1. Neuroscience
  2. Stem Cells and Regenerative Medicine

Patient-specific midbrain organoids with CRISPR correction recapitulate neuronopathic Gaucher disease phenotypes and enable evaluation of novel therapies

  1. Yi Lin
  2. Benjamin Liou
  3. Venette Fannin
  4. Stuart Adler
  5. Christopher N Mayhew
  6. Jason E Hammonds
  7. Yueh-Chiang Hu
  8. Jason Tchieu
  9. Wujuan Zhang
  10. Xueheng Zhao
  11. Rebecca L Beres
  12. Kenneth DR Setchell
  13. Ahmet Kaynak
  14. Xiaoyang Qi
  15. Ricardo A Feldman
  16. Ying Sun  Is a corresponding author
  1. Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, United States
  2. Department of Pediatrics, University of Cincinnati College of Medicine, United States
  3. Pluripotent Stem Cell Facility and Developmental Biology, Cincinnati Children’s Hospital Medical Center, United States
  4. Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, United States
  5. Transgenic Animal and Genome Editing Facility, Cincinnati Children’s Hospital Medical Center, United States
  6. Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, United States
  7. Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital Medical Center, United States
  8. Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati, College of Medicine, United States
  9. Department of Microbiology and Immunology, University of Maryland School of Medicine, United States
https://doi.org/10.7554/eLife.109518.3
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Cite this article
  1. Yi Lin
  2. Benjamin Liou
  3. Venette Fannin
  4. Stuart Adler
  5. Christopher N Mayhew
  6. Jason E Hammonds
  7. Yueh-Chiang Hu
  8. Jason Tchieu
  9. Wujuan Zhang
  10. Xueheng Zhao
  11. Rebecca L Beres
  12. Kenneth DR Setchell
  13. Ahmet Kaynak
  14. Xiaoyang Qi
  15. Ricardo A Feldman
  16. Ying Sun
(2026)
Patient-specific midbrain organoids with CRISPR correction recapitulate neuronopathic Gaucher disease phenotypes and enable evaluation of novel therapies
eLife 15:RP109518.
https://doi.org/10.7554/eLife.109518.3
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eLife Assessment

This study provides potentially important insights by establishing a human disease model and exploring therapeutic approaches. The evidence is generally convincing for descriptive and comparative findings. The authors present solid data, but evidence for proposed biological mechanisms and functional outcomes remains limited.

https://doi.org/10.7554/eLife.109518.3.sa0

Abstract

Neuronopathic Gaucher disease (nGD) is a lysosomal storage disorder caused by GBA1 mutations, leading to defective acid β-glucosidase (GCase) and accumulation of glycosphingolipid substrates, causing inflammation and neurodegeneration. Patients with nGD manifest severe neurological symptoms, but current animal models fail to fully recapitulate the human condition, posing a major barrier to the development of effective therapies targeting the brain. To bridge this gap, we have developed midbrain-like organoids (MLOs) from human induced pluripotent stem cells of nGD patients with GBA1L444P/P415R and GBA1L444P/RecNcil mutations to model nGD brain pathogenesis. These nGD MLOs exhibited GCase deficiency, resulting in diminished enzymatic function, accumulation of lipid substrates, widespread transcriptomic changes, and impaired dopaminergic neuron differentiation, mirroring nGD pathology. GBA1 mutation correction mediated by CRISPR/Cas9 restored GCase activity, normalized lipid substrate levels, and rescued dopaminergic neuron function, confirming the causal role of GBA1 mutations during early brain development. Using this novel platform, we further evaluated therapeutic strategies, including SapC-DOPS nanovesicles delivering GCase, AAV9-GBA1 gene therapy, and substrate reduction therapy with GZ452, a glucosylceramide synthase inhibitor currently under clinical investigation. These treatments either restored GCase activity, reduced lipid substrate accumulation, improved autophagic and lysosomal abnormalities, or ameliorated dysregulated genes involved in neural development. These patient-specific, 3D neural models offer a transformative, physiologically relevant platform for unraveling disease mechanisms and accelerating the discovery of therapies for patients with nGD.

Introduction

Gaucher disease (GD) is a lysosomal storage disorder caused by GBA1 mutations, which impair acid β-glucosidase (GCase). Defective GCase leads to accumulation of its glycosphingolipid substrates, glucosylceramide (GluCer) and glucosylsphingosine (GluSph), triggering inflammation and neurodegeneration. GD affects 1/450 in Ashkenazi individuals and 1/50,000 globally (Grabowski et al., 2010). There are three GD types: Type 1 presents mainly visceral symptoms and is not life-threatening (Grabowski et al., 2010), while neuronopathic GD (nGD, Types 2 and 3) involves severe neurological manifestations. Type 2 patients typically die by age 2, indicating early central nervous system (CNS) defects (Mignot et al., 2003; Reissner et al., 1998).

Current knowledge of brain pathogenesis in nGD is limited to a few postmortem brain analyses showing prominent neuronal loss and astrogliosis in the midbrain (Burrow et al., 2015; Wong et al., 2004; Conradi et al., 1984). GD mouse models, including GCase knockout, irreversible GCase inhibitor conduritol B-epoxide (CBE) induced mouse models, double transgenic mutant model harboring both Gba1 and Saposin C mutations (Saposin C is the activator of GCase), have been widely used to study disease pathogenesis and therapies (Enquist et al., 2007; Vardi et al., 2016; Xu et al., 2008; Xu et al., 2003; Sun et al., 2010; Qi et al., 1994). These models replicate neuronal loss and astrogliosis (Burrow et al., 2015; Wong et al., 2004; Conradi et al., 1984; Vardi et al., 2016; Dasgupta et al., 2015), but have limitations. The knockout and CBE-induced models lack GBA1 mutations, and the double transgenic model has a second gene that may change the GD phenotype, and knock-in models fail to mimic human phenotypes (Xu et al., 2003; Liu et al., 1998). For example, mice with the Gba1L444P/L444P or Gba1D409H/D409H mutations show no neuronopathic disease despite <10% of residual GCase activity (Xu et al., 2003; Liu et al., 1998; Pasmanik-Chor et al., 1996; Grabowski et al., 2015). These constraints highlight the need for physiologically relevant human nGD models.

Brain organoids derived from human induced pluripotent stem cells (hiPSC) emerged as a powerful 3D model to study brain development and CNS diseases (Birtele et al., 2025). Unlike 2D monolayer neural cells, brain organoids contain diverse neural and glial cell types arranged in 3D comprising subventricular zone and multiple organized cellular layers that more closely represent the spatial architecture of the human brain (Di Lullo and Kriegstein, 2017). They have been used to study neurodegenerative and lysosomal diseases, including Parkinson’s disease (PD), Alzheimer’s disease, and Sandhoff disease (Raja et al., 2016; Lancaster et al., 2013; Smits et al., 2019; Allende et al., 2018; Latour et al., 2019). A brain organoid derived from hiPSCs of a healthy individual with GBA1 knockout and α-synuclein overexpression exhibited characteristic PD markers (Jo et al., 2021). However, this model lacks patient-specific GBA1 mutations needed for clinical relevance. To develop a relevant model, we developed novel midbrain organoids from nGD patients with GBA1 mutations, a model not yet well studied.

The midbrain region is prominently affected in nGD (Burrow et al., 2015; Wong et al., 2004; Conradi et al., 1984). Patients with nGD often exhibit impaired vertical gaze and movement disorders. These symptoms correlate with midbrain involvement due to the sensitivity of this region to neuroinflammatory and degenerative processes (Burrow et al., 2015; Goker-Alpan and Ivanova, 2024). Both human and mouse studies indicate that the midbrain shows prominent substrate accumulation compared with other brain regions, suggesting it is particularly susceptible to pathological burden in GD midbrain (Burrow et al., 2015; Farfel-Becker et al., 2014; Jones et al., 2017; Xu et al., 2014). To model the midbrain-specific disease, we derived midbrain-like organoids (MLOs) from Type 2 patient-derived hiPSCs carrying either GBA1L444P/P415R or GBA1L444P/RecNcil mutations. These GD MLOs showed reduced GCase activity, lipid substrate accumulation, transcriptomic alterations, and impaired dopaminergic neuron differentiation. CRISPR/Cas9-mediated correction of GBA1 mutation confirmed the causal role of GBA1 mutations in these phenotypes and mitigated disease phenotypes. To explore therapeutic potential, we tested three emerging treatments in GD MLOs: CNS accessible enzyme therapy (SapC-DOPS-GCase), gene therapy (AAV9-GBA1), and substrate reduction therapy (SRT; GZ452). Our results demonstrate the utility of patient-derived MLOs for studying nGD pathogenesis and advance drug development.

Results

Generation and characterization of MLOs derived from hiPSCs

To generate MLOs from iPSCs, healthy hiPSCs were differentiated following a stepwise protocol, neural induction, neuroepithelial expansion, and maturation, adopted with modifications from previous studies (Jo et al., 2016; Kwak et al., 2020; Figure 1A). Midbrain specification during development requires appropriate posterior differentiation signals (Prakash and Wurst, 2006; Green et al., 2015). Our protocol used sequential activation/inhibition of critical signaling pathways involved in midbrain specification: Wnt signaling (activated by CHIR99021), BMP signaling (inhibited by dual-SMAD), and FGF signaling (activated by FGF8) (Figure 1A). MLOs were matured and characterized using immunofluorescence, gene expression, and immunoblotting. Week 8 MLOs showed diverse neural cell types, including pan-neurons (Tuj1/NeuN), astrocytes (GFAP), dopaminergic (DA) neurons (FOXA2/TH), and neural progenitor cells (SOX2/Ki67) (Figure 1B). Comparative analysis of forebrain marker FOXG1 expression between MLOs and cerebral organoids (COs) showed barely detectable FOXG1 in MLOs (Figure 1C). Quantitative RT-PCR analysis demonstrated a significant increase in midbrain/DA neuron-specific genes (FOXA2, ASCL1, LMX1A, PLZF, and TH) from week 3 and 8 MLOs, demonstrating the midbrain identity of these organoids. Expression of glial-specific genes (GLAST, S100B) increased over time, while pluripotency markers (SOX2, NANOG, OCT4) were downregulated, suggesting progressive neural differentiation (Figure 1D). Immunoblot further validated hiPSCs differentiation into MLOs by enhanced expression of neuronal (Tuj1, MAP2), DA neuronal (TH), and glial (GFAP, S100B) markers at week 8, with reduced Sox2 expression in MLOs versus hiPSCs (Figure 1E). Together, these results confirm the successful generation of MLOs with midbrain-like cellular composition and molecular identities.

Figure 1
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Generation and characterization of midbrain-like organoids (MLOs) from healthy human (h) iPSCs (WT-75.1 hiPSCs).

