Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review
Abstract
1. Introduction
2. Systemic Sclerosis Cardiac Disease: A Landscape of Intersecting Pathophysiology
3. Right Ventricular Dysfunction: The Contemporary Echocardiographic Picture
3.1. Speckle-Tracking Strain and Its Prognostic Dimensions
3.2. The Right Ventricular (RV)Myocardial Performance Index and Ventriculoarterial Coupling
3.3. Left Ventricular (LV)Mechanics and the Emerging Role of Myocardial Work Analysis
3.4. Multi-Domain Echocardiographic Integration
4. Pulmonary Microvascular Disease and Endothelial Dysfunction
4.1. Nailfold Capillaroscopy: A Window onto Systemic Microvascular Architecture
4.2. Flow-Mediated Dilation and Conduit Vessel Endothelial Dysfunction
4.3. The Peripheral–Cardiac Microvascular Axis: Cardiovascular Magnetic Resonance (CMR)and Capillaroscopy in Convergence
5. Mitochondrial Dysfunction and Metabolic Reprogramming in Systemic Sclerosis
5.1. Fibroblast Bioenergetics: Oxidative Phosphorylation as a Driver of Fibrosis
5.2. Immune Cell Mitochondrial Pathology: From Biomarker to Mechanism
5.3. The GRIM-19/STAT3/PINK1-Parkin Axis: Integrating Metabolism, Immunity, and Fibrosis
6. Circulating Cardiac Biomarkers: Diagnostic Architecture and Prognostic Yield
6.1. NT-proBNP and the Hemodynamic Stress Axis
6.2. High-Sensitivity Cardiac Troponin (hs-cTnT): The Cardiomyocyte Injury Dimension
6.3. CMR-Guided Therapeutic Monitoring: From Surveillance to Treatment Adaptation
7. Cross-Dimensional Synthesis: Toward an Integrated Model of SSc Cardiac Pathology
Strength of Evidence Across Integrated Model
8. Clinical Implications and Translational Perspectives
8.1. Reconceptualizing Early Detection in SSc Cardiac Disease
8.2. Therapeutic Targeting of Mitochondrial Pathways
8.3. The RV as a Primary Therapeutic Target
8.4. Sex as a Cross-Cutting Modifier of the Integrated Model
9. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| ASPECT 1: Right Ventricular Dysfunction and Echocardiography in Systemic Sclerosis | |||||
| Study Design | Sample Size | Population/Methods | Key Findings | Outcome/Biomarker | Ref. |
| Cross-sectional | 60 SSc/83 HC | Female SSc patients vs. healthy controls; echocardiography (RV MPI, TAPSE, TAPSE/sPAP) | RV MPI significantly elevated in SSc vs. controls despite preserved LV function; higher in ILD, reduced DLCO, and extensive skin involvement; RV MPI did not correlate with inflammatory markers or disease duration | RV MPI, TAPSE, TAPSE/sPAP ratio | [27] |
| Prospective observational | SSc cohort | Multi-biomarker approach combining echocardiographic strain, NT-proBNP, hs-cTnT, and 6MWT in SSc patients | Multi-biomarker combination improves risk stratification for early cardiac disease detection; individual biomarkers had limited discriminatory power alone | GLS, NT-proBNP, hs-cTnT, 6MWT composite | [35] |
| Cross-sectional | SSc vs. HC | Noninvasive LV myocardial work indices measured by echocardiographic pressure–strain loop analysis in SSc patients | Myocardial work indices (global work index, constructive work, wasted work) significantly impaired in SSc vs. controls, correlating with GLS; detects subclinical LV dysfunction before LVEF reduction | Myocardial work index, constructive/wasted work, GLS | [32] |
| Prospective cohort | n = 131 SSc | Speckle-tracking echocardiography (GLS, RV-GLS) in SSc patients with follow-up for mortality/CV events | GLS (LV and RV) independently predicted all-cause death and major cardiovascular events; cut-off GLS worse than −18% identified high-risk patients; RV-GLS prognostically stronger than TAPSE | LV-GLS, RV-GLS; mortality/CV events | [24] |
| Retrospective cohort | n = 262 SSc | Echocardiographic assessment of LV dysfunction in SSc-related PH; right heart catheterization (RHC)-confirmed PAHvs. non-PAH SSc | LV diastolic dysfunction grade ≥2 present in 37% of SSc-PAH; LV dysfunction independently associated with worse 6MWT and higher NT-proBNP; LV-RV interaction central to SSc-PAH hemodynamics | LV diastolic dysfunction grade, 6MWT, NT-proBNP | [31] |
