Research

We are advancing a precision-prevention paradigm for neurodegenerative diseases, shifting the focus from late-stage diagnosis to identifying disease risk and pathology years before clinical symptoms emerge. Our work investigates early molecular and cellular changes across the life course, including peripheral tissue pathology, non-motor symptoms, and systemic disease manifestations that may precede neurological decline.

By integrating clinical pathology, biomarker discovery, and longitudinal patient data, our long-term aim is to develop screening and surveillance strategies capable of detecting disease at the earliest possible stage. This approach supports proactive intervention, risk stratification, and improved patient outcomes, aligning with a broader vision of preventive neurology comparable to advances seen in oncology screening programmes.

Ultimately, our goal is to transform neurodegenerative disease management from reactive treatment to anticipatory prevention, enabling timely interventions that preserve function, extend quality of life, and reduce disease burden across populations..

Our research focuses on the discovery, validation, and clinical implementation of biomarkers that enable earlier diagnosis, disease monitoring, and therapeutic decision-making in neurodegenerative disorders. We investigate molecular, cellular, and tissue-based signatures of disease using advanced histopathological, genomic, and proteomic technologies, with particular emphasis on detecting pathological protein aggregation and inflammatory processes.

A central priority of our research is translating biomarker discoveries into clinically deployable tools, including minimally invasive diagnostics, point-of-care assays, and digital health technologies. These innovations support patient stratification, clinical trial readiness, and personalised treatment pathways.

We are particularly interested in aptamer technologies, and in collaboration with others, we are developing and testing aptamers for diagnostics and therapeutics in neurodegenerative diseases.

We are advancing the emerging field of pathomics, the quantitative and computational analysis of histopathological data to uncover novel disease mechanisms and diagnostic signatures. Our work leverages digital pathology, genomics, transcriptomics, spatial transcriptomics, artificial intelligence, and high-dimensional image analysis to transform tissue samples into rich datasets that capture morphological, molecular, and spatial information at unprecedented resolution.

By combining traditional pathology expertise with data science and machine learning, we aim to identify previously unrecognised patterns of disease progression, tissue vulnerability, and cellular resilience. These insights support the development of objective diagnostic criteria, reproducible research pipelines, and scalable tools for clinical decision-making.

By integrating -omics and pathology, we hope to uncover new insights into disease biology, serves, enabling the systematic integration of tissue-based evidence into translational and clinical research.

Neurodegenerative diseases are highly heterogeneous, with substantial variability in disease onset, progression, symptoms, and treatment response. Our research seeks to understand this heterogeneity by identifying biological and clinical factors that distinguish disease subtypes and predict patient trajectories.

We integrate molecular pathology, genetics, clinical phenotyping, and computational modelling to define biologically meaningful patient groups and uncover mechanisms driving disease variability. This work enables more accurate disease-state characterisation, better targeted therapies, and improved clinical trial design by ensuring that interventions are matched to the right patients at the right time.

Through precision medicine approaches, we aim to move beyond one-size-fits-all treatment strategies toward personalised care pathways that optimise outcomes and resource allocation in healthcare systems.