(A) A schematic overview of the procedures for generating MLOs from healthy WT-75.1 hiPSCs. (B) Representative confocal images showing architectural structure of week (Wk) 8 MLOs containing new-born neurons (Tuj1/NeuN), astrocytes (GFAP), dopaminergic neurons (FOXA2/TH), and neural progenitor cells (SOX2/Ki67). Merge images show the distribution of those cell markers. (C) FOXG1 expression in MLO and cerebral organoid (CO). Transcription factor FOXG1 (forebrain marker) was enriched in CO at Wk8 of differentiation but absent in MLO. Pan-neurons (NeuN) were both present in MLO and CO, as shown by NeuN immunostaining (neuronal marker). (D) Quantitative analysis of cell type specific genes expression for midbrain/dopaminergic neuron (FOXA2/ASCL1/LXM1A/PLZF/TH), glial cells (GLAST/S100B), and multipotent stem cells (SOX2/NANOG/OCT4) in Wk3 and Wk8 MLOs by qRT-PCR. Data are presented as mean ± SEM (n = 3 MLOs pooled for each group). (E) Immunoblot of Sox2, Tuj1, MAP2, TH, GFAP, and S100B in WT-75.1 hiPSCs and its derived MLO (Wk8, n = 3 MLOs pooled for each group) lysate. β-Actin was used as a loading control.

Figure 1—source data 1

Original files for western blot analysis are shown in Figure 1E.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig1-data1-v1.zip
Figure 1—source data 2

PDF file containing original western blots Figure 1E, including the relevant bands and sample conditions.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig1-data2-v1.zip

GCase deficiency in GD MLOs leads to glycosphingolipid accumulation and altered transcriptomic profiling

To model nGD and investigate the impact of GCase deficiency on MLOs, we generated GD MLO using the GD2-1260 hiPSC line derived from a GD Type 2 patient harboring GBA1L444P/P415R, compound heterozygous mutations, using the same protocol in Figures 1 and 2, Sun et al., 2015. Midbrain identity of GD MLOs was confirmed by TH/FOXA2 expression (Figure 3). Immunoblot showed an approximately 92.5% reduction in GCase protein levels in week 8 GD2-1260 MLOs versus WT-75.1 MLOs (Figure 2A). Consistent with reduced GCase protein, GCase activity decreased to 14.2% in GD2-1260 hiPSCs and 15.0% in GD2-1260 MLOs versus WT-75.1 (p < 0.001; Figure 2B). Bright-field imaging at weeks 4, 8, and 15 showed no difference in overall MLOs appearance between WT-75.1 and GD2-1260 MLOs (Figure 2C). MLO size measurements revealed a trend toward smaller GD2-1260 MLOs versus WT-75.1 at week 8, though not statistically significant (Figure 2D).

Figure 2 with 1 supplement see all
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GCase deficiency drives glycosphingolipid accumulation and transcriptomic alteration in GD MLOs.

The GD MLOs were generated as in Figure 1A. (A) Reduced GCase protein in GD MLO (GD2-1260). Wk8 MLOs (n = 3) were pooled as a biological sample. GAPDH was used as a loading control. (B) GCase activity in hiPSCs and MLOs (>3 MLOs were pooled for each group). Data were normalized to WT-75.1 control. (C) Representative images of WT-75.1 and GD2-1260 MLOs at Wks 4, 8, and 15 of differentiation. (D) MLO size was measured based on the area of MLO spheres and normalized to WT-75.1 control at each indicated time point. N ≥ 10 MLOs were quantified per group. (E, F) Measurement of total glucosylceramide (GluCer) and GluCer species in Wk15 MLO. (A, B, D, E–G) Data are presented as mean ± SEM. *p < 0.05, ***p < 0.001, ns, not significant, unpaired Student’s t-test. (G) Glucosylsphingosine (GluSph) levels in Wk15 and Wk28 MLOs (3~5 MLOs were pooled for each group). GluCer and GluSph levels in the organoids were measured by LC–MS/MS and normalized by corresponding total protein of MLO tissue lysate. (H) 3D principal component analysis (PCA) of bulk RNA sequencing (RNA-seq) data. The Euclidean distance of the normalized gene expression among healthy control (WT-75.1) and GD (GD2-1260) MLOs was used for sample clustering. Ellipsoids around each group indicate the distribution and spread of the samples within the sample group. Wk8 MLOs (n = 3) were pooled as one biological sample, and three samples were profiled in each group. (I) MA plot showing the distinct genes differentially expressed in GD MLOs. Statistically significant differentially expressed genes (DEGs; |fold change| ≥1, p-adj ≤0.05 and base mean ≥50) were highlighted in red. The number of DEGs downregulated and upregulated in GD2-1260 MLO against WT-75.1 MLO was shown. FC, fold change. Dysregulated pathways in GD MLOs analyzed by GO (gene ontology) (J) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (K) enrichment of DEGs. Both gene counts and level of significance (−log10 of p-value) were shown as stacked columns for each category. (L–O) Heatmaps of dysregulated pathways or biological functions in GD MLO. Specifically, aberrant expressions of genes involved in WNT signaling (L), anterior-posterior brain specification (M), neuronal function (N), and lysosome–phagosome (O) were shown.

Figure 2—source data 1

Original files for western blot analysis are shown in Figure 2A.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig2-data1-v1.zip
Figure 2—source data 2

PDF file containing original western blots Figure 2A, including the relevant bands and MLO sample names.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig2-data2-v1.zip
Figure 3
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Skewed specification of midbrain patterning and dopaminergic neuron differentiation in GD MLOs.

(A) Gene expression of FOXP1, FOXG1, and PAX6 in week 8 WT-75.1 and GD2-1260 MLOs. Data were plotted using RNA sequencing counts. ***p < 0.001, unpaired Student’s t-test. (B, C) Aberrant expression of FOXP1/FOXG1 transcription machinery for forebrain/midbrain patterning in GD MLOs. Representative confocal images (B) and quantification of Wk8 WT-75.1 and GD2-1260 MLOs, immunostained for FOXP1 (red) and FOXG1 (green), with DAPI (blue) labeling nuclei. Yellow arrows indicate FOXP1+FOXG1+ cells. Scale bar, 50 µm. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, unpaired Student’s t-test. (D) Confocal images of Wk6 MLOs, immunostained for midbrain patterning markers FOXA2 (green) or TH (red), with DAPI (blue) labeling nuclei. Scale bar, 200 µm. (E) Representative images of differentiating DA neurons in MLOs derived from WT-75.1 and GD2-1260 hiPSCs. TH (red), FOXA2 (green) were co-stained, with DAPI (blue) labeling nuclei. Yellow arrows indicate TH+FOXA2+ cells. Scale bar, 50 µm. (F) Quantification of midbrain progenitor markers ASCL1, TH, LMX1A, and PLZF expression in WT-75.1 and GD2-1260 MLOs at Wk3 and Wk8, measured by qRT-PCR and normalized to WT-75.1 hiPSC cells. Data are presented as mean ± SEM (n = 3–4 MLOs per group). *p < 0.05, **p < 0.01. (G) Immunoblot analysis of midbrain/dopaminergic neuron markers TH, FOXA2, and MAP2 in Wk16 MLOs. Protein samples were extracted from n = 3 MLOs from each group. β-Actin was used as a loading control. (H) Relative protein levels of TH, FOXA2, and MAP2 in Wk8 GD2-1260 MLOs compared to WT-75.1. Data are presented as mean ± SEM (n = 4 per group). *p < 0.05, **p < 0.01, unpaired Student’s t-test. (I) Dopamine levels in MLO culture medium assay by ELISA. Culture medium from four GD2-1260 MLOs or WT-75.1 MLOs at Wk12 cultured in 3 ml BGM medium for 72 hr was assayed. Data are presented as mean ± SEM (n = 5 per group). ***p < 0.001, unpaired Student’s t-test.

Figure 3—source data 1

Original files for western blot analysis are shown in Figure 3G.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig3-data1-v1.zip
Figure 3—source data 2

PDF file containing original western blots Figure 3G, including the relevant bands and MLO sample names.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig3-data2-v1.zip

Loss of GCase function in GD disrupts glycosphingolipid metabolism, a primary pathogenic factor in nGD (Ryckman et al., 2020). Mass spectrometry analysis demonstrated significant glycosphingolipid substrate accumulation in GD2-1260 MLOs. At week 15, total glucosylceramide (GluCer) level was elevated approximately 1.39-fold in GD2-1260 MLOs compared to WT-75.1 MLOs (p < 0.05; Figure 2E). GluCer analysis revealed marked accumulation of species 18:0 and 16:0, particularly brain predominant species (18:0) in GD2-1260 MLOs, while other species remained largely unchanged (Figure 2F, Figure 2—figure supplement 1). Similarly, glucosylsphingosine (GluSph), a toxic lipid associated with nGD (Burrow et al., 2015; Srikanth et al., 2021; Marshall et al., 2016), was significantly elevated approximately 3.3- and 5.6-fold in GD2-1260 MLOs at weeks 15 and 28, respectively, versus WT-75.1 controls (Figure 2G, Figure 2—figure supplement 1). These findings indicate profound lipid substrates dysregulation in GCase-deficient GD MLOs, consistent with the biochemical hallmark of GD.

To explore the transcriptomic consequences of GCase deficiency, we performed bulk RNA sequencing on week 8 MLOs, when DA neurons maturation and GD phenotypes were evident. Principal component analysis revealed distinct clustering of WT-75.1 and GD2-1260 MLOs, with the first principal component accounting for 53% of the variance, indicating significant transcriptomic differences between two genotype groups (Figure 2H). An MA plot identified 1429 differentially expressed genes (DEGs) in GD2-1260 MLOs compared to WT-75.1, with 664 genes upregulated and 765 genes downregulated. GO analysis of these DEGs revealed significant enrichment in pathways including cAMP, PI3K–AKT, and WNT signaling that control the nervous system development, axon guidance, and neuron differentiation (Figure 2J). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis similarly identified dysregulation in neural signaling pathways, synaptic transmission, and lysosomal function (Figure 2K). The heatmap of these DEGs elucidated specific gene expression changes within key pathways (Figure 2L–O), including WNT signaling (Figure 2L; Awad et al., 2017), anterior–posterior brain specification (Figure 2M), neuronal function (Figure 2N), and lysosome–phagosome (Figure 2O) in GD2-1260 MLOs, with many genes exhibiting upregulation or downregulation consistent with nGD pathology.

Collectively, these results demonstrate that GBA1 mutation in GD MLOs leads to reduced enzyme activity, causes lipid substrate accumulation, and alters transcriptomic profiles, particularly in neural development, signaling, and lysosomal function. These findings provide insights into nGD mechanism and support MLOs as a model for studying nGD.

Skewed specification of midbrain patterning and dopaminergic neuron differentiation in GD MLOs

Building on the molecular and transcriptomic hallmarks of GCase deficiency observed in nGD MLOs (Figure 2), we next investigated the impact on midbrain patterning and dopaminergic neuron differentiation (Figure 3). Firstly, RNA sequencing data revealed elevated FOXG1 and PAX6, and reduced FOXP1 mRNAs in GD2-1260 MLOs versus WT-75.1 MLOs at week 8 (Figures 2M and 3A). These genes are fate-determining regulators in controlling proper anterior–posterior neural patterning (Mato-Blanco et al., 2025; Ba et al., 2023; Ortiz et al., 2025). Immunofluorescence confirmed reduced FOXP1+ and increased FOXG1+ cell counts in GD2-1260 MLOs (Figure 3B, C). About 11.6% cells were FOXP1+FOXG1+ cells in GD2-1260 MLOs, but they were barely seen in WT-75.1 MLOs. These results indicate a significant disruption in the expression of genes involved in forebrain and midbrain patterning in GD MLOs.

