LRRK2 Gly2019Ser Mutation Promotes ER Stress via Interacting with THBS1/TGF‐β1 in Parkinson's Disease

Abstract The gene mutations of LRRK2, which encodes leucine‐rich repeat kinase 2 (LRRK2), are associated with one of the most prevalent monogenic forms of Parkinson's disease (PD). However, the potential effectors of the Gly2019Ser (G2019S) mutation remain unknown. In this study, the authors investigate the effects of LRRK2 G2019S on endoplasmic reticulum (ER) stress in induced pluripotent stem cell (iPSC)‐induced dopamine neurons and explore potential therapeutic targets in mice model. These findings demonstrate that LRRK2 G2019S significantly promotes ER stress in neurons and mice. Interestingly, inhibiting LRRK2 activity can ameliorate ER stress induced by the mutation. Moreover, LRRK2 mutation can induce ER stress by directly interacting with thrombospondin‐1/transforming growth factor beta1 (THBS1/TGF‐β1). Inhibition of LRRK2 kinase activity can effectively suppress ER stress and the expression of THBS1/TGF‐β1. Knocking down THBS1 can rescue ER stress by interacting with TGF‐β1 and behavior burden caused by the LRRK2 mutation, while suppression of TGF‐β1 has a similar effect. Overall, it is demonstrated that the LRRK2 mutation promotes ER stress by directly interacting with THBS1/TGF‐β1, leading to neural death in PD. These findings provide valuable insights into the pathogenesis of PD, highlighting potential diagnostic markers and therapeutic targets.


Figure S3
. WGCNA evaluated the genes that had varied expression patterns.Different databases contribute to the overall number of genes differently, with varying degrees of database overlap (Supplementary Figure 3A and 3B) (Supplementary Table 1).The 607 DEGs were hierarchically classified into 18 categories using WGCNA analysis,respectively: brown2,firebrick4,darkgreen,coral2,greenyellow,lightsteelblue,darkolivegreen4,darkred,darkolivegreen,brown4,yellow4,darkseagreen4,plum2,lightyellow,lightcoral,darkorange,royalblue,darkgrey,and black (Supplementary Figure 3C).The horizontal axis was the network's average connectivity (Supplementary Figure 3D), and the vertical axis was the scale-free topology fitting index R^2 (the values in the SFT.R.Sq column in the statistical data) (Supplementary Figure 3E).As a consequence of respringing the cluster tree in the heat map, we detected 18 modules of association between module attributes and the tree diagram of gene expression (Supplementary Figure 3F).The relationship of modules and a phenotype heat map was exhibited in the grouping of LRRK2 wild and mutation.The blue module showed the most robust inverse link with the LRRK2 mutation phenotype.(Supplementary Figure 3G).A tree of all gene expressions was created using 1-TOM cluster.D. The weight is represented by Soft Threshold (Power), while the vertical axis shows the network's average connectivity.E. Soft Threshold (Power) stands for the weight, and the scale-free topology fitting index R^2 is indicated on the vertical axis.F. The heat maps of module correlations display samples and genes in each cell, along with P values and correlation coefficients.G. Genes and samples are classified into PD and control correlations between modules in the heat maps, with correlation coefficients and P values in each cell.

Figure S1 .
Figure S1.The neuronal apoptosis level was assessed using flow cytometry analysis (a), and the percentage of apoptotic cells in the total neuronal population was calculated (b).Data were presented as means ± sd.The experiments were carried out three times (n=3).One-way ANOVA followed by Tukey's multiple comparison test in B. The difference in folds is statistically significant.**P < 0.01.
Figure S3.WGCNA analysis the genes which expressed differentially.A-B.The Venn diagrams of the four datasets.C. A tree of all gene expressions was created using 1-TOM cluster.D. The weight is represented by Soft Threshold (Power), while the vertical axis shows the network's average connectivity.E. Soft Threshold (Power) stands for the weight, and the scale-free topology fitting index R^2 is indicated on the vertical axis.F. The heat maps of module correlations display samples and genes in each cell, along with P values and correlation coefficients.G. Genes and samples are classified into PD and control correlations between modules in the heat maps, with correlation coefficients and P values in each cell.

Figure S4 .Figure S5 .Figure S6 .Figure S8 .Figure S10 .
Figure S4.The PPI network reveals interacting proteins.The STRING online tool constructed a PPI network for the genes in DEGs.There were more than 600 protein-protein interactions.

Figure S11 .
Figure S11.Two-dimensional interaction map of LRRK2 and THBS1.The "T chain" refers to THBS1, and the "L chain" refers to LRRK2.The rod-like structures represent the interacting amino acid residues.In the red-black diagram, the red dashed lines represent salt bridge interactions, while the green dashed lines represent hydrogen bond interactions.For example, a salt bridge interaction occurs between the negatively charged ASP1274 in LRRK2 and the positively charged LYS561 in THBS1 protein.

Figure S12 .
Figure S12.Two-dimensional interaction map of THBS1 and TGF-β1.The "T chain" represents THBS1, and the "H chain" represents TGF-β1.The rod-like structures represent the interacting amino acid residues.In the red-black diagram, the red dashed lines represent salt bridge interactions, while the green dashed lines represent hydrogen bond interactions.