A systematic review of advances in the knowledge and therapeutics of spinal myotropic atrophy from three-dimensional stem cell derived spinal organoid model

A systematic review of advances in the knowledge and therapeutics of spinal myotropic atrophy from three-dimensional stem cell derived spinal organoid model | 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 Systematic Review A systematic review of advances in the knowledge and therapeutics of spinal myotropic atrophy from three-dimensional stem cell derived spinal organoid model Prayash Paudel, Asutosh Sah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7162669/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Spinal Muscular Atrophy (SMA) is a fatal neurodegenerative disorder with limited therapies and incomplete mechanistic understanding. Emerging 3D spinal cord organoids derived from human pluripotent stem cells offer physiologically relevant models, enabling improved disease modeling and therapeutic exploration. This review highlights their potential in addressing critical gaps in SMA research. Methods This review systematically evaluates 3D spinal cord organoid studies modeling SMA, using strict PICO-based criteria, comprehensive database searches, and SYRCLE bias assessment to extract mechanistic, therapeutic, and methodological insights. Result We included 9 studies using 3D spinal organoids derived from human iPSCs to model SMA. Organoids effectively recapitulated motor neuron degeneration, developmental defects, and glial contributions. They enabled therapeutic testing (e.g., risdiplam, antisense oligonucleotides), but faced limitations in maturity, reproducibility, and cellular diversity. Despite these challenges, organoids surpassed traditional models, offering mechanistic insights and translational promise. Key research gaps include modeling chronic disease, integrating sensory-motor circuits, and improving vascularization. Discussion SMA organoids enable patient-specific drug testing and uncover novel mechanisms, but face limitations in vascularization, maturity, and heterogeneity. Despite challenges, they surpass traditional models and drive a shift toward multifaceted SMA therapeutics. However, a standardized protocol is necessary to improve reproducibility, minimize batch variability, and enable reliable cross-study comparisons in SMA organoid research—ultimately enhancing their translational utility in drug discovery and personalized medicine. organoids spinal organoids SMA spinal myotropic atrophy 3D model treatment Figures Figure 1 Introduction Spinal Muscular Atrophy (SMA), a devastating monogenic neurodegenerative disorder primarily caused by mutations in the SMN1 gene leading to survival motor neuron (SMN) protein deficiency, remains a significant cause of infant mortality and morbidity. While landmark disease-modifying therapies (nusinersen, risdiplam, onasemnogene abeparvovec) have transformed the clinical landscape, critical knowledge gaps and therapeutic limitations persist [ 1 ][ 2 ].Mechanistically, the precise spatiotemporal dynamics of SMN deficiency leading to motor neuron (MN) degeneration, the contribution of non-neuronal cells (e.g., astrocytes, microglia) within the spinal cord niche, and the reasons for differential therapeutic response or resistance are incompletely understood[ 3 ]. Therapeutically, existing treatments ameliorate but often do not fully reverse established pathology, have variable efficacy across SMA types and ages, present significant access and delivery challenges (particularly to the central nervous system), and carry substantial cost burdens [ 4 ]. Furthermore, the long-term consequences and potential novel therapeutic targets beyond SMN restoration require exploration[ 5 ]. Traditional research models have inherent limitations in addressing these gaps. Animal models (e.g., SMNΔ7 mice), while invaluable, exhibit species-specific differences in neurodevelopment, lifespan, and disease progression that complicate direct translation to humans[ 6 ]. Conventional 2D neuronal cultures lack the complex three-dimensional (3D) architecture, multicellular composition, and physiological cell-cell/cell-matrix interactions of the developing and diseased human spinal cord[ 7 ]. Consequently, there is a critical unmet need for more physiologically relevant human model systems that accurately recapitulate the intricate spinal cord microenvironment and SMA pathogenesis. The development of three-dimensional (3D) spinal cord organoids from human pluripotent stem cells (hPSCs) has enabled more physiologically relevant models of spinal cord development and disease. These organoids exhibit spatial patterning, contain both neural and glial populations, and can mature into myelinated neurons. Recent studies have demonstrated that replacing Matrigel with more defined and tissue-specific scaffold materials—such as decellularized brain extracellular matrix (DBECMH) and alginate hydrogels—enhances reproducibility and supports neural differentiation and maturation. Furthermore, patient-derived induced pluripotent stem cells (iPSCs) have been successfully used to generate disease-specific organoids, enabling the modeling of genetic disorders like ALS under defined 3D conditions[ 8 ][ 9 ]. This review is critically important because it will systematically synthesize and evaluate the rapidly accumulating body of evidence utilizing these advanced organoid models specifically for SMA research. This systematic review is critically necessary to synthesize the rapidly evolving, yet fragmented, application of 3D organoid technology specifically to SMA research. Its importance lies in addressing five distinct aims that collectively assess the maturity, utility, and future trajectory of this model system: To examine methodologies for generation, validation, and characterization: Current SMA organoid protocols vary widely in stem cell sources, scaffolds, and validation criteria (e.g., for motor neuron loss), compromising reproducibility. Our synthesis identifies best practices to ensure reliable models. To assess contribution to understanding pathophysiology: Animal/2D models fail to capture unique human pathology like developmental timing defects or glial dysfunction. We evaluate whether organoids successfully resolve these knowledge gaps. To evaluate application in therapeutics and personalized medicine: Existing SMA treatments show variable efficacy and lack patient-specific prediction tools. Our assessment explores organoids’ utility for drug screening, gene therapy testing, and personalized outcome modeling. To identify limitations, challenges, and reproducibility issues: Organoid studies are hampered by vascularization deficits, batch variability, and immature phenotypes. We systematically document these limitations to guide realistic model applications. To highlight gaps and recommend future directions: Fragmented progress obscures critical refinements needed for clinical impact. Our integrated analysis defines actionable steps—like multi-tissue integration and chronic disease modeling—to accelerate progress. No prior systematic review has thoroughly examined the five key areas within the context of SMA spinal organoid research: the methodological landscape, evidence for disease mechanisms, therapeutic applications in vitro, current limitations and challenges, and recommendations for future SMA-specific studies. Therefore, this systematic review is novel and urgently needed. It will provide the first dedicated, comprehensive synthesis evaluating how 3D spinal organoid models are actually being used in SMA research, how effectively they are advancing knowledge and therapy development, and what critical steps are required to overcome current barriers. This will accelerate the responsible and impactful integration of this transformative technology into the SMA research pipeline, ultimately aiding the quest for more effective and personalized therapies. The review is done in accordance to PRISMA 2020 guideline, the checklist of which are attached as S4_Appendix and S5_Appendix. Method 1. Eligibility Criteria Studies will be included based on the PICO framework: Population: In vitro 3D spinal cord organoids derived from human pluripotent stem cells (hPSCs/iPSCs) modeling spinal muscular atrophy (SMA). Intervention/Exposure: Use of organoids for (i) SMA pathophysiology investigation, (ii) therapeutic screening (e.g., SMN-enhancing compounds, gene therapies), or (iii) personalized medicine applications. Comparator: Traditional models (2D cultures, animal models) or control organoids (e.g., isogenic controls, healthy donor-derived). Outcomes: Methodological metrics (e.g., organoid reproducibility, cellular composition). Pathophysiological insights (e.g., motor neuron loss, glial dysfunction). Therapeutic efficacy (e.g., SMN protein restoration, neuronal survival). Limitations (e.g., batch variability, scalability). 