The skewed specification of midbrain patterning may contribute to dysregulated dopaminergic neuron development in GCase-deficient GD MLOs (Figure 3). There were clear differences in the expression of midbrain-specific markers between WT-75.1 and GD2-1260 organoids at week 6 (Figure 3D). In WT-75.1 MLOs, FOXA2 (a midbrain progenitor marker) and TH (dopaminergic neuron marker) were strongly expressed and co-localized (Figure 3D, E), indicating normal midbrain patterning. In contrast, GD2-1260 MLOs showed markedly reduced FOXA2+, TH+, and FOXA2+TH+ cells (Figure 3D, E). Quantitative analysis confirmed the significant reduction of midbrain progenitor markers (ASCL1, TH, FOXA2, and PLZF) in GD2-1260 MLOs versus WT-75.1 (Figure 3F). At week 8, expression levels of ASCL1, TH, FOXA2, and PLZF were significantly reduced by approximately 71.0%, 44.4%, 90.0%, and 69.8%, respectively, indicating a profound impairment in midbrain progenitor specification due to GCase deficiency. Immunoblot showed ~77.5% and~66.5% reductions in TH and FOXA2, respectively, and a 27.7% increase in MAP2 in GD2-1260 versus WT-75.1 MLOs (Figure 3H). Dopaminergic function was determined by measuring dopamine levels in the culture medium (Figure 3I). Dopamine levels in week 12 MLOs culture medium (72 hr culture) were 76.0% (p < 0.001) lower in GD2-1260 MLOs versus WT-75.1 MLOs, confirming impaired dopaminergic function in GD MLOs.

These results indicate that GCase deficiency leads to skewed midbrain patterning and dopaminergic neuron differentiation, underscoring the critical role of GCase in midbrain development, as revealed for the first time, using patient iPSC-derived brain organoids.

CRISPR/Cas9-mediated GBA1 mutation correction rescues disease phenotypes in GD MLOs

GD is an autosomal recessive disorder. Individuals who are carriers or heterozygous for GBA1 mutations typically do not exhibit disease phenotypes (Grabowski et al., 2010). To determine whether correction of the GBA1 mutation could rescue GD phenotypes in GD MLOs, we used CRISPR/Cas9 technology to correct the L444P mutation in GD2-1260 hiPSCs (GBA1L444P/P415R) and generated isogenic iso-GD2-1260 hiPSCs with a heterozygous genotype of GBA1WT/P415R (Figure 4A; Figure 4—figure supplement 1). Karyotype analysis of GD2-1260 and iso-GD2-1260 demonstrated no detectable chromosomal abnormalities, confirming the genetic stability of both cell lines (Figure 4—figure supplement 1D). Furthermore, genetic correction did not alter the expression of hiPSC-related pluripotent genes (Figure 4—figure supplement 1E). The MLOs derived from WT-75.1, GD2-1260, and iso-GD2-1260 hiPSCs were then compared to evaluate the impact of mutation correction on GD phenotypes.

Figure 4 with 2 supplements see all
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Mutation correction significantly rescued disease phenotypes in GD MLOs.

(A) Schematic overview of CRISPR/Cas9-mediated mutation correction of the GBA1 L444P mutation in GD2-1260 hiPSCs, converting the L444P (L444P/P415R) mutation (Proline, P to Leucine, L) to the wild-type sequence (WT-P415R), generating isogenic iso-GD2-1260 hiPSCs. The mutated base C in amino acid code ‘CCG’ for proline (P) was corrected to T to decode leucine (L, CTG), which was confirmed by genome sequencing of GBA1 locus. (B, C) Immunoblot analysis of GCase protein and quantification in week 16 MLOs derived from WT-75.1, GD2-1260, and iso-GD2-1260 hiPSCs. β-Actin was used as a loading control. Data are presented as mean ± SEM (n = 2 pooled, and 3 biological replicates per group). ***p < 0.001, unpaired Student’s t-test. (D) Relative GCase activity in GD2-1260 and iso-GD2-1260 hiPSCs and Wk8 MLOs, normalized to WT-75.1 controls. Data are presented as mean ± SEM (2 MLOs pooled, n = 3 per group). ***p < 0.001, unpaired Student’s t-test. (E) Measurement of GluSph levels in WT-75.1, GD2-1260, and iso-GD2-1260 MLOs at Wk15 and Wk28 and their culture medium at Wk15, quantified by LC–MS/MS and normalized to total protein of tissue lysate. Data are presented as mean ± SEM. For GluSph in MLO, three MLOs were pooled and n = 3 per group. For MLO secreted GluSph, MLO culture medium in wells containing four MLOs were collected, n = 3 per group. **p < 0.01; ns, not significant. One-way ANOVA test. (F) Representative bright-field images of WT-75.1, GD2-1260, and iso-GD2-1260 MLOs at day 2, Wks 4, 8, and 15 of differentiation. Scale bar, 1 mm. For side-by-side comparison, images for WT-75.1 and GD2-1260 at Wks 4, 8, and 15 were taken from Figure 2C. (G) MLO size quantification for WT-75.1, GD2-1260, and iso-GD2-1260 MLOs at Wks 4, 8, and 15. MLOs size was analyzed by NIS elements and presented as the area (µm2) of MLO at indicated time point. N ≥ 10 MLOs were quantified per group. Data are presented as mean ± SEM. One-way ANOVA. ns, not significant. Immunoblot analysis of midbrain/dopaminergic neuron markers TH and FOXA2 (H) and their relative quantification (I) in Wk8 MLOs. Protein samples were extracted from n = 3 MLOs from each group. GAPDH was used as a loading control. Data are presented as mean ± SEM. One-way ANOVA test with Tukey’s test; *p < 0.05, ***p < 0.001. (J) Dopamine levels in the culture medium of Wk12 MLOs derived from WT-75.1, GD2-1260, and iso-GD2-1260 hiPSCs, measured after 72 hr in BGM medium (n = 4 MLOs per samples, 3 biological replicates). Data are presented as mean ± SEM (n = 5 per group). One-way ANOVA test with Tukey’s test; *p < 0.05, ***p < 0.001. (K, L) Immunoblot analysis of autophagy–lysosomal pathway markers LAMP1 and Cathepsin D (K) and quantification (L) in Wk16 MLOs. GAPDH was used as a loading control. Data are presented as mean ± SEM. One-way ANOVA test with Tukey’s test; *p < 0.05, ***p < 0.001, ns, not significant. Immunoblot analysis of LC3-I and LC3-II (M) and quantification (N) in Wk16 MLOs. Protein samples were extracted from n = 3 MLOs for each group. GAPDH was used as a loading control. Data are presented as mean ± SEM. One-way ANOVA test with Tukey’s test; **p < 0.01, ***p < 0.001; ns, not significant. (O) Immunoblot analysis of mTOR signaling pathway components [4E-BP1, P-4E-BP1(THR37/46), S6, and P-S6 (Ser235/236)] in Wk16 MLOs. β-Actin was used as a loading control. (P) Quantification of protein levels of mTOR signaling pathway components. Data are normalized to WT-75.1 and presented as mean ± SEM. Immunoblot analysis for panels H and I and K–P was performed using the lysate from 3 MLOs pooled per group, 3 repeated experiments. One-way ANOVA test with Tukey’s test. ***p < 0.001; ns, not significant.

Figure 4—source data 1

Original files for western blot analysis are shown in Figure 4B, H, K, M, O.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig4-data1-v1.zip
Figure 4—source data 2

PDF file containing original western blots Figure 4B, H, K, M, O, including the relevant bands for immunoblotted targets and MLO samples.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig4-data2-v1.zip

At week 16, GCase protein in iso-GD2-1260 MLOs was restored to 45.8% of WT-75.1 levels (Figure 4B, C), consistent with correction of one GBA1 allele (Sun et al., 2015). GCase activity also improved, reaching 43.9% and 46.4% of WT-75.1 levels in GD2-1260 hiPSCs and MLOs, respectively, versus approximately 15% in GD2-1260 hiPSCs and MLOs (Figure 4D). Despite reduced GCase, early neural rosette formation in GD2-1260 MLOs remained largely unaffected in GD2-1260 and iso-GD2-1260, with similar counts of SOX2+Ki67+ proliferating neural progenitor cells in neural rosettes (Figure 4—figure supplement 2), suggesting early neural development is not impacted by GBA1 L444P mutation.

GBA1 L444P mutation correction ameliorated lipid substrate accumulation in iso-GD2-1260 MLOs. GluSph levels, which were elevated in GD2-1260 MLOs at weeks 15 and 28 (approximately 3.3- and 5.6-fold higher than WT-75.1, respectively; p < 0.01), were normalized to WT-75.1 levels (Figure 4E). Organoid size of iso-GD2-1260 MLOs was similar to WT-75.1 and GD2-1260 MLOs at weeks 4, 8, and 15 (Figure 4F, G).

Correction of the L444P mutation restored midbrain and dopaminergic neuron differentiation. TH and FOXA2 levels, which were reduced in week 16 GD2-1260 MLOs by approximately 76.4% and 72.4%, respectively, were restored in iso-GD2-1260 MLOs to WT-75.1 levels for TH, and approximately 53% of WT-75.1 levels for FOXA2 (Figure 4H, I). Dopamine levels in iso-GD2-1260 MLOs culture matched those in WT-75.1, unlike the reduced levels in GD2-1260 MLOs (Figure 4J), indicating restored dopaminergic function. The autophagy–lysosomal pathway, which is dysregulated in nGD, was partially corrected by GBA1 mutation restoration (Figure 4K, L). Immunoblot analysis of lysosomal proteins showed that LAMP1 levels, which were significantly decreased in GD2-1260 MLOs by approximately 42.5% versus WT-75.1, were partially restored in iso-GD2-1260 MLOs (Figure 4K, L); however, Cathepsin D levels remained unchanged (Figure 4K, L). Dysregulated autophagy flux demonstrated by the elevated LC3-II and LC3-I was not significantly improved in isogenic MLOs compared to GD2-1260 MLOs (Figure 4M, N).

GCase deficiency leads to mTOR hyperactivation in nGD (Dasgupta et al., 2015; Peng et al., 2023; Brown et al., 2019). In GD2-1260 MLOs, levels of 4E-BP1 and its phosphorylated form P-4E-BP1 (Thr37/46) were significantly elevated (Figure 4O). These levels were normalized or significantly reduced in iso-GD2-1260 MLOs. While S6 and its phosphorylated form (P-Ser235/236) remain unchanged (Figure 4O, P).

These results demonstrate that CRISPR/Cas9-mediated correction of GBA1 mutation in GD2-1260 hiPSCs effectively rescues key nGD phenotypes and downstream effects, highlighting gene correction as a therapeutic strategy and validating MLOs as a preclinical disease model.

SapC-DOPS nanoparticle-mediated GCase enzyme therapy corrects GD phenotypes in GD MLOs

SapC-DOPS nanoparticles, composed of saposin C (SapC) and dioleoylphosphatidylserine (DOPS), showed promise as a CNS-targeted delivery system for lysosomal disorders like nGD (Sun et al., 2020; Zhao et al., 2015). The effectiveness of this approach in rescuing GD phenotypes was evaluated in MLOs derived from GD2-1260 hiPSCs and another GD2 hiPSC line, GD2-10-257, which carries the GBA1L444P/RecNcil mutation (Panicker et al., 2012). MLOs were derived from these hiPSCs following the protocol in Figure 1 and described in the Methods section. SapC-DOPS nanoparticle was formulated with fGCase, a recombinant GCase variant with over 21-fold longer active half-life at lysosomal pH than wild-type GCase (Comper et al., 2025; Hughes and Ferrante, 2023; Figure 5A).

