The Spence Lab

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  • About the Spence Lab

Paired biomarker and therapeutic strategies to advance precision medicine in neurodegenerative diseases.

Based in the School of Medicine, Medical Sciences and Nutrition at the University of Aberdeen in Scotland, the Spence Lab (PI Dr Holly Spence) takes a disease-agnostic approach to understanding the physical biology of ALS and other neurodegenerative diseases. Our research centres on detailed phenotyping to investigate how metal dysregulation and other endophenotype specific pathologies contribute to neurodegeneration across conditions.

Through integration of clinical data, brain imaging, histopathological, and multi-omics analyses, we aim to advance precision medicine by developing paired biomarker and treatment target strategies tailored to specific disease endophenotypes.

Core Concepts

1. Metal Dysregulation in Neurodegenerative Disease
Metal dyshomeostasis, particularly involving iron, is a common feature across neurodegenerative diseases and can be visualised in vivo using MRI. Our work has identified disease-specific regional patterns of iron accumulation that correlate directly with protein misfolding and symptom burden, providing insight into how metal dysregulation may drive or track pathological progression in conditions such as ALS and Alzheimer’s disease.

2. Biomarkers
We are exploring novel imaging-based biomarkers to better characterise neurodegenerative disease in vivo, including through the application of Fast-Field Cycling NMR and Field-Cycling Imaging to ALS and other neurodegenerative diseases. These emerging techniques offer new ways to probe tissue microenvironments and molecular dynamics, with the aim of translating imaging findings into clinically useful biomarkers for diagnosis, stratification, and treatment monitoring.

3. Environmental Exposures
Our research examines how environmental pollutants, including PM2.5 and ambient lead exposure, contribute to cognitive decline. We have shown that these exposures are detrimental to cognitive health, with evidence pointing to redox imbalance and cytotoxic dysregulation as key mechanisms linking environmental exposure to neurodegenerative risk.

4. Dataset Integration
We take a data-driven approach to neurodegenerative disease research, applying machine learning methods to integrate diverse datasets, including imaging, histopathological, and multi-omics data. This non-biased and comprehensive strategy allows us to identify patterns and relationships that might be missed by studying individual data types in isolation.