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. 2025 Apr 10;15:12286. doi: 10.1038/s41598-025-96884-w

Transcriptome signatures of human neural stem cells derived from LRRK2 gene therapeutic cells

Doyeong Kim 1,#, Sang-Min Park 1,#, Seo-Young Lee 2, Sun-Ku Chung 2,✉
PMCID: PMC11986138  PMID: 40210948

Abstract

The LRRK2 G2019S mutation is known to have a high penetrance rate associated with Parkinson’s disease (PD), prevalent across both familial and sporadic PD cases and implicated in neurodegenerative mechanisms. This mutation disrupts several key cellular processes, particularly affecting the endoplasmic reticulum and mitochondrial functions in neural stem cells (NSCs), which are crucial for protein homeostasis and energy metabolism. Although aging is a major risk factor for PD, the complex interplay between LRRK2 G2019S and aging-related cellular dysfunction in NSCs remains poorly understood. In this study, we performed a comprehensive transcriptomic analysis to characterize the temporal transcriptional changes in LRRK2 G2019S-carrying NSCs across sequential passages, resembling cellular aging. BAC DNA-mediated correction of the LRRK2 mutation significantly restored dysregulated cellular processes, including endoplasmic reticulum-associated protein processing, mitochondrial function, and vesicular trafficking pathways, thereby restoring cellular homeostasis in NSCs. Notably, aged NSCs harboring the LRRK2 G2019S mutation exhibited pronounced alterations in epithelial-mesenchymal transition or TGF-β signaling, exacerbating declines in NSC function. Our findings elucidate the molecular mechanisms underlying LRRK2 G2019S-mediated pathogenesis in aging NSCs and highlight the therapeutic potential of genetic correction strategies for PD treatment.

Keywords: LRRK2 G2019S, Parkinson’s disease, Neural stem cell, Transcriptome signatures

Subject terms: Regulatory networks, Parkinson's disease

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disease caused by the loss of dopaminergic neurons in the substantia nigra, resulting in a variety of motor and non-motor symptoms1. Among the genetic contributors to PD, the leucine-rich repeat kinase 2 (LRRK2) G2019S mutation is one of the most prevalent, negatively affecting neural stem cell (NSC) function and neuronal survival2. LRRK2 plays a pivotal role in regulating various cellular functions, including modulation of endoplasmic reticulum (ER) stress. The ER, particularly the rough ER, is central to protein synthesis, folding, modification, and transport. Under pathological conditions, the accumulation of misfolded or unfolded proteins leads to ER stress, which is a common feature in neurodegenerative diseases, including PD3. The LRRK2 G2019S mutation exacerbates ER stress, contributing to dopaminergic neuron degeneration4,5. LRRK2 also interacts with substrates such as RAB proteins, which are key regulators of vesicle trafficking and targeting, including ER-Golgi transport6,7. Mutations in LRRK2 disturb vesicular physiology, leading to increased ER stress and disrupted cellular homeostasis8. Additionally, LRRK2 regulates processes related to the endosomal–lysosomal pathway and autophagy9, and its mutations have been linked to lysosomal defects10,11. Despite harboring PD-linked mutations such as LRRK2 G2019S, individuals often do not develop PD symptoms until later in life, indicating that aging significantly contributes to disease onset12. Aging is the most significant risk factor for PD, with most cases emerging in individuals over 60. Recent research has shown that LRRK2 mutations can lead to an age-dependent decline in cellular function13–16, underscoring the importance of analyzing the combined effects of aging and LRRK2 G2019S mutation in understanding PD pathology.

LRRK2 G2019S is well known as an autosomal dominant mutation associated with PD17. This type of mutation should be replaced with a normal base to essentially eliminate the dominant effect. Therefore, gene correction strategies for LRRK2 G2019S mutation using gene editing tools such as zinc finger nuclease (ZFN), CRISPR/Cas9, helper-dependent adenovirus vector (HDAdV), and bacterial artificial chromosome-mediated homologous recombination (BAC-mediated HR) as gene therapy have shown promise in alleviating the pathological effects. First, Reinhardt et al.18 demonstrated that ZFNs could correct the mutation in induced pluripotent stem cells (iPSCs) derived from PD patients, alleviating pathological changes via regulation of the ERK signaling pathway. Similarly, Liu et al.16 utilized HDAdVs to correct the mutation, restoring functional deficits in patient-derived iPSCs.More recently, BAC DNA has gained attention for its efficiency in correcting such mutations due to its capacity to encompass large genomic regions with high accuracy. In previous studies, we employed BAC DNA to correct the LRRK2 G2019S mutation, using homology arms of approximately 100 kb to efficiently target the mutant allele19. However, it remains crucial to assess the impact of this correction on NSC function and integrity, particularly in the context of aging.

