Biology subjects

Athauda, D.

Publications and source records attributed to Athauda, D..

8 recordsLinked to original sources

bioRxiv2024

The diversity of SNCA transcripts in neurons, and its impact on antisense oligonucleotide therapeutics

The role of the SNCA gene locus in driving Parkinsons disease (PD) through rare and common genetic variation is well-recognized, but the transcriptional diversity of SNCA in vulnerable cell types remains unclear. We performed SNCA long-read RNA sequencing in human dopaminergic neurons and show that annotated SNCA transcripts account for only 5% of expression. Rather, the majority of expression (75%) at the SNCA locus originates from transcripts with alternative 5 and 3 untranslated regions. Importantly, 10% originates from transcripts encoding open reading frames not previously annotated, which are translated and detectable in human postmortem brain. Defining the 3 untranslated regions enabled the rational design of antisense oligonucleotides targeting the majority of SNCA transcripts, leading to the effective reversal of PD pathology, including protein aggregation, mitochondrial dysfunction, and toxicity. Resolving the complexity of the SNCA transcriptional landscape impacts RNA therapies and highlights differences in protein isoforms and their contribution to disease.

neuroscience↗

bioRxiv2024

Alpha-synuclein aggregates trigger anti-viral immune pathways and RNA editing in human astrocytes

RNA editing is a post transcriptional mechanism that targets changes in RNA transcripts to modulate innate immune responses. We report the role of astrocyte specific, ADAR1 mediated RNA editing in neuroinflammation in Parkinsons disease. We generated hiPSC-derived astrocytes, neurons and co-cultures and exposed them to small soluble alpha-synuclein aggregates. Oligomeric alpha-synuclein triggered an inflammatory glial state associated with TLR activation, viral responses, and cytokine secretion. This reactive state resulted in loss of neurosupportive functions, and the induction of neuronal toxicity. Notably, interferon response pathways were activated leading to upregulation, and isoform switching of the RNA deaminase enzyme, ADAR1. ADAR1 mediates A-to-I RNA editing, and increases in RNA editing were observed in inflammatory pathways in cells, as well as in post-mortem human PD brain. Aberrant, or dysregulated, ADAR1 responses and RNA editing may lead to sustained inflammatory reactive states in astrocytes triggered by alpha-synuclein aggregation, and this may drive the neuroinflammatory cascade in Parkinsons.

neuroscience↗

bioRxiv2024

GLP-1 receptor agonism ameliorates Parkinsons disease through modulation of neuronal insulin signalling and glial suppression

Neuronal insulin resistance is linked to the pathogenesis of Parkinsons disease through unclear, but potentially targetable, mechanisms. We delineated neuronal and glial mechanisms of insulin resistance and glucagon-like 1 peptide (GLP-1) receptor agonism in human iPSC models of synucleinopathy, and corroborated our findings in patient samples from a Phase 2 trial of a GLP-1R agonist in Parkinsons (NCT01971242). Human iPSC models of synucleinopathy exhibit neuronal insulin resistance and dysfunctional insulin signalling, which is associated with inhibition of the neuroprotective Akt pathways, and increased expression of the MAPK-associated p38 and JNK stress pathways. Ultimately, this imbalance is associated with cellular stress, impaired proteostasis, accumulation of -synuclein, and neuronal loss. The GLP-1R agonist exenatide led to restoration of insulin signalling, associated with restoration of Akt signalling and suppression of the MAPK pathways in neurons. GLP-1R agonism reverses the neuronal toxicity associated with the synucleinopathy, through reduction of oxidative stress, improved mitochondrial and lysosomal function, reduced aggregation of -synuclein, and enhanced neuronal viability. GLP-1R agonism further suppresses synuclein induced inflammatory states in glia, leading to neuroprotection through non cell autonomous effects. In the exenatide-PD2 clinical trial, exenatide treatment was associated with clinical improvement in individuals with higher baseline MAPK expression (and thus insulin resistance). Exenatide treatment led to a reduction of -synuclein aggregates, and a reduction in inflammatory cytokine IL-6. Taken together, our patient platform defines the mechanisms of GLP-1R action in neurons and astrocytes, identifies the population likely to benefit from GLP-1R agonism, and highlights the utility of GLP-1R agonism as a disease modifying strategy in synucleinopathies.