2. Exclusion Criteria: Non-human models, non-spinal organoids, or non-SMA studies. Reviews, conference abstracts (unless containing original data), non-English publications. Studies not reporting outcomes relevant to the five review aims. Information sources A comprehensive literature search was conducted across multiple electronic databases, including PubMed/MEDLINE (via NCBI), Embase (via Elsevier), and Google Scholar, until July 7, 2025. No date or language restrictions were applied during the search. To ensure thorough coverage, backward citation tracking was performed by manually screening reference lists of all eligible publications and relevant reviews. This process identified additional studies not captured by database searches. Search strategy A comprehensive search strategy, guided by the PICO framework, was conducted across PubMed/MEDLINE, Embase, Web of Science, Scopus, and Cochrane Central up to July 16, 2025. The strategy combined controlled vocabulary (MeSH/Emtree) and keywords related to: Population/Disease: Spinal Muscular Atrophy, SMA, SMN1 deficiency, survival motor neuron Model System: 3D organoid, spinal cord organoid, stem cell-derived model, neural organoid Intervention/Application: drug screening, gene therapy testing, pathophysiological modeling, personalized medicine Outcomes: organoid reproducibility, motor neuron loss, SMN protein dynamics, therapeutic efficacy No language or date restrictions were applied during database searches. Post-search limits aligned with eligibility criteria (e.g., exclusion of non-English studies, animal-only models). The complete search strategies—including database-specific syntax, field codes (e.g., [tiab], [Mesh]), keyword variations, and platform adaptations—are documented in Supplementary Appendix S1. Selection process The literature search was conducted by PP. All identified studies from electronic databases and manual searches were exported to Google Sheets. Duplicates were manually identified, recorded, and removed. The remaining titles and abstracts were independently screened by both authors (PP and AS). Full-text articles of potentially eligible studies were then retrieved and assessed for final inclusion. Any disagreements were resolved through consensus. Data collection process Data extraction was independently performed by PP and AA using Google Sheets. Both reviewers were blinded to each other’s work. Any discrepancies were resolved through mutual agreement. All required data were available in the included studies; therefore, there was no need to contact the original authors for missing information. No automation tools were employed during the study selection or data extraction processes. Study risk of bias assessment Two reviewers (PP, AS) independently assessed the risk of bias for all included studies using the SYRCLE Risk of Bias tool, which is specifically designed for animal and preclinical research. The tool evaluates ten domains across selection, performance, detection, attrition, reporting, and other potential sources of bias. Discrepancies between reviewers were resolved through discussion and consensus. The overall risk of bias for each study was classified as follows: low risk if all key domains were adequately addressed; high risk if one or more domains exhibited significant methodological concerns; and unclear risk if one or more domains lacked sufficient reporting detail. No adaptations of the SYRCLE tool were made, and no automation tools or author contact were used during the risk of bias assessment. Result Study selection A total of 102 [PubMed (30), Embase (22), Google Scholar (50)] articles were retrieved using our search strategy, and 42 records were discarded owing to duplication. The remaining 60 articles were subjected to title and abstract screening. Out of which, we excluded 48 articles and retained the remaining 12 articles for further evaluation by reading the full texts. All the 12 articles were retrieved and were assessed for eligibility. Among them, 3 reports were excluded due to irrelevant data. Thus, 9 eligible articles were finally included in this study. PRISMA flow diagram showing study selection process is in Fig. 1. Risk of bias assessment Risk of Bias (RoB) was assessed across nine included studies using the SYRCLE 10-item tool. Most studies demonstrated low risk of bias in domains related to baseline group comparability, completeness of outcome data, and selective reporting. This reflects the consistent use of patient- and control-derived iPSC organoid models, adequate reporting of sample sizes, and comprehensive inclusion of both primary and secondary outcomes. The studies were methodologically consistent in experimental design and biologically relevant modeling. A detailed breakdown of the item-by-item RoB assessment for each study is provided in S2_Appendix. Methodologies for Generation, Validation, and Characterization of Disease-Specific Spinal Organoids Organoid Generation Organoid generation across studies relied on human SMA iPSCs differentiated via conserved signaling pathways. Hor et al. (2018) [ 10 ] established a foundational protocol using dual SMAD inhibition, retinoic acid (RA), and SHH agonists (purmorphamine) to generate ventralized spinal tissue, with Matrigel encapsulation enabling 3D self-organization. Faravelli et al. 2022 [ 11 ], 2025 [ 12 ] advanced this with free-floating embryoid body (EB) methods, while their 2025 study incorporated a heparin-supplemented dual-phase system to enhance neural induction efficiency. The most significant innovation came from Grass et al. 2024 [ 13 ], who primed iPSCs into neuromesodermal progenitors (NMPs) using WNT/FGF activation—mimicking embryonic axial elongation—and combined this with CRISPR-mediated SMN1 correction. Winanto et al. 2019 [ 14 ] demonstrated that bioreactor culture alone could achieve segment-specific (brachial/thoracic) patterning, highlighting self-organization capacity. Later studies (Corti et al. 2025 [ 15 ]; Angelo et al. 2024 [ 16 ]) embedded therapeutics (e.g., risdiplam analogues) directly into differentiation protocols, enabling real-time assessment of drug effects on development. Validation Organoids consistently mirrored human spinal cord biology. Spatial organization was confirmed by specific markers: SOX1⁺ neural progenitors localized apically, while ISL1⁺ motor neurons occupied basal regions (Hor et al. 2018 [ 10 ]; Buchner et al. 2023 [ 17 ]). Functional validation further supported this resemblance. Neuromuscular junctions formed within the organoids were capable of triggering muscle contractions (Hor et al. 2018 [ 10 ]; Winanto et al. 2019 [ 14 ]). Electrophysiological activity, including spontaneous firing and responses to glutamate, was detected using multi-electrode arrays (Faravelli et al. 2022 [ 11 ]; Corti et al. 2025 [ 15 ]). Additionally, single-cell RNA sequencing revealed transcriptomic profiles closely matching those of the human fetal spinal cord (Faravelli et al. 2022 [ 11 ]; Corti et al. 2025 [ 15 ]). Characterization in Disease Modeling SMA organoids revealed critical disease mechanisms that closely recapitulate aspects of the human condition. Notably, there was a delayed yet pronounced loss of motor neurons, peaking at day 35, with Type I SMA organoids showing only 13.5% motor neuron survival compared to controls—reflecting clinical progression (Hor et al. 2018 [ 10 ]). Additional pathophysiological features included cell-cycle dysregulation, marked by CDK4/6 overexpression, and synaptic dysfunction characterized by reduced expression of SYT4 and NRXN1 (Hor et al. 2018 [ 10 ]; Faravelli et al. 2022 [ 11 ]). A neuromesodermal imbalance was also observed, with an overproduction of mesodermal cells at the expense of neural tissue (Grass et al. 2024 [ 13 ]). At the network level, SMA organoids exhibited glutamate-driven hyperexcitability (Faravelli et al. 2025 [ 12 ]). On the therapeutic front, several interventions demonstrated rescue effects, including CDK4/6 inhibitors (Hor et al. 2018 [ 10 ]), antisense oligonucleotides (Faravelli et al. 2025 [ 12 ]), and risdiplam analogues (D’Angelo 2024 [ 16 ]; Corti et al. 2025 [ 15 ]), with treatment efficacy shown to be dependent on timing. Assessing the Contribution of 3D Organoid Models to Understanding Disease Pathophysiology and Cellular Mechanisms Three-dimensional spinal organoid models have collectively revealed novel insights into Spinal Muscular Atrophy (SMA) pathophysiology, demonstrating that the disease involves interconnected developmental and degenerative processes. Hor et al. 2018 [ 10 ] established that motor neurons form normally but undergo rapid post-developmental degeneration driven by aberrant cell-cycle re-entry—a mechanism characterized by CDK/cyclin overexpression triggering apoptosis. Complementing this, Grass et al. 2024 [ 13 ] discovered fundamental neurodevelopmental defects in neural stem cell specification, showing SMA organoids develop imbalanced neuromesodermal progenitor commitment that favors mesodermal over neural lineages. Corti et al. 2024 [ 18 ] further confirmed developmental abnormalities extend beyond motor neurons to multiple spinal cell types. These models exposed broader cellular mechanisms underlying SMA pathology. Faravelli et al. 2022 [ 11 ], 2025 [ 12 ] identified pervasive transcriptional dysregulation across neural progenitors and neurons, manifesting as synaptic gene suppression (e.g., SYT, NRXN) and CNS-wide electrophysiological hyperexcitability in both spinal and brain organoids. Buchner et al. 2023 [ 17 ] demonstrated non-cell-autonomous contributions, revealing dysfunctional astrocyte/microglia interactions exacerbate motor neuron degeneration. Winanto et al. 2019 [ 14 ] confirmed the selective vulnerability of motor neurons within 3D microenvironments, observing accelerated cell death and synaptic defects mirroring human neuropathology. Together, these studies establish SMA as a multilevel disorder involving defective lineage commitment, cell-cycle dysregulation, network-level dysfunction, and glia-mediated toxicity. Collectively, these studies show that 3D organoids uniquely model human-specific SMA pathophysiology—spanning developmental defects, neurodegeneration, and glial involvement—while serving as platforms for therapy validation. Evaluating the Use of 3D Organoid Models in Therapeutic Screening, Drug Discovery, and Personalized Medicine for Disease Our analysis of nine studies demonstrates the significant role of 3D spinal organoids in advancing SMA drug discovery and therapeutic testing. Hor et al. 2018 [ 10 ] and Winanto et al. 2019 [ 14 ] established that SMA organoids replicate disease pathology (e.g., motor neuron degeneration), enabling high-throughput screening of neuroprotective drugs like CDK4/6 inhibitors (PD 0332991), which improved neuron survival in 3D microenvironments. Drug optimization was consistently achieved: Corti et al. 2024, 2025 [ 15 , 18 ] used organoids to validate risdiplam-like compounds that corrected SMN2 splicing and identified optimal dosing (150 nM every 2 days) and critical treatment windows (initiation at day 45 enhanced motor neuron differentiation). Similarly, Faravelli et al. [ 11 , 12 ] demonstrated peptide-conjugated antisense oligonucleotides (r6-MO) restored SMN protein levels and reversed neuronal hyperexcitability across genetic backgrounds. For personalized applications, Grass et al. 2024 [ 13 ] and D’Angelo et al. 2024 [ 16 ] showed organoids mirrored patient-specific severity (Type I vs. II SMA), predicting individualized responses to long-term risdiplam treatment while monitoring tolerance and transcriptomic changes. Buchner et al. 2023 [ 17 ] further highlighted organoids' utility in testing combination therapies (e.g., rapamycin for ALS comorbidity) and immune interactions. Limitations included batch variability and absent vascular components (Corti et al., 2024 [ 18 ]), but all studies confirmed organoids surpassed 2D models in modeling drug efficacy within human-relevant tissue complexity. Identifying Current Limitations, Methodological Challenges, and Reproducibility Issues in the Use of 3D Organoids Our analysis of seven studies [ 10 – 14 , 17 , 18 ] identified several recurring limitations and reproducibility challenges in 3D spinal organoid models for SMA. First, limited cellular diversity remains a significant constraint, as many organoids lack key cell types such as dorsal sensory neurons, astrocytes, oligodendrocytes, as well as vascular and immune components—factors essential for accurately modeling disease pathology (Hor et al. 2018 [ 10 ]; Grass et al. 2024[ 13 ]; Corti et al. 2024[ 18 ]). Second, reproducibility issues are prevalent, driven by protocol variations (such as morphogen timing and cell-seeding density), batch effects in single-cell RNA sequencing, and heterogeneity among iPSC lines, all of which complicate cross-study comparisons (Faravelli et al.