai DM, Marioni RE, Hayward C, Campbell A, Porteous D, et al. Reference ranges for GDF-15, and risk factors associated with GDF-15, in a large general population cohort. Clin Chem Lab Med. 2022 Oct 26;60(11):1820–9. doi:10.1515/cclm-2022-0135 PubMed PMID: 35976089. Jena J, García-Peña LM, Pereira RO. The roles of FGF21 and GDF15 in mediating the mitochondrial integrated stress response. Front Endocrinol (Lausanne). 2023 Sep 25;14. doi:10.3389/fendo.2023.1264530 Benarroch E. What Are the Roles of Mitochondrial Stress Responses and Mitohormesis in Neurodegenerative Disorders? Neurology. 2026 Feb 10;106(3). doi:10.1212/WNL.0000000000214618 Riar AK, Burstein SR, Palomo GM, Arreguin A, Manfredi G, Germain D. Sex specific activation of the ERα axis of the mitochondrial UPR (UPRmt) in the G93A-SOD1 mouse model of familial ALS. Hum Mol Genet. 2017 Apr 1;26(7):1318–27. doi:10.1093/hmg/ddx049 Hu Y, Chen X, Li X, Li Z, Diao H, Liu L, et al. MicroRNA‑1 downregulation induced by carvedilol protects cardiomyocytes against apoptosis by targeting heat shock protein 60. Mol Med Rep. 2019 May;19(5):3527–36. doi:10.3892/mmr.2019.10034 PubMed PMID: 30896796. Krishnan-Sivadoss I, Mijares-Rojas IA, Villarreal-Leal RA, Torre-Amione G, Knowlton AA, Guerrero-Beltrán CE. Heat shock protein 60 and cardiovascular diseases: An intricate love-hate story. Med Res Rev. 2021 Jan;41(1):29–71. doi:10.1002/med.21723 PubMed PMID: 32808366. Echevarria L, Benistan K, Toussaint A, Dubourg O, Hagege AA, Eladari D, et al. X-chromosome inactivation in female patients with Fabry disease. Clin Genet. 2016 Jan;89(1):44–54. doi:10.1111/cge.12613 PubMed PMID: 25974833. Klinge CM. Estrogenic control of mitochondrial function. Redox Biol. 2020 Apr;31:101435. doi:10.1016/j.redox.2020.101435 PubMed PMID: 32001259. Wischhusen J, Melero I, Fridman WH. Growth/Differentiation Factor-15 (GDF-15): From Biomarker to Novel Targetable Immune Checkpoint. Front Immunol. 2020;11:951. doi:10.3389/fimmu.2020.00951 PubMed PMID: 32508832. Burtscher J, Soltany A, Visavadiya NP, Burtscher M, Millet GP, Khoramipour K, et al. Mitochondrial stress and mitokines in aging. Aging Cell. 2023 Feb;22(2):e13770. doi:10.1111/acel.13770 PubMed PMID: 36642986. Davis RL, Liang C, Sue CM. A comparison of current serum biomarkers as diagnostic indicators of mitochondrial diseases. Neurology. 2016 May 24;86(21):2010–5. doi:10.1212/WNL.0000000000002705 Romanello V, Sandri M. Implications of mitochondrial fusion and fission in skeletal muscle mass and health. Semin Cell Dev Biol. 2023 Jul;143:46–53. doi:10.1016/j.semcdb.2022.02.011 Ortiz A, Abiose A, Bichet DG, Cabrera G, Charrow J, Germain DP, et al. Time to treatment benefit for adult patients with Fabry disease receiving agalsidase β: data from the Fabry Registry. J Med Genet. 2016 Jul;53(7):495–502. doi:10.1136/jmedgenet-2015-103486 PubMed PMID: 26993266. Ishii S, Chang HH, Kawasaki K, Yasuda K, Wu HL, Garman SC, et al. Mutant alpha-galactosidase A enzymes identified in Fabry disease patients with residual enzyme activity: biochemical characterization and restoration of normal intracellular processing by 1-deoxygalactonojirimycin. Biochem J. 2007 Sep 1;406(2):285–95. doi:10.1042/BJ20070479 PubMed PMID: 17555407. Csordás G, Renken C, Várnai P, Walter L, Weaver D, Buttle KF, et al. Structural and functional features and significance of the physical linkage between ER and mitochondria. J Cell Biol. 2006 Sep 25;174(7):915–21. doi:10.1083/jcb.200604016 PubMed PMID: 16982799. Lukas J, Giese AK, Markoff A, Grittner U, Kolodny E, Mascher H, et al. Functional characterisation of alpha-galactosidase a mutations as a basis for a new classification system in fabry disease. PLoS Genet. 2013;9(8):e1003632. doi:10.1371/journal.pgen.1003632 PubMed PMID: 23935525. Yam GHF, Zuber C, Roth J. A synthetic chaperone corrects the trafficking defect and disease phenotype in a protein misfolding disorder. FASEB J. 2005 Jan;19(1):12–8. doi:10.1096/fj.04-2375com PubMed PMID: 15629890. Abe A, Gregory S, Lee L, Killen PD, Brady RO, Kulkarni A, et al. Reduction of globotriaosylceramide in Fabry disease mice by substrate deprivation. J Clin Invest. 2000 Jun;105(11):1563–71. doi:10.1172/JCI9711 PubMed PMID: 10841515. Dobrovolny R, Dvorakova L, Ledvinova J, Magage S, Bultas J, Lubanda JC, et al. Relationship between X-inactivation and clinical involvement in Fabry heterozygotes. Eleven novel mutations in the alpha-galactosidase A gene in the Czech and Slovak population. J Mol Med (Berl). 2005 Aug;83(8):647–54. doi:10.1007/s00109-005-0656-2 PubMed PMID: 15806320. Additional Declarations No competing interests reported. Supplementary Files SupplementaryfigureS1.pdf Supplementary figure S1. Elevated serum mitokine levels in Fabry disease patients. Serum levels of (A) fibroblast growth factor-21 (FGF-21) and (B) growth differentiation factor-15 (GDF-15) were measured by ELISA in FD patients and healthy controls stratified by sex. (C) Demographic characteristics of study participants. Male FD patients show significantly elevated GDF-15 levels compared to healthy male controls (935 vs. 559 pg/ml, **p=0.002), while FGF-21 levels and both mitokines in females show no significant differences from controls. Individual data points are shown with median and interquartile range. Statistical analysis by Mann-Whitney U test; **p<0.01, ns = not significant. These findings suggest sex-specific mitochondrial dysfunction patterns in FD. SupplementaryfileUncroppedgels.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 May, 2026 Reviews received at journal 11 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 06 Apr, 2026 Submission checks completed at journal 06 Apr, 2026 First submitted to journal 02 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-9304477\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":621846789,\"identity\":\"2d4b0d8f-0a77-4d82-9933-fd0ad0bf933c\",\"order_by\":0,\"name\":\"Lucia Lavalle\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Lucia\",\"middleName\":\"\",\"lastName\":\"Lavalle\",\"suffix\":\"\"},{\"id\":621846790,\"identity\":\"3486d77c-f917-4991-8442-b632a5b2c67b\",\"order_by\":1,\"name\":\"Hibba Kurdi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hibba\",\"middleName\":\"\",\"lastName\":\"Kurdi\",\"suffix\":\"\"},{\"id\":621846792,\"identity\":\"6b555567-4cff-446e-aa78-f215b1d6e853\",\"order_by\":2,\"name\":\"David Moreno Martinez\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"David\",\"middleName\":\"Moreno\",\"lastName\":\"Martinez\",\"suffix\":\"\"},{\"id\":621846794,\"identity\":\"6ec022f5-633f-4d64-81a4-50eab26266d3\",\"order_by\":3,\"name\":\"Vincent Muczynski\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Vincent\",\"middleName\":\"\",\"lastName\":\"Muczynski\",\"suffix\":\"\"},{\"id\":621846796,\"identity\":\"168ca48b-5c21-4c44-816b-296931b72709\",\"order_by\":4,\"name\":\"Simon Heales\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Simon\",\"middleName\":\"\",\"lastName\":\"Heales\",\"suffix\":\"\"},{\"id\":621846798,\"identity\":\"a378f322-e5bc-4664-b34e-6e0eb7a0a4ff\",\"order_by\":5,\"name\":\"Derralynn Hughes\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDCCAyCiAIglGBiYgZQciEGEFgOEFmOoFgPitSQ2ENLCd7z32YcfBofzzKV7jF8XVNSlb5duf8BcUPEHpxbJM8eNZ/YYHC62nHPGzHrGmcO5O+ecMWCecQa3LQY30pgZeAwOJ264kWNmzNt2IBfIYGDmbcOj5f4zZsY/cC3/6tINbqQ/YOb9h88WNmZmqC3Gj3kbmBMMbiQYMPM24NYieSaNmVnGIB2oJa2MmefYYUOgXoPDPMeMcWrhO36MmfFNhTVQS/Lmzzw1dfJAhz18zFMjh1MLFDSDCDZ4vB8gpB4I6kAE8wciVI6CUTAKRsEIBACOole9Fl6WtgAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Derralynn\",\"middleName\":\"\",\"lastName\":\"Hughes\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-02 14:39:03\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9304477/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9304477/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":107244793,\"identity\":\"2e1b23ee-9eb0-4ca8-9b7f-141d58b1fd83\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:54\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":143721,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGenotype-specific heat shock protein expression in Fabry disease fibroblasts.\\u003c/strong\\u003e (A) Representative western blots showing Hsp60 and Hsp10 expression in wild-type (WT), nonsense variant (R220X), and missense variant (R301Q) fibroblast cell lines. Na+/K+-ATPase serves as a loading control. (B) Quantification of heat shock protein levels normalised to loading control and expressed as a percentage of wild-type. The missense variant R301Q shows marked upregulation of both Hsp60 (187% of WT) and Hsp10 (127% of WT), while the nonsense variant R220X exhibits reduced expression (Hsp60: 45%, Hsp10: 18% of WT). Data represent single experiments from characterised cell lines. These findings suggest that missense variants causing protein misfolding trigger robust mitochondrial stress response than nonsense variants resulting in protein absence .\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/305a4183013d1a37e6541bd9.png\"},{\"id\":107244711,\"identity\":\"7f271c81-e6c4-4b7f-85a1-2743e5026ae1\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:43\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":279950,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eIntracellular Hsp60 levels in peripheral blood mononuclear cells from Fabry disease patients.