neuroscience↗

bioRxiv2022

Protein aggregation and calcium dysregulation are the earliest hallmarks of synucleinopathy in human midbrain dopaminergic neurons

Mutations in the SNCA gene cause autosomal dominant Parkinsons disease (PD), with progressive loss of dopaminergic neurons in the substantia nigra, and accumulation of aggregates of -synuclein. However, the sequence of molecular events that proceed from the SNCA mutation during development, to its end stage pathology is unknown. Utilising human induced pluripotent stem cells (hiPSCs) with SNCA mutations, we resolved the temporal sequence of pathophysiological events that occur during neuronal differentiation in order to discover the early, and likely causative, events in synucleinopathies. We adapted a small molecule-based protocol that generates highly enriched midbrain dopaminergic (mDA) neurons (>80%). We characterised their molecular identity using single-cell RNA sequencing and their functional identity through the synthesis and secretion of dopamine, the ability to generate action potentials, and form functional synapses and networks. RNA velocity analyses confirmed the developmental transcriptomic trajectory of midbrain neural precursors into mDA neurons using our approach, and identified key driver genes in mDA neuronal development. To characterise the synucleinopathy, we adopted super-resolution methods to determine the number, size and structure of aggregates in SNCA-mutant mDA neurons. At one week of differentiation, prior to maturation to mDA neurons of molecular and functional identity, we demonstrate the formation of small aggregates; specifically, {beta}-sheet rich oligomeric aggregates, in SNCA-mutant midbrain immature neurons. The aggregation progresses over time to accumulate phosphorylated aggregates, and later fibrillar aggregates. When the midbrain neurons were functional, we observed evidence of impaired physiological calcium signalling, with raised basal calcium, and impairments in cytosolic and mitochondrial calcium efflux. Once midbrain identity fully developed, SNCA-mutant neurons exhibited bioenergetic impairments, mitochondrial dysfunction and oxidative stress. During the maturation of mDA neurons, upregulation of mitophagy and autophagy occured, and ultimately these multiple cellular stresses lead to an increase in cell death by six weeks post-differentiation. Our differentiation paradigm generates an efficient model for studying disease mechanisms in PD, and highlights that protein misfolding to generate intraneuronal oligomers is one of the earliest critical events driving disease in human neurons, rather than a late-stage hallmark of the disease.

neuroscience↗

bioRxiv2022

Structural conversion of α-synuclein at the mitochondria induces neuronal toxicity

Aggregation of -Synuclein (-Syn) drives Parkinsons disease, although the initial stages of self-assembly and structural conversion have not been captured inside neurons. We track the intracellular conformational states of -Syn utilizing a single-molecule FRET biosensor, and show that -Syn converts from its monomeric state to form two distinct oligomeric states in neurons in a concentration dependent, and sequence specific manner. 3D FRET-CLEM reveals the structural organization, and location of aggregation hotspots inside the cell. Notably multiple intracellular seeding events occur preferentially on membrane surfaces, especially mitochondrial membranes. The mitochondrial lipid, cardiolipin triggers rapid oligomerization of A53T -Syn, and cardiolipin is sequestered within aggregating lipid-protein complexes. Mitochondrial aggregates impair complex I activity and increase mitochondrial ROS generation, which accelerates the oligomerization of A53T -Syn, and ultimately causes permeabilization of mitochondrial membranes, and cell death. Patient iPSC derived neurons harboring A53T mutations exhibit accelerated oligomerization that is dependent on mitochondrial ROS, early mitochondrial permeabilization and neuronal death. Our study highlights a mechanism of de novo oligomerization at the mitochondria and its induction of neuronal toxicity.