In addition to PD, mutations in the LRRK2 gene have been found to be associated with neurodegenerative disease such as Alzheimer’s disease (AD) and Amyotrophic lateral sclerosis (ALS). According to a summary of PD pathological findings, 79% of LRRK2 G2019S mutation carriers are investigated to have some degree of tau and LB pathology20. In this regard, it has been demonstrated that immunopositivity of AD-type tau is observed in several region of the brain, including the midbrain, of PD patients with LRRK2 G2019S mutation21. Additionally, while studies have suggested the correlation between LRRK2 mutations and AD as well as ALS22,23, applying of the gene correction of LRRK2 G2019S on these diseases has yet to be reported.

In this study, we performed a genome-wide analysis to evaluate the effects of aging in combination with the LRRK2 G2019S mutation and its correction via BAC DNA on NSC integrity. As a mimic of cellular aging, we analyzed transcriptome signatures from passages 1, 2, and 13 of isogenic NSC lines derived from iPSCs that had undergone genetic correction with BAC DNA. Our findings suggest that correcting the LRRK2 G2019S mutation in NSCs rescues dysregulated functions of the ER and mitochondria. Furthermore, we propose that the LRRK2 G2019S mutation, when combined with aging, may impair NSC integrity by upregulating genes related to epithelial-mesenchymal transition (EMT) or transforming growth factor-beta (TGF-β) signaling.

Results

Restoration of cellular functions following BAC DNA-mediated correction of the LRRK2 G2019S mutation

Given the pivotal role of ER dysfunction in PD pathology, we investigated whether correcting the LRRK2 G2019S mutation could restore ER-related cellular functions. To address this, we analyzed transcriptome data from passage 2 of NSC lines derived from isogenic iPSCs that underwent BAC DNA-mediated correction and compared them to uncorrected mutant lines. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we identified notable changes in the expression of genes involved in the protein processing pathway within the ER (Fig. 1). Specifically, following correction, genes responsible for proper protein folding and the degradation of misfolded proteins, such as those encoding protein disulfide isomerase (PDI), oligosaccharyltransferase (OST), and Heat Shock Protein 40 (Hsp40), were upregulated. In contrast, genes associated with apoptosis triggered by prolonged ER stress, such as those encoding Apoptosis Signal-Regulating Kinase 1 (ASK1), mitogen-activated protein kinase kinase 7 (MKK7), and c-Jun N-terminal kinase (JNK), were downregulated. And, we individually verified the expression of several genes, including DDOST encoding OST and MAP3K5 encoding ASK1, and confirmed that the were consistent with our analysis (Supplementary Figure S1). These results suggest that the LRRK2 G2019S mutation disrupts the transcriptional regulation of several critical ER-related genes, and that genetic correction effectively restores this regulation, leading to a recovery of protein quality control functions and a reduction in ER stress markers.

Fig. 1.

Fig. 1

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Expression changes of genes associated with protein processing in the endoplasmic reticulum by the correction of LRRK2 by BAC DNA. The changes in gene expression associated with the KEGG pathway "Protein Processing in the Endoplasmic Reticulum" (KEGG ID: 04141) in NSCs harboring the LRRK2 G2019S mutation, comparing cells corrected with BAC DNA to uncorrected controls at passage 2. Genes are color-coded based on log2 fold change (log2FC) values, with red indicating upregulation and green indicating downregulation. Key changes include the upregulation of chaperones (Hsp40, Hsp70), protein disulfide isomerases (PDIs), and oligosaccharyltransferases (OSTs), along with the downregulation of the ASK1-MKK7-JNK signaling pathway.

To gain deeper insight into the biological pathways affected by the correction of the LRRK2 G2019S mutation, we performed Gene Set Enrichment Analysis (GSEA) (Supplementary Table S1). Consistent with the results observed in Fig. 1, this analysis revealed that BAC DNA-mediated correction of the LRRK2 G2019S mutation restored key pathways involved in ER protein quality control, which is crucial for proper protein processing. Notably, the correction upregulated pathways responsible for protein folding, de novo protein folding, and the stabilization of misfolded proteins (Fig. 2, i). As seen in Fig. 1, misfolded proteins are typically cleared through the ER-associated degradation (ERAD) pathway and subsequently degraded by the ubiquitin–proteasome system24, which is disrupted by the LRRK2 G2019S mutation25. Our data further demonstrated that genetic correction increased the expression of genes involved in the ubiquitin–proteasome pathway (Figs. 1 and 2, ii), supporting the recovery of cellular mechanisms responsible for maintaining protein homeostasis.

Fig. 2.

Fig. 2

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Pathway analysis of the LRRK2 correction by BAC DNA. Gene set enrichment analysis of the LRRK2 correction by BAC DNA using the gene sets obtained from MsigDB. The identified pathways were categorized into seven functional groups: (i) protein folding, including chaperone-mediated protein folding and stabilization, de novo protein folding, and response to misfolded proteins. (ii) ubiquitin/proteasome system, including proteasome degradation and regulation of ubiquitin ligase activity. (iii) mitochondrial expression, including mitochondrial translation, translational termination, and protein import. (iv) mitochondrial repair, including electron transport chain assembly and oxidative phosphorylation system maintenance. (v) vesicle trafficking, including ER-to-Golgi transport, COPII-mediated vesicle budding, and cargo concentration in the endoplasmic reticulum. (vi) vesicle targeting, including protein localization to mitochondria and the Golgi. (vii) lysosomal system, including on endosomal transport, endosome-to-lysosome trafficking, and autophagy regulation. The resulting normalized enrichment scores (NES), significance calculated as -log10(adjusted P-value), and the size of the gene sets are presented. GO, gene ontology; BC, BioCarta; WP, WikiPahtways; RE, Reactome.