[ 11 , 12 ]; Buchner et al. 2023[ 17 ]; Winanto et al. 2019[ 14 ]). Third, many organoids exhibit functional immaturity, with underdeveloped electrophysiological properties, limited viability beyond 90 days, and delayed neuronal maturation, making it difficult to model chronic SMA phenotypes effectively (Hor et al. 2018[ 10 ]; Faravelli et al. 2022 [ 11 ]; Grass et al. 2024[ 13 ]). Fourth, technical barriers such as complex protocols involving CRISPR editing of SMN genes, reliance on Matrigel-based culture systems, and resource-intensive assays like high-density multi-electrode arrays (HD-MEA) and single-cell RNA-seq limit scalability and widespread adoption (Grass et al. 2024[ 13 ]; Corti et al. 2024[ 18 ]; Buchner et al. 2023 [ 17 ]). Finally, even promising therapeutic interventions, such as SMN1 gene conversion, only achieved partial phenotypic rescue, indicating the presence of unresolved disease modifiers that require further investigation (Grass et al. 2024 [ 13 ]; Faravelli et al. 2025 [ 12 ]). Identifying Gaps and Guiding Future Research in Spinal Muscular Atrophy (SMA) Using Organoid Models Our systematic review synthesized findings from key studies using 3D spinal organoids to model spinal muscular atrophy (SMA). Hor et al. 2018 [ 10 ] found that current organoids lack sensory neurons and non-neuronal cells (e.g., glia), limiting insights into sensory-motor circuits and neuroinflammation. They recommended developing integrated organoids and standardizing functional assays. Faravelli et al. 2022 [ 11 ] noted poor cellular diversity and maturity, urging optimized protocols for vascularization and multi-tissue assembloids. Grass et al. 2024 [ 13 ] highlighted limited representation of SMA heterogeneity and epigenetic uncertainties, calling for multi-tissue assembloids and untagged models. Faravelli et al. 2025 [ 12 ] identified gaps in modeling late-stage disease and systemic interactions, emphasizing extended cultures and CRISPR tools for SMN2 splicing. Corti et al. 2024 [ 18 ] revealed that organoids fail to recapitulate functional neuromuscular junctions (NMJs) or chronic pathology, recommending NMJ-integrated models and physiological assessments. Buchner et al. 2023 [ 17 ] found inadequate modeling of region-specific vulnerability (e.g., lumbar neurons) and vascularization, suggesting axial patterning and vascular integration. Finally, Winanto et al. 2019 [ 14 ] observed a lack of sensory-motor circuits and unresolved motor neuron vulnerability, proposing fused organoids and single-cell technologies. Collectively, these studies underscore critical gaps in cellular complexity, disease-stage modeling, and functional validation, while prioritizing recommendations for multi-tissue integration, patient-specific screening, and advanced physiological readouts. Discussion Prior to the advent of 3D spinal organoid models, fundamental questions about the core pathological sequence in Spinal Muscular Atrophy (SMA) remained contentious. Crucially, it was unclear whether motor neuron degeneration stemmed primarily from intrinsic developmental defects occurring during their formation, or from a distinct neurodegenerative process triggered post-maturation. Furthermore, the potential contribution of non-neuronal cells within the spinal cord niche to disease initiation or progression was difficult to dissect. This impasse began to resolve with the adaptation of organoid technology to model the human spinal cord. These 3D self-organizing structures derived from hPSCs provided the first in vitro system capable of recapitulating the complex spatiotemporal dynamics of human spinal cord development and maturation within a multicellular environment. This breakthrough finally enabled direct observation of human motor neuron ontogeny and degeneration, offering a unique lens to address the persistent mechanistic ambiguities that had hindered therapeutic target identification beyond SMN restoration and obscured optimal intervention windows. This systematic review represents the first comprehensive synthesis of how three-dimensional spinal organoid models are transforming spinal muscular atrophy research. Collectively, the evidence from Hor et al. 2018 [ 10 ], Faravelli et al. [ 11 , 12 ], and Grass et al. 2024 [ 13 ] challenges fundamental assumptions about SMA pathology. These studies demonstrate through human-derived systems that SMA is not solely a neurodegenerative condition but involves critical developmental disruptions. Specifically, Hor et al. 2018 [ 10 ] resolved longstanding controversy by showing motor neurons develop normally but degenerate rapidly after maturation, while Faravelli et al. 2025 [ 12 ] revealed synaptic dysregulation and electrophysiological hyperactivity precede neuronal loss. Grass et al. 2024 [ 13 ] further identified neuromesodermal patterning defects, establishing that SMA pathogenesis begins earlier than previously recognized and extends beyond motor neurons. Therapeutically, work by Corti et al. 2024, 2025 [ 15 , 18 ], D’Angelo et al. 2024 [ 16 ], and Hor et al. 2018[ 10 ] proves organoids are powerful platforms for translational discovery. Corti et al. 2025[ 15 ] demonstrated these models accurately predict patient-specific responses to SMN-restoring therapies like risdiplam, including optimal dosing windows and differential effects across SMA subtypes. D’Angelo et al. 2024[ 16 ] extended this by showing organoids can forecast individual tolerance to long-term treatments. Hor et al. 2018[ 10 ] made the critical discovery that CDK4/6 inhibitors rescue neurons independent of SMN restoration, revealing new therapeutic avenues. However, Grass et al. 2024[ 13 ] and Faravelli et al. 2025[ 12 ] provide sobering evidence that developmental defects persist even after genetic correction, highlighting limitations of current SMN-targeted approaches. Significant knowledge gaps remain, as emphasized by Buchner et al. 2023 [ 17 ] and Winanto et al. 2019 [ 14 ]. The absence of vascular networks and immune cells in current models limits insights into neuroinflammation and systemic pathology. Missing sensory-motor circuits prevent full exploration of network dysfunction. Yet despite these constraints, the collective findings position organoids as uniquely valuable human-relevant systems that outperform animal models in three key areas: capturing human-specific developmental timelines, revealing non-neuronal contributions to disease as shown by Buchner et al. 2023 [ 17 ], and modeling patient-specific therapeutic responses as demonstrated by D’Angelo et al. 2024 [ 16 ]. The convergence of evidence confirms organoids are driving a paradigm shift from viewing SMA as a motor neuron-focused degeneration to recognizing it as a dynamic developmental-degenerative disorder requiring combinatorial treatments. These models have already accelerated drug discovery, personalized therapeutic testing, and mechanistic understanding in ways impossible with traditional approaches. While technical limitations remain, the trajectory established by these studies points toward increasingly sophisticated human models that will fundamentally advance SMA therapeutics. The primary studies synthesized in this review exhibit recurring limitations that constrain their translational impact. Hor et al. 2018 [ 10 ] first highlighted the critical absence of sensory neurons and non-neuronal cells (e.g., astrocytes, microglia) in organoids, restricting modeling of neuroinflammation and sensory-motor circuits. This cellular simplification was corroborated by Grass et al. 2024 [ 13 ], who noted inadequate representation of SMA's systemic pathology (e.g., cardiac/metabolic defects) due to missing multi-tissue interactions. Buchner et al. 2023 [ 17 ] further emphasized the lack of vascularization and region-specific vulnerability (e.g., lumbar motor neurons), limiting insights into therapy delivery and spatial disease mechanisms. Reproducibility emerged as a major concern: Faravelli et al. 2022, 2025 [ 11 , 12 ] and Winanto et al. 2019 [ 14 ] identified significant batch-to-batch variability from protocol inconsistencies (e.g., morphogen timing, scaffold materials) and iPSC line heterogeneity, complicating cross-study validation. Corti et al. 2024 [ 18 ], 2025 [ 15 , 18 ] added that resource-intensive functional assays (e.g., HD-MEA electrophysiology) hindered scalability, while Grass et al. 2024 [ 13 ] observed CRISPR-editing artifacts affecting phenotypic accuracy. Functional immaturity universally limited disease modeling: Hor et al. 2018 [ 10 ] and Faravelli et al. 2022 [ 11 ] reported short organoid viability (< 90 days) and immature electrophysiology, precluding chronic SMA stage analysis. Even therapeutic interventions showed partial efficacy: Grass et al. 2024 [ 13 ] found persistent developmental defects post-SMN1 correction, and Faravelli et al. 2025 [ 12 ] noted incomplete rescue of synaptic dysfunction despite SMN restoration—suggesting unresolved disease modifiers. Finally, D’Angelo et al. 2024 [ 16 ] and Corti et al. 2025 [ 15 ] revealed that organoids failed to fully mirror clinical heterogeneity (e.g., Type I vs. III differential responses), underscoring gaps in personalized prediction accuracy. Despite certain limitations, this review highlights spinal organoids as transformative tools in SMA research, offering unprecedented insights into human-specific disease mechanisms and advancing therapeutic development. As emphasized