\\u003c/strong\\u003e (A) Representative western blots showing Hsp60 expression in PBMCs from healthy controls (HC) and Fabry disease (FD) patients with different genotypes. Na+/K+-ATPase serves as a loading control. (B) Quantification of Hsp60 levels for individual patients, normalised to Na+/K+-ATPase within each gel. Samples were analysed across multiple gels as described in the methods section. (C) Summary data showing Hsp60 levels as a percentage of healthy control median for males and females separately. While no significant overall difference exists between FD patients and controls, substantial inter-patient variability is observed, with some patients showing \\u0026gt;2-fold elevation and others \\u0026lt;50% of control levels. Males: n=14 FD patients, n=3 controls; Females: n=13 FD patients, n=1 control. Statistical analysis by Mann-Whitney U test; ns = not significant.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/1157a13fd73d15356847a28e.png\"},{\"id\":107244840,\"identity\":\"eb3dfb8e-615b-4487-b59d-acf08a6e3c22\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:59\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":262766,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAssociations between intracellular Hsp60 expression, age, clinical severity and organ-specific outcomes in Fabry.\\u003c/strong\\u003e (A) Correlation between Hsp60 levels and age in healthy controls (n=4) showing the expected positive relationship (r²=1.0, p=0.04). (B) Age-Adjusting Severity Score (AASS) comparison between patients with high vs low Hsp60 levels, stratified by sex. In females, higher Hsp60 levels are associated with higher severity scores (*p \\u0026lt; 0.05), while males show no significant association. (C) Correlation between Hsp60 levels and age in FD patients. In males, no significant association is observed. In females, a negative relationship is seen (r² = −0.57, p = 0.02), in contrast to the positive age relationship observed in healthy controls. Data are coloured by AASS category. (D) Correlation analyses between intracellular Hsp60 levels (normalised to loading control) and clinical outcomes in male patients. Overall severity (AASS): \\u0026nbsp;separate analyses are shown for N215S patients (red symbols, negative trend: r = −0.67, p = 0.06) and non-N215S patients (black symbols, positive trend: r = 0.54, p = 0.12). Left ventricular mass index (LVMI): higher Hsp60 correlates with lower LVMI (r² = −0.82, p = 0.01), with a particularly strong relationship in N215S patients (r² = −1.0, p = 0.017). Glomerular filtration rate (GFR): N215S individuals show preserved renal function with higher Hsp60 (r² = 0.89, p = 0.006), whereas non-N215S show the opposite pattern (r² = −0.89, p = 0.006). (E) Correlation analyses between intracellular Hsp60 levels and clinical outcomes in female: higher Hsp60 levels correlate with greater AASS (r² = 0.54, p = 0.03) and with higher LVMI (r² = 0.66, p = 0.045). These findings indicate that altered mitochondrial stress responses in FD are independent of chronological ageing and exhibit sex- and genotype-specific associations with clinical severity and organ involvement.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/1ba60e3a8e948b5373c36b15.png\"},{\"id\":107244790,\"identity\":\"2daf33df-2071-4d01-8bc6-5b80649f0f15\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:52\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":232171,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eRelationships between circulating mitokines, ageing, intracellular Hsp60 and clinical outcomes in Fabry disease. \\u003c/strong\\u003e(A)\\u003cstrong\\u003e \\u003c/strong\\u003eCorrelation analyses between serum mitokines and age in Fabry disease (FD) and healthy controls (HC). FGF-21 shows a significant positive correlation with age in FD patients (r = 0.39, p = 0.02) but not in controls (r = 0.09, p = 0.68). GDF-15 demonstrates strong positive correlations with age in both FD patients (r = 0.64, p \\u0026lt; 0.0001) and controls (r = 0.63, p = 0.0007), with a steeper slope in FD patients. Red symbols indicate female patients, and black symbols indicate male patients. These data suggest accelerated mitochondrial ageing in FD, with greater age-related increases in stress-responsive mitokines compared to healthy individuals. (B) Correlation analyses between intracellular Hsp60 levels and serum mitokines in FD patients. In males, higher Hsp60 correlates strongly with lower FGF-21 (r = −0.75, p = 0.004), while no significant correlation is observed in females. In females, higher Hsp60 correlates with lower GDF-15 (r = −0.57, p = 0.047), whereas no correlation is observed in males (r = 0.04, p = 0.90). N215S patients are indicated in red. (C) Summary correlation matrices showing the direction and strength of associations between intracellular Hsp60, serum mitokines, age, left ventricular mass index (LVMI), glomerular filtration rate (GFR), Mainz Severity Score Index (MSSI), and Age-Adjusting Severity Score (AASS). These inverse and age-dependent relationships indicate coordinated but sex-specific mitochondrial stress responses, where intracellular stress-response activation may reduce the need for systemic mitokine signalling or reflect differential pathway activation across patient subgroups.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/b82eb0c43c67b0828ddafae1.png\"},{\"id\":107482412,\"identity\":\"5ee3b111-3fbd-4798-9bfa-8d10037c9dba\",\"added_by\":\"auto\",\"created_at\":\"2026-04-22 02:23:28\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1347824,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/0b0f7395-2062-4c35-856b-0363dd4c1397.pdf\"},{\"id\":107244709,\"identity\":\"664c6d17-a738-4fa6-80d2-96cca41bc7b9\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:43\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":90804,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSupplementary figure S1. Elevated serum mitokine levels in Fabry disease patients\\u003c/strong\\u003e. Serum levels of (A) fibroblast growth factor-21 (FGF-21) and (B) growth differentiation factor-15 (GDF-15) were measured by ELISA in FD patients and healthy controls stratified by sex. (C) Demographic characteristics of study participants. Male FD patients show significantly elevated GDF-15 levels compared to healthy male controls (935 vs. 559 pg/ml, **p=0.002), while FGF-21 levels and both mitokines in females show no significant differences from controls. Individual data points are shown with median and interquartile range. Statistical analysis by Mann-Whitney U test; **p\\u0026lt;0.01, ns = not significant. These findings suggest sex-specific mitochondrial dysfunction patterns in FD.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"SupplementaryfigureS1.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/f9fff8428e38e82401f08a0d.pdf\"},{\"id\":107244791,\"identity\":\"1b253254-a938-4bbc-b6a4-0b5dc620c996\",\"added_by\":\"auto\",\"created_at\":\"2026-04-19 07:55:53\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":298918,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryfileUncroppedgels.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9304477/v1/0ac90fe72577d7fb534b018a.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Mitochondrial stress markers associate with phenotypic variability in Fabry disease\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eFabry disease (FD) is a progressive, X-linked lysosomal storage disorder caused by deficient α-galactosidase A activity, leading to globotriaosylceramide (Gb3) accumulation in multiple organ systems (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). The clinical heterogeneity of FD is striking, ranging from severe classical phenotypes manifesting in childhood to late-onset variants with organ-specific manifestations that may not appear until middle age (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e). This phenotypic variability cannot be fully explained by residual enzyme activity alone, as patients with similar biochemical profiles often exhibit markedly different clinical courses (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e). Understanding the molecular mechanisms underlying this heterogeneity is crucial for optimising therapeutic strategies and improving patient outcomes.\\u003c/p\\u003e \\u003cp\\u003eAgeing and lysosomal storage disorders share common features of proteostatic stress, characterised by the accumulation of misfolded proteins and declining cellular quality control mechanisms (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e). In Fabry disease, evidence suggests that cellular dysfunction extends beyond Gb3 accumulation, encompassing mitochondrial abnormalities, oxidative stress, and inflammatory responses (\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e). The progressive nature of FD manifestations with age suggests that cellular stress responses may become overwhelmed over time, contributing to organ dysfunction.