Parkinson9s disease is a common and incurable neurodegenerative disease, and the fastest growing neurological disease. Parkinson9s disease results in progressive neurodegeneration, with worsening severity and involvement of multiple areas of the brain over time. However, as with all neurodegenerative conditions, progression is highly variable, and the potential mechanisms that underly any individual9s progression span different biological scales - at the brain micro and macrostructural level, the variabilty may be due to where the pathology starts, and the pattern of damage across circuits, and at the circuit and cellular level, the variability may be due to the regional cellular vulnerability and organelle dysfunction, and molecular pathways disrupted. This project crosses clinical, computational, and cellular neuroscience 0e it aims to map the mechanisms of disease progression in parkinson9s disease (pd) across multiple biological scales, from cells to circuits, in pd. Harnessing a ucl based longitudinal cohort of newly diagnosed sporadic and familial pd patients, the crick-ucl project team have already collected digital measures of clinical progression, quantitative measures of brain microstructure progression, fluid biomarkers, and patient derived cells, all in the same individuals. This phd project will investigate this rich dataset to: define the structural characteristics of progression subtypes, such as cortical dominant pdd, with rapid progression to dementia, and brainstem dominant pdd, with slow progression to dementia utilise the patient derived cells (ipsc derived neurons, and transdifferentiated neurons) combined with organellar imaging to understand the cellular phenotype for these subtypes (iii) define the molecular basis for these subtypes using advanced sequencing approaches in patient cells and biofluids. Together the cellular and molecular basis will enable mechanistic pathways to be dissected on an individual level, and deep learning classifiers will generate predictors of which mechanistic subtype exists within an individual. The patient derived cell platform will then be used to test a range of gene editing and small molecule therapies that target the known pathways that are affected in pd progression. Overall, this project will characterise how pathophysiological mechanisms at different scales interact to result in the clinical syndrome observed, and which mechanisms can be successfully targeted in different individuals with different mechanistic subtypes of disease, thus forming the basis of precision medicine in pd. The university partner for this project is ucl. Candidate background this project will suit a clinician with a background in neurological or psychiatric disease, and with an interest in discovering fundamental molecular and cellular mechanisms of disease using patient derived stem cells. The candidate would be motivated to learn the techniques of cell biology to model disease. The candidate would benefit from any previous experience in analytical skills, as the data science aspects of the project to interrogate datasets across the different scales is a significant aspect. Medical relevance as with all neurodegenerative conditions, parkinson's disease is variable and heterogeneous in its presentation and in its progression. The basis of this heterogeneity is not well understood, although the fact that different gene mutations can cause different progression subtypes, suggests strongly that the molecular pathway that is predominant in an individual renders them vulnerable to the progression subtype they will develop. It is critical to gain a mechanistic understanding of these brain subtypes in life so that treatments can be targeted towards an individual's subtype - at the moment the treatments are considered as 'one size fits all', and as a result, there have been no successful clinical trials in this disease. This project, by addressing the heterogeneity across multiple biological scales, brings precision to the mechanistic underpinnings of progression, and paves the way for predicting better individualised therapies. References d\'sa k, choi ml, wagen az, set f3-salvia n, kopach o, evans jr, rodrigues m, lopez-garcia p, lachica j, clarke be, singh j, ghareeb a, bayne j, grant-peters m, garcia-ruiz s, chen z, rodriques s, athauda d, gustavsson ek, gagliano taliun sa, toomey c, reynolds rh, young g, strohbuecker s, warner t, rusakov da, patani r, bryant c, klenerman da, gandhi s, ryten m. Astrocytic rna editing regulates the host immune response to alpha-synuclein. 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