Meet the team

Cynthia Sandor

"The UK DRI is the ideal place to perform my research programme. It offers an exciting research environment. Importantly, the UK DRI research groups have expertise complementary to our computational expertise." Cynthia Sandor
UK DRI Group Leader

Dr Cynthia Sandor is a Group Leader at the UK DRI at Imperial and an Edmond J. Safra Lecturer and a UK Research and Innovation Future Leader Fellow at Imperial College London. She was previously a Sêr Cymru II Fellow and UK DRI Emerging Leader at the UK DRI at Cardiff, sponsored by Group Leader Prof Caleb Webber. After training as a veterinary surgeon at the University of Liège, Dr Sandor completed her PhD (Pr Michel Georges) before moving onto her first postdoctoral post at Harvard Medical School and the Broad Institute, where she contributed to multiple genetics studies on auto-immune diseases such as Crohn’s disease and Rheumatoid arthritis. Next, while undertaking postdoctoral studies at the University of Oxford, Dr Sandor worked on evaluation of the validity of induced pluripotent stem cell derived neuronal models using bulk and single RNA sequencing experiments. This research contributed to the first single-cell human substantia nigra atlas - a brain region heavily impacted by Parkinson’s disease. Dr Sandor's current research is aiming to identify accessible and early biomarkers that can help detect individuals living with Parkinson's or other dementia disorders in the general population. Working with different data types and multiple clinical datasets, her team develop statistical/machine learning approaches to understand and predict the clinical presentation and progression of disease in people living with Parkinson’s.

1. At a glance

A critical challenge in medicine is to understand why patients with the same disorder can often show different clinical symptoms. For the 10 million people living worldwide with Parkinson’s disease, this is especially true with variations in age of onset, the rate of disease progression, and symptom type and severity.

Dr Cynthia Sandor aims to bring greater understanding by using computational approaches on large cohorts of people living with Parkinson’s disease, for which detailed datasets are available, including clinical, imaging and genetic data. Her studies so far have shown that people with Parkinson’s, who also have a high genetic risk for Alzheimer’s disease, develop more severe symptoms. Identifying these different subtypes of Parkinson’s, based on robust data, will help researchers understand the different disease mechanisms involved and will open the door for personalised therapeutics.

2. Scientific goals

The clinical presentation of Parkinson’s disease can vary between individuals in terms of age of onset, the rate of progression and the type and severity of symptoms. However, the reasons behind this are not clear. Large, detailed datasets of people living with Parkinson’s provide a wealth of information about the disease, including clinical, imaging, biosample and genetic data, which can be used to find answers to these questions.

Dr Cynthia Sandor is using computational approaches to analyse the variety of information available in the large Parkinson’s disease datasets. This includes expanding upon a computer model that Dr Sandor has previously created, which uses multiple clinically observed phenotypes, to integrate data from brain scans and prior disease-knowledge, as well as changes over time. She aims to determine how the immune system changes during Parkinson’s by detecting blood gene expression profiles that correlate with, or predict, disease progression. Dr Sandor is also measuring blood samples to identify early indicators that rapid eye movement (REM) sleep behaviour disorder (RBD) will develop into Parkinson’s disease by constructing construct a comprehensive bulk and single-cell multi-omics atlas.

Using multiple data types in analyses allows researchers to understand molecular processes in more detail, but this often requires sophisticated computational techniques, such as when using this approach to construct networks of genes based on their functions. Alongside her research programme, Dr Sandor is developing a new application, called Rshiny, to make this process easier, which will benefit the projects of other dementia researchers.

Main objectives and research goals:

In this UK DRI programme, Dr Sandor’s aims use the computational studies to determine subtypes of Parkinson’s disease and to advance knowledge of its disease mechanisms on a cellular and molecular level. This has the potential to identify biomarkers of the disease and opens the door for the development of personalised treatments for Parkinson’s.

1. Develop computational approaches to exploit the full potential of cohorts with detailed phenotypes.

2. Stratify people with Parkinson’s, for which detailed phenotypes are described, by blood-based immune signatures.

3. Perform bulk and single-cell multi-omic profiling and methylation blood profiling on a cohort of people with REM sleep behaviour disorder to identify biomarkers for the conversion to Parkinson’s disease.

4. Develop user-friendly tools to explore different large genomic datasets.

3. Team members

Samuel Keat (Research Assistant, funded by Ser Cymru II programme)
Ann-Kathrin Schalkamp (PhD student, funded by Health and Care Research Wales Health)
Marirena Bafaloukou (Research Assistant)
Anastasia Ilina (Research Assistant)

4. Collaborations

Within UK DRI:

  • Prof Caleb Webber, UK DRI at Cardiff
  • Prof Phil Taylor, UK DRI at Cardiff
  • Dr Sarah Carpanini, UK DRI at Cardiff

Beyond UK DRI:

  • Dr Kathryn Peall, Cardiff University
  • Prof Neil Harrison, Cardiff University
  • Prof Nigel Williams, Cardiff University
  • Prof Michele Hu, University of Oxford

5. Topics

Parkinson’s disease, Neurodegenerative disorders, statistical genetics, genomics, bioinformatics, genomics, functional genomics, electronic health records

6. Techniques

Mixed Models, Bioinformatics and network approaches, single-cell, new sequencing technologies

7. Key publications

Sandor C, Millin S, Dahl A, Lawton M, Hubbard L, Bojovic B, et al. 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. bioRxiv. 2021:655217.

Sandor C, Agarwal D, Volpato V, Caffrey TM, Monzon-Sandoval J, Bowden R, et al. A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders. Nat Commun. 2020;11(1):4183

Sandor C, Robertson P, Lang C, Heger A, Booth H, Vowles J, et al. Transcriptomic profiling of purified patient-derived dopamine neurons identifies convergent perturbations and therapeutics for Parkinson's disease. Hum Mol Genet. 2017;26(3):552-66.