by the cited studies, continued efforts to enhance biological complexity, improve physiological relevance, standardize protocols, and incorporate patient diversity will be essential to fully realize their potential in delivering urgently needed personalized therapies. This systematic review underscores two critical implications for SMA clinical management and research policy. First, clinical practice must prioritize early intervention and personalized treatment selection, as organoid data confirm that therapeutic efficacy diminishes with delayed administration and varies significantly across subtypes. Second, funding bodies and regulators should strategically invest in organoid technology validation and standardization. This includes establishing accredited organoid cores for preclinical drug testing and creating policy frameworks that recognize human organoid data in therapeutic approval pathways—accelerating translation while reducing reliance on animal models with limited human relevance. Four key priorities have emerged to advance the field. First, developing multi-tissue assembloids that integrate vascular and immune cells is essential to more accurately model systemic pathology. Second, establishing large-scale iPSC biobanks that capture the full spectrum of SMA heterogeneity (types I–IV) will facilitate personalized drug screening and therapeutic development. Third, standardizing functional endpoints—such as neuromuscular junction maturation and electrophysiological biomarkers—is critical for enabling reliable cross-study comparisons. Fourth, innovating long-term culture systems, including the use of perfusion bioreactors, will allow researchers to study late-stage disease progression in greater detail. To maximize clinical impact, these efforts should be driven by collaborative consortia. Declarations Registration and Protocol This review is registered in PROSPERO. The review protocol is available on the PROSPERO record. No amendments were made to the registered information or protocol. Support No financial support was received for this review. Funders or sponsors had no role in the review. Competing Interests The authors declare no competing interests related to this review. Availability of Data, Code, and Other Materials: Data collection forms, extracted data, analysis data, analytic code, and other materials used in this review are available on S3_Appendix. References Nishio H, Niba ETE, Saito T, Okamoto K, Takeshima Y, Awano H. Spinal Muscular Atrophy: The Past, Present, and Future of Diagnosis and Treatment. 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Stem Cell-Derived Spinal Cord Organoid Model: Temporal and Cell-Specific Analysis of Molecular Effects of a Risdiplam Analogue (N2.002). Neurology 2025;104. https://doi.org/10.1212/WNL.0000000000208466. D’Angelo A, Beatrice F, Ongaro J, Rinchetti P, Faravelli I, Miotto M, et al. Three-Dimensional Stem Cell-derived Spinal Cord Model for Investigating Therapeutic Mechanisms of Risdiplam-like Compounds in Spinal Muscular Atrophy (P2-11.001). Neurology 2024;102. https://doi.org/10.1212/WNL.0000000000205358. Buchner F, Dokuzluoglu Z, Grass T, Rodriguez-Muela N. Spinal Cord Organoids to Study Motor Neuron Development and Disease. Life 2023;13. https://doi.org/10.3390/life13061254. Corti S, D’Angelo A, Beatrice F, Ongaro J, Rinchetti P, Faravelli I, et al. 149VP 3D stem cell-derived spinal cord/muscle organoid model for studying and treating neuromuscular diseases. Neuromuscular Disorders 2024;43:104441.584. https://doi.org/10.1016/j.nmd.2024.07.593. Additional Declarations No competing interests reported. Supplementary Files S1Appendix.docx S2Appendix.xlsx S3Appendix.xlsx S4Appendix.docx S5Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7162669","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":488756465,"identity":"563ab5b3-0d8d-4143-bf96-5a4b6a7bd9d9","order_by":0,"name":"Prayash 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Asutosh","middleName":"","lastName":"Sah","suffix":""}],"badges":[],"createdAt":"2025-07-19 07:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7162669/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7162669/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87711672,"identity":"5a29e432-e4a4-4bce-84fc-ecba2b833f5e","added_by":"auto","created_at":"2025-07-28 08:44:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":176889,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA flow diagram showing study selection process.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e*Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003etotal number across all databases/registers).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e**If automation tools were used, indicate how many records were excluded by a human and how many were excluded by\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eautomation tools.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7162669/v1/a04e9ed03b0d134186d3f4c9.png"},{"id":99795501,"identity":"5ca03825-2c9f-4086-a639-34443a2125d8","added_by":"auto","created_at":"2026-01-08 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08:52:06","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15473,"visible":true,"origin":"","legend":"","description":"","filename":"S2Appendix.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7162669/v1/0204398660233133ec1ee565.xlsx"},{"id":87711678,"identity":"7e1f0d37-d603-4478-b192-64869495b66f","added_by":"auto","created_at":"2025-07-28 08:44:06","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":34541,"visible":true,"origin":"","legend":"","description":"","filename":"S3Appendix.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7162669/v1/c2d3f9723464153182351c11.xlsx"},{"id":87711681,"identity":"2f0d2698-0c58-4bce-a287-e867a552bc56","added_by":"auto","created_at":"2025-07-28 08:44:07","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":276192,"visible":true,"origin":"","legend":"","description":"","filename":"S4Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7162669/v1/c9b5e0593eaf66c928c8221d.docx"},{"id":87711683,"identity":"91673e24-9aee-4b77-84ce-809ec98f1c24","added_by":"auto","created_at":"2025-07-28 08:44:07","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":270183,"visible":true,"origin":"","legend":"","description":"","filename":"S5Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7162669/v1/dbb7462c9ba2833b7d221e67.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA systematic review of advances in the knowledge and therapeutics of spinal myotropic atrophy from three-dimensional stem cell derived spinal organoid model\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpinal Muscular Atrophy (SMA), a devastating monogenic neurodegenerative disorder primarily caused by mutations in the \u003cem\u003eSMN1\u003c/em\u003e gene leading to survival motor neuron (SMN) protein deficiency, remains a significant cause of infant mortality and morbidity. While landmark disease-modifying therapies (nusinersen, risdiplam, onasemnogene abeparvovec) have transformed the clinical landscape, critical knowledge gaps and therapeutic limitations persist [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].Mechanistically, the precise spatiotemporal dynamics of SMN deficiency leading to motor neuron (MN) degeneration, the contribution of non-neuronal cells (e.g., astrocytes, microglia) within the spinal cord niche, and the reasons for differential therapeutic response or resistance are incompletely understood[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therapeutically, existing treatments ameliorate but often do not fully reverse established pathology, have variable efficacy across SMA types and ages, present significant access and delivery challenges (particularly to the central nervous system), and carry substantial cost burdens [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, the long-term consequences and potential novel therapeutic targets beyond SMN restoration require exploration[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTraditional research models have inherent limitations in addressing these gaps. Animal models (e.g., SMNΔ7 mice), while invaluable, exhibit species-specific differences in neurodevelopment, lifespan, and disease progression that complicate direct translation to humans[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Conventional 2D neuronal cultures lack the complex three-dimensional (3D) architecture, multicellular composition, and physiological cell-cell/cell-matrix interactions of the developing and diseased human spinal cord[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Consequently, there is a critical unmet need for more physiologically relevant \u003cem\u003ehuman\u003c/em\u003e model systems that accurately recapitulate the intricate spinal cord microenvironment and SMA pathogenesis.\u003c/p\u003e\u003cp\u003eThe development of three-dimensional (3D) spinal cord organoids from human pluripotent stem cells (hPSCs) has enabled more physiologically relevant models of spinal cord development and disease. These organoids exhibit spatial patterning, contain both neural and glial populations, and can mature into myelinated neurons. Recent studies have demonstrated that replacing Matrigel with more defined and tissue-specific scaffold materials—such as decellularized brain extracellular matrix (DBECMH) and alginate hydrogels—enhances reproducibility and supports neural differentiation and maturation. Furthermore, patient-derived induced pluripotent stem cells (iPSCs) have been successfully used to generate disease-specific organoids, enabling the modeling of genetic disorders like ALS under defined 3D conditions[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This review is critically important because it will systematically synthesize and evaluate the rapidly accumulating body of evidence utilizing these advanced organoid models specifically for SMA research.\u003c/p\u003e\u003cp\u003eThis systematic review is critically necessary to synthesize the rapidly evolving, yet fragmented, application of 3D organoid technology specifically to SMA research. Its importance lies in addressing five distinct aims that collectively assess the maturity, utility, and future trajectory of this model system:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo examine methodologies for generation, validation, and characterization: Current SMA organoid protocols vary widely in stem cell sources, scaffolds, and validation criteria (e.g., for motor neuron loss), compromising reproducibility. Our synthesis identifies best practices to ensure reliable models.