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Universal latent axes capturing Parkinson’s patient deep phenotypic variation reveals patients with a high genetic risk for Alzheimer’s disease are more likely to develop a more aggressive form of Parkinson’s

Cynthia Sandor, Stephanie Millin, Andrew Dahl, Michael Lawton, Leon Hubbard, Bobby Bojovic, Marine Peyret-Guzzon, Hannah Matten, Christine Blancher, Nigel Williams, Yoav Ben-Shlomo, Michele T. Hu, Donald G. Grosset, Jonathan Marchini, Caleb Webber
doi: https://doi.org/10.1101/655217
Cynthia Sandor
1UK Dementia Research Institute, Cardiff University, Cardiff, UK
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Stephanie Millin
2Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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Andrew Dahl
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
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Michael Lawton
4School of Social and Community Medicine, University of Bristol, Bristol, UK
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Leon Hubbard
5MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
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Bobby Bojovic
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
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Marine Peyret-Guzzon
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
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Hannah Matten
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
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Christine Blancher
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
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Nigel Williams
5MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
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Yoav Ben-Shlomo
4School of Social and Community Medicine, University of Bristol, Bristol, UK
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Michele T. Hu
6Oxford Parkinson’s Disease Centre, Department of Physiology, Anatomy and Genetics, Le Gros Clark Building, University of Oxford, Oxford, UK
7Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.
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Donald G. Grosset
8Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom
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Jonathan Marchini
3Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
9Department of Statistics, University of Oxford, Oxford, UK
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  • For correspondence: webberc4@cardiff.ac.uk marchini@stats.ox.ac.uk
Caleb Webber
1UK Dementia Research Institute, Cardiff University, Cardiff, UK
2Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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  • For correspondence: webberc4@cardiff.ac.uk marchini@stats.ox.ac.uk
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Abstract

The generation of deeply phenotyped patient cohorts offers an enormous potential to identify disease subtypes but are currently limited by the cohort size and the heterogeneity of the clinical assessments collected across different cohorts. Identifying the universal axes of clinal severity and progression is key to accelerating our understanding of how disease manifests and progresses. These universal axes would accelerate our understanding of how Parkinson’s disease (PD) manifests and progresses through which patients may be appropriately compared appropriately stratified, and personalised therapeutic strategies and treatments can be developed and targeted. We developed a Bayesian multiple phenotype mixed model incorporating the genetic relationships between individuals which is able to reduce a wide-array of different clinical measurements into a smaller number of continuous underlying factors named phenotypic axis. We identify three principal axes of PD patient phenotypic variation which are reproducibly found across three independent, deeply and diversely phenotyped cohorts. Together they explain over 75% of the observed clinical variation and remain robustly captured with a fraction of the clinically-recorded features. The most influential axis was associated with the genetic risk of Alzheimer’s disease (AD) and involves genetic pathways associated with neuroinflammation. Our results suggest PD patients with a high genetic risk for AD are more likely to develop a more aggressive form of PD including, but not limited to, dementia.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 18, 2021.
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Universal latent axes capturing Parkinson’s patient deep phenotypic variation reveals patients with a high genetic risk for Alzheimer’s disease are more likely to develop a more aggressive form of Parkinson’s
Cynthia Sandor, Stephanie Millin, Andrew Dahl, Michael Lawton, Leon Hubbard, Bobby Bojovic, Marine Peyret-Guzzon, Hannah Matten, Christine Blancher, Nigel Williams, Yoav Ben-Shlomo, Michele T. Hu, Donald G. Grosset, Jonathan Marchini, Caleb Webber
bioRxiv 655217; doi: https://doi.org/10.1101/655217
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Universal latent axes capturing Parkinson’s patient deep phenotypic variation reveals patients with a high genetic risk for Alzheimer’s disease are more likely to develop a more aggressive form of Parkinson’s
Cynthia Sandor, Stephanie Millin, Andrew Dahl, Michael Lawton, Leon Hubbard, Bobby Bojovic, Marine Peyret-Guzzon, Hannah Matten, Christine Blancher, Nigel Williams, Yoav Ben-Shlomo, Michele T. Hu, Donald G. Grosset, Jonathan Marchini, Caleb Webber
bioRxiv 655217; doi: https://doi.org/10.1101/655217

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