| Cross-sectional | n = 71 SSc/20 HC | Speckle-tracking 2D strain analysis of RV free wall in SSc patients vs. healthy controls | Unique basal-predominant RV longitudinal strain pattern in SSc (vs. apical pattern in IPAH); reduced basal RV free wall strain correlated with mRSS and PAP; pattern distinct from PAH-related RV remodeling | RV longitudinal strain (segmental), basal–apical gradient | [25] |
| ASPECT 2: Pulmonary Microvascular Disease and Endothelial Dysfunction | |||||
| Study Design | Sample Size | Population/Methods | Key Findings | Outcome/Biomarker | Ref. |
| Cross-sectional comparative | n = 20 SSc-PAH/5 IPAH | CMR (T1/T2 mapping, ECV, stress perfusion) + nailfold capillaroscopy (NCD, PORH) in SSc-PAH vs. IPAH patients | SSc-PAH showed higher T2 and ECV vs. IPAH; NCD correlated with ECV (r = −0.443) and T2 (r = −0.464); PORH correlated with relative myocardial upslope; peripheral microvascular dysfunction mirrors cardiac microvascular inflammation/fibrosis | NCD, PORH, ECV, T2 mapping, myocardial upslope | [6] |
| Multi-center observational | n = 244 SSc | NVC pattern (early/active/late) and capillary density in SSc patients; correlation with PAH diagnosis by RHC | Late capillaroscopic pattern and low capillary density independently associated with PAH (OR 3.14); density < 3.5 caps/mm strongest predictor; NVC loss distinguished SSc-PAH from SSc-nonPAH | NVC pattern, capillary density, PAH diagnosis | [36] |
| Derivation + validation cohort | n = 656 derivation | NFC scoring system developed in SSc/Raynaud’s patients; derivation and external validation of microvascular scoring index | Novel NFC composite score discriminated SSc from primary Raynaud’s with area under the curve (AUC)> 0.90; late-pattern NFC associated with digital ulcers and PAH risk; validated in independent cohort | NFC composite score, digital ulcers, PAH risk | [37] |
| Case–control | SSc vs. HC | Flow-mediated dilation (FMD) and nitroglycerin-mediated dilation assessed in SSc patients vs. controls | FMD significantly reduced in SSc vs. controls; FMD inversely correlated with disease duration and modified Rodnan skin score; endothelial dysfunction predates clinical organ involvement | FMD (%), NMD, mRSS, disease duration | [38] |
| ASPECT 3: Mitochondrial Dysfunction and Oxidative Stress in Systemic Sclerosis | |||||
| Study Design | Sample Size | Population/Methods | Key Findings | Outcome/Biomarker | Ref |
| Experimental (murine + in vitro) | Bleomycin SSc model | GRIM-19 overexpression in bleomycin-induced SSc model; STAT3 mitochondrial signaling assessed; Th2/Th17 cells evaluated | GRIM-19 overexpression reduced skin thickness and fibrosis; suppressed mitochondrial STAT3 phosphorylation; inhibited Th2/Th17 differentiation; mitophagy promoted via STAT3-PINK1/Parkin axis | Mitochondrial STAT3, PINK1/Parkin, IL-4, IL-17 | [10] |
| Translational (fibroblast + in vitro) | SSc vs. HD fibroblasts | Metabolic profiling (oxygen consumption rate (OCR), extracellular acidification rate (ECAR)) of SSc dermal fibroblasts vs. healthy donor controls; TGF-beta1 stimulation; mitochondrial dynamics (fusion/fission) | SSc fibroblasts showed enhanced mitochondrial respiration (higher OCR) and increased mitochondrial fusion; TGF-beta1 amplified metabolic reprogramming; glycolysis-to-OXPHOS shift central to pro-fibrotic phenotype | OCR, ECAR, mitochondrial fusion/fission markers, TGF-beta1 | [9] |
| Cross-sectional comparative | lcSSc +/− ME/CFS vs. HC | Mitochondrial gene expression and electron transport chain profiling in peripheral blood mononuclear cells (PBMCs)from limited cutaneous SSc with and without chronic fatigue; qPCR | Distinct mitochondrial signature in lcSSc-ME/CFS: reduced ND4 (CI) and CyB (CIII), increased Cox7C (CIV) transcripts; elevated mitochondrial ROS markers; pattern could distinguish disease subsets; fatigue linked to mitochondrial bioenergetic failure | electron transport chain (ETC) complex I/IV expression, mtDNA integrity, PBMC bioenergetics | [39] |