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo assess contribution to understanding pathophysiology: Animal/2D models fail to capture unique human pathology like developmental timing defects or glial dysfunction. We evaluate whether organoids successfully resolve these knowledge gaps.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo evaluate application in therapeutics and personalized medicine: Existing SMA treatments show variable efficacy and lack patient-specific prediction tools. Our assessment explores organoids’ utility for drug screening, gene therapy testing, and personalized outcome modeling.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo identify limitations, challenges, and reproducibility issues: Organoid studies are hampered by vascularization deficits, batch variability, and immature phenotypes. We systematically document these limitations to guide realistic model applications.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo highlight gaps and recommend future directions: Fragmented progress obscures critical refinements needed for clinical impact. Our integrated analysis defines actionable steps—like multi-tissue integration and chronic disease modeling—to accelerate progress.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNo prior systematic review has thoroughly examined the five key areas within the context of SMA spinal organoid research: the methodological landscape, evidence for disease mechanisms, therapeutic applications in vitro, current limitations and challenges, and recommendations for future SMA-specific studies.\u003c/p\u003e\u003cp\u003eTherefore, this systematic review is novel and urgently needed. It will provide the first dedicated, comprehensive synthesis evaluating how 3D spinal organoid models are actually being used in SMA research, how effectively they are advancing knowledge and therapy development, and what critical steps are required to overcome current barriers. This will accelerate the responsible and impactful integration of this transformative technology into the SMA research pipeline, ultimately aiding the quest for more effective and personalized therapies. The review is done in accordance to PRISMA 2020 guideline, the checklist of which are attached as S4_Appendix and S5_Appendix.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e1. Eligibility Criteria\u003c/p\u003e\u003cp\u003eStudies will be included based on the PICO framework:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePopulation: \u003cem\u003eIn vitro\u003c/em\u003e 3D spinal cord organoids derived from human pluripotent stem cells (hPSCs/iPSCs) modeling spinal muscular atrophy (SMA).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIntervention/Exposure: Use of organoids for (i) SMA pathophysiology investigation, (ii) therapeutic screening (e.g., SMN-enhancing compounds, gene therapies), or (iii) personalized medicine applications.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eComparator: Traditional models (2D cultures, animal models) or control organoids (e.g., isogenic controls, healthy donor-derived).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOutcomes:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMethodological metrics (e.g., organoid reproducibility, cellular composition).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePathophysiological insights (e.g., motor neuron loss, glial dysfunction).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTherapeutic efficacy (e.g., SMN protein restoration, neuronal survival).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLimitations (e.g., batch variability, scalability).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e2. Exclusion Criteria:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eNon-human models, non-spinal organoids, or non-SMA studies.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eReviews, conference abstracts (unless containing original data), non-English publications.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStudies not reporting outcomes relevant to the five review aims.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eInformation sources\u003c/p\u003e\u003cp\u003eA comprehensive literature search was conducted across multiple electronic databases, including PubMed/MEDLINE (via NCBI), Embase (via Elsevier), and Google Scholar, until July 7, 2025. No date or language restrictions were applied during the search. To ensure thorough coverage, backward citation tracking was performed by manually screening reference lists of all eligible publications and relevant reviews. This process identified additional studies not captured by database searches.\u003c/p\u003e\u003cp\u003eSearch strategy\u003c/p\u003e\u003cp\u003eA comprehensive search strategy, guided by the PICO framework, was conducted across PubMed/MEDLINE, Embase, Web of Science, Scopus, and Cochrane Central up to July 16, 2025. The strategy combined controlled vocabulary (MeSH/Emtree) and keywords related to:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePopulation/Disease: Spinal Muscular Atrophy, SMA, SMN1 deficiency, survival motor neuron\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eModel System: 3D organoid, spinal cord organoid, stem cell-derived model, neural organoid\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIntervention/Application: drug screening, gene therapy testing, pathophysiological modeling, personalized medicine\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOutcomes: organoid reproducibility, motor neuron loss, SMN protein dynamics, therapeutic efficacy\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eNo language or date restrictions were applied during database searches. Post-search limits aligned with eligibility criteria (e.g., exclusion of non-English studies, animal-only models). The complete search strategies—including database-specific syntax, field codes (e.g., [tiab], [Mesh]), keyword variations, and platform adaptations—are documented in Supplementary Appendix S1.\u003c/p\u003e\u003cp\u003eSelection process\u003c/p\u003e\u003cp\u003eThe literature search was conducted by PP. All identified studies from electronic databases and manual searches were exported to Google Sheets. Duplicates were manually identified, recorded, and removed. The remaining titles and abstracts were independently screened by both authors (PP and AS). Full-text articles of potentially eligible studies were then retrieved and assessed for final inclusion. Any disagreements were resolved through consensus.\u003c/p\u003e\u003cp\u003eData collection process\u003c/p\u003e\u003cp\u003eData extraction was independently performed by PP and AA using Google Sheets. Both reviewers were blinded to each other’s work. Any discrepancies were resolved through mutual agreement. All required data were available in the included studies; therefore, there was no need to contact the original authors for missing information.\u003c/p\u003e\u003cp\u003eNo automation tools were employed during the study selection or data extraction processes.\u003c/p\u003e\u003cp\u003eStudy risk of bias assessment\u003c/p\u003e\u003cp\u003eTwo reviewers (PP, AS) independently assessed the risk of bias for all included studies using the SYRCLE Risk of Bias tool, which is specifically designed for animal and preclinical research. The tool evaluates ten domains across selection, performance, detection, attrition, reporting, and other potential sources of bias. Discrepancies between reviewers were resolved through discussion and consensus.\u003c/p\u003e\u003cp\u003eThe overall risk of bias for each study was classified as follows: low risk if all key domains were adequately addressed; high risk if one or more domains exhibited significant methodological concerns; and unclear risk if one or more domains lacked sufficient reporting detail. No adaptations of the SYRCLE tool were made, and no automation tools or author contact were used during the risk of bias assessment.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003eStudy selection\u003c/p\u003e\n\u003cp\u003eA total of 102 [PubMed (30), Embase (22), Google Scholar (50)] articles were retrieved using our search strategy, and 42 records were discarded owing to duplication. The remaining 60 articles were subjected to title and abstract screening. Out of which, we excluded 48 articles and retained the remaining 12 articles for further evaluation by reading the full texts. All the 12 articles were retrieved and were assessed for eligibility. Among them, 3 reports were excluded due to irrelevant data. Thus, 9 eligible articles were finally included in this study.\u003c/p\u003e\n\u003cp\u003ePRISMA flow diagram showing study selection process is in Fig. 1.\u003c/p\u003e\n\u003cp\u003eRisk of bias assessment\u003c/p\u003e\n\u003cp\u003eRisk of Bias (RoB) was assessed across nine included studies using the SYRCLE 10-item tool. Most studies demonstrated low risk of bias in domains related to baseline group comparability, completeness of outcome data, and selective reporting. This reflects the consistent use of patient- and control-derived iPSC organoid models, adequate reporting of sample sizes, and comprehensive inclusion of both primary and secondary outcomes. The studies were methodologically consistent in experimental design and biologically relevant modeling. A detailed breakdown of the item-by-item RoB assessment for each study is provided in S2_Appendix.\u003c/p\u003e\n\u003cp\u003eMethodologies for Generation, Validation, and Characterization of Disease-Specific Spinal Organoids\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOrganoid Generation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrganoid generation across studies relied on human SMA iPSCs differentiated via conserved signaling pathways. Hor et al. (2018) [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e] established a foundational protocol using dual SMAD inhibition, retinoic acid (RA), and SHH agonists (purmorphamine) to generate ventralized spinal tissue, with Matrigel encapsulation enabling 3D self-organization. Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e], 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e] advanced this with free-floating embryoid body (EB) methods, while their 2025 study incorporated a heparin-supplemented dual-phase system to enhance neural induction efficiency. The most significant innovation came from Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e], who primed iPSCs into neuromesodermal progenitors (NMPs) using WNT/FGF activation\u0026mdash;mimicking embryonic axial elongation\u0026mdash;and combined this with CRISPR-mediated SMN1 correction. Winanto et al. 2019 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] demonstrated that bioreactor culture alone could achieve segment-specific (brachial/thoracic) patterning, highlighting self-organization capacity. Later studies (Corti et al. 2025 [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]; Angelo et al. 2024 [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]) embedded therapeutics (e.g., risdiplam analogues) directly into differentiation protocols, enabling real-time assessment of drug effects on development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrganoids consistently mirrored human spinal cord biology. Spatial organization was confirmed by specific markers: SOX1⁺ neural progenitors localized apically, while ISL1⁺ motor neurons occupied basal regions (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]; Buchner et al. 2023 [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]). Functional validation further supported this resemblance. Neuromuscular junctions formed within the organoids were capable of triggering muscle contractions (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]; Winanto et al. 2019 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]). Electrophysiological activity, including spontaneous firing and responses to glutamate, was detected using multi-electrode arrays (Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]; Corti et al. 2025 [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]). Additionally, single-cell RNA sequencing revealed transcriptomic profiles closely matching those of the human fetal spinal cord (Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]; Corti et al. 2025 [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization in Disease Modeling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSMA organoids revealed critical disease mechanisms that closely recapitulate aspects of the human condition. Notably, there was a delayed yet pronounced loss of motor neurons, peaking at day 35, with Type I SMA organoids showing only 13.5% motor neuron survival compared to controls\u0026mdash;reflecting clinical progression (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]). Additional pathophysiological features included cell-cycle dysregulation, marked by CDK4/6 overexpression, and synaptic dysfunction characterized by reduced expression of SYT4 and NRXN1 (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]; Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]). A neuromesodermal imbalance was also observed, with an overproduction of mesodermal cells at the expense of neural tissue (Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]). At the network level, SMA organoids exhibited glutamate-driven hyperexcitability (Faravelli et al. 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]). On the therapeutic front, several interventions demonstrated rescue effects, including CDK4/6 inhibitors (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]), antisense oligonucleotides (Faravelli et al. 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]), and risdiplam analogues (D\u0026rsquo;Angelo 2024 [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]; Corti et al. 2025 [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]), with treatment efficacy shown to be dependent on timing.\u003c/p\u003e\n\u003cp\u003eAssessing the Contribution of 3D Organoid Models to Understanding Disease Pathophysiology and Cellular Mechanisms\u003c/p\u003e\n\u003cp\u003eThree-dimensional spinal organoid models have collectively revealed novel insights into Spinal Muscular Atrophy (SMA) pathophysiology, demonstrating that the disease involves interconnected developmental and degenerative processes. Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e] established that motor neurons form normally but undergo rapid post-developmental degeneration driven by aberrant cell-cycle re-entry\u0026mdash;a mechanism characterized by CDK/cyclin overexpression triggering apoptosis. Complementing this, Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e] discovered fundamental neurodevelopmental defects in neural stem cell specification, showing SMA organoids develop imbalanced neuromesodermal progenitor commitment that favors mesodermal over neural lineages. Corti et al. 2024 [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] further confirmed developmental abnormalities extend beyond motor neurons to multiple spinal cell types.\u003c/p\u003e\n\u003cp\u003eThese models exposed broader cellular mechanisms underlying SMA pathology. Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e], 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e] identified pervasive transcriptional dysregulation across neural progenitors and neurons, manifesting as synaptic gene suppression (e.g., SYT, NRXN) and CNS-wide electrophysiological hyperexcitability in both spinal and brain organoids. Buchner et al. 2023 [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] demonstrated non-cell-autonomous contributions, revealing dysfunctional astrocyte/microglia interactions exacerbate motor neuron degeneration. Winanto et al. 2019 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] confirmed the selective vulnerability of motor neurons within 3D microenvironments, observing accelerated cell death and synaptic defects mirroring human neuropathology. Together, these studies establish SMA as a multilevel disorder involving defective lineage commitment, cell-cycle dysregulation, network-level dysfunction, and glia-mediated toxicity.\u003c/p\u003e\n\u003cp\u003eCollectively, these studies show that 3D organoids uniquely model human-specific SMA pathophysiology\u0026mdash;spanning developmental defects, neurodegeneration, and glial involvement\u0026mdash;while serving as platforms for therapy validation.\u003c/p\u003e\n\u003cp\u003eEvaluating the Use of 3D Organoid Models in Therapeutic Screening, Drug Discovery, and Personalized Medicine for Disease\u003c/p\u003e\n\u003cp\u003eOur analysis of nine studies demonstrates the significant role of 3D spinal organoids in advancing SMA drug discovery and therapeutic testing. Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e] and Winanto et al. 2019 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] established that SMA organoids replicate disease pathology (e.g., motor neuron degeneration), enabling high-throughput screening of neuroprotective drugs like CDK4/6 inhibitors (PD 0332991), which improved neuron survival in 3D microenvironments.\u003c/p\u003e\n\u003cp\u003eDrug optimization was consistently achieved: Corti et al. 2024, 2025 [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] used organoids to validate risdiplam-like compounds that corrected SMN2 splicing and identified optimal dosing (150 nM every 2 days) and critical treatment windows (initiation at day 45 enhanced motor neuron differentiation). Similarly, Faravelli et al. [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e] demonstrated peptide-conjugated antisense oligonucleotides (r6-MO) restored SMN protein levels and reversed neuronal hyperexcitability across genetic backgrounds.\u003c/p\u003e\n\u003cp\u003eFor personalized applications, Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e] and D\u0026rsquo;Angelo et al. 2024 [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e] showed organoids mirrored patient-specific severity (Type I vs. II SMA), predicting individualized responses to long-term risdiplam treatment while monitoring tolerance and transcriptomic changes. Buchner et al. 2023 [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] further highlighted organoids\u0026apos; utility in testing combination therapies (e.g., rapamycin for ALS comorbidity) and immune interactions.\u003c/p\u003e\n\u003cp\u003eLimitations included batch variability and absent vascular components (Corti et al., 2024 [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]), but all studies confirmed organoids surpassed 2D models in modeling drug efficacy within human-relevant tissue complexity.\u003c/p\u003e\n\u003cp\u003eIdentifying Current Limitations, Methodological Challenges, and Reproducibility Issues in the Use of 3D Organoids\u003c/p\u003e\n\u003cp\u003eOur analysis of seven studies [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] identified several recurring limitations and reproducibility challenges in 3D spinal organoid models for SMA. First, limited cellular diversity remains a significant constraint, as many organoids lack key cell types such as dorsal sensory neurons, astrocytes, oligodendrocytes, as well as vascular and immune components\u0026mdash;factors essential for accurately modeling disease pathology (Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]; Grass et al. 2024[\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]; Corti et al. 2024[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]). Second, reproducibility issues are prevalent, driven by protocol variations (such as morphogen timing and cell-seeding density), batch effects in single-cell RNA sequencing, and heterogeneity among iPSC lines, all of which complicate cross-study comparisons (Faravelli et al.[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]; Buchner et al. 2023[\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]; Winanto et al. 2019[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]). Third, many organoids exhibit functional immaturity, with underdeveloped electrophysiological properties, limited viability beyond 90 days, and delayed neuronal maturation, making it difficult to model chronic SMA phenotypes effectively (Hor et al. 2018[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]; Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]; Grass et al. 2024[\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]). Fourth, technical barriers such as complex protocols involving CRISPR editing of SMN genes, reliance on Matrigel-based culture systems, and resource-intensive assays like high-density multi-electrode arrays (HD-MEA) and single-cell RNA-seq limit scalability and widespread adoption (Grass et al. 2024[\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]; Corti et al. 2024[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]; Buchner et al. 2023 [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]). Finally, even promising therapeutic interventions, such as SMN1 gene conversion, only achieved partial phenotypic rescue, indicating the presence of unresolved disease modifiers that require further investigation (Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]; Faravelli et al. 