Figure 5 with 2 supplements see all
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Delivery of GCase to MLOs via SapC-DOPS nanoparticles corrects GD phenotypes.

(A) Schematic illustration of SapC-DOPS nanoparticle-mediated delivery of recombinant GCase (fGCase) to MLOs. SapC-DOPS nanoparticles carrying fGCase or fluorescent label CVM were co-cultured with MLOs, followed by short-term (48 hr) or 2-week treatment period before analysis. (B) Confocal images of untreated and SapC-DOPS-CVM-treated MLOs, showing uptake of CVM (magenta) with DAPI (blue) labeling nuclei. Scale bars: 200 µm (left panel), 50 µm (right panels, magnified regions a and b). (C) GCase activity in WT-75.1 and GD2-1260 MLOs following a 48-hr treatment with SapC-DOPS-fGCase. Data are presented as mean ± SEM (3 MLOs pooled, n = 3 per group). ***p < 0.001, one-way ANOVA test. (D) Confocal images of WT-75.1, GD2-1260, and GD2-10-257 MLOs treated with SapC-DOPS or SapC-DOPS-fGCase for 2 weeks, immunostained for GCase (green) with DAPI (blue) labeling nuclei. Scale bar, 200 µm. (E–G) GCase activity and protein in WT-75.1 and GD (GD2-1260, GD2-10-257) MLOs treated with SapC-DOPS or SapC-DOPS-fGCase for 2 weeks, measured by enzymatic assay and immunoblot. Data are presented as mean ± SEM (3 MLOs pooled, n = 3–4 per group). ***p < 0.001; ns, not significant. One-way ANOVA test. Protein samples were extracted from n = 3 MLOs for each group. (H, I) GluSph levels in WT-75.1 and GD (GD2-1260, GD2-10-257) MLOs treated with SapC-DOPS or SapC-DOPS-fGCase for 2 weeks, quantified by LC–MS/MS and normalized to total protein. Data are presented as mean ± SEM (3 MLOs pooled, n = 3–4 per group). ***p < 0.001; **p < 0.01; ns, not significant. One-way ANOVA test. (J) Immunoblot analysis of autophagy–lysosomal and mTOR pathway proteins in SapC-DOPS or SapC-DOPS-fGCase treated GD2-1260 MLOs. GAPDH was used as a loading control. Protein samples were extracted from n = 3 MLOs for each group. Protein levels are normalized to WT-75.1 untreated controls (set to 1.0).

Figure 5—source data 1

Original files for western blot analysis are shown in Figure 5E, F, G, J.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig5-data1-v1.zip
Figure 5—source data 2

PDF file containing original western blots Figure 5E, F, G, J, including the relevant bands for immunoblotted targets, MLO sample and experimental conditions.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig5-data2-v1.zip

To test SapC-DOPS uptake, WT-75.1 MLOs were co-cultured with CVM (CellVue Maroon) loaded SapC-DOPS nanoparticles for 48 hr. CVM signals were detected throughout the organoids, confirming successful cargo delivery (Figure 5B). SapC-DOPS-fGCase was then prepared with 0.6 µg/ml fGCase (Sun et al., 2020) and co-cultured with MLOs. After 48 hr, treatment significantly increased GCase activity in GD2-1260 MLOs, restoring it to approximately 66.7% of WT-75.1 levels, confirming efficient delivery (Figure 5C).

To evaluate efficacy, GD2-1260 and GD2-10-257 MLOs were treated for 2 weeks with SapC-DOPS or SapC-DOPS-fGCase. Confocal imaging confirmed restored GCase expression, with SapC-DOPS-fGCase-treated GD2-1260 and GD2-10-257 MLOs showing increased GCase approaching the level in WT-75.1 MLO (Figure 5D). Additionally, SapC-DOPS-fGCase treatment significantly elevated GCase load in both dopaminergic neurons (TH+) and astrocytes (GFAP+), as shown by colocalization of GCase with TH and GFAP in GD2-1260 and GD2-10-257 MLOs, respectively (Figure 5—figure supplement 1A–D). Consistent with the results obtained with GD2-1260 MLOs (Figure 4H), reduction of TH in GD2-10-257 MLOs at weeks 16 and 28 was evident (Figure 5—figure supplement 1E). Corresponding to increased GCase protein, SapC-DOPS-fGCase treatment elevated GCase activity to 2.3-fold of untreated WT-75.1 MLO (Figure 5E). In GD2-1260 MLOs, SapC-DOPS-fGCase fully restored GCase activity to WT levels, while SapC-DOPS alone had no effect (Figure 5F). Similar GCase restoration was observed in the additional patient organoids, GD2-10-257 MLOs, indicating the effectiveness of this approach across different GD MLO models with various GBA1 mutations (Figure 5G). Importantly, SapC-DOPS-fGCase significantly reduced elevated GluSph levels in GD2-1260 and GD2-10-257 MLOs, matching WT-75.1 levels (Figure 5H, I), confirming effective lipid substrate clearance by delivered fGCase.

Furthermore, we evaluated the impact of SapC-DOPS-fGCase on the autophagy and lysosomal pathway and mTOR signaling. fGCase was found effectively delivered to lysosomal compartments, evidenced by colocalization of LAMP1 and LC3-II in treated GD2-1260 and GD2-10-257 MLOs (Figure 5—figure supplement 2A–D), indicating restoration of GCase in lysosomal and autophagosome compartments. However, analysis of protein levels showed that decreased LAMP1 expression in GD2-1260 MLOs was not altered following SapC-DOPS-fGCase treatment (Figure 5J). The elevated LC3-II levels, an indicator of impaired autophagic flux, were reduced upon treatment, suggesting enhanced autophagic activity (Figure 5J). Moreover, phosphorylated 4E-BP1 (Thr37/46), but not total 4E-BP1, was improved in SapC-DOPS-fGCase treated MLOs, reflecting a decrease in mTOR hyperactivation (Figure 5J). We anticipate that a longer duration of SapC-DOPS-fGCase exposure in nGD MLOs may produce a more robust therapeutic effect in rescuing nGD-associated phenotypes, which will be evaluated in future studies.

In conclusion, the effective restoration of GCase activity and correction of selected molecular and biochemical GD phenotypes highlight both the utility of the MLO platform for studying nGD and the therapeutic potential of this nanoparticle-based approach for treating nGD.

AAV-mediated gene transfer in GD MLOs enhances GCase activity and mitigates GD phenotypes

AAV-based gene therapies have shown clinical safety and efficacy in neurodegenerative diseases (AlZaidy et al., 2019; Drag et al., 2023). Trials for GD Type 1 (NCT05487599) and Type 2 (NCT04411654) using AAV9 have initiated. While animal models support AAV’s effectiveness in GD, its cellular impact on human or patient-derived models remains unknown. To investigate the therapeutic effect of AAV gene therapy in human GD organoids, AAV9-GBA1 was injected at a dose of 1.8 × 1010 vg per organoid at week 13 and evaluated 3 weeks after the injection (Figure 6A). In WT-75.1 MLOs, GCase activity was significantly increased in AAV9-GBA1-treated MLOs compared to untreated controls at week 15 (Figure 6B, left panel), suggesting effective transgene expression in normal organoids. AAV9-GBA1 restored GCase activity in GD2-1260 and GD2-10-257 MLOs to 47.8% and 37.7% of WT-75.1 levels, respectively (p < 0.001), compared to 6.0% and 8.8% in untreated controls (Figure 6B, middle and right panels). Immunoblot results further confirmed the restoration of GCase protein in AAV9-GBA1-treated GD MLOs (Figure 6B, bottom panel). Mass spectrometry analysis showed that AAV9-GBA1 normalized GluSph levels in GD2-1260 and GD2-10-257 MLOs, contrasting with elevated levels in untreated MLOs versus WT-75.1 controls (Figure 6C), indicating effective clearance of toxic lipid substrates in MLO by AAV gene therapy. Of note, LAMP1 levels were elevated after AAV9-GBA1 treatment, reflecting correction of lysosomal dysfunction (Figure 6D). However, the protein level of DA neuron marker (TH) was not significantly increased after AAV gene therapy compared to the untreated group, suggesting longer treatment or earlier gene therapy intervention might be needed to recover dopaminergic neurons. Confocal imaging corroborated that AAV9-GBA1-treated GD2-1260 MLOs exhibited GFP signals and restored GCase expression in pan-neurons, DA neurons, and astrocytes (Figure 6E).

Figure 6
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AAV9-GBA1 gene therapy mitigates disease phenotypes in GD MLOs.

(A) Schematic illustration of AAV9-GBA1 gene therapy delivery to MLOs using a nanoliter injector. AAV9 vectors carrying the GBA1 gene (AAV9-GBA1) are administered to Wk13 MLOs. The samples were analyzed after 3 weeks of treatment. (B) GCase activity in WT-75.1, GD2-1260, and GD2-10-257 MLOs and AAV9-GBA1-treated MLOs were measured by enzymatic assay. Data are presented as mean ± SEM (3 MLOs pooled, n = 3–6 per group). ***p < 0.001, one-way ANOVA test. (C) GluSph levels in AAV9-GBA1-treated GD and control MLOs were quantified by LC–MS/MS and normalized to total protein. Data are presented as mean ± SEM (3 MLOs pooled, n ≥ 3 per group). ***p < 0.001; ns, not significant. One-way ANOVA test. (D) Immunoblot analysis of LAMP1 and TH in WT-75.1 and in GD2-1260 MLOs untreated or treated with AAV9-GBA1. Protein samples were extracted from n = 3 MLOs for each group. Protein levels are normalized to WT-75.1 untreated controls (set to 1.0). (E) Transgene expressions (yellow arrows and enlarged insert) in neurons (NeuN), DA neurons (TH), and astrocytes (GFAP) of AAV9-GBA1-treated GD2-1260 MLOs. Scale bar = 50 µm.

Figure 6—source data 1

Original files for western blot analysis are shown in Figure 6B, D.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig6-data1-v1.zip
Figure 6—source data 2

PDF file containing original western blots Figure 6B, D, including the relevant bands for immunoblotted targets, MLO sample, and experimental conditions.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig6-data2-v1.zip

These results collectively demonstrate that AAV9-GBA1 gene therapy effectively corrected GCase deficiency, reduced GluSph accumulation, and ameliorates lysosomal pathology in GD MLOs, highlighting its therapeutic potential for nGD.

SRT reduces lipid accumulation and improves lysosomal function in GD MLOs

Current SRT in the standard clinical treatments for GD (Aerts et al., 2006; Scott, 2015) has limited efficacy in addressing the neurological manifestations of nGD due to their inability to cross the blood–brain barrier efficiently. GZ-682452 (termed herein as GZ452) is an analogue of venglustat that is presently under clinical evaluation for treating nGD (Schiffmann et al., 2024). To evaluate the human MLO as a preclinical model for SRT drug development, we assessed GZ452’s effects on MLO growth, lipid accumulation, midbrain markers, and lysosomal function.