In addition to restoring ER function, LRRK2 correction led to increased expression of genes associated with mitochondrial function (Fig. 2, iii), including mitochondrial gene expression, translation, and protein import. This was accompanied by the upregulation of oxidative phosphorylation pathways and protein folding mechanisms. Furthermore, oxidative stress markers decreased, while ATP production increased, indicating improved mitochondrial function following LRRK2 correction. Furthermore, BAC DNA-mediated correction enhanced pathways involved in cellular respiration via the oxidative phosphorylation system within mitochondria (Fig. 2, iv). Our results also showed that multiple pathways related to vesicular trafficking were upregulated, including both anterograde ER-to-Golgi vesicle transport and retrograde Golgi-to-ER vesicle transport (Fig. 2, v). In line with these findings, KEGG pathway analysis showed increased expression of genes related to coat protein complex II-mediated vesicle transport, a critical step in the secretion pathway (Fig. 1). We also observed that genes involved in vesicle targeting and protein localization were upregulated following correction (Fig. 2, vi). Lastly, LRRK2 correction enhanced multiple pathways involved in endosomal transport, lysosome function, and autophagosome formation (Fig. 2, vii), consistent with previous findings that LRRK2 inhibitor treatment enhances lysosome formation and function26. The upregulation of autophagy and vesicle-mediated transport pathways may contribute to mitigate neuroinflammation by facilitating the clearance of toxic protein aggregates and regulating cytokine release. Altogether, these findings suggest that LRRK2 correction restores multiple critical cellular functions that are disrupted in mutant cells, contributing to overall cellular homeostasis.

Comparison with previous gene correction studies

We compared the effects of our BAC DNA-mediated correction with previous transcriptomic studies using ZFN-mediated or HDAdV-mediated corrections (Table 1). Reinhardt et al.18 reported that the LRRK2 G2019S mutation increased cellular toxicity and led to neurite shortening in midbrain dopaminergic neurons. These phenotypes were caused by the dysregulation of several genes, including CPNE8, ANXA1, MAP7, and CADPS2, which were downregulated, and UHRF2, which was upregulated in response to the LRRK2 G2019S mutation. Our data showed that CPNE8 expression was only restored following LRRK2 correction in NSCs, with an increase observed after correction (Fig. 3A). Consistent with the reduction of ERK pathway activity observed in the ZFN-mediated LRRK2 correction, we also found that downstream genes of KRAS, which can activate the ERK pathway, were downregulated following BAC DNA-mediated correction (Fig. 3B, i). Similarly, as ZFN-mediated LRRK2 correction reduced apoptotic sensitivity in the study by Reinhardt et al., our results showed that apoptotic processes involved in development and morphogenesis were also reduced following the correction (Fig. 3B, ii).

Table 1.

Studies on LRRK2 mutation correction with publicly available transcriptome data.

Author Year Correction method Transcriptome data type Sample information GEO accession number
Reinhardt et al 2013 ZFN Microarray 2 mDANs, 3 mDANs with mutation, 3 mDANs after correction GSE43364
Liu et al 2012 HDAdV Microarray 2 fibroblast, 4 fibroblasts with mutation, 2 iPSCs, 4 iPSCs with mutation, 2 ESCs GSE33298
2012 HDAdV Microarray 3 NSCs, 3 NSCs with mutation, 3 NSCs with mutation treated by inhibitor GSE36321
Do et al. (This study) 2020 BAC RNA-seq

Passage 1: 1 NSCs with mutation, 1 NSC after correction

Passage 2: 3 NSCs with mutation, 3 NSCs after correction

Passage 13: 1 NSC with mutation, 1 NSC after correction

 GSE183499
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Fig. 3.

Fig. 3

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Comparison of gene signature with other correction methods. (A) Five genes dysregulated by LRRK2 G2019S mutation in the study of Reinhardt et al. The fold change (FC) and significance, calculated as −log10 (adjusted P-value), from differential gene expression analysis after LRRK2 correction by BAC DNA are presented. (B) Gene set enrichment analysis of the LRRK2 correction by BAC DNA using the gene sets obtained from MsigDB. The selected pathways were associated with (i) downstream KRAS, (ii) apoptotic process, (iii) nuclear envelope, and (iv) epigenetic modification. The resulting normalized enrichment scores (NES), significance calculated as −log10 (adjusted P-value), and the size of the gene sets are presented. OS, oncogenic signature gene sets; GO, gene ontology; RE, Reactome.