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]).\u003c/p\u003e\n\u003cp\u003eIdentifying Gaps and Guiding Future Research in Spinal Muscular Atrophy (SMA) Using Organoid Models\u003c/p\u003e\n\u003cp\u003eOur systematic review synthesized findings from key studies using 3D spinal organoids to model spinal muscular atrophy (SMA). Hor et al. 2018 [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e] found that current organoids lack sensory neurons and non-neuronal cells (e.g., glia), limiting insights into sensory-motor circuits and neuroinflammation. They recommended developing integrated organoids and standardizing functional assays. Faravelli et al. 2022 [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e] noted poor cellular diversity and maturity, urging optimized protocols for vascularization and multi-tissue assembloids. Grass et al. 2024 [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e] highlighted limited representation of SMA heterogeneity and epigenetic uncertainties, calling for multi-tissue assembloids and untagged models.\u003c/p\u003e\n\u003cp\u003eFaravelli et al. 2025 [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e] identified gaps in modeling late-stage disease and systemic interactions, emphasizing extended cultures and CRISPR tools for SMN2 splicing. Corti et al. 2024 [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] revealed that organoids fail to recapitulate functional neuromuscular junctions (NMJs) or chronic pathology, recommending NMJ-integrated models and physiological assessments. Buchner et al. 2023 [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] found inadequate modeling of region-specific vulnerability (e.g., lumbar neurons) and vascularization, suggesting axial patterning and vascular integration. Finally, Winanto et al. 2019 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] observed a lack of sensory-motor circuits and unresolved motor neuron vulnerability, proposing fused organoids and single-cell technologies.\u003c/p\u003e\n\u003cp\u003eCollectively, these studies underscore critical gaps in cellular complexity, disease-stage modeling, and functional validation, while prioritizing recommendations for multi-tissue integration, patient-specific screening, and advanced physiological readouts.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePrior to the advent of 3D spinal organoid models, fundamental questions about the core pathological sequence in Spinal Muscular Atrophy (SMA) remained contentious. Crucially, it was unclear whether motor neuron degeneration stemmed primarily from intrinsic developmental defects occurring during their formation, or from a distinct neurodegenerative process triggered post-maturation. Furthermore, the potential contribution of non-neuronal cells within the spinal cord niche to disease initiation or progression was difficult to dissect. This impasse began to resolve with the adaptation of organoid technology to model the human spinal cord. These 3D self-organizing structures derived from hPSCs provided the first in vitro system capable of recapitulating the complex spatiotemporal dynamics of human spinal cord development and maturation within a multicellular environment. This breakthrough finally enabled direct observation of human motor neuron ontogeny and degeneration, offering a unique lens to address the persistent mechanistic ambiguities that had hindered therapeutic target identification beyond SMN restoration and obscured optimal intervention windows.\u003c/p\u003e\u003cp\u003eThis systematic review represents the first comprehensive synthesis of how three-dimensional spinal organoid models are transforming spinal muscular atrophy research. Collectively, the evidence from Hor et al. 2018 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Faravelli et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and Grass et al. 2024 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] challenges fundamental assumptions about SMA pathology. These studies demonstrate through human-derived systems that SMA is not solely a neurodegenerative condition but involves critical developmental disruptions. Specifically, Hor et al. 2018 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] resolved longstanding controversy by showing motor neurons develop normally but degenerate rapidly after maturation, while Faravelli et al. 2025 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] revealed synaptic dysregulation and electrophysiological hyperactivity precede neuronal loss. Grass et al. 2024 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] further identified neuromesodermal patterning defects, establishing that SMA pathogenesis begins earlier than previously recognized and extends beyond motor neurons.\u003c/p\u003e\u003cp\u003eTherapeutically, work by Corti et al. 2024, 2025 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], D\u0026rsquo;Angelo et al. 2024 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and Hor et al. 2018[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] proves organoids are powerful platforms for translational discovery. Corti et al. 2025[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] demonstrated these models accurately predict patient-specific responses to SMN-restoring therapies like risdiplam, including optimal dosing windows and differential effects across SMA subtypes. D\u0026rsquo;Angelo et al. 2024[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] extended this by showing organoids can forecast individual tolerance to long-term treatments. Hor et al. 2018[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] made the critical discovery that CDK4/6 inhibitors rescue neurons independent of SMN restoration, revealing new therapeutic avenues. However, Grass et al. 2024[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and Faravelli et al. 2025[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] provide sobering evidence that developmental defects persist even after genetic correction, highlighting limitations of current SMN-targeted approaches.\u003c/p\u003e\u003cp\u003eSignificant knowledge gaps remain, as emphasized by Buchner et al. 2023 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and Winanto et al. 2019 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The absence of vascular networks and immune cells in current models limits insights into neuroinflammation and systemic pathology. Missing sensory-motor circuits prevent full exploration of network dysfunction. Yet despite these constraints, the collective findings position organoids as uniquely valuable human-relevant systems that outperform animal models in three key areas: capturing human-specific developmental timelines, revealing non-neuronal contributions to disease as shown by Buchner et al. 2023 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and modeling patient-specific therapeutic responses as demonstrated by D\u0026rsquo;Angelo et al. 2024 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe convergence of evidence confirms organoids are driving a paradigm shift from viewing SMA as a motor neuron-focused degeneration to recognizing it as a dynamic developmental-degenerative disorder requiring combinatorial treatments. These models have already accelerated drug discovery, personalized therapeutic testing, and mechanistic understanding in ways impossible with traditional approaches. While technical limitations remain, the trajectory established by these studies points toward increasingly sophisticated human models that will fundamentally advance SMA therapeutics.\u003c/p\u003e\u003cp\u003eThe primary studies synthesized in this review exhibit recurring limitations that constrain their translational impact. Hor et al. 2018 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] first highlighted the critical absence of sensory neurons and non-neuronal cells (e.g., astrocytes, microglia) in organoids, restricting modeling of neuroinflammation and sensory-motor circuits. This cellular simplification was corroborated by Grass et al. 2024 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], who noted inadequate representation of SMA's systemic pathology (e.g., cardiac/metabolic defects) due to missing multi-tissue interactions. Buchner et al. 2023 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] further emphasized the lack of vascularization and region-specific vulnerability (e.g., lumbar motor neurons), limiting insights into therapy delivery and spatial disease mechanisms.\u003c/p\u003e\u003cp\u003eReproducibility emerged as a major concern: Faravelli et al. 2022, 2025 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and Winanto et al. 2019 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] identified significant batch-to-batch variability from protocol inconsistencies (e.g., morphogen timing, scaffold materials) and iPSC line heterogeneity, complicating cross-study validation. Corti et al. 2024 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], 2025 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] added that resource-intensive functional assays (e.g., HD-MEA electrophysiology) hindered scalability, while Grass et al. 2024 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] observed CRISPR-editing artifacts affecting phenotypic accuracy.