GZ452 toxicity was first evaluated in WT-75.1 MLOs. Treatment at 0.3, 1, 2, and 3 µM over 6 weeks modestly reduced MLO size at 1 µM, with the 2 and 3 µM doses significantly decreasing size versus untreated controls (Figure 7A), indicating a high dose of GZ452 notably suppressed MLO growth. We next tested GZ452 at doses (0.01, 0.05, and 0.3 µM) over 6 weeks in WT-75.1 MLOs. GZ452 dose-dependently reduced total GluCer levels (Figure 7B) and GluCer species, with the 0.3 µM dose showing the most pronounced effect (Figure 7C).

Figure 7 with 1 supplement see all
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Substrate reduction therapy with GZ452 reduces lipid accumulation and improves autophagic and lysosomal abnormalities in GD MLOs.

(A) Assessment of GZ452 tolerated dose in healthy MLO and the effect of GZ452 on organoid growth in WT-75.1 MLOs over 6 weeks. Data are presented as mean ± SEM (3 MLOs pooled, n = 3). *p < 0.05, **p < 0.01; one-way ANOVA test. Total GluCer levels (B) and distribution of GluCer species (C) in WT-75.1 MLOs with various doses of GZ452 at Wk6. Data are presented as mean ± SEM (3 MLOs pooled, n = 3 per concentration). *p < 0.05, **p < 0.01; one-way ANOVA test. (D) Schematic of the experimental timeline for short-term (2 weeks) GZ452 treatment of GD MLOs. GluCer (E) and GluSph (F) levels in WT-75.1 and GD2-1260 MLOs at Wk15 under short-term GZ452 treatment. Data were normalized to protein mass. Data are presented as mean ± SEM (3 MLOs pooled, n = 3–4). *p < 0.05, **p < 0.01; one-way ANOVA test. (G) Schematic of the experimental timeline for long-term (28 weeks) GZ452 treatment in GD MLOs. (H) GluSph levels in MLOs at Wk15 under long-term GZ452 treatment. Data were normalized to protein mass. Data are presented as mean ± SEM (3 MLOs pooled, n = 3–8). ***p < 0.01, ns, not significant; one-way ANOVA test. (I) Immunoblot analysis of LAMP1 and LC3-I/II in substrate reduction therapy (SRT)-treated GD2-1260 MLOs for 28 weeks, with β-actin as loading control. Protein samples were extracted from n = 3 MLOs for each group. (J) Quantification of LAMP1 and LC3-II/I in MLOs. Protein levels are normalized to WT-75.1 untreated controls (set to 1.0). Data are presented as mean ± SEM (n = 3). **p < 0.01; ***p < 0.001; ns, not significant. One-way ANOVA with Tukey’s test.

Figure 7—source data 1

Original files for western blot analysis are shown in Figure 7I.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig7-data1-v1.zip
Figure 7—source data 2

PDF file containing original western blots Figure 7I, including the relevant bands for immunoblotted targets, MLO sample, and experimental conditions.

https://cdn.elifesciences.org/articles/109518/elife-109518-fig7-data2-v1.zip

Expression of midbrain markers ASCL1, TH, and PLZF in WT-75.1 MLOs was largely unaffected by GZ452 (0.3 µM) treatment started at week 6, with no significant changes in relative mRNA levels compared to untreated controls (Figure 7—figure supplement 1). We therefore applied this optimal tolerated GZ452 dose of 0.3 µM (300 nM) in short-term (2 weeks) and long-term (up to 28 weeks) treatment to test its therapeutic effects in GD MLOs. After 2 weeks of treatment starting in week 13, GZ452 significantly ameliorated GluCer and GluSph accumulation in GD2-1260 MLOs (Figure 7E, F). Long-term GZ452 treatment from day 2 to week 28 robustly cleared GluSph storage and normalized it to the WT level (Figure 7G, H). Immunoblot analysis showed that long-term GZ452 treatment improved lysosomal function, partially restoring LAMP1 levels (0.8 ± 0.1; p < 0.05) and reducing LC3-II by 21.4% (p < 0.01) (Figure 7I, J). These findings demonstrate that GZ452 effectively reduced lipid accumulation and improves lysosomal function in GD MLOs, supporting its therapeutic potential for ameliorating key disease phenotypes.

Discussion

We developed MLOs from two GD Type 2 patient-derived hiPSCs, offering deepened understanding to disease pathogenesis and an advanced model system for drug discovery. To our knowledge, this is the first GD brain organoid model derived from patient cells. These GD MLOs harbor prevalent GBA1L444P/P415R and GBA1L444P/RecNcil mutations, replicated key nGD phenotypes, including reduced GCase activity, glycosphingolipids accumulation, lysosomal abnormalities, and impaired dopaminergic neuron differentiation (Supplementary file 1). Emerging interventions, CRISPR/Cas9-mediated gene correction, SapC-DOPS-fGCase nanoparticle, and AAV9-GBA1 gene therapy, significantly restored GCase function and mitigated disease hallmarks in GD MLOs, supporting their use in preclinical studies (Supplementary file 1). Additionally, dysregulated Wnt signaling and impaired dopaminergic neuron differentiation in GD MLOs provide novel insights into nGD pathogenesis and potential therapeutic targets. This research underscores the utility of patient-derived MLOs as a human-relevant platform for modeling disease complexity and testing drug responses to bridge preclinical and clinical research.

Our findings revealed nGD-specific phenotypes in MLOs, including reduced GCase activity, GluCer and GluSph accumulation, and altered mTOR and autophagosome–lysosomal pathways, closely reflecting patient neuropathology (Burrow et al., 2015; Brown et al., 2019). Unlike Gba1 knockout animal models, which lack patient-specific genetic and epigenetic diversity, patient-derived MLOs retain heterozygous or compound heterozygous background, enabling study of disease mechanisms and modifier genes. Partial rescue in isogenic iso-GD2-1260 MLOs, where mutation correction alleviated but did not fully resolve abnormalities, highlights the model’s value in capturing nGD pathology and guiding personalized precision therapeutic strategies. This model offers a more advanced and physiologically relevant platform than traditional gene knockout or transgenic models, better capturing the complexity of nGD pathology.

Transcriptomic analysis of GD MLOs uncovered dysregulated Wnt signaling, a critical pathway in early brain development, highlighting a mechanistic insight into nGD pathogenesis. Aligning with Awad et al., who reported that downregulated Wnt/β-catenin signaling impairs DA neuron differentiation in nGD hiPSC-derived neuronal progenitors (Awad et al., 2017), our MLOs exhibited reduced FOXA2+ DA progenitors and TH+ mature DA neurons, along with decreased dopamine release in culture medium. Transcriptome analysis of the GD MLOs identified 1429 DEGs enriched in Wnt signaling, axon guidance, and neuron differentiation pathways, indicating that GCase deficiency disrupts midbrain patterning and neuronal specification. This finding is further supported by reduced expression of midbrain markers (e.g., FOXA2, TH), reduced dopamine release from DA neurons, and skewed forebrain/midbrain patterning genes (e.g., FOXP1, FOXG1) in GD MLOs. Compared to GBA1 KO iPSC-derived MLOs, which showed only a marginal reduction in dopaminergic neuron differentiation and no significant dysregulation of FOXG1 expression (Jo et al., 2021), our MLO model exhibits a distinct and more disease-relevant phenotype. These results suggest that aberrant Wnt signaling contributes to impaired dopaminergic neuron development and may drive the disease pathogenesis in nGD. Thus, targeting Wnt-related pathways could offer a therapeutic strategy to address early developmental defects in nGD. Comparative analysis with prior transcriptomic data from nGD mouse midbrain showed consistent dysregulation in axon guidance, synaptic signaling, lipid metabolism, nervous system development, etc. (Supplementary file 2; Dasgupta et al., 2015), supporting the fidelity of our human MLO model. Moreover, midbrain organoids at 35 days of development closely correspond to the human embryonic midbrain at approximately 9 weeks, while 70-day-old organoids align more closely with the 10-week stage (Zagare et al., 2022). These correlations highlight the importance of initiating treatment during the fetal stage, which may be critical for preventing the disease.

Isogenic MLOs generated by correcting the GBA1 L444P mutation in GD2-1260 hiPSCs using CRISPR/Cas9 revealed the key genetic mechanisms in nGD. The resulting WT/P415R genotype in iso-GD2-1260 partially rescued nGD phenotypes. GCase activity restored to nearly 50% of WT-75.1 levels, with normalized GluSph levels and improved TH expression. However, partial recovery of FOXA2 (53% of WT-75.1), along with persistent LC3 and LAMP1 abnormalities, may contribute to remaining pathology. These findings imply that the retained P415R mutation in this isogenic line may contribute to residual lysosomal dysfunction, potentially exerting a negative effect, as it has been reported to be associated with altered GCase stability and activity in previous studies (Grace et al., 1991; Ron et al., 2005). The partial rescue in iso-GD2-1260 MLOs suggests that the P415R mutation may affect disease severity and therapeutic response, deserving further investigation into the specific role of P415R mutation in GD and assessing whether dual mutation correction is required for full phenotypic normalization.

Evaluation of GZ452, a CNS-accessible SRT drug (Peng et al., 2021), in GD2-1260 MLOs showed significant reduction in GluCer and GluSph levels at a well-tolerated dose, alongside partial restoration of lysosomal and autophagy markers (LAMP1, LC3-II). Unlike higher doses that affected organoid growth, 0.3 µM preserved MLO size and expression of midbrain markers (ASCL1, TH, PLZF) involved in organoid differentiation and growth. These findings underscore the value of the MLOs for assessing drug safety (e.g., organoid size as a toxicity indicator) and efficacy in a human-specific, midbrain-relevant model before clinical studies. Our study demonstrated positive therapeutic outcomes using AAV9-GBA1 gene therapy and SapC-DOPS nanoparticle-mediated GCase delivery in GD2-1260 and GD2-10-257 MLOs. AAV9-GBA1 restored GCase activity, while SapC-DOPS-fGCase elevated GCase activity to WT levels; both approaches effectively reduced GluSph. Based on prior studies showing no region-specific effects in GD patients and mice, these therapies may also be effective in other brain organoid types, such as COs (Burrow et al., 2015; Sun et al., 2013). The novelty of employing MLOs lies in their ability to concurrently test these diverse therapeutic modalities: SRT, gene therapy, and nanoparticle-based enzyme delivery within a patient-derived system that replicates nGD pathology, offering the unique patient-MLO system to assess complex cellular responses that directly reflect patient-specific conditions.

Unlike animal models, MLOs provide a controlled environment to evaluate dose-dependent effects and cellular responses, enabling the identification of optimal therapeutic windows while minimizing the risk of adverse outcomes in patients with nGD. Moreover, the FDA has increasingly encouraged the use of organoid systems in drug development, recognizing their potential to improve preclinical testing and reduce reliance on animal models. Therefore, the adaptability of MLOs to test advanced interventions, coupled with their alignment with regulatory trends favoring human-relevant models, positions them as a great tool for accelerating the translation of innovative treatments from preclinical research to clinical application.