\\u003c/p\\u003e \\u003cp\\u003eThe mitochondrial unfolded protein response (mtUPR) represents a conserved quality control mechanism activated by mitochondrial proteostatic stress (\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e). Upon detecting mitochondrial dysfunction, cells initiate a coordinated nuclear-mitochondrial signalling pathway that up-regulates protective factors, including mitochondrial chaperones such as heat shock protein 60 (Hsp60) (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e). Additionally, mitochondrial stress triggers the cellular release of signalling molecules termed mitokines, including fibroblast growth factor 21 (FGF-21) and growth differentiation factor 15 (GDF-15), which coordinate systemic metabolic responses (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). While engagement of mitochondrial stress responses is generally cytoprotective, sustained signalling may become maladaptive and contribute to pathology (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eSeveral observations support a role for mitochondrial stress responses in the pathogenesis of Fabry disease. First, lysosomal dysfunction can impair mitochondrial function through disrupted calcium homeostasis and altered autophagy (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). Second, the accumulation of misfolded α-galactosidase A variants may create additional proteostatic stress (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e). Third, the progressive, age-related nature of FD complications mirrors patterns seen in other conditions characterised by chronic mitochondrial stress signalling (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). These effects may vary by variant class, as missense and nonsense GLA variants are associated with different molecular consequences (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eWe hypothesised that altered Hsp60 expression and mitokine levels are associated with phenotypic variability in Fabry disease and correlate with disease severity, particularly in cardiac and renal manifestations. Furthermore, we predicted that sex-specific differences in mitochondrial stress responses might help explain the different clinical patterns observed between male and female FD patients.\\u003c/p\\u003e\"},{\"header\":\"2. Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Study Design and Participants\\u003c/h2\\u003e \\u003cp\\u003e This cross-sectional study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC: 20/WM/0329) and the study was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent. We recruited 27 FD patients (14 males, 13 females) with confirmed GLA mutations and documented enzyme activity measurements before treatment initiation. Healthy controls for Hsp60 analyses included (n\\u0026thinsp;=\\u0026thinsp;4; 3 males, 1 female). In contrast, the mitokine analyses included a larger cohort of age- and sex-matched volunteers without known genetic disorders (n\\u0026thinsp;=\\u0026thinsp;25; 17 males, 8 females).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Clinical Assessments\\u003c/h2\\u003e \\u003cp\\u003eClinical data were collected retrospectively from medical records. Disease severity was assessed using the Mainz Severity Score Index (MSSI) and Age-Adjusting Severity Score (AASS) (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e). The cardiac evaluation included electrocardiogram and cardiac magnetic resonance imaging, with left ventricular mass index (LVMI) calculated using the Devereux formula (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). Left ventricular hypertrophy was defined as LVMI\\u0026thinsp;\\u0026ge;\\u0026thinsp;78 g/m\\u0026sup2; (males) or \\u0026ge;\\u0026thinsp;74 g/m\\u0026sup2; (females)(\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e). Renal function was assessed by estimating glomerular filtration rate (eGFR) using the CKD-EPI Eq.\\u0026nbsp;(20). Patients were classified as classical or late-onset based on residual enzyme activity and characteristic symptoms (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Laboratory Methods\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.1 Cell Culture and Protein Analysis\\u003c/h2\\u003e \\u003cp\\u003ePeripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation and cultured for 6 days in RPMI-1640 medium. Whole-cell lysates were prepared using mammalian cell lysis buffer with protease inhibitors. Hsp60 levels were measured by western blotting using an anti-Hsp60 monoclonal antibody (Bio-techne, NBP2-34670H) with Na+/K+-ATPase as loading control. Samples were analysed across multiple gels. For female samples, a consistent control sample was included across all gels. For male samples, one of three wild-type control samples was included within each gel. Densitometric quantification was normalised within each gel to the loading control. Fibroblast cell lines GM00302, GM00881, GM00882 (Coriell Institute) were grown in EMEM medium.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.2 Serum Mitokine Analysis\\u003c/h2\\u003e \\u003cp\\u003eBased on manufacturer protocols, Serum FGF-21 and GDF-15 levels were measured using commercial ELISA kits (R\\u0026amp;D Systems, DF2100 and DGD150).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Statistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eData analysis was performed using GraphPad Prism 8.0. Continuous variables are presented as median with interquartile range. Group comparisons used Mann-Whitney U tests or Kruskal-Wallis tests with Dunn's post-hoc correction. Correlations were assessed using Spearman's rank correlation. Multiple linear regression was employed to identify predictors of clinical outcomes. We applied Bonferroni correction for primary analyses (α\\u0026thinsp;=\\u0026thinsp;0.01) to address multiple testing and reported effect sizes alongside p-values. Statistical significance was set at p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 for exploratory analyses.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Patient Characteristics\\u003c/h2\\u003e \\u003cp\\u003eTwenty-seven FD patients were included: 14 males (9 with N215S variant, 5 with other variants) and 13 females. Patient demographics are summarised in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Males with the N215S variant showed predominantly cardiac phenotypes, while non-N215S males exhibited more classical, multisystem disease. Female patients exhibited variable phenotypes, independent of their genotype.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003ePatient demographics\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParameters\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOverall\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eN\\u0026thinsp;=\\u0026thinsp;19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN\\u0026thinsp;=\\u0026thinsp;17\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN215S\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003enon-N215S\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eN (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9 (47.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10 (52.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (years) at diagnosis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e48.9 (19.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24.5 (17.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e37 (17.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMedian (range)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54 (13 to 71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26 (1 to 53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e37.5 (5 to 69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCurrently on treatment, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9 (100)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10 (100)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12 (70.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEnzyme replacement therapy, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6 (60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6 (50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePharmacological chaperone therapy, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8 (88.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4 (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6 (50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (years) at treatment commencement\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e50.8 (18.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e29.5 (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e36.9 (15.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMedian (range)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e57 (15 to 71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e31.5 (2 to 53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e39 (12 to 63)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eClassic Fabry disease cardinal features\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAcroparesthesias, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8 (47.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFabry crisis, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0 (0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4 (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4 (23.