| Case–control | n = 25 SSc/20 HC | Quantitative PCR-based mtDNA copy number measurement in CD14+ monocytes from SSc patients; correlation with clinical disease features | Significantly increased mtDNA copy number in SSc CD14+ monocytes vs. controls; higher mtDNA-CN correlated with shorter disease duration; proposed as compensatory response to mitochondrial dysfunction; IL-6 secretion elevated in SSc monocytes | mtDNA copy number (CD14+ monocytes), IL-6, disease duration | [40] |
| ASPECT 4: Circulating Cardiac Biomarkers and Primary Cardiac Involvement | |||||
| Study Design | Sample Size | Population/Methods | Key Findings | Outcome/Biomarker | Ref |
| Prospective interventional | n = 35 SSc-pHI (from 684) | CMR-proven SSc primary heart involvement (pHI); immunosuppressive therapy initiated; follow-up CMR at 6–18 months; T1/T2 mapping, (extracellular volume fraction) ECV, LGE | Immunosuppressive therapy reduced myocardial edema (T2 decrease) and fibrosis (ECV reduction); STIR abnormalities normalized in 60%; LGE extent decreased; CMR parametric mapping guides treatment response monitoring | T1/T2 mapping, ECV, LGE, STIR; CMR response to IS | [41] |
| Prospective cohort | n = 245 SSc/50 HC | hs-cTnT and NT-proBNP measured in 245 SSc patients; correlation with echocardiographic abnormalities, skin score, ECG findings | hs-cTnT > 0.014 ng/mL in 32.3%; NT-proBNP > 125 pg/mL in 31.8%; both correlated with diffuse cutaneous SSc and mRSS; elevated markers associated with lower LVEF and RBBB; independent of classical CV risk factors | hs-cTnT, NT-proBNP, LVEF, mRSS | [42] |
| Prospective multi-center cohort | n = 675 SSc | NT-proBNP, hs-cTnT, CRP measured in CSRG registry; prospective follow-up for cardiopulmonary outcomes (death, PAH, systolic dysfunction, arrhythmia, ILD) | NT-proBNP, hs-cTnT, and CRP each independently predicted death and PAH in multivariate analysis; NT-proBNP + CRP most strongly linked to PH; hs-cTnT associated with systolic dysfunction; CRP predicted ILD progression | NT-proBNP, hs-cTnT, CRP; PAH, death, ILD outcomes | [43] |
| Cross-sectional case–control | n = 161 SSc/213 HC | hs-cTnT and NT-proBNP by electrochemiluminescence in SSc vs. age/sex-matched controls; multivariate logistic regression for precapillary PH | hs-cTnT and NT-proBNP significantly elevated in SSc vs. controls (p < 0.001); NT-proBNP exclusively linked to precapillary PH; normal combined hs-cTnT + NT-proBNP has NPV 92% for PH; hs-cTnT associated with diffuse SSc and diabetes | hs-cTnT, NT-proBNP; PH detection, NPV | [44] |
| ASPECT 5: Cross-Dimensional Correlations—RV Function, Microvascular Disease, Biomarkers, and Mitochondria | |||||
| Study Design | Sample Size | Population/Methods | Key Findings | Outcome/Biomarker | Ref. |
| Cross-sectional (multi-modal) | n = 20 SSc-PAH/5 IPAH | Simultaneous CMR (perfusion, fibrosis, edema), echocardiography, and nailfold capillaroscopy in SSc-PAH vs. IPAH; correlation of peripheral vascular, cardiac, and microvascular domains | Peripheral NCD correlated with cardiac ECV and T2 (fibrosis and inflammation); post-occlusive reactive hyperemia (PORH)linked to myocardial upslope; diastolic parameters correlated with NCD; SSc-specific microvascular–cardiac axis identified as driver of excess mortality over IPAH | Peripheral NCD, cardiac ECV, T2, myocardial perfusion, diastolic function | [6] |
| Multi-dimensional observational | SSc cohort | Combined echocardiographic strain (GLS, RV strain), NT-proBNP, hs-cTnT, and functional capacity (6MWT) integrated for cardiac risk stratification | Combinatorial biomarker model superior to single-domain assessment; GLS correlated with NT-proBNP and hs-cTnT elevation; low GLS + elevated NT-proBNP identified highest risk phenotype; multi-domain approach captures RV-LV–biomarker interdependence | GLS, RV strain, NT-proBNP, hs-cTnT, 6MWT; composite risk score | [35] |