In addition, Liu et al.16 reported that HDAdV-mediated LRRK2 correction restored nuclear architecture impairments caused by the mutation. Our results confirmed these findings, showing enhanced pathways related to nuclear envelope organization following LRRK2 correction (Fig. 3B, iii). Furthermore, Liu et al. also suggested that the LRRK2 G2019S mutation led to epigenetic modifications, particularly H3K4 methylation. Our data similarly indicated that histone modifications, including H3K4 trimethylation, were decreased by the correction (Fig. 3B, iv). These findings underscore the effectiveness of BAC DNA-mediated correction in mitigating multiple pathological processes associated with the LRRK2 G2019S mutation.

Impact of aging on NSC integrity

To investigate how aging influences the penetrance of the LRRK2 G2019S mutation, we examined the effect of in vitro aging by analyzing expression changes in age-related genes at passages 1 and 13 of NSCs harboring either the LRRK2 G2019S mutation or wild-type LRRK2, corrected by BAC DNA. Differentiation from iPSCs to NSCs takes 10 days in terms of differentiation process, which means the most suitable differentiation process, which represents passage 1 and is the optimal differentiation process and duration to maintain NSC integrity. However, when maintained continuously until passage 13 without additional differentiation steps, LRRK2 G2019S rapidly reaches the limit of long-term culture of NSCs, which is indicated by changes in the expression pattern of marker genes associated with cell transformation. A previous transcriptomic study identified three common aging-related genes in aging fibroblasts, neurons, and the brain: RANBP17, LAMA3, and PCDH1027. In our analysis, the nuclear transport receptor RanBP17 and the nuclear lamin alpha subunit, encoded by RANBP17 and LAMA3 respectively, were consistently downregulated at passage 13 compared to passage 1 (Fig. 4A, B). These two genes are involved in nuclear architecture, and disruptions in this structure are closely linked to aging. Therefore, the reduced expression of these nuclear protein-encoding genes across passages suggests that in vitro passaging of NSCs mimics age-related declines in cellular integrity, regardless of the presence of the LRRK2 G2019S mutation.

Fig. 4.

Fig. 4

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Passaging-induced aging effects on NSC gene expression. Gene expression levels were analyzed in NSCs at passages 1 and 13, calculated as log2(TPM + 1). (A) Heatmap of age-related genes, normalized by row for gene-level comparison. (B) The expression levels of age-related genes that are significantly downregulated with passaging. (C) Heatmap of NSC marker genes, normalized by row for gene-level comparison. (D) The expression levels of NSC marker genes that are significantly downregulated with passaging. (E) The expression levels of PROM1 and SOX1, with significant downregulation observed only in the presence of the mutation during passaging.

NSCs play a crucial role in maintaining and repairing the nervous system, and their functionality is influenced by aging. Aging acts as a pathological risk factor that reduces the number of NSCs by affecting nutrient delivery due to changes in vascular permeability as well as changes in the brain microenvironment caused by microglia that induce neuroinflammation. It also causes changes in the energy metabolism of NSCs, which mainly uses glycolysis, thereby affecting metabolic conversion and inducing changes in cell identity. NSC integrity means self-renewal, proliferation, and provision of neural derivatives. PD is known to be caused by the functional loss of dopaminergic neurons among neural derivatives derived from NSCs, but the loss of the identity of NSCs, which are their source, will inevitably limit the resource supply for neurogenesis28. Preserving NSC identity serves as a key indicator of cellular functionality. Therefore, we further analyzed the expression of several key NSC marker genes at passage 13 compared to passage 1 (Fig. 4C). We observed a significant reduction in the expression of PAX6, a representative marker of NSCs29 (Fig. 4D). Additionally, we confirmed the downregulation of PAX3, SLC2A1, MSI1, NEFL, RELN, EOMES, EGR1, FOS, and EGR2 during the passage process (Fig. 4D). Among these, EGR1 and FOS are known to be associated with the active state of NSCs, rather than their quiescent state30, and FOS and EGR2 have been identified as crucial for NSC proliferation and long-term maintenance31. These results also supported that in vitro passaging of NSCs mimics age-related decline in NSC functions.

However, unlike the above markers, PROM1 and SOX1 did not show significant differences when comparing passage 1 and 13 cells (Fig. 4E, left). Interestingly, previous studies have shown that LRRK2-G2019S mutant NSCs exhibit accelerated differentiation, leading to a more rapid loss of both proliferative capacity and stemness32. When we specifically compared the mutant NSCs at passage 13 with the other conditions (Fig. 4E, right), we found that PROM1 and SOX1 were downregulated with aging only in the mutant LRRK2 NSCs. This indicates that their expression is generally stable during in vitro aging but specifically affected by the presence of the LRRK2 G2019S mutation. This suggests that aging and the LRRK2 G2019S mutation interact to exacerbate the decline in NSC identity.