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAngiokeratoma, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3 (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3 (17.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDecreased sweating, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (44.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6 (35.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCornea verticillata*, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0 (0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2 (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2 (11.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbnormal pure tone audiometry, n (missing)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6 (0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11 (0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean age (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e67 (6.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42.3 (6.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e46.6 (21.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMedian age (range)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e65 (62 to 76)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e41.5 (35 to 55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e57 (4 to 69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLVH on image, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7 (77.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7 (41.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean age (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e57.4 (8.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42.2 (8.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e54.7 (9.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMedian age (range)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e57 (45 to 71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e41 (29 to 53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e52 (42\\u0026ndash;69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCKD stages (mL/min/1.73m2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1 (\\u0026gt;\\u0026thinsp;90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2 (60\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;89)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3A (45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3B (30\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e4 (\\u0026gt;\\u0026thinsp;15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e5 (\\u0026lt;\\u0026thinsp;15 or on dialysis)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGI symptoms during childhood\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4 (30.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSerious clinical outcomes**, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6 (66.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6 (46.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOverall severity at sampling\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMild (MSSI\\u0026thinsp;\\u0026lt;\\u0026thinsp;20), n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (44.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3 (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10 (5.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate (MSSI\\u0026thinsp;=\\u0026thinsp;20\\u0026ndash;40), n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3 (33.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6 (35.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere (MSSI\\u0026thinsp;\\u0026gt;\\u0026thinsp;40), n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (22.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2 (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1 (5.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge adjusting score\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-5.7 (6.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8.7 (9.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.8 (10.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMedian\\u003c/p\\u003e \\u003cp\\u003e (range)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-6.9\\u003c/p\\u003e \\u003cp\\u003e (-15.8 to 6.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7\\u003c/p\\u003e \\u003cp\\u003e (-9.6 to 22.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.1\\u003c/p\\u003e \\u003cp\\u003e (-14.3 to 24.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e* Cornea verticillata was not assessed for all patients.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e**Serious clinical outcomes include myocardial infarction, stroke, transient ischaemic attack, implantation of pacemaker or of implantable cardiovascular defibrillator, the development of atrial fibrillation, and chronic kidney disease (CKD) 3A (GFR \\u0026lt;\\u0026thinsp;59ml/min/1.73m2).N: number, SD: standard deviation, LVH: left ventricular hypertrophy, GI: gastrointestinal.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Mitochondrial Stress Response in Fabry Fibroblasts\\u003c/h2\\u003e \\u003cp\\u003eInitial characterisation using immortalised fibroblast cell lines revealed fundamental differences in cellular stress responses between variant types (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The missense R301Q variant exhibited a marked elevation of both Hsp60 (187% of the wild-type level) and Hsp10 (127% of the wild-type level), consistent with mitochondrial stress responses involving the mtUPR pathway. In contrast, the nonsense R220X variant exhibited substantially reduced levels (Hsp60: 45%, Hsp10: 18% of wild-type).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThese findings suggest distinct pathogenic mechanisms: missense variants create a \\\"protein misfolding burden\\\" that triggers compensatory stress responses. In contrast, nonsense variants result in \\\"protein absence\\\" without the additional proteostatic stress of misfolded protein accumulation. This distinction has implications for understanding why patients with similar residual enzyme activities can exhibit different clinical trajectories and treatment responses.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Hsp60 Levels in Fabry Disease Patients\\u003c/h2\\u003e \\u003cp\\u003eWestern blot analysis of PBMCs revealed substantial variability in Hsp60 levels among FD patients, with some individuals showing\\u0026thinsp;\\u0026gt;\\u0026thinsp;2-fold elevation and others\\u0026thinsp;\\u0026lt;\\u0026thinsp;50% of healthy control levels (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). No significant overall difference was observed between FD patients and controls when analysed as a group (males: 254% vs 100%, p\\u0026thinsp;=\\u0026thinsp;NS; females: 89% vs 100%, p\\u0026thinsp;=\\u0026thinsp;NS).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eHowever, the relationship between Hsp60 and ageing differed markedly between patients and controls. While healthy controls showed the expected positive correlation between Hsp60 and age (r\\u0026sup2;=1.0, p\\u0026thinsp;=\\u0026thinsp;0.04, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA), this relationship was absent in FD patients (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC), suggesting altered mitochondrial stress response independent of chronological ageing.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 Sex-Specific Associations with Clinical Severity\\u003c/h2\\u003e \\u003cp\\u003eHsp60 levels showed sex-specific associations with disease severity. In females, higher Hsp60 levels correlated significantly with greater age-adjusted clinical severity (AASS: r\\u0026sup2;=0.54, p\\u0026thinsp;=\\u0026thinsp;0.03, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eE) and inversely with younger age at sampling (r\\u0026sup2;= -0.57, p\\u0026thinsp;=\\u0026thinsp;0.02, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC), contrasting with the positive age correlation in healthy controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA).\\u003c/p\\u003e \\u003cp\\u003eThe relationship between Hsp60 and cardiac outcomes revealed opposite patterns in males and females. In males, higher Hsp60 levels strongly correlated with lower LVMI (r\\u0026sup2;=-0.82, p\\u0026thinsp;=\\u0026thinsp;0.01), suggesting a cardioprotective effect (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eD). This relationship was most pronounced in the N215S subgroup. Conversely, in females, higher Hsp60 levels are associated with higher LVMI (r\\u0026sup2;=0.66, p\\u0026thinsp;=\\u0026thinsp;0.045), indicating a potential maladaptive response (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eE).\\u003c/p\\u003e \\u003cp\\u003eAssociation with renal function also differed by sex and genotype. In N215S males, again higher Hsp60 levels correlated with better preserved GFR (r\\u0026sup2;=0.89, p\\u0026thinsp;=\\u0026thinsp;0.006), while non-N215S males showed the opposite relationship (r\\u0026sup2;=-0.89, p\\u0026thinsp;=\\u0026thinsp;0.006). Females showed a weak positive trend that did not reach statistical significance.