| Prospective cohort (cross-domain) | n = 131 SSc | RV-GLS by speckle-tracking correlated with NT-proBNP, troponin levels, and clinical disease features in SSc; RV function as integrative marker | RV-GLS decline correlated with NT-proBNP and hs-cTnT elevations; RV functional impairment reflected downstream biomarker release; RV strain linked mechanistically to biomarker-detected myocardial injury, supporting cross-dimensional RV-biomarker model | RV-GLS vs. NT-proBNP, hs-cTnT; cross-domain RV-biomarker correlation | [24] |
| Cross-Dimensional Link | Evidence Base | Strength | Principal Limitation/Requirement |
|---|---|---|---|
| Circulating biomarkers (NT-proBNP, hs-cTn) ↔ RV dysfunction & cardiopulmonary mortality | Multiple human SSc/SSc-PAH cohorts; prognostic association replicated | Strong | Associational, not mechanistic; does not localize injury |
| Peripheral microvascular damage (capillaroscopy) ↔ cardiac microvascular/RV dysfunction | Human SSc; direct correlations (Vos, r ≈ −0.44/−0.46) + CMR | Moderate | Single small (n ≈ 20) cross-sectional study; needs replication |
| CMR myocardial inflammation (T2) ↔ reversibility with immunosuppression | Human SSc [41] | Moderate | Limited cohort; not specific to the mitochondrial model |
| Fibroblast bioenergetic reprogramming → dermal fibrosis | Human SSc dermal fibroblasts; functional + metabolomic [9,57] | Moderate | Direct but dermal-only; cross-sectional in vitro |
| Fibroblast bioenergetic reprogramming → cardiac fibrosis | Extrapolated from dermal; shared TGF-β1 signaling | Inferred | No SSc cardiac fibroblast bioenergetic data exist |
| GRIM-19/STAT3/PINK1-Parkin → fibrosis | Single murine bleomycin model + dermal fibroblast work [10] | Weak | Animal + non-cardiac human tissue; cardiac relevance untested |
| PBMC ETC transcript changes → cardiac pathology | lcSSc-fatigue; qPCR transcripts [39] | Weak | Non-cardiac cell type, transcript-only, fatigue (not cardiac) cohort |
| Monocyte mtDNA copy number → disease activity/cardiac injury | Human SSc monocytes [40] | Weak | Compensatory marker; cardiac link not tested |
| mtDNA-DAMP → TLR9/NLRP3 → myocardial inflammation | Mechanistic analogy from other diseases | Inferred | No direct evidence in SSc myocardium |
| Mitochondrial dysfunction → RV myocardial injury (overall bridge) | Composite inference across the above | Inferred | Requires direct cardiac mitochondrial measurement |
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Coppi, F.; Pagnoni, G.; Renda, G.; Sbarra, F.; De Cesare, D.; Marangi, F.; Baccarani, A.; Aschieri, D.; Mattioli, A.V.; Dei Cas, A.; et al. Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review. Int. J. Mol. Sci. 2026, 27, 7683. https://doi.org/10.3390/ijms27177683
Coppi F, Pagnoni G, Renda G, Sbarra F, De Cesare D, Marangi F, Baccarani A, Aschieri D, Mattioli AV, Dei Cas A, et al. Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review. International Journal of Molecular Sciences. 2026; 27(17):7683. https://doi.org/10.3390/ijms27177683
Chicago/Turabian StyleCoppi, Francesca, Gianluca Pagnoni, Giulia Renda, Francesco Sbarra, Damiano De Cesare, Francesco Marangi, Alessio Baccarani, Daniela Aschieri, Anna Vittoria Mattioli, Alessandra Dei Cas, and et al. 2026. "Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review" International Journal of Molecular Sciences 27, no. 17: 7683. https://doi.org/10.3390/ijms27177683
APA StyleCoppi, F., Pagnoni, G., Renda, G., Sbarra, F., De Cesare, D., Marangi, F., Baccarani, A., Aschieri, D., Mattioli, A. V., Dei Cas, A., Fedele, F., Nasi, M., Giuggioli, D., Pinti, M., Bigdelu, L., Fereydouni, N., & Darroudi, S. (2026). Mitochondrial Dysregulation and Molecular Signaling in Systemic Sclerosis Cardiac Disease: An Integrative Echocardiographic, Microvascular, and Biomarker Review. International Journal of Molecular Sciences, 27(17), 7683. https://doi.org/10.3390/ijms27177683