Combined effect of LRRK2 mutation and aging on NSCs

To systematically investigate how the LRRK2 G2019S mutation affects the deterioration of NSC integrity during aging, we analyzed differentially expressed genes in mutant NSCs at passage 13, comparing them to other conditions, including mutant NSCs at passage 1 and corrected NSCs at both passages 1 and 13. This analysis revealed 47 upregulated and 24 downregulated genes (Fig. 5A and Supplementary Table S2). Interestingly, we observed that ANXA1, an ERK pathway downstream gene, was significantly upregulated in aged mutant cells, consistent with previous findings in LRRK2 mutant cells18. In contrast, DSP, a marker gene for epithelial state33, was significantly downregulated in aged mutant cells (Fig. 5B).

Fig. 5.

Fig. 5

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Characteristics of aged LRRK2 G2019S mutant NSCs. (A) Volcano plot showing differential gene expression in LRRK2 G2019S mutant NSCs at passage 13 compared to a reference group comprising mutant NSCs at passage 1 and corrected NSCs at passages 1 and 13. (B) Expression levels of ANXA1 and DSP. (C) ORA results highlighting enriched pathways for upregulated genes. (D) Venn diagram (left) illustrating the overlap of upregulated genes involved in the epithelial-mesenchymal transition (EMT) and TGF-β receptor signaling pathways, along with expression levels of SPP1 and THBS1 (right). (E) ORA results highlighting enriched pathways for downregulated genes.

We further explored the biological pathways enriched in aged mutant cells to understand the molecular mechanisms underlying the combined effects of the LRRK2 mutation and aging (Fig. 5C). Pathway enrichment analysis revealed that the upregulated genes in aged mutant cells were enriched in epithelial-mesenchymal transition (EMT), a biological process crucial for the transdifferentiation from epithelial to mesenchymal phenotypes, which is increasingly recognized as part of the aging process34. Additionally, the upregulated genes were enriched in transforming growth factor-beta (TGF-β) receptor signaling pathways, which are known to induce EMT and are closely associated with aging-related disorders35. Among the upregulated genes, SPP1 and THBS1 were identified as common players in both EMT and TGF-β pathways (Fig. 5D). These genes have been shown to facilitate both EMT and TGF-β signaling36–39. On the other hand, downregulated genes in aged mutant cells were enriched in pathways related to dopaminergic neurogenesis and differentiation, highlighting a potential loss of function in NSCs (Fig. 5E). Thus, the combination of aging and the LRRK2 G2019S mutation may disrupt the integrity and self-renewal of NSCs over time, leading to impaired functionality and potential deficits in neurogenesis across passages. Likeness, LRRK2 G2019S isogenic line presented important signatures such as EMT or TGF-β signaling that may affect NSCs integrity in aging. In general, TGF-β is well known as a key player in inducing EMT in cancer cells, and thus is a target for anti-tumor therapy. Therefore, this suggests that blocking TGF-β signaling may preserve NSCs integrity by inhibiting cell transformation.

Discussion

PD is a complex neurodegenerative disorder, with the LRRK2 G2019S mutation being one of the most significant genetic contributors to its pathogenesis40. Despite the functional diversity of LRRK2 across multiple biological processes, its precise role in PD remains unclear41. In our study, we show that the LRRK2 G2019S mutation significantly disrupts key cellular functions in NSCs, particularly affecting ER stress and mitochondrial function, which are critical for protein folding and energy metabolism. Notably, we found that the use of BAC DNA-mediated correction effectively restored these critical cellular functions, highlighting the potential of gene-editing therapies to reverse cellular dysfunction caused by the mutation. Furthermore, our results suggest that aging amplifies the detrimental effects of the LRRK2 G2019S mutation, leading to the activation of pathways such as EMT and TGF-β signaling, while downregulating key genes involved in NSC maintenance. From a drug repositioning perspective, the anticancer effect of TGF-β, which has already been shown to target cancer patients, may be effective in fundamentally maintaining the characteristics of NSCs. Therefore, this may lead to high therapeutic efficacy in preclinical PD models or anti-TGF-β-based clinical trials in the future. The strategy suggests that addressing both genetic mutations and the aging process is crucial for the development of effective PD treatments. The restoration of cellular function following BAC DNA-mediated correction supports further investigation into gene-editing strategies targeting LRRK2 mutations as a promising approach for PD therapy. Referring to other gene-editing strategies and BAC DNA-mediated LRRK2 gene correction in detail, ZFNs and HDAdVs has been useful as a gene correction tool with the advantage that target gene replacement can be achieved economically and efficiently using programmable site-specific nuclease, respectively, and accurate correction of target locus by homologous recombination with homology arm. In comparison, the BAC DNA-mediated gene correction requires some sophisticated manipulation because it requires approximately 100 Kb of homology arm, but the advantage of being able to accurately target the desired locus, and it carries natural chromosomal setting by manipulating with the BAC library, and not only that, it also has the advantage in that it can avoid immune responses caused by helper virus contamination.