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.5 Serum Mitokine Levels\\u003c/h2\\u003e \\u003cp\\u003eAnalysis of serum mitokines revealed significantly elevated GDF-15 levels in male FD patients compared to healthy controls (935 vs 559 pg/ml, p\\u0026thinsp;=\\u0026thinsp;0.002). These levels also exceed published population medians for healthy males, including younger adults (\\u0026lt;\\u0026thinsp;30 years: 483 pg/mL) and those aged 50\\u0026ndash;59 (931 pg/mL)(\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e) FGF-21 levels showed no significant difference (Figure S4). Both mitokines correlated positively with age in FD patients, with stronger correlations than observed in healthy controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e), suggesting accelerated mitochondrial ageing.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn males, Hsp60 levels showed a strong inverse correlation with FGF-21 (r\\u0026sup2;=-0.75, p\\u0026thinsp;=\\u0026thinsp;0.004), while females showed a weaker negative correlation with GDF-15 (r\\u0026sup2;=-0.57, p\\u0026thinsp;=\\u0026thinsp;0.047) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). These relationships suggest coordinated but sex-specific mitochondrial stress responses.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.6 Association with Disease Severity and Outcomes\\u003c/h2\\u003e \\u003cp\\u003eBoth mitokines correlated positively with disease severity scores in males, with particularly strong associations in the N215S subgroup (MSSI vs FGF-21: r\\u0026sup2;=0.87, p\\u0026thinsp;=\\u0026thinsp;0.005; MSSI vs GDF-15: r\\u0026sup2;=0.73, p\\u0026thinsp;=\\u0026thinsp;0.03). No significant correlations were observed in females.\\u003c/p\\u003e \\u003cp\\u003ePatients with documented cardiomyopathy had significantly higher GDF-15 levels (935 vs 610 pg/ml, p\\u0026thinsp;=\\u0026thinsp;0.02), and both mitokines were elevated in patients with left ventricular hypertrophy (FGF-21: 160 vs 98 pg/ml, p\\u0026thinsp;=\\u0026thinsp;0.04; GDF-15: 975 vs 656 pg/ml, p\\u0026thinsp;=\\u0026thinsp;0.01). Similar patterns were observed for clinically significant renal events, with GDF-15 showing the strongest associations (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.7 Impact of Treatment Timing\\u003c/h2\\u003e \\u003cp\\u003eAn important finding was the strong correlation between age at treatment initiation and serum mitokine levels. Males who started treatment at older ages had significantly elevated FGF-21 (r\\u0026sup2;=0.43, p\\u0026thinsp;=\\u0026thinsp;0.04) and GDF-15 (r\\u0026sup2;=0.58, p\\u0026thinsp;=\\u0026thinsp;0.006) levels, with similar patterns in females for GDF-15 (r\\u0026sup2;=0.70, p\\u0026thinsp;=\\u0026thinsp;0.007). This relationship was independent of the current treatment type, suggesting a degree of irreversibility of mitochondrial dysfunction beyond a critical age threshold.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.8 Predictive Modelling\\u003c/h2\\u003e \\u003cp\\u003eMultiple linear regression analysis identified key predictors of clinical outcomes. For MSSI in males, the best model (r\\u0026sup2;=0.76, p\\u0026thinsp;=\\u0026thinsp;0.004) included GDF-15 (β\\u0026thinsp;=\\u0026thinsp;0.01, p\\u0026thinsp;=\\u0026thinsp;0.009), GLA protein levels (β\\u0026thinsp;=\\u0026thinsp;37.3, p\\u0026thinsp;=\\u0026thinsp;0.006), and Hsp60 (β=-52.2, p\\u0026thinsp;=\\u0026thinsp;0.003), explaining 76% of severity score variance. In the N215S male subgroup, FGF-21 alone explained 92% of MSSI variance (β\\u0026thinsp;=\\u0026thinsp;0.12, p\\u0026thinsp;=\\u0026thinsp;0.01).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1 Overall Findings\\u003c/h2\\u003e \\u003cp\\u003eThis study provides the first systematic investigation of mtUPR related markers in Fabry disease, revealing complex sex- and genotype-specific patterns that may contribute to phenotypic heterogeneity. Hsp60 is induced as part of the mtUPR but is not specific to this pathway, while circulating mitokines reflect broader mitochondrial stress responses. Their coordinated alteration is consistent with engagement of mitochondrial stress pathways at both cellular and systemic levels (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe most striking finding was the opposite relationship between Hsp60 levels and cardiac outcomes in males versus females. In males, higher Hsp60 levels were associated with better preserved cardiac architecture, while the relationship was reversed in females. This sex dimorphism may reflect fundamental differences in X-linked inheritance patterns, hormonal influences on mitochondrial function, and cellular stress responses.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2 Sex-Specific Mitochondrial Stress Responses\\u003c/h2\\u003e \\u003cp\\u003eThe contrasting relationships between Hsp60 levels and cardiac outcomes in males versus females likely reflect X-linked inheritance patterns and hormonal influences on mitochondrial function (\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e). In males who carry only one X chromosome, uniform GLA expression patterns may allow for more predictable mitochondrial stress responses. The protective association of higher Hsp60 with lower LVMI in males aligns with studies showing cardioprotective effects of moderate Hsp60 upregulation (\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eConversely, the positive correlation between Hsp60 and LVMI in females may reflect X-inactivation mosaicism leading to variable cellular stress responses (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). Females with higher Hsp60 levels were paradoxically younger, suggesting early-onset, severe disease rather than a protective stress response. This pattern may indicate that in severely affected female patients, mitochondrial stress responses may become maladaptive in contexts of overwhelming cellular stress.\\u003c/p\\u003e \\u003cp\\u003eThe observation that females showed a negative correlation between Hsp60 and age, contrasting with the positive correlation in healthy controls, suggests that normal ageing patterns are disrupted. This may be related to the modulatory effects of oestrogen on mitochondrial function and stress responses (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3 Mitokine Elevation and Clinical Implications\\u003c/h2\\u003e \\u003cp\\u003eElevated GDF-15 levels in male FD patients align with its established role as a stress-responsive mitokine in cardiovascular and renal disease (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e). GDF-15 has emerged as a biomarker of mitochondrial dysfunction and is elevated in various cardiovascular conditions (\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eComparative biomarker studies suggest that GDF-15 provides a more global signal across mitochondrial disease phenotypes, while FGF-21 is more influenced by muscle involvement (\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e). Consistent with this, mechanistic studies indicate that mitochondrial stress in skeletal muscle is a major driver of FGF-21 secretion, whereas GDF-15 integrates mitochondrial stress signals across tissues (\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e). The strong relationship between treatment timing and mitokine levels has important clinical implications. Patients initiating therapy after age 40 showed markedly elevated mitokine levels, suggesting a greater burden of mitochondrial stress at the time of intervention. This observation supports current discussions supporting early therapeutic intervention, even in asymptomatic patients (\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e). Is late treatment just a surrogate for late onset patients?\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.4 Genotype-Specific Responses: Implications for Disease Mechanisms\\u003c/h2\\u003e \\u003cp\\u003eThe striking differences in mitochondrial stress marker patterns between N215S and non-N215S patients suggest fundamentally distinct pathogenic mechanisms underlying these Fabry disease subtypes. These findings challenge the traditional view of FD as a uniform lysosomal storage disorder and point toward genotype-specific therapeutic requirements.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec23\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e4.4.1 Protein Misfolding vs. Protein Absence Paradigms\\u003c/h2\\u003e \\u003cp\\u003eThe N215S variant exemplifies the later-onset missense mutation with cellular trafficking abnormalities within Fabry disease. This missense mutation results in a thermolabile enzyme that misfolds in the endoplasmic reticulum (ER), triggering ER-associated degradation (ERAD) and subsequently activating downstream stress responses (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). Our fibroblast data demonstrate that missense variants, such as R301Q, produce robust Hsp60 upregulation (187% of wild-type), consistent with a pronounced mitochondrial stress response in response to proteostatic stress.