neuroscience↗

bioRxiv2022

Deep learning in human neurons predicts mechanistic subtypes of Parkinson's

Parkinsons disease (PD) is a common, devastating, and incurable neurodegenerative disorder. Several molecular mechanisms have been proposed to drive PD, with genetic and pathological evidence pointing towards aberrant protein homeostasis and mitochondrial dysfunction. PD is clinically highly heterogeneous, it is likely that different mechanisms underlie the pathology in different individuals, each requiring a specific targeted treatment. Recent advances in stem cell technology and fluorescent live-cell imaging have enabled the generation of patient-derived neurons with different mechanistic subtypes of PD. Here, we performed multi-dimensional fluorescent labelling of organelles in iPSC-derived neurons, in healthy control cells, and in four different disease subclasses. We generated a machine learning-based model that can simultaneously predict the presence of disease, and its primary mechanistic subtype. We independently trained a series of classifiers using both quantitative single-cell fluorescence variables and images to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whilst image based deep neural networks predict control, and four distinct disease subtypes with an accuracy of 95%. The classifiers achieve their accuracy across all subtypes primarily utilizing the organellar features of the mitochondria, with additional contribution of the lysosomes, confirming their biological importance in PD. Taken together, we show that machine learning approaches applied to patient-derived cells are able to predict disease subtypes, demonstrating that this approach may be used to guide personalized treatment approaches in the future.

cell biology↗

bioRxiv2020

Highly enriched hiPSC-derived midbrain dopaminergic neurons robustly models Parkinson's disease.

The development of human induced pluripotent stem cells (hiPSC) has greatly aided our ability to model neurodegenerative diseases. However, generation of midbrain dopaminergic (mDA) neurons is a major challenge and protocols are variable. Here, we developed a method to differentiate hiPSCs into enriched populations (>80%) of mDA neurons using only small molecules. We confirmed the identity of the mDA neurons using single-cell RNA-sequencing and detection of classical markers. Single-cell live imaging demonstrated neuronal calcium signalling and functional dopamine transport. Electrophysiology measures highlighted the ability to form synapses and networks in culture. Patient-specific hiPSC lines differentiated to produce functional mDA neurons that exhibit the hallmarks of synucleinopathy including: aggregate formation, oxidative stress as well as mitochondrial dysfunction and impaired lysosomal dynamics. In summary, we establish a robust differentiation paradigm to generate enriched mDA neurons from hiPSCs, which can be used to faithfully model key aspects of Parkinsons disease (PD), providing the potential to further elucidate molecular mechanisms contributing to disease development.

neuroscience↗

bioRxiv2018

The BRadykinesia Akinesia INcoordination (BRAIN) tap test: capturing the sequence effect

BackgroundThe BRAIN tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinsons disease (PD).\n\nObjectivesTo develop a new parameter which detects a sequence effect and to reliably distinguish between PD patients on and off medication. Alongside, we sought to validate a mobile version of the test for use on smartphones and tablet devices.\n\nMethodsBRAIN test scores in 61 patients with PD and 93 healthy controls were compared. A range of established parameters captured speed and accuracy of alternate taps. The new VS (Velocity Score) recorded the inter-tap speed. Decrement in the VS was used as a marker for the sequence effect. In the validation phase, 19 PD patients and 19 controls were tested using multiple types of hardware platforms including smart devices.\n\nResultsQuantified slopes from the VS demonstrated bradykinesia (sequence effect) in PD patients (slope cut-off -0.002) with sensitivity of 58% and specificity of 81% (discovery phase of the study) and sensitivity of 65% and specificity of 88% (validation phase). All BRAIN test parameters differentiated between on medication and off medication states in PD. Most BRAIN tap test parameters had high test-retest reliability values (ICC>0.75). Differentiation between PD patients and controls was possible on all hardware versions of the test.\n\nConclusionThe BRAIN tap test is a simple, user-friendly and free-to-use tool for assessment of upper limb motor dysfunction in PD, which now includes a measure of bradykinesia.

neuroscience↗