There are limitations in our current MLOs, such as lacking a vascular system and microglia. The absence of microglia and vasculature may contribute to incomplete phenotyping and phenotypic rescue observed in our therapeutic experiments. Without vascularization, cells in the core may experience hypoxic and nutrient deprivation, leading to cell death or necrosis in deeper layers in long-term culture. This limitation may partially explain the incomplete restoration of dopaminergic markers (TH, FOXA2) and partial recovery of LAMP1 following SapC-DOPS-fGCase and AAV9-GBA1 treatments. Additionally, the lack of microglia limits the modulation of neuroinflammation, which hinders the clearance of toxic lipid substrates and mediates neuronal damage in GD. Elevated GluSph and impaired dopaminergic differentiation observed in GD MLOs may not fully reflect the inflammatory process. Dysregulated Wnt signaling and lysosomal and autophagic markers (LAMP1, LC3-II/I) could be amplified by microglial activation in vivo. To improve model fidelity, future studies would incorporate vascularization (e.g., endothelial co-culture or microfluidics) to enhance oxygen and nutrient distribution and integrate microglia via directed differentiation (Cakir et al., 2022) or co-culture with hiPSC-derived microglia (Sabate-Soler et al., 2022) to enhance the relevance of MLOs for long-term nGD research and drug testing.

In conclusion, patient-derived MLOs offer an advanced, human-relevant platform for elucidating nGD pathogenesis and evaluating therapies, overcoming limitations of traditional models. Dysregulated Wnt signaling and impaired dopaminergic neuron differentiation, along with partial rescue of phenotypes through gene correction, highlight the complex genetic and developmental underpinnings of nGD. The efficacy assessment of SapC-DOPS-fGCase, AAV9-GBA1, and SRT-GZ452 therapies underscores the targeted interventions and safety evaluation of these approaches in patient-derived brain organoid models. While limitations such as lack of vascularization and microglia constrain modeling of neuroinflammation, these challenges can be addressed as discussed above and using advanced culturing techniques. Collectively, our findings lay the groundwork for developing patient-specific preclinical models to support personalized therapeutic strategies, while also advocating for the continued refinement of MLO systems to accelerate the discovery of effective treatments for nGD.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
AntibodyTuj1 (mouse monoclonal)BioLegendCat#801201; RRID:AB_23137731:1000 in immunoblot; 1:100 in immunostaining
AntibodyNeuN (mouse monoclonal)MilliporeCat#MAB377; RRID:AB_22987721:100 in immunostaining
AntibodyFOXA2 (rabbit monoclonal)Cell Signaling TechnologyCat#8186S; RRID:AB_108910551:1000 in immunoblot; 1:100 in immunostaining
AntibodyGFAP (mouse monoclonal)STEMCELL TechnologiesCat#60048.1; RRID:AB_30950921:1000 in immunoblot; 1:100 in immunostaining
AntibodyTH (rabbit polyclonal)MilliporeCat#AB152; RRID:AB_3902041:1000 in immunoblot; 1:100 in immunostaining
AntibodyTH (mouse monoclonal)Cell Signaling TechnologyCat#45648S; RRID:AB_36776401:50 in immunostaining
Antibody4e-bp1 (rabbit polyclonal)Cell Signaling TechnologyCat#9452S; RRID:AB_3316921:1000 in immunoblot
AntibodyPhospho-4E-BP1 (Thr37/46) (rabbit monoclonal)Cell Signaling TechnologyCat#2855S; RRID:AB_5608351:1000 in immunoblot
Antibodyβ-Actin (mouse monoclonal)InvitrogenCat#MA5-15739; RRID:AB_109794091:1000 in immunoblot
AntibodyCathepsin D (rabbit monoclonal)NovusbioCat#NBP2-67477; RRID:AB_30950931:1000 in immunoblot
AntibodyFOXG1 (rabbit polyclonal)AbcamCat#ab18259; RRID:AB_7324151:100 in immunostaining
AntibodyFOXP1 (mouse monoclonal)MilliporeCat#MAB45341; RRID:AB_36583141:100 in immunostaining
AntibodyGAPDH (mouse monoclonal)MilliporeCat#MAB374; RRID:AB_21074451:1000 in immunoblot
AntibodyGFP (chicken polyclonal)AbcamCat#ab13970; RRID:AB_3007981:100 in immunostaining
AntibodyGFP (mouse monoclonal)InvitrogenCat#A11120; RRID:AB_2215681:100 in immunostaining
AntibodyhGCase (NY#10, rabbit polyclonal)Made in labMade in lab, NY#10; RRID:AB_36776411:1000 in immunoblot; 1:100 in immunostaining
AntibodySOX2 (rabbit monoclonal)Cell Signaling TechnologyCat#23064S; RRID:AB_27141461:1000 in immunoblot; 1:100 in immunostaining
AntibodyKi67 (mouse monoclonal)Cell Signaling TechnologyCat#9449S; RRID:AB_27977031:100 in immunostaining
AntibodyLamp1 (mouse monoclonal)BiossCat#bsm-51301M; RRID:AB_36776421:1000 in immunoblot; 1:100 in immunostaining
AntibodyLC3B (rabbit polyclonal)NovusbioCat#NB100-2220; RRID:AB_100031461:1000 in immunoblot; 1:100 in immunostaining
AntibodyMAP2 (rabbit polyclonal)Cell Signaling TechnologyCat#4542S; RRID:AB_106937821:1000 in immunoblot; 1:100 in immunostaining
AntibodyPAX6 (rabbit polyclonal)CovanceCat#14811801; RRID:AB_23150641:100 in immunostaining
AntibodyS6 Ribosomal Protein (rabbit monoclonal)Cell Signaling TechnologyCat#2217S; RRID:AB_3313551:1000 in immunoblot
AntibodyPhospho-S6 Ribosomal Protein (Ser235/236) (rabbit monoclonal)Cell Signaling TechnologyCat#4856S; RRID:AB_21810371:1000 in immunoblot
Chemical compound, drugAscorbic acidPeprotechCat#5088177
Chemical compound, drugdb-cAMPSigma-AldrichCat#D0627-250MG
Chemical compound, drugY-27632; ROCK inhibitorTocris BioscienceCat#1254
Commercial assay or kitCEPTBio-TechneCat#7991
Chemical compound, drugDorsomorphinMilliporeCat#171261-1MG
Chemical compound, drugA83-01STEMCELL TechnologiesCat#72024
Chemical compound, drugCHIR99021STEMCELL TechnologiesCat#72052
Chemical compound, drugIWP2STEMCELL TechnologiesCat#72122
Chemical compound, drugSAGSTEMCELL TechnologiesCat#73412
Peptide, recombinant proteinVitronectinThermo FisherCat#A14700
Peptide, recombinant proteinFGF-Basic (FGF-b, human)Thermo FisherCat#PHG0264
Peptide, recombinant proteinFGF8Thermo FisherCat#100-25A-100UG
Peptide, recombinant proteinLamininSTEMCELL TechnologiesCat#77003
Peptide, recombinant proteinBDNFSTEMCELL TechnologiesCat#78005.1
Peptide, recombinant proteinGDNFSTEMCELL TechnologiesCat#78058.1
Peptide, recombinant proteinGrowth Factor Reduced (GFR) MatrigelCorningCat#354230
Commercial assay or kitDopamine ELISA KitAbnovaCat#KA3838
Cell line (Homo sapiens)WT-75.1PSCF at CCHMC (Sun et al., 2015; Pitstick et al., 2022)RRID:CVCL_C1UB
Cell line (H. sapiens)GD2-1260PSCF at CCHMC (Sun et al., 2015)
Cell line (H. sapiens)GD2-10-257See Awad et al., 2017
Sequence-based reagentNANOG FPSee Kwak et al., 2020PCR primersTGCAACCTGAAGACGTGTGA
Sequence-based reagentNANOG RPSee Kwak et al., 2020PCR primersCTATGAGGGATGGGAGGA
Sequence-based reagentOCT4 FPSee Kwak et al., 2020PCR primersGACAGGGGGAGGGGAGGAGCTAGG
Sequence-based reagentOCT4 RPSee Kwak et al., 2020PCR primersCTTCCCTCCAACCAGTTGCCCCAAAC
Sequence-based reagentPLZF FPSee Kwak et al., 2020PCR primersTCCCGCCCGACTGGAGGATA
Sequence-based reagentPLZF RPSee Kwak et al., 2020PCR primersTTCTTTCCTGGCTCCCCGCTC
Sequence-based reagentFOXG1 FPSee Kwak et al., 2020PCR primersGCGGGCCAGACCAGTTACTT
Sequence-based reagentFOXG1 RPSee Kwak et al., 2020PCR primersCCCAGACAGTCCCGTCGTAA
Sequence-based reagentTH FPSee Kwak et al., 2020PCR primersCTGAGATTCGGGCCTTCGAC
Sequence-based reagentTH RPSee Kwak et al., 2020PCR primersTGCACCTAGCCAATGGCACT

Maintenance of hiPSCs and generation of MLOs

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Three hiPSC lines (WT-75.1, GD2-1260, and GD2-10-257) generated previously (Sun et al., 2015; Awad et al., 2017) (refer to Key resources table above) were maintained in mTeSR1 complete medium (StemCell) on 6-well plates coated with Vitronectin (1:100 diluted in DPBS, 1 ml/well, incubated at RT for 1 hr). HiPSCs at ~70% confluency were treated and replated at 1:20 to 1:60 ratios, with optional 10 μM ROCK inhibitor (Y-27632, StemCell) for survival. All hiPSC lines were authenticated using short tandem repeat profiling and were verified as mycoplasma-free.

MLO generation method was modified based on published protocol (Kwak et al., 2020; Jo et al., 2016). Briefly, hiPSCs were pretreated with 50 μM Y-27632 for 1 hr, dissociated with Accutase (Millipore-Sigma) into singlets, centrifuged (200 × g, 5 min), and resuspended in embryoid body (EB) medium (EBM; consisting of DMEM/F12, 20% KnockOut Serum Replacement (KSR), 1% penicillin/streptomycin, GlutaMAX, NEAA, 55 μM β-mercaptoethanol, 1 μg/ml heparin, 3% FBS, 4 ng/ml bFGF, 1× CEPT). For each organoid, 1.2–1.5 × 10⁴ hiPSC cells were seeded in 100 μl EBM per well in ultra-low attachment (ULA) U-bottom 96-well plates, centrifuged at 500 × g for 3 min, and incubated at 37°C, 5% CO2; on day 2, 150 μl EBM with 4 ng/ml bFGF (no ROCK inhibitor) was added. Once the EBs grow to 400–475 μm in size, they were transferred to a new ULA 96-well plate with 125 μl brain organoid generation medium (BGM, consisting of 50% DMEM/F12, 50% Neurobasal, 1× N2, 1× B27 without vitamin A, 1% penicillin/streptomycin, 1% GlutaMAX, 1% NEAA, 55 μM β-mercaptoethanol, 1 μg/ml heparin) supplemented with dual SMAD inhibitors (SMADi: 2 μM dorsomorphin, 2 μM A83-01, 3 μM CHIR99021, 1 μM IWP2), refreshed every other day until day 11. On day 7 or 8, mesencephalic floor plate induction was initiated by adding 125 μl BGM containing 1×SMADi, 100 ng/ml FGF8, and 2 μM SAG until day 16. On day 11, four EBs were transferred to one well of ULA 24-well plates with 500 μl BGM-MLOs induction medium, consisting of BGM with 100 ng/ml FGF8, 2 μM SAG, 200 ng/ml laminin, 2.5 μg/ml insulin, 2% Growth Factor Reduced (GFR) Matrigel, and refreshed with Matrigel on day 14. On day 16, three MLOs per well were transferred to ULA 6-well plates in brain organoid maturation medium (BGM-BMM), consisting of BGM with 10 ng/ml BDNF, 10 ng/ml GDNF, 200 μM ascorbic acid, 125 μM db-cAMP, 1% GFR Matrigel, cultured on an orbital shaker (100 rpm) to reduce spontaneous fusion with medium changes every 3 days. Starting at day 30, GFR Matrigel was removed, and brain organoids were cultured solely in GFR Matrigel-free BGM-BMM medium till the date of analysis.