\\u003c/p\\u003e \\u003cp\\u003eThis misfolded protein burden creates a dual pathology: (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e) enzyme deficiency leading to substrate accumulation and (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e) continuous proteostatic stress from attempted protein folding and degradation. The ER-mitochondria contact sites (mitochondrial-associated membranes) serve as critical communication hubs where ER stress can contribute to mitochondrial stress signalling (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). In N215S patients, this creates a chronic state of integrated stress response activation that may fundamentally alter cellular metabolism and stress tolerance.\\u003c/p\\u003e \\u003cp\\u003eConversely, nonsense variants like R220X represent a \\\"protein absence disorder,\\\" where mRNA degradation via nonsense-mediated decay prevents the accumulation of misfolded proteins (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e). Our data show minimal Hsp60 upregulation (45% of wild-type) in these variants, suggesting that the absence of misfolded protein reduces proteostatic stress despite equivalent or greater substrate accumulation. This suggests the relevant pathology is primarily lysosomal dysfunction without the added burden of protein misfolding stress.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec24\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e4.4.2 Therapeutic Implications of Mechanistic Differences\\u003c/h2\\u003e \\u003cp\\u003eThese mechanistic distinctions have therapeutic implications. N215S patients showed that 92% of MSSI variance was explained by FGF-21 levels alone, indicating a tight coupling between mitochondrial stress and clinical severity. This suggests that therapies targeting proteostasis (such as pharmacological chaperones) may be particularly beneficial for missense variants by reducing the protein misfolding burden and consequently decreasing proteostatic and mitochondrial stress (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eIn addition, our treatment analysis revealed that patients receiving pharmacological chaperone therapy showed different mitokine patterns compared to enzyme replacement therapy, with stronger correlations between treatment initiation age and FGF-21 levels (r\\u0026sup2;=0.65, p\\u0026thinsp;=\\u0026thinsp;0.002). This suggests that successful protein rescue by chaperones may specifically ameliorate the proteostatic stress component of disease pathogenesis.\\u003c/p\\u003e \\u003cp\\u003eFor nonsense variants, the primary pathology stems from substrate accumulation rather than protein misfolding stress. These patients may benefit more from substrate reduction or enzyme replacement if their cellular stress responses are less overwhelmed by proteostatic burden (\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec25\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e4.4.3 Sex-Specific Interactions with Genotype\\u003c/h2\\u003e \\u003cp\\u003eThe interaction between genotype and sex adds another layer of complexity. In N215S males, higher Hsp60 levels strongly correlated with better renal function (r\\u0026sup2;=0.89, p\\u0026thinsp;=\\u0026thinsp;0.006), suggesting that a more effective mitochondrial stress response may be associated with cytoprotection when proteostatic stress is manageable. However, even high Hsp60 levels are associated with worse outcomes in females with severe phenotypes, possibly reflecting X-inactivation mosaicism creating cellular populations with varying stress tolerance (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThis sex-genotype interaction may explain why some female N215S patients develop severe phenotypes despite this variant's \\\"late-onset\\\" classification. Cellular mosaicism may create focal areas of high misfolded protein burden that overwhelm local stress responses, leading to tissue-specific pathology despite overall preserved enzyme activity.\\u003c/p\\u003e \\u003cp\\u003eThese observations highlight the need for future work that clarifies the cellular basis of these sex- and genotype-specific responses, including how mitochondrial stress responses are modulated across different tissues.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec26\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e4.4.4 Evolutionary and Clinical Perspectives\\u003c/h2\\u003e \\u003cp\\u003eFrom an evolutionary perspective, preserving missense variants like N215S in the population, despite their pathogenic potential, may reflect residual protein function under optimal conditions. The amenability of many missense variants to pharmacological chaperone therapy supports this concept\\u0026sup3;⁶. However, chronic proteostatic stress may accelerate cellular ageing processes, explaining the delayed but progressive nature of complications in these patients.\\u003c/p\\u003e \\u003cp\\u003eClinically, these findings suggest that Fabry disease represents at least two distinct disorders: a \\\"protein misfolding lysosomal disease\\\" (exemplified by N215S and similar variants) and a \\\"classical lysosomal storage disease\\\" (exemplified by nonsense variants). This distinction may require different monitoring strategies, with mitokine levels being potentaillyuseful for the former group, and traditional biomarkers (lyso-Gb3, clinical symptoms) being more relevant for the latter.\\u003c/p\\u003e \\u003cp\\u003eThe therapeutic window concept also differs between groups. Missense variant patients may have a narrower therapeutic window due to cumulative proteostatic damage, explaining why early intervention is particularly relevant for preventing irreversible mitochondrial dysfunction. Nonsense variant patients may have more predictable progression patterns based primarily on substrate accumulation kinetics and so while early therapy is not less relevant it is more obviously prompted by the onset of clinical features.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec27\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.5 Therapeutic Implications\\u003c/h2\\u003e \\u003cp\\u003eThese findings have several potential therapeutic implications. First, mitokine levels, particularly GDF-15, may serve as biomarkers for monitoring treatment response and disease progression. Second, the relationship between treatment initiation age and mitochondrial dysfunction markers supports aggressive early treatment strategies. Third, sex-specific differences in mitochondrial stress responses may require tailored treatment approaches.\\u003c/p\\u003e \\u003cp\\u003eThe observation that pharmacological chaperone therapy (PCT) showed different associations with mitokine levels compared to enzyme replacement therapy suggests that treatment modalities targeting protein folding may have distinct effects on mitochondrial stress responses.\\u003c/p\\u003e \\u003cp\\u003eMitochondrial stress markers may also help refine treatment stratification by identifying patients with greater vulnerability to mitochondrial dysfunction or differential responses to specific therapies\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec28\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.6 Study Limitations\\u003c/h2\\u003e \\u003cp\\u003eSeveral limitations warrant consideration. The cross-sectional design precludes the determination of causality between mtUPR related markers and clinical outcomes. In addition, the markers used here do not provide definitive evidence of mtUPR activation.\\u003c/p\\u003e \\u003cp\\u003eThe relatively small sample size, particularly for subgroup analyses, limits statistical power and generalisability. Given the modest numbers within sex- and genotype-stratified analyses, these findings should be regarded as exploratory and hypothesis-generating and may be susceptible to statistical artefact. The study design also does not allow full adjustment for potential confounders, including age, treatment status, genotype, co-morbidities, and other clinical variables.\\u003c/p\\u003e \\u003cp\\u003eWe measured Hsp60 in PBMCs, which may not accurately reflect organ-specific mitochondrial stress. PBMCs also represent a heterogeneous cell population, and inter-individual variation in cellular composition may influence Hsp60 levels independently of disease-related stress responses. Tissue-specific markers would provide more direct evidence of organ-level mitochondrial stress. Furthermore, PBMCs were cultured before analysis, and ex vivo culture conditions may themselves influence stress protein expression. Another important limitation relates to Hsp60 quantification, which was performed by western blotting. This is a semi-quantitative technique and is subject to technical and inter-experimental variability despite normalisation to a loading control. Samples were analysed across multiple gels; a consistent reference control sample was used across gels for female experiments. However, in male experiments different control samples were used across gels, and inter-gel variability therefore cannot be fully excluded.\\u003c/p\\u003e \\u003cp\\u003eWe cannot exclude the influence of co-morbidities, medications, or environmental factors on the mitochondrial stress markers assessed. Future studies should include a comprehensive assessment of potential confounders.\\u003c/p\\u003e \\u003cp\\u003eFinally, the mechanistic basis for sex-specific differences remains unclear. Functional studies examining patterns of X-inactivation, hormonal influences, and cellular stress responses are required to elucidate the underlying mechanisms.