Single-Cell Transcriptomics of Parkinson's Disease Human In Vitro Models Reveals Dopamine Neuron-Specific Stress Responses

Targeting α-Synuclein in Parkinson's Disease by Induced Pluripotent Stem Cell Models

Parkinson's disease (PD) is a progressive, neurodegenerative disorder characterized by motor and non-motor symptoms. To date, no specific treatment to halt disease progression is available, only medication to alleviate symptoms can be prescribed. The main pathological hallmark of PD is the development of neuronal inclusions, positive for α-synuclein (α-syn), which are termed Lewy bodies (LBs) or Lewy neurites. However, the cause of the inclusion formation and the loss of neurons remain largely elusive. Various genetic determinants were reported to be involved in PD etiology, including SNCA, DJ-1, PRKN, PINK1, LRRK2, and GBA. Comprehensive insights into pathophysiology of PD critically depend on appropriate models. However, conventional model organisms fall short to faithfully recapitulate some features of this complex disease and as a matter-of-fact access to physiological tissue is limiting. The development of disease models replicating PD that are close to human physiology and dynamic enough to analyze the underlying molecular mechanisms of disease initiation and progression, as well as the generation of new treatment options, is an important and overdue step. Recently, the establishment of induced pluripotent stem cell (iPSC)-derived neural models, particularly from genetic PD-variants, developed into a promising strategy to investigate the molecular mechanisms regarding formation of inclusions and neurodegeneration. As these iPSC-derived neurons can be generated from accessible biopsied samples of PD patients, they carry pathological alterations and enable the possibility to analyze the differences compared to healthy neurons. This review focuses on iPSC models carrying genetic PD-variants of α-syn that will be especially helpful in elucidating the pathophysiological mechanisms of PD. Furthermore, we discuss how iPSC models can be instrumental in identifying cellular targets, potentially leading to the development of new therapeutic treatments. We will outline the enormous potential, but also discuss the limitations of iPSC-based α-syn models.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Are Lysosomes Potential Therapeutic Targets for Parkinson's Disease?

Parkinson´s Disease (PD) is the second most common neurodegenerative disorder, affecting ~2-3% of the population over 65 years old. In addition to progressive degeneration of nigrostriatal neurons, the histopathological feature of PD is the accumulation of misfolded α-synuclein protein in abnormal cytoplasmatic inclusions, known as Lewy Bodies (LBs). Recently, Genome-Wide Association Studies (GWAS) have indicated a clear association of variants within several lysosomal genes with risk for PD. Newly evolving data have been shedding light on the relationship between lysosomal dysfunction and alpha-synuclein aggregation. Defects in lysosomal enzymes could lead to the insufficient clearance of neurotoxic protein materials, possibly leading to selective degeneration of dopaminergic neurons. Specific modulation of lysosomal pathways and their components could be considered a novel opportunity for therapeutic intervention for PD. The purpose of this review is to illustrate lysosomal biology and describe the role of lysosomal dysfunction in PD pathogenesis. Finally, the most promising novel therapeutic approaches designed to modulate lysosomal activity, as a potential disease-modifying treatment for PD will be highlighted.

Identification of ASCL1 as a determinant for human iPSC-derived dopaminergic neurons

During cellular specification, transcription factors orchestrate cellular decisions through gene regulation. By hijacking these transcriptional networks, human pluripotent stem cells (hPSCs) can be specialized into neurons with different molecular identities for the purposes of regenerative medicine and disease modeling. However, molecular fine tuning cell types to match their in vivo counterparts remains a challenge. Directing cell fates often result in blended or incomplete neuron identities. A better understanding of hPSC to neuron gene regulation is needed. Here, we used single cell RNA sequencing to resolve some of these graded molecular identities during human neurogenesis from hPSCs. Differentiation platforms were established to model neural induction from stem cells, and we characterized these differentiated cell types by 10x single cell RNA sequencing. Using single cell trajectory and co-expression analyses, we identified a co-regulated transcription factor module expressing achaete-scute family basic helix-loop-helix transcription factor 1 (ASCL1) and neuronal differentiation 1 (NEUROD1). We then tested the function of these transcription factors in neuron subtype differentiation by gene knockout in a novel human system that reports the expression of tyrosine hydroxylase (TH), the rate limiting enzyme in dopamine synthesis. ASCL1 was identified as a necessary transcription factor for regulating dopaminergic neurotransmitter selection.