Immunostaining and image analysis of sectioned MLOs

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Organoids were washed with 1xDPBS and fixed in 4% paraformaldehyde overnight at 4°C. After washing with PBS-T (1x DPBS with 0.1% Tween 20), organoids were cryoprotected in 30% sucrose solution until fully equilibrated. Samples were then embedded in gelatin solution (7.5% gelatin, 10% sucrose in 1x DPBS) at 37°C for 1 hr, snap-frozen in a dry ice/ethanol slurry, and stored at –80°C. Cryosectioning was performed to obtain 16-μm-thick sections. For immunofluorescence, sections were air-dried and outlined with a hydrophobic PAP pen before being blocked with 5% normal goat serum in PBS-T for 1 hr, incubated overnight with primary antibodies (Key Resources Table) in primary antibody dilution buffer (PBS-T with 5% BSA and 0.05% sodium azide), and followed by secondary antibodies (Alexa Fluor conjugates) for 1 hr at room temperature. Slides were washed, stained with DAPI solution (0.2 μg/ml), mounted with Antifade Mounting Medium (VECTASHIELD, H-1000-10), and imaged at ×10 magnification for whole organoid scans or ×60 magnification for detailed cellular analysis using a fluorescence confocal microscope (Nikon Eclipse Ti) (Nikon, Tokyo, Japan) to assess neuronal organization of MLOs. The morphologies of neurons, astrocytes, and colocalization analysis were performed by taking multi-layer stacking (Z-stack) images under 60×oil immersion objective lens. Quantitative immunofluorescence analyses (e.g., cell counts for FOXP1+, FOXG1+, SOX2+, and Ki67 + cells, as well as marker colocalization) were performed using ImageJ (NIH) on at least 3–5 randomly selected non-overlapping fields of view (FOVs) per organoid section, with a minimum of 3 organoids per differentiation batch. Each FOV was imaged at consistent magnification (×60) and z-stack depth to ensure comparable sampling across conditions. Data from individual FOVs were first averaged within each organoid to obtain an organoid-level mean, and then biological replicates (independent differentiations, n ≥ 3) were averaged to generate the final group mean ± SEM.

Genome editing patient iPSC clones

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The iPSC line (GD2-1260) used for gene correction was derived from fibroblasts obtained from a GD Type 2 patient carrying compound heterozygous GBA1 mutations (P415R/L444P) (Sun et al., 2015). A guide (g) RNA was designed to target SpCas9-mediated double-strand break introduction proximal to the L444P mutation (GBA1 mutation at nt14446, T>C) in GD2-1260. Oligonucleotides (caccGAAGAACGACCCGGACGCAG and aaacCTGCGTCCGGGTCGTTCTTC; overhangs in lower case; target mutation site underlined; IDT) transcribing the sgRNA target sequence were annealed and cloned via BbsI restriction digest into plasmid pX458M that contains a U6 promoter-driven sgRNA and a SpCas9-2A-EGFP expression cassette. The pX458M plasmid is modified from the pX458 plasmid (Addgene #48138) (Ran et al., 2013) and carries an optimized sgRNA scaffold (Chen et al., 2013). The targeting activity of this plasmid was validated by the T7E1 assay using 293 cells. GD2-1260 cells were transfected with pX458M and a phosphorothioate-modified single-stranded oligonucleotide (ssODN; IDT) donor template using TransIT-LT1 (Mirus). The ssODN (Figure 4—figure supplement 1) was designed to introduce the desired wild-type GBA1 sequence flanked by homology arms to the targeted genomic region. The ssODN was also designed to contain silent mutations to prevent retargeting by SpCas9 and to introduce a BtgI restriction site to facilitate identification of targeted clones. Forty-eight hours post-transfection, GFP-positive cells were isolated by FACS and replated at cloning density (250–500 cells/well of a 6-well matrigel-coated plate). Replated cells were cultured for 4 days in mTeSR1 containing 10% CloneR (StemCell Technologies), using the manufacturer’s recommended protocol. Cells were subsequently fed daily with mTeSR1 for an additional 9 days before colonies were manually harvested and expanded for genotyping. Primers VS4247 (gtgcgtaactttgtcgacagtcc) and VS4249 (ctgagagtgtgatcctgccaag) were used to PCR amplify the targeted GBA1 genomic region and products were subjected to BtgI digestion to identify putative edited clones. Selected clones were subsequently confirmed by Sanger sequencing. This gene editing strategy is expected to also target the GBA1 pseudogene due to the identical target sequence which limits the gene correction on certain mutations (e.g., P415R) (Horowitz et al., 1989; Woo et al., 2021), but the chance to target other off-targets is low due to low off-target scores ranked based on the MIT Specificity Score analysis (Hsu et al., 2013).

SapC-DOPS-fGCase treatment of MLOs

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As previously described (Sun et al., 2020; Zhao et al., 2015), SapC-DOPS nanovesicles were formulated by combining saposin C (SapC) with dioleoylphosphatidylserine (DOPS) to encapsulate either recombinant human acid β-glucosidase (fGCase, Freeline Therapeutics) or fluorescent CellVue Maroon (CVM) for uptake studies. The SapC-DOPS-fGCase complex was prepared at a final concentration of 0.6 µg/ml fGCase and added to the BGM culture medium of MLOs derived from WT-75.1, GD2-1260, and GD2-10-257 hiPSC lines. To assess nanovesicle uptake, WT-75.1 MLOs at week 13 were co-cultured with SapC-DOPS-CVM for 48 hr, followed by confocal imaging to confirm internalization of the fluorescent CVM within the organoids.

For enzyme delivery and therapeutic evaluation, MLOs were treated with SapC-DOPS-fGCase or SapC-DOPS alone (control) for a 48-hr period to assess uptake and enzyme activity. For long-term treatment efficacy, MLOs were treated for 2 weeks before evaluating therapeutic efficacy. During treatment, MLOs were maintained in BGM media containing nanovesicles and were replaced every 3 days to ensure consistent exposure. Post-treatment, MLOs were harvested for confocal imaging, enzymatic assays, and biochemical analyses to assess GCase activity, protein expression, and correction of GD phenotypes.

AAV injection into MLOs

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Transfer vector of AAV9-GBA1 virus containing GBA1/GFP expressing cassette (CB-GBA1-IRES-GFP) was packaged in AAV9 capsid at AAVnerGene (Rockville, MD, USA). For the delivery of AAV9-GBA1 gene therapy to MLOs, a precise injection protocol was employed using a nanoliter injector system (World Precision Instruments). MLOs derived from WT-75.1, GD2-1260, and GD2-10-257 hiPSC lines were placed in a dish containing sterile 1x PBS. A glass pipette connected to a gas injector was lowered into the center of each MLO at a desired depth of 200–300 µm, as determined by microscopic visualization. A volume of 500 nl (0.5 µl) of AAV9-GBA1 vector, at a concentration of 3.6 × 10¹³ vg/mL, was injected into 10 sites of MLOs at a volume of 50 nl per injection site. The injection glass needle was retracted slowly after completion of the injection to minimize damage and ensure vector distribution. Morphology and viability were assessed post-injection, and MLOs were then maintained in culture for 3 weeks prior to subsequent analyses.

SRT treatment of MLOs

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For evaluation of the tolerated dose of SRT, WT-75.1 MLOs were treated with SRT compound GZ452 (AstaTech, P14969), also named GZ-682452, an analogue of venglustat (Marshall et al., 2016), at concentrations of 0.3, 1, 2, and 3 µM starting on day 0 for a period of 6 weeks. MLO size was measured weekly using bright-field microscopy and analyzed with ImageJ software to assess morphological changes. For short-term SRT treatment, 13-week-old GD2-1260 MLO were treated with 300 nM GZ452 for 3 weeks, with medium refreshed every 3 days to maintain consistent drug exposure. For long-term SRT treatment, GZ452 treatment at the concentration of 300 nM was started at the beginning of MLO generation (day 1) and continued for 28 weeks before collection for analysis. Untreated MLOs served as controls.

Glycosphingolipids analyses

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MLOs were washed with ice-cold PBS and homogenized and sonicated in sterile ddH2O. Glycosphingolipids were then extracted from tissue homogenates using chloroform/methanol following the protocol outlined previously (Sun et al., 2013). Aliquots of lipid extracts were processed for GluCer and GluSph quantification by ultra-high-performance chromatography coupled to tandem mass spectrometry (UHPLC–MS/MS) using a Waters Xevo TQ-S Micro triple quadrupole mass spectrometer (Waters, Milford, MA) at CCHMC Clinical Mass Spectrometry Laboratory. Chromatographic separation for GluCer and GluSph was achieved using a XSelect CSH C18 XP Column (100 × 2.1 mm, 2.5 µm, Waters) column. Quantification by LC–MS/MS was operated in the multiple reaction monitoring mode, with detection of the transition pair of the individual protonated parent ions of GluCers and daughter ion m/z 264.2. GluSph was measured by monitoring the mass transition m/z 462.3 > 282.4. The sphingoid base for all GluCer species analyzed is d18:1. Calibration curves were prepared for C16 GluCer, C18 GluCer, C24 GluCer, and C24:1 GluCer using C18 glucosyl(β) ceramide-D5 as the internal standard. Quantification of GluCer species with various fatty acid chain lengths was realized by the calibration curve of each species or with the closest fatty acyl chain length. The quantification of GluSph was based on the calibration curve using glucosyl(β) sphingosine-D5 as the internal standard. The calibration curve for GluCer and GluSph was 25 pg to 10 ng on column. Three QCs at low, medium, and high levels (50 pg, 0.5 ng, and 5.0 ng) were prepared in organic solvent and analyzed along with samples. The GluCer and GluSph levels in MLO were normalized to total MLO protein (mg) that were used for glycosphingolipids analyses. Protein mass was determined by BCA assay and glycosphingolipid was expressed as pmol/mg protein. Additionally, GluSph levels in the culture medium were quantified and normalized to the medium volume (pmol/ml) (Zhang et al., 2017).

Measuring dopamine levels by ELISA

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Dopamine levels in MLO culture medium were quantified using the Dopamine ELISA Kit (Abnova) that involves dopamine extraction, acylation, and enzymatic conversion before assay. Briefly, MLO culture medium was collected from four MLOs cultured in 3 ml BGM medium for 72 hr. Dopamine extraction was performed by pipetting 10 µl of standards, controls, and 750 µl of the sample into the extraction plate wells, filling each to 750 µl with deionized water, followed by 25 µl of TE buffer. Shake the covered plate for 60 min at room temperature (RT, 20–25°C) at 600 rpm, wash with 1 ml wash buffer twice, then acylate with 150 µl acylation buffer and 25 µl acylation reagent for 20 min. After washing again, elute with 100 µl hydrochloric acid, and transfer 90 µl of supernatant to the microtiter plate for enzymatic conversion with 25 µl freshly prepared enzyme solution, incubating at 37°C for 2 hr. Then, 100 µl of the converted samples and 50 µl dopamine antiserum were added to the dopamine microtiter strips. The mixture was then incubated overnight at 2–8°C. The strips were then washed and incubated with 100 µl enzyme conjugate for 30 min, followed by 100 µl of substrate for 20–30 min, and finally, 100 µl of stop solution was added. Absorbance was measured at 450 nm within 10 min, and dopamine concentrations were calculated using a calibration curve, applying the correction factor (10/500 = 0.02) to adjust and normalize by sample volume.