\u003c/p\u003e\u003cp\u003eFunctional immaturity universally limited disease modeling: Hor et al. 2018 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and Faravelli et al. 2022 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] reported short organoid viability (\u0026lt;\u0026thinsp;90 days) and immature electrophysiology, precluding chronic SMA stage analysis. Even therapeutic interventions showed partial efficacy: Grass et al. 2024 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found persistent developmental defects post-SMN1 correction, and Faravelli et al. 2025 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] noted incomplete rescue of synaptic dysfunction despite SMN restoration\u0026mdash;suggesting unresolved disease modifiers.\u003c/p\u003e\u003cp\u003eFinally, D\u0026rsquo;Angelo et al. 2024 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and Corti et al. 2025 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] revealed that organoids failed to fully mirror clinical heterogeneity (e.g., Type I vs. III differential responses), underscoring gaps in personalized prediction accuracy.\u003c/p\u003e\u003cp\u003eDespite certain limitations, this review highlights spinal organoids as transformative tools in SMA research, offering unprecedented insights into human-specific disease mechanisms and advancing therapeutic development. As emphasized by the cited studies, continued efforts to enhance biological complexity, improve physiological relevance, standardize protocols, and incorporate patient diversity will be essential to fully realize their potential in delivering urgently needed personalized therapies.\u003c/p\u003e\u003cp\u003eThis systematic review underscores two critical implications for SMA clinical management and research policy. First, clinical practice must prioritize early intervention and personalized treatment selection, as organoid data confirm that therapeutic efficacy diminishes with delayed administration and varies significantly across subtypes. Second, funding bodies and regulators should strategically invest in organoid technology validation and standardization. This includes establishing accredited organoid cores for preclinical drug testing and creating policy frameworks that recognize human organoid data in therapeutic approval pathways\u0026mdash;accelerating translation while reducing reliance on animal models with limited human relevance.\u003c/p\u003e\u003cp\u003eFour key priorities have emerged to advance the field. First, developing multi-tissue assembloids that integrate vascular and immune cells is essential to more accurately model systemic pathology. Second, establishing large-scale iPSC biobanks that capture the full spectrum of SMA heterogeneity (types I\u0026ndash;IV) will facilitate personalized drug screening and therapeutic development. Third, standardizing functional endpoints\u0026mdash;such as neuromuscular junction maturation and electrophysiological biomarkers\u0026mdash;is critical for enabling reliable cross-study comparisons. Fourth, innovating long-term culture systems, including the use of perfusion bioreactors, will allow researchers to study late-stage disease progression in greater detail. To maximize clinical impact, these efforts should be driven by collaborative consortia.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eRegistration and Protocol\u003c/p\u003e\n\u003cp\u003eThis review is registered in PROSPERO. The review protocol is available on the PROSPERO record. No amendments were made to the registered information or protocol.\u003c/p\u003e\n\u003cp\u003eSupport\u003cbr\u003e\u0026nbsp;No financial support was received for this review. Funders or sponsors had no role in the review.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests related to this review.\u003c/p\u003e\n\u003cp\u003eAvailability of Data, Code, and Other Materials:\u003cbr\u003e Data collection forms, extracted data, analysis data, analytic code, and other materials used in this review are available on S3_Appendix.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNishio H, Niba ETE, Saito T, Okamoto K, Takeshima Y, Awano H. Spinal Muscular Atrophy: The Past, Present, and Future of Diagnosis and Treatment. Int J Mol Sci 2023;24. https://doi.org/10.3390/ijms241511939.\u003c/li\u003e\n\u003cli\u003eKeinath MC, Prior DE, Prior TW. Spinal muscular atrophy: Mutations, testing, and clinical relevance. Application of Clinical Genetics 2021;14:11\u0026ndash;25. https://doi.org/10.2147/TACG.S239603.\u003c/li\u003e\n\u003cli\u003eJangi M, Fleet C, Cullen P, Gupta S V., Mekhoubad S, Chiao E, et al. SMN deficiency in severe models of spinal muscular atrophy causes widespread intron retention and DNA damage. Proc Natl Acad Sci U S A 2017;114:E2347\u0026ndash;56. https://doi.org/10.1073/pnas.1613181114.\u003c/li\u003e\n\u003cli\u003eDay JW, Howell K, Place A, Long K, Rossello J, Kertesz N, et al. Advances and limitations for the treatment of spinal muscular atrophy. BMC Pediatr 2022;22. https://doi.org/10.1186/s12887-022-03671-x.\u003c/li\u003e\n\u003cli\u003eChaytow H, Faller KME, Huang YT, Gillingwater TH. Spinal muscular atrophy: From approved therapies to future therapeutic targets for personalized medicine. Cell Rep Med 2021;2. https://doi.org/10.1016/j.xcrm.2021.100346.\u003c/li\u003e\n\u003cli\u003eDuque SI, Arnold WD, Odermatt P, Li X, Porensky PN, Schmelzer L, et al. A large animal model of spinal muscular atrophy and correction of phenotype. Ann Neurol 2015;77:399\u0026ndash;414. https://doi.org/10.1002/ana.24332.\u003c/li\u003e\n\u003cli\u003eHan Y, King M, Tikhomirov E, Barasa P, Souza CDS, Lindh J, et al. Towards 3D Bioprinted Spinal Cord Organoids. Int J Mol Sci 2022;23. https://doi.org/10.3390/ijms23105788.\u003c/li\u003e\n\u003cli\u003eWu W, Liu Y, Liu R, Wang Y, Zhao Y, Li H, et al. Decellularized Brain Extracellular Matrix Hydrogel Aids the Formation of Human Spinal-Cord Organoids Recapitulating the Complex Three-Dimensional Organization. ACS Biomater Sci Eng 2024;10:3203\u0026ndash;17. https://doi.org/10.1021/acsbiomaterials.4c00029.\u003c/li\u003e\n\u003cli\u003eChooi WH, Ng CY, Ow V, Harley J, Ng W, Hor J, et al. Defined Alginate Hydrogels Support Spinal Cord Organoid Derivation, Maturation, and Modeling of Spinal Cord Diseases. Adv Healthc Mater 2023;12. https://doi.org/10.1002/adhm.202202342.\u003c/li\u003e\n\u003cli\u003eHor JH, Soh ESY, Tan LY, Lim VJW, Santosa MM, Winanto, et al. Cell cycle inhibitors protect motor neurons in an organoid model of Spinal Muscular Atrophy. Cell Death Dis 2018;9. https://doi.org/10.1038/s41419-018-1081-0.\u003c/li\u003e\n\u003cli\u003eUNIVERSIT\u0026Aacute; DEGLI STUDI DI MILANO. n.d.\u003c/li\u003e\n\u003cli\u003eFaravelli I, Rinchetti P, Tambalo M, Simutin I, Mapelli L, Mancinelli S, et al. Targeted Antisense Oligonucleotide Treatment Rescues Developmental Alterations in Spinal Muscular Atrophy Organoids 2025. https://doi.org/10.1101/2025.01.17.633436.\u003c/li\u003e\n\u003cli\u003eGrass T, Dokuzluoglu Z, Buchner F, Rosignol I, Thomas J, Caldarelli A, et al. Isogenic patient-derived organoids reveal early neurodevelopmental defects in spinal muscular atrophy initiation. 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Neurology 2024;102. https://doi.org/10.1212/WNL.0000000000205358.\u003c/li\u003e\n\u003cli\u003eBuchner F, Dokuzluoglu Z, Grass T, Rodriguez-Muela N. Spinal Cord Organoids to Study Motor Neuron Development and Disease. Life 2023;13. https://doi.org/10.3390/life13061254.\u003c/li\u003e\n\u003cli\u003eCorti S, D\u0026rsquo;Angelo A, Beatrice F, Ongaro J, Rinchetti P, Faravelli I, et al. 149VP 3D stem cell-derived spinal cord/muscle organoid model for studying and treating neuromuscular diseases. Neuromuscular Disorders 2024;43:104441.584. https://doi.org/10.1016/j.nmd.2024.07.593.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"organoids, spinal organoids, SMA, spinal myotropic atrophy, 3D model, treatment","lastPublishedDoi":"10.21203/rs.3.rs-7162669/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7162669/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction\u003c/p\u003e\u003cp\u003eSpinal Muscular Atrophy (SMA) is a fatal neurodegenerative disorder with limited therapies and incomplete mechanistic understanding. Emerging 3D spinal cord organoids derived from human pluripotent stem cells offer physiologically relevant models, enabling improved disease modeling and therapeutic exploration. This review highlights their potential in addressing critical gaps in SMA research.\u003c/p\u003e\u003cp\u003eMethods\u003c/p\u003e\u003cp\u003eThis review systematically evaluates 3D spinal cord organoid studies modeling SMA, using strict PICO-based criteria, comprehensive database searches, and SYRCLE bias assessment to extract mechanistic, therapeutic, and methodological insights.\u003c/p\u003e\u003cp\u003eResult\u003c/p\u003e\u003cp\u003eWe included 9 studies using 3D spinal organoids derived from human iPSCs to model SMA. Organoids effectively recapitulated motor neuron degeneration, developmental defects, and glial contributions. They enabled therapeutic testing (e.g., risdiplam, antisense oligonucleotides), but faced limitations in maturity, reproducibility, and cellular diversity. Despite these challenges, organoids surpassed traditional models, offering mechanistic insights and translational promise. Key research gaps include modeling chronic disease, integrating sensory-motor circuits, and improving vascularization.\u003c/p\u003e\u003cp\u003eDiscussion\u003c/p\u003e\u003cp\u003eSMA organoids enable patient-specific drug testing and uncover novel mechanisms, but face limitations in vascularization, maturity, and heterogeneity. Despite challenges, they surpass traditional models and drive a shift toward multifaceted SMA therapeutics. However, a standardized protocol is necessary to improve reproducibility, minimize batch variability, and enable reliable cross-study comparisons in SMA organoid research\u0026mdash;ultimately enhancing their translational utility in drug discovery and personalized medicine.\u003c/p\u003e","manuscriptTitle":"A systematic review of advances in the knowledge and therapeutics of spinal myotropic atrophy from three-dimensional stem cell derived spinal organoid model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 08:44:02","doi":"10.21203/rs.3.rs-7162669/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2b84dcb-768c-4527-a212-e5b760566139","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-06T22:53:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 08:44:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7162669","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7162669","identity":"rs-7162669","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}