Single-cell Transcriptional Changes in Neurodegenerative Diseases

In recent decades, our understanding of the molecular changes involved in neurodegenerative diseases has been transformed. Single-cell RNA sequencing and single-nucleus RNA sequencing technologies have been applied to provide cellular and molecular details of the brain at the single-cell level. This has expanded our knowledge of the central nervous system and provided insights into the molecular vulnerability of brain cell types and underlying mechanisms in neurodegenerative diseases. In this review, we highlight the recent advances and findings related to neurodegenerative diseases using these cutting-edge technologies.

Integration of functional genomics data to uncover cell type-specific pathways affected in Parkinson's disease

Parkinson's disease (PD) is the second most prevalent late-onset neurodegenerative disorder worldwide after Alzheimer's disease for which available drugs only deliver temporary symptomatic relief. Loss of dopaminergic neurons (DaNs) in the substantia nigra and intracellular alpha-synuclein inclusions are the main hallmarks of the disease but the events that cause this degeneration remain uncertain. Despite cell types other than DaNs such as astrocytes, microglia and oligodendrocytes have been recently associated with the pathogenesis of PD, we still lack an in-depth characterisation of PD-affected brain regions at cell-type resolution that could help our understanding of the disease mechanisms. Nevertheless, publicly available large-scale brain-specific genomic, transcriptomic and epigenomic datasets can be further exploited to extract different layers of cell type-specific biological information for the reconstruction of cell type-specific transcriptional regulatory networks. By intersecting disease risk variants within the networks, it may be possible to study the functional role of these risk variants and their combined effects at cell type- and pathway levels, that, in turn, can facilitate the identification of key regulators involved in disease progression, which are often potential therapeutic targets.

Molecular signatures from multi-omics of autism spectrum disorders and schizophrenia

The genetic and phenotypic heterogeneity of autism spectrum disorder (ASD) impedes the unification of multiple biological hypotheses in an attempt to explain the complex features of ASD, such as impaired social communication, social interaction deficits, and restricted and repetitive patterns of behavior. However, recent psychiatric genetic studies have identified numerous risk genes and chromosome loci (copy number variation: CNV) which enable us to analyze at the single gene level and utilize system-level approaches. In this review, we focus on ASD as a major neurodevelopmental disorder and review recent findings mainly from the bioinformatics of omics studies. Additionally, by comparing these data with other major psychiatric disorders, including schizophrenia (SCZ), we identify unique characteristics of both diseases from multiple enrichment, pathway, and protein-protein interaction networks (PPIs) analyses using susceptible genes found in recent large-scale genetic studies. These unified, systematic approaches highlight unique characteristics of both disorders from multiple aspects and demonstrate how convergent pathways can contribute to an understanding of the complex etiology of such neurodevelopmental and neuropsychiatric disorders.

Uncovering the impact of noncoding variants in neurodegenerative brain diseases

Neurodegenerative brain diseases (NBDs) are characterized by cognitive decline and movement impairments caused by neuronal loss in different brain regions. A large fraction of the genetic heritability of NBDs is not explained by the current known mutations. Genome-wide association studies identified novel disease-risk loci, adding to the genetic basis of NBDs. Many of the associated variants reside in noncoding regions with distinct molecular functions. Genetic variation in these regions can alter functions and contribute to disease pathogenesis. Here, we discuss noncoding variants associated with NBDs. Methods for better functional interpretation of noncoding variation will expand our knowledge of the genetic architecture of NBDs and broaden the routes for therapeutic strategies.

The transcription factor BCL11A defines distinct subsets of midbrain dopaminergic neurons

Midbrain dopaminergic (mDA) neurons are diverse in their projection targets, effect on behavior, and susceptibility to neurodegeneration. Little is known about the molecular mechanisms establishing this diversity during development. We show that the transcription factor BCL11A is expressed in a subset of mDA neurons in the developing and adult murine brain and in a subpopulation of pluripotent-stem-cell-derived human mDA neurons. By combining intersectional labeling and viral-mediated tracing, we demonstrate that Bcl11a-expressing mDA neurons form a highly specific subcircuit within the murine dopaminergic system. In the substantia nigra, the Bcl11a-expressing mDA subset is particularly vulnerable to neurodegeneration upon α-synuclein overexpression or oxidative stress. Inactivation of Bcl11a in murine mDA neurons increases this susceptibility further, alters the distribution of mDA neurons, and results in deficits in skilled motor behavior. In summary, BCL11A defines mDA subpopulations with highly distinctive characteristics and is required for establishing and maintaining their normal physiology.

Human inducible pluripotent stem cells: Realization of initial promise in drug discovery

Over the course of the last decade, the biopharmaceutical industry has slowly adopted human inducible pluripotent stem cell (hiPSC) technology to enable the development of humanized model systems to test new therapeutic molecules and drug modalities. The adoption of hiPSC-based models by the industry has increased appreciably in the past 3-5 years. This increase has paralleled the explosion in availability of high-quality human genetic data to mine for new drug targets and the emergence of human-specific therapeutic modalities.