Our findings align with and expand upon previous studies linking LRRK2 G2019S mutations to cellular dysfunctions, particularly in ER stress, mitochondrial dynamics, and protein degradation pathways. Increased susceptibility to ER stress has been well-documented in LRRK2 G2019S transgenic mice42, consistent with our observations of downregulated expression of genes involved in protein folding and chaperone activity in mutant cells. LRRK2 mutations have also been shown to exacerbate ER stress through interactions with s such as Thrombospondin 1 (THBS1)/TGF-β43, which is consistent with our findings, where THBS1 was significantly upregulated in aged mutant cells. Additionally, LRRK2-G2019S mutant astrocytes exhibit an increase in the apoptotic ER stress response, typified by PERK signaling44. Our study complements these findings by showing that BAC DNA-mediated correction reduces the activity of the ASK1/MKK7/JNK axis, which is involved in apoptosis. Together, these findings reinforce the link between LRRK2 mutations, chronic ER stress, and Parkinson’s disease PD pathology.

In addition, it has also been demonstrated that LRRK2 mutations impair mitochondrial function, consistent with previous findings of increased susceptibility to mitochondrial damage in LRRK2 G2019S transgenic mice42. This dysfunction is partly linked to the interaction of LRRK2 with DLP1, a key regulator of mitochondrial fission45, and mitochondrial complex I impairment, which leads to oxidative stress and reduced energy production46. This aligns with our observations of decreased oxidative phosphorylation and mitochondrial dysfunction in mutant NSCs. Furthermore, mitophagy, the process of clearing damaged mitochondria, is compromised in LRRK2 mutations, and studies in LRRK2 G2019S knock-in mice have shown that pharmacological interventions can rescue this defect, suggesting the therapeutic potential of targeting mitochondrial quality control in PD47. In particular, recent research has shown that LRRK2 regulates ER-mitochondrial tethering through the PERK-mediated ubiquitination pathway, further connecting LRRK2 mutations to ER stress and mitochondrial dysfunction25.

Importantly, recent studies have highlighted the interconnectedness of ER stress, autophagy, and neurodegeneration in PD, showing how these processes collectively contribute to disease progression48. ER dysfunction disrupts protein folding homeostasis, leading to the misfolding and aggregation of α-synuclein, a defining pathological feature of PD. LRRK2 plays a crucial role in regulating lysosomal function and autophagy49, and its G2019S mutation has been shown to disrupt ER homeostasis, exacerbating proteotoxic stress and impairing the ubiquitin–proteasome system. Our results demonstrate that correcting the LRRK2 G2019S mutation restores cellular homeostasis, including recovery of disrupted autophagy pathways, protein degradation systems, and the ubiquitin–proteasome pathway. In addition, LRRK2 mutations are associated with dysregulation of the ER-mitochondrial contact site, which is known to result in impaired mitochondrial energy metabolism and increased oxidative stress. BAC DNA-based gene correction appears to alleviate these dysfunctions, restoring ER-mitochondrial interactions, reducing oxidative stress, and improving cellular energy metabolism. Additionally, the interaction between LRRK2 kinase and Rab29 is known to influence Golgi-to-plasma membrane recycling50, which aligns with our findings that show BAC DNA correction restored disrupted vesicular trafficking pathways. Together, these findings suggest that LRRK2 G2019S mutations drive NSC dysfunction and cellular aging by impacting multiple interconnected pathways, including mitochondrial dynamics, ER stress, autophagy, and vesicle trafficking. Given the critical role of ER dysfunction in PD pathogenesis, our results further support gene-editing approaches as a potential therapeutic strategy for mitigating ER stress-related neurodegeneration.

Our findings show that the combination of the LRRK2 G2019S mutation and aging significantly impairs NSC integrity, as evidenced by the upregulation of EMT-related genes. Normally, iPSC-derived NSC differentiation is tightly regulated by the inhibition of pathways such as dual SMADs, BMP, and TGF-β, preventing the transition to a mesenchymal phenotype51. However, in mutant aged cells, this inhibitory mechanism may weaken or become bypassed, leading to the upregulation of EMT-related genes. This suggests that the LRRK2 G2019S mutation, in conjunction with aging, impairs regulatory processes that maintain epithelial characteristics in NSCs, allowing EMT-related pathways to become more prominent. Such dysregulation could reduce NSC self-renewal capacity and increase cellular stress, contributing to broader NSC aging processes characterized by changes in cellular phenotype and function driven by both mutations and age-related signaling52. Future studies should explore whether interventions targeting these pathways could restore the balance between epithelial and mesenchymal states in mutant aged NSCs, potentially mitigating the detrimental effects of the LRRK2 G2019S mutation in the context of aging.

