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Wolfson Institute of Population Health
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Dr Petroula Proitsi, MSc in Human Molecular Genetics, MSc in Medical Statistics, PhD in Neuroscience

Petroula

Reader in Genetic Epidemiology, Deputy Lead for the Digital and Health Data Science Theme at the WIPH

Email: p.proitsi@qmul.ac.uk

Profile

I trained in Biological Sciences (BSc) and Human Molecular Genetics (MSc) and completed a PhD in Neuroscience at King’s College London. During my first post-doctoral fellowship, funded by Alzheimer’s Research UK at King’s College London, I completed an MSc in Medical Statistics at the London School of Hygiene and Tropical Medicine. I was then awarded an EMBO Travel Fellowship to visit the University of Hong Kong. Subsequently, I received an Alzheimer’s Society Research Fellowship, spending one year at the University of Hong Kong before moving back to King’s College London. This was followed by a Springboard Fellowship at the MRC Centre for Lifelong Health and Ageing at UCL and an Alzheimer’s Research UK Senior Research Fellowship at King’s College London, after which I moved to QMUL.

My work focuses on integrating data across different biological layers, such as genetics, proteomics, and metabolomics, to improve early detection and disentangle causal pathways in dementia and other neurodegenerative diseases.

Outside of work, I enjoy spending time with my daughters, running, doing yoga, and cooking.

Research

Research Interests:

Causal inference in dementia and neurodegenerative diseases

Early dementia detection

Multi-omics, Biomarkers

Publications

  • Proitsi P, Ebshiana A, Wretlind A et al. (2026). Alterations in the brain lipidome of Alzheimer's disease donors with rare TREM2 risk variants. nameOfConference


  • Abdolkarimi D, Liu Y, Gilchrist L et al. (publicationYear). Circulating inflammatory proteins predict dementia risk, and are linked to structural brain changes and modifiable risk factors. nameOfConference


  • Liu Y, Wretlind A, Abdolkarimi D et al. (2025). Associations between Plasma Metabolites, Dementia and Modifiable Risk Factors. nameOfConference


  • Calhas S, Liu Y, Waters S et al. (2025). Leveraging multi‐modal data for individualised risk prediction for dementia. nameOfConference


  • Abdolkarimi D, Liu Y, Waters S et al. (2025). Identifying a signature of inflammatory blood proteins predicting dementia. nameOfConference


  • Proitsi P (2025). Integrative Multi‐Omics Approaches to improve early Detection and Decipher Causal Pathways in Dementia. nameOfConference


  • Howard DM, Gilchrist L, Proitsi P et al. (2025). Immune and metabolic disturbance as a function of genetic risk and phase of illness in major depression. nameOfConference


  • Wretlind A, Xu J, Chen W et al. (2025). Lipid profiling reveals unsaturated lipid reduction in women with Alzheimer's disease. nameOfConference


  • Xu J, Doig AJ, Michopoulou S et al. (publicationYear). Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning. nameOfConference


  • Chandra A, Levett BA, Waters S et al. (2025). Evaluating the link between hearing loss and Alzheimer’s disease neuropathology: A systematic review and meta-analysis. nameOfConference


View profile publication page

Supervision

Dorsa Abdolkarimi, MRC DTP PhD, “Identifying signatures of blood proteins predicting incident of dementia.”

Sara Metelo Calhas Ferreira, Wellcome Trust HDiP, “Individualised risk prediction for dementia: deriving actionable information from multimodal health data.”

Lachlan Gilchrist, KCL Drive-Health CDT PhD, “Investigating the genetic and molecular overlap between Alzheimer’s disease and depression.” (Second supervisor)

 

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