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"5. Conclusions\",\"content\":\"\\u003cp\\u003eThis study shows that mtUPR related markers exhibits sex- and genotype-specific patterns in Fabry disease that are associated with cardiac and renal disease severity. Higher intracellular Hsp60 levels are associated with lower LVMI in males but higher in females, while elevated serum mitokines, particularly GDF-15, are associated with disease severity and late treatment initiation.\\u003c/p\\u003e \\u003cp\\u003eThese findings suggest that mitochondrial stress responses may contribute significantly to phenotypic heterogeneity in Fabry disease and may have potential as biomarkers for disease monitoring and optimisation of treatment timing. The strong association between treatment initiation age and mitokine levels supports early therapeutic intervention and suggests that mitochondrial dysfunction may become irreversible beyond a critical age threshold.\\u003c/p\\u003e \\u003cp\\u003eFuture longitudinal studies are needed to validate these markers for clinical use and to elucidate the mechanistic basis for sex-specific differences in mitochondrial stress responses. Understanding these pathways may lead to new therapeutic targets and personalised treatment approaches for Fabry disease.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;This study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC: 20/WM/0329). All participants provided written informed consent.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Derralynn Hughes has received consulting and speaking fees from Sanofi, Takeda, Chiesi and Amicus, and consulting fees from Ultragenyx, Sangamo, Idorsia, Spur Therapeutics and Relay Therapeutics, administered through UCL Consultants and used in part to support research in lysosomal storage disorders. David Moreno Martinez has received honoraria for speaking engagements, advisory board participation and travel grants from Sanofi, Takeda, Chiesi and Amicus. The remaining authors declare that they have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;This work was supported by the Royal Free Charity.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; contributions\\u003c/strong\\u003e\\u003cbr\\u003e\\u0026nbsp;Lucia Lavalle designed the study, performed experiments, analysed the data, and drafted the manuscript. Derralynn Hughes conceived and supervised the study and contributed to data interpretation and manuscript revision. Hibba Kudri contributed to acquisition of cardiac data.\\u003cbr\\u003e\\u0026nbsp;David Moreno Martinez contributed to patient recruitment and clinical data collection. Vincent Muczynski contributed to laboratory experiments, including mitokine measurements. Simon Heales contributed to study oversight and critical revision of the manuscript. All authors read and approved the final manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eGermain DP. Fabry disease. Orphanet J Rare Dis. 2010 Nov 22;5:30. doi:10.1186/1750-1172-5-30 PubMed PMID: 21092187.\\u003c/li\\u003e\\n \\u003cli\\u003eNowak A, Huynh-Do U, Krayenbuehl PA, Beuschlein F, Schiffmann R, Barbey F. Fabry disease genotype, phenotype, and migalastat amenability: Insights from a national cohort. J Inherit Metab Dis. 2020 Mar;43(2):326\\u0026ndash;33. doi:10.1002/jimd.12167 PubMed PMID: 31449323.\\u003c/li\\u003e\\n \\u003cli\\u003eOrtiz A, Germain DP, Desnick RJ, Politei J, Mauer M, Burlina A, et al. Fabry disease revisited: Management and treatment recommendations for adult patients. Mol Genet Metab. 2018 Apr;123(4):416\\u0026ndash;27. doi:10.1016/j.ymgme.2018.02.014 PubMed PMID: 29530533.\\u003c/li\\u003e\\n \\u003cli\\u003eBellettato CM, Scarpa M. Pathophysiology of neuropathic lysosomal storage disorders. J Inherit Metab Dis. 2010 Aug;33(4):347\\u0026ndash;62. doi:10.1007/s10545-010-9075-9 PubMed PMID: 20429032.\\u003c/li\\u003e\\n \\u003cli\\u003eLane-Donovan C, Paredes M, Kao AW. The lysosome and proteostatic stress at the intersection of pediatric neurological disorders and adult neurodegenerative diseases. Prog Neurobiol. 2025 Dec;255:102854. doi:10.1016/j.pneurobio.2025.102854\\u003c/li\\u003e\\n \\u003cli\\u003eRozenfeld P, Feriozzi S. Contribution of inflammatory pathways to Fabry disease pathogenesis. Mol Genet Metab. 2017 Nov;122(3):19\\u0026ndash;27. doi:10.1016/j.ymgme.2017.09.004 PubMed PMID: 28947349.\\u003c/li\\u003e\\n \\u003cli\\u003eShen JS, Meng XL, Moore DF, Quirk JM, Shayman JA, Schiffmann R, et al. Globotriaosylceramide induces oxidative stress and up-regulates cell adhesion molecule expression in Fabry disease endothelial cells. Mol Genet Metab. 2008 Nov;95(3):163\\u0026ndash;8. doi:10.1016/j.ymgme.2008.06.016 PubMed PMID: 18707907.\\u003c/li\\u003e\\n \\u003cli\\u003eShpilka T, Haynes CM. The mitochondrial UPR: mechanisms, physiological functions and implications in ageing. Nat Rev Mol Cell Biol. 2018 Feb;19(2):109\\u0026ndash;20. doi:10.1038/nrm.2017.110 PubMed PMID: 29165426.\\u003c/li\\u003e\\n \\u003cli\\u003eM\\u0026uuml;nch C, Harper JW. Mitochondrial unfolded protein response controls matrix pre-RNA processing and translation. Nature. 2016 Jun 30;534(7609):710\\u0026ndash;3. doi:10.1038/nature18302 PubMed PMID: 27350246.\\u003c/li\\u003e\\n \\u003cli\\u003eKim KH, Jeong YT, Oh H, Kim SH, Cho JM, Kim YN, et al. Autophagy deficiency leads to protection from obesity and insulin resistance by inducing Fgf21 as a mitokine. Nat Med. 2013 Jan;19(1):83\\u0026ndash;92. doi:10.1038/nm.3014 PubMed PMID: 23202295.\\u003c/li\\u003e\\n \\u003cli\\u003eZhao Q, Wang J, Levichkin I V, Stasinopoulos S, Ryan MT, Hoogenraad NJ. A mitochondrial specific stress response in mammalian cells. EMBO J. 2002 Sep 2;21(17):4411\\u0026ndash;9. doi:10.1093/emboj/cdf445 PubMed PMID: 12198143.\\u003c/li\\u003e\\n \\u003cli\\u003eAnderson NS, Haynes CM. Folding the Mitochondrial UPR into the Integrated Stress Response. Trends Cell Biol. 2020 Jun;30(6):428\\u0026ndash;39. doi:10.1016/j.tcb.2020.03.001 PubMed PMID: 32413314.\\u003c/li\\u003e\\n \\u003cli\\u003ePlotegher N, Duchen MR. Crosstalk between Lysosomes and Mitochondria in Parkinson\\u0026rsquo;s Disease. Front Cell Dev Biol. 2017;5:110. doi:10.3389/fcell.2017.00110 PubMed PMID: 29312935.\\u003c/li\\u003e\\n \\u003cli\\u003eLenders M, Stappers F, Brand E. In Vitro and In Vivo Amenability to Migalastat in Fabry Disease. Mol Ther Methods Clin Dev. 2020 Dec 11;19:24\\u0026ndash;34. doi:10.1016/j.omtm.2020.08.012 PubMed PMID: 32995357.\\u003c/li\\u003e\\n \\u003cli\\u003eJovaisaite V, Mouchiroud L, Auwerx J. The mitochondrial unfolded protein response, a conserved stress response pathway with implications in health and disease. J Exp Biol. 2014 Jan 1;217(Pt 1):137\\u0026ndash;43. doi:10.1242/jeb.090738 PubMed PMID: 24353213.\\u003c/li\\u003e\\n \\u003cli\\u003eLenders M, Rudolph E, Brand E. Impact of ER stress and the unfolded protein response on Fabry disease. EBioMedicine. 2025 May;115:105733. doi:10.1016/j.ebiom.2025.105733\\u003c/li\\u003e\\n \\u003cli\\u003eHughes DA, Ramaswami U, Barba Romero M\\u0026Aacute;, Deegan P. Age adjusting severity scores for Anderson\\u0026ndash;Fabry Disease. Mol Genet Metab. 2010;101(2):219\\u0026ndash;27. doi:https://doi.org/10.1016/j.ymgme.2010.06.002\\u003c/li\\u003e\\n \\u003cli\\u003eDevereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol. 1986 Feb 15;57(6):450\\u0026ndash;8. doi:10.1016/0002-9149(86)90771-x PubMed PMID: 2936235.\\u003c/li\\u003e\\n \\u003cli\\u003eChuang ML, Gona P, Hautvast GLTF, Salton CJ, Breeuwer M, O\\u0026rsquo;Donnell CJ, et al. CMR reference values for left ventricular volumes, mass, and ejection fraction using computer-aided analysis: the Framingham Heart Study. J Magn Reson Imaging. 2014 Apr;39(4):895\\u0026ndash;900. doi:10.1002/jmri.24239 PubMed PMID: 24123369.\\u003c/li\\u003e\\n \\u003cli\\u003eLamb EJ, Levey AS, Stevens PE. The Kidney Disease Improving Global Outcomes (KDIGO) guideline update for chronic kidney disease: evolution not revolution. Clin Chem. 2013 Mar;59(3):462\\u0026ndash;5. doi:10.1373/clinchem.2012.184259 PubMed PMID: 23449698.\\u003c/li\\u003e\\n \\u003cli\\u003eSmid BE, van der Tol L, Cecchi F, Elliott PM, Hughes DA, Linthorst GE, et al. Uncertain diagnosis of Fabry disease: consensus recommendation on diagnosis in adults with left ventricular hypertrophy and genetic variants of unknown significance. Int J Cardiol. 2014 Dec 15;177(2):400\\u0026ndash;8. doi:10.1016/j.ijcard.2014.09.001 PubMed PMID: 25442977.\\u003c/li\\u003e\\n \\u003cli\\u003eWelsh P, Kimenai DM, Marioni RE, Hayward C, Campbell A, Porteous D, et al. Reference ranges for GDF-15, and risk factors associated with GDF-15, in a large general population cohort. Clin Chem Lab Med. 2022 Oct 26;60(11):1820\\u0026ndash;9. doi:10.1515/cclm-2022-0135 PubMed PMID: 35976089.\\u003c/li\\u003e\\n \\u003cli\\u003eJena J, Garc\\u0026iacute;a-Pe\\u0026ntilde;a LM, Pereira RO. The roles of FGF21 and GDF15 in mediating the mitochondrial integrated stress response. Front Endocrinol (Lausanne). 2023 Sep 25;14. doi:10.3389/fendo.2023.1264530\\u003c/li\\u003e\\n \\u003cli\\u003eBenarroch E. What Are the Roles of Mitochondrial Stress Responses and Mitohormesis in Neurodegenerative Disorders? Neurology. 