Dopamine Transporter Is a Master Regulator of Dopaminergic Neural Network Connectivity

Dopaminergic neurons of the substantia nigra pars compacta (SNC) and ventral tegmental area (VTA) exhibit spontaneous firing activity. The dopaminergic neurons in these regions have been shown to exhibit differential sensitivity to neuronal loss and psychostimulants targeting dopamine transporter. However, it remains unclear whether these regional differences scale beyond individual neuronal activity to regional neuronal networks. Here, we used live-cell calcium imaging to show that network connectivity greatly differs between SNC and VTA regions with higher incidence of hub-like neurons in the VTA. Specifically, the frequency of hub-like neurons was significantly lower in SNC than in the adjacent VTA, consistent with the interpretation of a lower network resilience to SNC neuronal loss. We tested this hypothesis, in DAT-cre/loxP-GCaMP6f mice of either sex, when activity of an individual dopaminergic neuron is suppressed, through whole-cell patch clamp electrophysiology, in either SNC or VTA networks. Neuronal loss in the SNC increased network clustering, whereas the larger number of hub-neurons in the VTA overcompensated by decreasing network clustering in the VTA. We further show that network properties are regulatable via a dopamine transporter but not a D2 receptor dependent mechanism. Our results demonstrate novel regulatory mechanisms of functional network topology in dopaminergic brain regions.SIGNIFICANCE STATEMENT In this work, we begin to untangle the differences in complex network properties between the substantia nigra pars compacta (SNC) and VTA, that may underlie differential sensitivity between regions. The methods and analysis employed provide a springboard for investigations of network topology in multiple deep brain structures and disorders.

Employing core regulatory circuits to define cell identity

The interplay between extrinsic signaling and downstream gene networks controls the establishment of cell identity during development and its maintenance in adult life. Advances in next-generation sequencing and single-cell technologies have revealed additional layers of complexity in cell identity. Here, we review our current understanding of transcription factor (TF) networks as key determinants of cell identity. We discuss the concept of the core regulatory circuit as a set of TFs and interacting factors that together define the gene expression profile of the cell. We propose the core regulatory circuit as a comprehensive conceptual framework for defining cellular identity and discuss its connections to cell function in different contexts.

The evolution of the concept of stress and the framework of the stress system

Stress is a central concept in biology and has now been widely used in psychological, physiological, social, and even environmental fields. However, the concept of stress was cross-utilized to refer to different elements of the stress system including stressful stimulus, stressor, stress response, and stress effect. Here, we summarized the evolution of the concept of stress and the framework of the stress system. We find although the concept of stress is developed from Selye's "general adaptation syndrome", it has now expanded and evolved significantly. Stress is now defined as a state of homeostasis being challenged, including both system stress and local stress. A specific stressor may potentially bring about specific local stress, while the intensity of stress beyond a threshold may commonly activate the hypothalamic-pituitary-adrenal axis and result in a systematic stress response. The framework of the stress system indicates that stress includes three types: sustress (inadequate stress), eustress (good stress), and distress (bad stress). Both sustress and distress might impair normal physiological functions and even lead to pathological conditions, while eustress might benefit health through hormesis-induced optimization of homeostasis. Therefore, an optimal stress level is essential for building biological shields to guarantee normal life processes.

Single-Cell RNA Sequencing in Parkinson's Disease

Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson's disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global view of cellular composition and phenotype of PD at the single-cell resolution. Here, we reviewed recent sc/snRNA-seq efforts that have successfully characterized diverse cell-type populations and identified cell type-specific disease associations in PD. We also examined how these studies have employed computational and analytical tools to analyze and interpret the rich information derived from sc/snRNA-seq. Finally, we highlighted important limitations and emerging technologies for addressing key technical challenges currently limiting the integration of new findings into clinical practice.

Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons

Advances in single cell genomics and transcriptomics have shown that at tissue level there is complex cellular heterogeneity. To understand the effect of this inter-cell heterogeneity on metabolism it is essential to develop a single cell lipid profiling approach that allows the measurement of lipids in large numbers of single cells from a population. This will provide a functional readout of cell activity and membrane structure. Using liquid extraction surface analysis coupled with high-resolution mass spectrometry we have developed a high-throughput method for untargeted single cell lipid profiling. This technological advance highlighted the importance of cellular heterogeneity in the functional metabolism of individual human dopamine neurons, suggesting that A53T alpha-synuclein (SNCA) mutant neurons have impaired membrane function. These results demonstrate that this single cell lipid profiling platform can provide robust data that will expand the frontiers in biomedical research.