In particular, our pathway enrichment analysis revealed that Secreted Phosphoprotein 1 (SPP1) and THBS1 are key players in the activation of the EMT and TGF-β signaling pathways in aged LRRK2 G2019S mutant cells. SPP1 has been shown to promote EMT in colorectal cancer, facilitating metastasis36, and it also enhances TGF-β signaling in fibroblasts through matrix metalloproteinases (MMPs) in dystrophin-deficient muscles37. Similarly, THBS1 has been found to drive EMT in colorectal liver metastasis38 and to activate TGF-β signaling in glioma cells, promoting cell migration39. In addition to these findings, recent studies in Parkinson’s disease models have demonstrated that the LRRK2 G2019S mutation exacerbates ER stress through its interaction with THBS1 and TGF-β1, suggesting that these proteins may also play crucial roles in neurodegeneration43. Notably, inhibiting THBS1 or TGF-β1 has been reported to significantly reduce ER stress and neuronal damage, indicating that targeting these pathways could offer potential therapeutic strategies to prevent neurodegeneration. These findings align with our results, where SPP1 and THBS1 were upregulated in aged mutant NSCs, suggesting that their roles in promoting EMT and TGF-β signaling extend beyond cancer and fibroblasts to NSC dysfunction and aging-related phenotypic changes. This highlights the broader implications of these pathways in driving cellular aging, reducing NSC self-renewal, and impairing neurogenesis. Future studies should target SPP1 and THBS1 as potential therapeutic strategies to mitigate the adverse effects of aging and the LRRK2 mutation on NSC integrity.

One limitation of our study is that, while we identified key pathways affected by the LRRK2 G2019S mutation and aging, the precise molecular mechanisms by which these pathways contribute to NSC dysfunction remain unclear. The candidate genes and pathways whose dysregulation is exacerbated by aging in LRRK2 G2019S NSCs provide useful starting points for in-depth mechanistic research. Future studies should include protein-level and functional assays to verify whether the observed transcript-level changes indeed translate into protein dysregulation and to determine whether these proteins undergo specific post-translational modifications that drive pathophysiology. In addition, employing loss-of-function or gain-of-function approaches for selected candidates in LRRK2 G2019S NSCs will help elucidate direct causal links to ER stress responses or mitochondrial deficits. Collectively, these follow-up experiments will be crucial for capturing the precise molecular mechanisms that connect the LRRK2 G2019S mutation, aging, and NSC dysfunction.

Furthermore, In vivo validation will be essential to fully assess the therapeutic potential of this correction approach within a physiological context. However, publicly available age-stratified transcriptomic datasets for LRRK2 G2019S transgenic or knock-in mouse brains are currently limited. Similarly, brain transcriptomic data from LRRK2-mutant PD patients remain unavailable. This limitation makes direct in vivo validation through comparative transcriptomic analysis challenging at this stage. Despite these constraints, our study establishes a critical foundation for future investigations, as longitudinal in vivo transcriptomic analyses in age-matched LRRK2 G2019S animal models will be essential to confirm the progressive molecular changes observed in our NSC model. In addition, in vivo transplantation studies using BAC DNA-corrected NSCs in LRRK2 G2019S models, focusing on long-term efficacy through the integration of corrected cells into neuronal networks and their functional contributions to brain health, will be crucial for assessing the overall success of this approach in treating PD. Taken together, these future directions will be pivotal in bridging the gap between in vitro findings and in vivo disease mechanisms, ultimately advancing the development of targeted therapeutic strategies for LRRK2-associated PD.

Methods

Induction towards neural stem cells

Both LRRK2 G2019S-mutant iPSCs and gene-corrected iPSCs were maintained in mTeSR1 medium on Matrigel-coated plates. These iPSCs were induced toward neural stem cells as previously reported46,47. Briefly, the iPSC colonies were detached by collagenase A treatment and incubated for 6 h in DMEM/F12 supplemented with 2% B27 (without vitamin A, 12587-010 Gibco), 1% N-2 (17502-048 Gibco), 10 μM Y-27632 (Tocris Biochem), 500 ng/ml noggin (120-10C Peprotech), 20 μM SB431542 (S4317-5MG Sigma), and 2 ng/ml bFGF (Peprotech) in non-adherent conditions. Cells were plated on Poly-L-Ornithine/Laminin (P4638-1G Sigma; L2020-1MG Sigma) coated dishes and cultured for 10 days in the same medium as above. On day 11, cells were detached mechanically, re-plated on Poly-L-Ornithine/Laminin-coated dishes, and cultured in neural induction medium containing DMEM/F12 and neurobasal medium in 1:1 ratio supplemented with 2% B27, 1% N-2, 0.5% Glutamax (35050-038 Gibco), 10 ng/ml epidermal growth factor (EGF; AF-100-15 Peprotech), and 10 ng/ml bFGF. The cells were mechanically passaged and maintained in neural induction medium until analysis. At the end of passages 1, 2 and 13, cells were lysed and total RNA was extracted using the RNeasy Mini Kit (QIAGEN) according to the manufacturer’s protocol.

