Decoding Parkinson's disease - iPSC-derived models in the OMICs era

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

From Lysosomal Storage Disorders to Parkinson's Disease - Challenges and Opportunities

Lysosomes are specialized organelles with an acidic pH that act as recycling hubs for intracellular and extracellular components. They harbour numerous different hydrolytic enzymes to degrade substrates like proteins, peptides, and glycolipids. Reduced catalytic activity of lysosomal enzymes can cause the accumulation of these substrates and loss of lysosomal integrity, resulting in lysosomal dysfunction and lysosomal storage disorders (LSDs). Post-mitotic cells, such as neurons, seem to be highly sensitive to damages induced by lysosomal dysfunction, thus LSDs often manifest with neurological symptoms. Interestingly, some LSDs and Parkinson's disease (PD) share common cellular pathomechanisms, suggesting convergence of aetiology of the two disease types. This is further underlined by genetic associations of several lysosomal genes involved in LSDs with PD. The increasing number of lysosome-associated genetic risk factors for PD makes it necessary to understand functions and interactions of lysosomal proteins/enzymes both in health and disease, thereby holding the potential to identify new therapeutic targets. In this review, we highlight genetic and mechanistic interactions between the complex lysosomal network, LSDs and PD, and elaborate on methodical challenges in lysosomal research.

Druggable transcriptomic pathways revealed in Parkinson's patient-derived midbrain neurons

Complex genetic predispositions accelerate the chronic degeneration of midbrain substantia nigra neurons in Parkinson’s disease (PD). Deciphering the human molecular makeup of PD pathophysiology can guide the discovery of therapeutics to slow the disease progression. However, insights from human postmortem brain studies only portray the latter stages of PD, and there is a lack of data surrounding molecular events preceding the neuronal loss in patients. We address this gap by identifying the gene dysregulation of live midbrain neurons reprogrammed in vitro from the skin cells of 42 individuals, including sporadic and familial PD patients and matched healthy controls. To minimize bias resulting from neuronal reprogramming and RNA-seq methods, we developed an analysis pipeline integrating PD transcriptomes from different RNA-seq datasets (unsorted and sorted bulk vs. single-cell and Patch-seq) and reprogramming strategies (induced pluripotency vs. direct conversion). This PD cohort’s transcriptome is enriched for human genes associated with known clinical phenotypes of PD, regulation of locomotion, bradykinesia and rigidity. Dysregulated gene expression emerges strongest in pathways underlying synaptic transmission, metabolism, intracellular trafficking, neural morphogenesis and cellular stress/immune responses. We confirmed a synaptic impairment with patch-clamping and identified pesticides and endoplasmic reticulum stressors as the most significant gene-chemical interactions in PD. Subsequently, we associated the PD transcriptomic profile with candidate pharmaceuticals in a large database and a registry of current clinical trials. This study highlights human transcriptomic pathways that can be targeted therapeutically before the irreversible neuronal loss. Furthermore, it demonstrates the preclinical relevance of unbiased large transcriptomic assays of reprogrammed patient neurons.