GCase activity assay

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GCase enzyme activities in hiPSCs and MLOs were determined fluorometrically with 4-methylumbelliferyl-β-D-glucopyranoside (4MU-Glc) in the presence of the GCase irreversible inhibitor, CBE (2 mM, Millipore, Bedford, MD) as previously described (Zhao et al., 2023). Briefly, hiPSC cell pellet or MLO tissues were homogenized using Precellys Evo Homogenizer/CK Mix beads (Bertin Technologies, France) in 1% sodium taurocholate/1% Triton X-100 (Tc/Tx) solution. GCase enzyme activity was then determined by 4MU-Glc as substrate in 0.25% Tc/Tx diluted in 0.1 M citrate phosphate buffer (pH 5.6). Protein concentrations were determined by BCA assay for normalization. The GCase-specific activity was calculated by subtracting non-specific activity (with CBE) from total activity (without CBE) and normalized to total protein mass.

Transcriptome analysis of MLOs

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Total RNAs were extracted from week 8 MLOs using the RNeasy Mini Kit (QIAGEN). Total RNAs (150–300 ng), quantified by Qubit (Invitrogen) high-sensitivity spectrofluorometric assay, were poly-A selected and reverse transcribed using Illumina’s TruSeq stranded mRNA library preparation kit (Illumina). Each sample was fitted with one of 96 adapters containing different 8-base molecular barcodes for high-level multiplexing. After 15 cycles of PCR amplification, completed libraries were sequenced on NovaSeq 6000 (Illumina), generating 30 million high-quality 100-base-long paired-end reads per sample. A quality control check on the fastq files was performed using FastQC. Upon passing basic quality metrics, the reads were trimmed to remove adapters and low-quality reads using default parameters in Trimmomatic (Version 0.33). The trimmed reads were then mapped to human reference genome GRCh38 using default parameters with strandness option in Hisat2 (Version 2.0.5), achieving a mapping rate greater than 90%. Transcript or gene abundance was determined using kallisto (Version 0.43.1). A transcriptome index in kallisto was created using Ensembl cDNA sequences for the reference genome. This index was then used to quantify transcript abundance in raw counts and transcripts per million. Differential expression analysis was performed using the R package DESeq2 (Love et al., 2014). Genes with BaseMean ≥50, |fold change| ≥2, p-adj ≤0.05 were identified as DEGs. Heatmaps were made using the R package ggplot2. Gene enrichment analysis using cellular component, KEGG pathways, molecular function, and biological process (GO analysis) was performed using DAVID 6.8 (Sherman et al., 2022). Three MLOs were pooled for each sample, and three samples were profiled for each genotype. MLO sequencing datasets and partially processed results have been deposited to the National Center for Biotechnology Information (NCBI)’s Gene Expression Omnibus (GEO) database (GSE303993).

Gene expression analysis by qRT-PCR

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Total RNA was isolated from MLO tissue using the RNeasy Kit (QIAGEN). Quantitative RT-PCR was carried out as described previously using primers listed in Key Resources Table (Dai et al., 2018). Housekeeping gene GAPDH or ACTB was used as internal controls for mRNA quantification. Relative expression of mRNAs was determined by the 2−∆∆CT method.

Immunoblotting

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Immunoblotting was used to detect protein expression in iPSCs and MLOs. Briefly, brain organoids or cells were homogenized in freshly prepared RIPA buffer with protease inhibitors and anti-phosphatase inhibitors using a Precellys Evo Homogenizer (Bertin). The samples were then centrifuged at 12,000 × g for 10 min to produce lysate for electrophoresis, membrane transferring, and detection using primary and secondary antibodies indicated in Key Resources Table. Semi-quantification of proteins was performed using ImageJ (NIH).

Statistical analysis

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For comparisons between two groups, data were analyzed using unpaired two-tailed Student’s t-tests when the sample size was ≥6 per group and normality was confirmed by the Shapiro–Wilk test. When the normality assumption was not met or when sample sizes were small (n < 6), the non-parametric Mann–Whitney U test was used instead. For comparisons involving three or more groups, one-way ANOVA followed by Tukey’s multiple comparison test was applied when data were normally distributed; otherwise, the non-parametric Dunn’s multiple comparison test was used. Exclusion of outliers was made based on cutoffs of the mean ± 2 standard deviations. All statistical analyses were performed using GraphPad Prism 10 software. Exact p-values are reported throughout the manuscript and figures where feasible. A p-value <0.05 was considered statistically significant.

Data availability

RNA sequence data generated in this study were deposited in NIH GEO (accession number GSE303993) and are publicly available now. All data generated or analyzed during this study are included in the manuscript, supporting files, and source data files.

The following data sets were generated
    1. Lin Y
    2. Sun Y
    (2025) NCBI Gene Expression Omnibus
    ID GSE303993. Developing Midbrain-like Organoid of Gaucher Disease as A Platform for Drug Assessment.
    https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE303993
The following previously published data sets were used

References

  20. Book
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    2. Petsko GA
    3. Kolodny EH
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    Gaucher disease
    In: Valle D, Beaudet B, Vogelstein KW, Antonarakis SE, Ballabio A, Scriver CR, Sly WS, Childs B, Bunz F, editors. The Online Metabolic and Molecular Bases of Inherited Diseases. The McGraw-Hill Companies, Inc. pp. 3635–3668.
    1. Grace ME
    2. Berg A
    3. He GS
    4. Goldberg L
    5. Horowitz M
    6. Grabowski GA
    (1991)
    Gaucher disease: heterologous expression of two alleles associated with neuronopathic phenotypes
    American Journal of Human Genetics 49:646–655.
    1. Qi X
    2. Leonova T
    3. Grabowski GA
    (1994)
    Functional human saposins expressed in Escherichia coli: evidence for binding and activation properties of saposins C with acid beta-glucosidase
    The Journal of Biological Chemistry 269:16746–16753.

Article and author information

Author details

  1. Yi Lin

    Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8209-1185

  2. Benjamin Liou

    Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Formal analysis, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4848-3964

  3. Venette Fannin

    Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared

  4. Stuart Adler

    Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared

  5. Christopher N Mayhew

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Pluripotent Stem Cell Facility and Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared

  6. Jason E Hammonds

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared

  7. Yueh-Chiang Hu

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Transgenic Animal and Genome Editing Facility, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared

  8. Jason Tchieu

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9793-9836

  9. Wujuan Zhang

    Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Data curation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  10. Xueheng Zhao

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Data curation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  11. Rebecca L Beres

    Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared

  12. Kenneth DR Setchell

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    Contribution
    Data curation, Writing – review and editing
    Competing interests
    discloses outside this work equity in Asklepion Pharmaceuticals, Baltimore, and Aliveris s.r.l. Italy and is a consultant to Mirum Pharmaceuticals

  13. Ahmet Kaynak

    Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati, College of Medicine, Cincinnati, United States
    Contribution
    Data curation, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6551-1125

  14. Xiaoyang Qi

    1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    2. Division of Hematology/Oncology, Department of Internal Medicine, University of Cincinnati, College of Medicine, Cincinnati, United States
    Contribution
    Conceptualization, Resources, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5363-1760

  15. Ricardo A Feldman

    Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, United States
    Contribution
    Resources, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6090-0439

  16. Ying Sun

    1. Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, United States
    2. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing – original draft, Writing – review and editing
    For correspondence
    ying.sun@cchmc.org
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2979-4735

Funding

National Institute of Health (R21HD1027881)

  • Ying Sun
  • Christopher N Mayhew

National Institute of Health (R21OD033660)

  • Ying Sun

National Institute of Health (R01NS138309)

  • Ying Sun
  • Xiaoyang Qi

National Institute of Health (R01NS103931)

  • Ying Sun

Cincinnati Children's Hospital Medical Center (Center of Pediatric Genomics Award)

  • Ying Sun

Cincinnati Children's Hospital Medical Center (Research Innovation Pilot Funding Program Award)

  • Ying Sun
  • Yi Lin
  • Jason E Hammonds

National Institutes of Health (2UL1TR001425-05A1, CHMC-CTSA 00003827)

  • Ying Sun

The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by the Cincinnati Children’s Pluripotent Stem Cell Facility (RRID:SCR_022634), Clinical and Biomedical Mass Spectrometry Facility (RRID:SCR_022638), and Transgenic Animal and Genome Editing Facility (RRID:SCR_022642). Authors acknowledge Freeline Therapeutics (now Spur Therapeutics) for providing the fGCase under a Material Transfer Agreement. This work is supported by awards from the National Institutes of Health (grant numbers R21HD1027881, R21OD033660, and R01NS138309 to YS; R01NS103931 partly to YS; R21HD1027881 partly to CNM; R01NS138309 partly to XQ); the National Center for Advancing Translational Sciences of the National Institutes of Health (Award Number 2UL1TR001425-05A1, CHMC-CTSA 00003827 to YS); Cincinnati Children’s Hospital Medical Center (CCHMC) Center of Pediatric Genomics Award to YS; CCHMC Research Innovation Pilot Funding Program Award to YS, YL, and JEH. The funding source did not have any role in study design, data collection, data analysis, interpretation, or writing of the report.

Ethics

This work has been reviewed and approved by the Cincinnati Children's Hospital Medical Center (CCHMC) and University of Cincinnati (UC) Embryonic Stem Cell Research Oversight (ESCRO) committee under ESCRO protocol #EIPHG3114_R3. Primary fibroblast (GM01260) for generating GD2-1260 iPSC was obtained from the Coriell Institute for Medical Research under Material Transfer Agreement. WT-75.1 iPSC was generated using fibroblasts cultured from discarded circumcision tissue obtained from a healthy donor (provided by Dr. Susanne Wells, Division of Hematology/Oncology, CCHMC; Institutional Review Board No. 02-9-29X) at CCHMC. The procedures used to generate the GD2-1260 iPSC and WT-75.1 iPSC lines at CCHMC have been reviewed and approved by the CCHMC/UC ESCRO committee. Skin biopsies to generate GD2-10-257 iPSCs were obtained from NIH with informed consent and were approved by the Institutional Review Board (IRB). The procedures used to generate the GD-2-10-257 nGD iPSC line at the University of Maryland Baltimore (UMB) have been reviewed and approved by the UMB IRB and ESCRO committees.

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  1. Yi Lin
  2. Benjamin Liou
  3. Venette Fannin
  4. Stuart Adler
  5. Christopher N Mayhew
  6. Jason E Hammonds
  7. Yueh-Chiang Hu
  8. Jason Tchieu
  9. Wujuan Zhang
  10. Xueheng Zhao
  11. Rebecca L Beres
  12. Kenneth DR Setchell
  13. Ahmet Kaynak
  14. Xiaoyang Qi
  15. Ricardo A Feldman
  16. Ying Sun
(2026)
Patient-specific midbrain organoids with CRISPR correction recapitulate neuronopathic Gaucher disease phenotypes and enable evaluation of novel therapies
eLife 15:RP109518.
https://doi.org/10.7554/eLife.109518.3

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