Neuronal death signaling pathways triggered by mutant LRRK2

Doubly Constrained C-terminal of Roc (COR) Domain-Derived Peptides Inhibit Leucine-Rich Repeat Kinase 2 (LRRK2) Dimerization

Missense mutations along the leucine-rich repeat kinase 2 (LRRK2) protein are a major contributor to Parkinson's Disease (PD), the second most commonly occurring neurodegenerative disorder worldwide. We recently reported the development of allosteric constrained peptide inhibitors that target and downregulate LRRK2 activity through disruption of LRRK2 dimerization. In this study, we designed doubly constrained peptides with the objective of inhibiting C-terminal of Roc (COR)-COR mediated dimerization at the LRRK2 dimer interface. We show that the doubly constrained peptides are cell-permeant, bind wild-type and pathogenic LRRK2, inhibit LRRK2 dimerization and kinase activity, and inhibit LRRK2-mediated neuronal apoptosis, and in contrast to ATP-competitive LRRK2 kinase inhibitors, they do not induce the mislocalization of LRRK2 to skein-like structures in cells. This work highlights the significance of COR-mediated dimerization in LRRK2 activity while also highlighting the use of doubly constrained peptides to stabilize discrete secondary structural folds within a peptide sequence.

Homozygous mutation of the LRRK2 ROC domain as a novel genetic model of parkinsonism

Background

Parkinson’s disease (PD) is one of the most important neurodegenerative disorders in elderly people. Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are found in a large proportion of the patients with sporadic and familial PD. Mutations can occur at different locations in the LRRK2. Patients with LRRK2 ROC-COR mutations face an increased risk of typical motor symptoms of PD, along with cognitive decline. An animal model with a monogenic LRRK2 gene mutation is a suitable model for exploring the pathophysiology of PD and identifying potential drug therapies. However, the effect of homozygous (HOM) LRRK2 in PD pathophysiology is unclear.

Methods

We established human LRRK2 (hLRRK2) R1441G HOM transgenic (Tg) mice to explore the phenotype and pathological features that are associated with hLRRK2 R1441G Tg mouse models and discuss the potential clinical relevance. The open field test (OFT) was performed to examine motor and nonmotor behaviors. A CatWalk analysis system was used to study gait function. [¹⁸F]FDOPA PET was used to investigate functional changes in the nigrostriatal pathway in vivo. Transmission electron microscopy was used to examine the morphological changes in mitochondria and lysosomes in the substantia nigra.

Results

The R1441G HOM Tg mice demonstrated gait disturbance and exhibited less anxiety-related behavior and exploratory behavior than mice with hLRRK2 at 12 months old. Additionally, [¹⁸F]FDOPA PET showed a reduction in FDOPA uptake in the striatum of the HOM Tg mice. Notably, there was significant lysosome and autophagosome accumulation in the cytoplasm of dopaminergic neurons in R1441G hemizygous (HEM) and HOM mice. Moreover, it was observed using transmission electron microscopy (TEM) that the mitochondria of R1441G Tg mice were smaller than those of hLRRK2 mice.

Conclusion

This animal provides a novel HOM hLRRK2 R1441G Tg mouse model that reproduces some phenotype of Parkinsonism in terms of both motor and behavioral dysfunction. There is an increased level of mitochondrial fission and no change in the fusion process in the group of HOM hLRRK2 R1441G Tg mouse. This mutant animal model of PD might be used to study the mechanisms of mitochondrial dysfunction and explore potential new drug targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12929-022-00844-9.

Identification of Targets from LRRK2 Rescue Phenotypes

Parkinson’s disease (PD) is an age-dependent neurodegenerative condition. Leucine-rich repeat kinase 2 (LRRK2) mutations are the most frequent cause of sporadic and autosomal dominant PD. The exact role of LRRK2 protective variants (R1398H, N551K) together with a pathogenic mutant (G2019S) in aging and neurodegeneration is unknown. We generated the following myc-tagged UAS-LRRK2 transgenic Drosophila: LRRK2 (WT), N551K, R1398H, G2019S single allele, and double-mutants (N551K/G2019S or R1398H/G2019S). The protective variants alone were able to suppress the phenotypic effects caused by the pathogenic LRRK2 mutation. Next, we conducted RNA-sequencing using mRNA isolated from dopaminergic neurons of these different groups of transgenic Drosophila. Using pathway enrichment analysis, we identified the top 10 modules (p < 0.05), with “LRRK2 in neurons in Parkinson’s disease” among the candidates. Further dissection of this pathway identified the most significantly modulated gene nodes such as eEF1A2, ACTB, eEF1A, and actin cytoskeleton reorganization. The induction of the pathway was successfully restored by the R1398H protective variant and R1398H-G2019S or N551K-G2019S rescue experiments. The oxidoreductase family of genes was also active in the pathogenic mutant and restored in protective and rescue variants. In summary, we provide in vivo evidence supporting the neuroprotective effects of LRRK2 variants. RNA sequencing of dopaminergic neurons identified upregulation of specific gene pathways in the Drosophila carrying the pathogenic variant, and this was restored in the rescue phenotypes. Using protective gene variants, our study identifies potential new targets and provides proof of principle of a new therapeutic approach that will further our understanding of aging and neurodegeneration in PD.

Translational Informatics for Parkinson's Disease: from Big Biomedical Data to Small Actionable Alterations

Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.