RNA-seq data acquisition

Library construction was performed using the QuantSeq 3 mRNA-Seq Library Prep Kit (Lexogen, Inc., Vienna, Austria) following the provided guidelines. Total RNA was prepared and hybridized with an oligo-dT primer containing an Illumina-compatible sequence, followed by reverse transcription. RNA template degradation preceded the initiation of second-strand synthesis by using a random primer with an Illumina-compatible linker. After purifying the double-stranded library to eliminate reaction components, PCR amplification introduced the necessary adapter sequences for cluster generation, with a final library purification from the PCR materials. High-throughput sequencing was performed as single-end 75 sequencing using a NextSeq 550 (Illumina, Inc., San Diego, CA, USA).

Differential expressed gene analysis

Gene expression analysis was conducted in R (v4.3.3) using the edgeR package (v4.0.16). Lowly expressed genes were filtered out with the filterByExpr function to retain genes with sufficient expression across samples. Differential expression analysis between groups was performed, and P-values were adjusted for multiple comparisons using the False Discovery Rate (FDR) method. Gene expression levels were normalized and quantified as Transcripts Per Million (TPM) to facilitate comparisons across samples.

Quantitative real-time PCR

Cellular RNA was isolated using the RNeasy Mini Kit (QIAGEN) according to the manufacturer’s instructions. cDNA was synthesized from 2 µg of total RNA using the Superscript III First Strand Synthesis System for RT-PCR (Invitrogen), and cDNA was diluted to a constant concentration. Quantitative PCR was carried out using Power SYBR Green PCR Master Mix (Applied Biosystems) and a QuantStudio™ 6 Flex real-time PCR System (Applied Biosystems) under the following conditions: 40 cycles of DNA denaturation at 95 °C for 5 s, DNA annealing with each primer pair at 55–60 °C for 30 s, and polymerization at 72 °C for 30 s. The average Ct value for each gene was determined and normalized with the GAPDH gene. The sequences of the primers are as follows: DDOSTF, 5´-TGCGGGATTGAGTTTGACGA-3´; DDOSTR, 5´- AGCAGGTTCTCAGTGTCAGC-3´; MAP3K5F, 5´-GGTGCAAAGCGAAGGACAAG-3´; MAP3K5R, 5´-GAAGCTCCATGGTCTCTGCT-3´; SPP1F, 5´-AGCAGAATCTCCTAGCCCCA-3´; SPP1R, 5´-TGGTCATGGCTTTCGTTGGA-3´; THBS1F, 5´-CACTCTGGCCAGGTCTTCAG-3´; THBS1R, 5´-GGTTGCCAGGAGAGCTTCTT-3´.

KEGG pathway analysis

We utilized the pathview (v.1.42.0) package in R to visualize fold changes in gene expression within the context of KEGG pathways. The log2 fold change values from the DESeq2 differential expression analysis were used as input for the visualization. Gene symbols were employed as the gene identifier, and the analysis was performed for the human KEGG pathways. For this study, we focused on the KEGG pathway "Protein processing in endoplasmic reticulum" (KEGG pathway ID: 04141).

Gene set enrichment analysis

Gene set enrichment analysis (GSEA) were performed using the fgsea (v.1.28.0) package in R. Four gene sets from MSigDB were utilized, each corresponding to different pathway collections: Hallmark gene sets (h.all.v7.2.symbols.gmt), Gene Ontology (GO) biological processes (c5.go.bp.v7.2.symbols.gmt), Curated gene sets (c2.cp.v7.2.symbols.gm), Oncogenic signatures (c6.all.v7.2.symbols.gmt). For each of the gene sets, GSEA was performed on the differential expression analysis results using pre-ranked gene statistics. Specifically, the log fold change statistics from the DESeq2 analysis were used as input for the fgsea function. The following parameters were applied: minimum gene set size of 5, maximum gene set size of 500, and 10,000 permutations for each analysis.

Over-representation analysis

To investigate functional enrichment in the gene expression data, we performed over-representation analysis (ORA) on lists of specifically upregulated and downregulated genes. ORA was conducted using the Enrichr tool with curated databases, including with ‘MSigDB Hallmark 2020’, ‘WikiPathways 2019 Human’, and ‘GO Biological Process 2018’. The significance of enrichment for each term was quantified as −log10 (adjusted P-value).

Supplementary Information

Supplementary Information 1. (619.3KB, xlsx)
Supplementary Information 2. (173.7KB, docx)

Acknowledgements

This work was funded by Korea Institute of Oriental Medicine, KSN2213010 and KSN1621131. This work was supported by BK21 FOUR Program by Chungnam National University Research Grant, 2024.

Author contributions

D.K., S.P., S.C. wrote the main manuscript text, S.L. performed experiments; D.K., S.P., S.C. analyzed and interpreted the data, S.C. conceived and designed the experiments. All authors reviewed the manuscript.

Data availability

The RNA-seq datasets generated and analyzed in this study will be available in the gene expression omnibus (GEO) repository under accession number GSE183499.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Doyeong Kim and Sang-Min Park have equally contributed to this work.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-96884-w.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information 1. (619.3KB, xlsx)
Supplementary Information 2. (173.7KB, docx)

Data Availability Statement

The RNA-seq datasets generated and analyzed in this study will be available in the gene expression omnibus (GEO) repository under accession number GSE183499.

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