2026 Feb 10;106(3). doi:10.1212/WNL.0000000000214618\\u003c/li\\u003e\\n \\u003cli\\u003eRiar AK, Burstein SR, Palomo GM, Arreguin A, Manfredi G, Germain D. Sex specific activation of the ER\\u0026alpha; axis of the mitochondrial UPR (UPRmt) in the G93A-SOD1 mouse model of familial ALS. Hum Mol Genet. 2017 Apr 1;26(7):1318\\u0026ndash;27. doi:10.1093/hmg/ddx049\\u003c/li\\u003e\\n \\u003cli\\u003eHu Y, Chen X, Li X, Li Z, Diao H, Liu L, et al. MicroRNA‑1 downregulation induced by carvedilol protects cardiomyocytes against apoptosis by targeting heat shock protein 60. Mol Med Rep. 2019 May;19(5):3527\\u0026ndash;36. doi:10.3892/mmr.2019.10034 PubMed PMID: 30896796.\\u003c/li\\u003e\\n \\u003cli\\u003eKrishnan-Sivadoss I, Mijares-Rojas IA, Villarreal-Leal RA, Torre-Amione G, Knowlton AA, Guerrero-Beltr\\u0026aacute;n CE. Heat shock protein 60 and cardiovascular diseases: An intricate love-hate story. Med Res Rev. 2021 Jan;41(1):29\\u0026ndash;71. doi:10.1002/med.21723 PubMed PMID: 32808366.\\u003c/li\\u003e\\n \\u003cli\\u003eEchevarria L, Benistan K, Toussaint A, Dubourg O, Hagege AA, Eladari D, et al. X-chromosome inactivation in female patients with Fabry disease. Clin Genet. 2016 Jan;89(1):44\\u0026ndash;54. doi:10.1111/cge.12613 PubMed PMID: 25974833.\\u003c/li\\u003e\\n \\u003cli\\u003eKlinge CM. Estrogenic control of mitochondrial function. Redox Biol. 2020 Apr;31:101435. doi:10.1016/j.redox.2020.101435 PubMed PMID: 32001259.\\u003c/li\\u003e\\n \\u003cli\\u003eWischhusen J, Melero I, Fridman WH. Growth/Differentiation Factor-15 (GDF-15): From Biomarker to Novel Targetable Immune Checkpoint. Front Immunol. 2020;11:951. doi:10.3389/fimmu.2020.00951 PubMed PMID: 32508832.\\u003c/li\\u003e\\n \\u003cli\\u003eBurtscher J, Soltany A, Visavadiya NP, Burtscher M, Millet GP, Khoramipour K, et al. Mitochondrial stress and mitokines in aging. Aging Cell. 2023 Feb;22(2):e13770. doi:10.1111/acel.13770 PubMed PMID: 36642986.\\u003c/li\\u003e\\n \\u003cli\\u003eDavis RL, Liang C, Sue CM. A comparison of current serum biomarkers as diagnostic indicators of mitochondrial diseases. Neurology. 2016 May 24;86(21):2010\\u0026ndash;5. doi:10.1212/WNL.0000000000002705\\u003c/li\\u003e\\n \\u003cli\\u003eRomanello V, Sandri M. Implications of mitochondrial fusion and fission in skeletal muscle mass and health. Semin Cell Dev Biol. 2023 Jul;143:46\\u0026ndash;53. doi:10.1016/j.semcdb.2022.02.011\\u003c/li\\u003e\\n \\u003cli\\u003eOrtiz A, Abiose A, Bichet DG, Cabrera G, Charrow J, Germain DP, et al. Time to treatment benefit for adult patients with Fabry disease receiving agalsidase \\u0026beta;: data from the Fabry Registry. J Med Genet. 2016 Jul;53(7):495\\u0026ndash;502. doi:10.1136/jmedgenet-2015-103486 PubMed PMID: 26993266.\\u003c/li\\u003e\\n \\u003cli\\u003eIshii S, Chang HH, Kawasaki K, Yasuda K, Wu HL, Garman SC, et al. Mutant alpha-galactosidase A enzymes identified in Fabry disease patients with residual enzyme activity: biochemical characterization and restoration of normal intracellular processing by 1-deoxygalactonojirimycin. Biochem J. 2007 Sep 1;406(2):285\\u0026ndash;95. doi:10.1042/BJ20070479 PubMed PMID: 17555407.\\u003c/li\\u003e\\n \\u003cli\\u003eCsord\\u0026aacute;s G, Renken C, V\\u0026aacute;rnai P, Walter L, Weaver D, Buttle KF, et al. Structural and functional features and significance of the physical linkage between ER and mitochondria. J Cell Biol. 2006 Sep 25;174(7):915\\u0026ndash;21. doi:10.1083/jcb.200604016 PubMed PMID: 16982799.\\u003c/li\\u003e\\n \\u003cli\\u003eLukas J, Giese AK, Markoff A, Grittner U, Kolodny E, Mascher H, et al. Functional characterisation of alpha-galactosidase a mutations as a basis for a new classification system in fabry disease. PLoS Genet. 2013;9(8):e1003632. doi:10.1371/journal.pgen.1003632 PubMed PMID: 23935525.\\u003c/li\\u003e\\n \\u003cli\\u003eYam GHF, Zuber C, Roth J. A synthetic chaperone corrects the trafficking defect and disease phenotype in a protein misfolding disorder. FASEB J. 2005 Jan;19(1):12\\u0026ndash;8. doi:10.1096/fj.04-2375com PubMed PMID: 15629890.\\u003c/li\\u003e\\n \\u003cli\\u003eAbe A, Gregory S, Lee L, Killen PD, Brady RO, Kulkarni A, et al. Reduction of globotriaosylceramide in Fabry disease mice by substrate deprivation. J Clin Invest. 2000 Jun;105(11):1563\\u0026ndash;71. doi:10.1172/JCI9711 PubMed PMID: 10841515.\\u003c/li\\u003e\\n \\u003cli\\u003eDobrovolny R, Dvorakova L, Ledvinova J, Magage S, Bultas J, Lubanda JC, et al. Relationship between X-inactivation and clinical involvement in Fabry heterozygotes. Eleven novel mutations in the alpha-galactosidase A gene in the Czech and Slovak population. J Mol Med (Berl). 2005 Aug;83(8):647\\u0026ndash;54. doi:10.1007/s00109-005-0656-2 PubMed PMID: 15806320.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"orphanet-journal-of-rare-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ojrd\",\"sideBox\":\"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/ojrd/default.aspx\",\"title\":\"Orphanet Journal of Rare Diseases\",\"twitterHandle\":\"@bmc\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Fabry disease, mitochondrial unfolded protein response, Hsp60, mitokines (FGF-21, GDF-15), and phenotypic heterogeneity\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9304477/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9304477/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground:\\u003c/strong\\u003e Fabry disease (FD) exhibits marked clinical heterogeneity that cannot be fully explained by residual α-galactosidase A activity. Mitochondrial dysfunction has been reported in FD, but the role of mitochondrial stress remains unexplored.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eObjective:\\u003c/strong\\u003e To investigate whether mitochondrial unfolded protein response (mtUPR) related markers associate with phenotypic variability and correlates with disease severity.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e We measured intracellular heat-shock protein 60 (Hsp60) by western blotting in peripheral blood mononuclear cells from 27 FD patients (14 males, 13 females). Serum fibroblast growth-factor-21 and growth differentiation-factor-15 were measured in 35 patients. Clinical outcomes included Mainz Severity Score Index, Age-Adjusting Severity Score, estimated glomerular filtration rate, and left-ventricular mass index (LVMI).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e Hsp60 showed variability, with sex-specific associations. In males, higher Hsp60 correlated with lower LVMI (r²=-0.82, p=0.01) and preserved renal function in late-onset \\u0026nbsp;patients (r²=0.89, p=0.006). In females, higher Hsp60 associated with higher LVMI (r²=0.66, p=0.045) and greater clinical severity. Male patients had elevated growth differentiation-factor-15 \\u0026nbsp;vs controls (935 vs 559 pg/ml, p=0.002). Both mitokines correlated with age and disease severity.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusions: \\u003c/strong\\u003emtUPR related markers exhibit sex- and genotype-specific patterns associated with disease severity, suggesting that mitochondrial stress contributes to phenotypic heterogeneity and may serve as biomarkers for \\u0026nbsp;treatment optimisation.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Mitochondrial stress markers associate with phenotypic variability in Fabry disease\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-04-19 07:54:56\",\"doi\":\"10.21203/rs.3.rs-9304477/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2026-05-14T07:15:19+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-11T15:19:58+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"24289440164975929494274900372777423416\",\"date\":\"2026-04-23T17:21:21+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"73302148469310213566262156576760073068\",\"date\":\"2026-04-20T07:33:07+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-04-16T19:55:39+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"249344120765333318714408257072358436230\",\"date\":\"2026-04-13T00:11:24+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-04-08T11:48:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-04-06T11:08:33+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-04-06T11:08:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Orphanet Journal of Rare Diseases\",\"date\":\"2026-04-02T14:26:29+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"orphanet-journal-of-rare-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ojrd\",\"sideBox\":\"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/ojrd/default.aspx\",\"title\":\"Orphanet Journal of Rare Diseases\",\"twitterHandle\":\"@bmc\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"d0904e5c-8788-4210-a2d6-4c9c839633e7\",\"owner\":[],\"postedDate\":\"April 19th, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2026-05-14T07:15:19+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-11T15:19:58+00:00\",\"index\":31,\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"in-revision\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-14T07:26:07+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-04-19 07:54:56\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9304477\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9304477\",\"identity\":\"rs-9304477\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}