"We're using advanced computational biology to model the effects of genetic changes linked with dementia." Georgina Menzies
UK DRI Collaborating Fellow
A Sêr Cymru Fellow, Dr Georgina Menzies joined the UK DRI in Cardiff in 2018. She originally studied forensic science, before obtaining her PhD from Swansea University where she developed a molecular dynamics platform for DNA analysis. Bringing skills in mathematical modelling and large data sets, Georgina will research the genetics of Alzheimer’s disease and other neurodegenerative diseases.
1. At a glance
Modelling the impact of genetic changes linked with dementia
Through: Sêr Cymru II Fellowship
We each have an estimated 20,000 genes that contain the information needed to make functional molecules called proteins. Proteins are large, complex molecules that play fundamental structural, functional, and regulatory roles in our body’s tissues and organs.
Most cases of dementia are complex and are caused by a combination of genetic, environmental and lifestyle factors. Using powerful new approaches involving sequencing the DNA of many thousands of people, researchers are identifying many of the genetic variations that can influence a person’s risk of getting different neurodegenerative diseases but don’t guarantee it. Studying the function of these risk genes is fuelling our understanding of the biological processes that contribute to disease development. But in many cases, these genetic variations are subtle changes – and scientists don’t understand their functional impact.
Dr Georgina Menzies is using advanced computational biology to model the effects of genetic changes linked with dementia on the resulting protein molecule. Her work will help researchers around the world to better understand the biological mechanisms involved in neurodegeneration and help prioritise which genetic risk factors are the most relevant targets for new drugs to prevent or treat dementia.
2. Scientific goals
Genetic and genomic technologies have advanced to the point where large-scale studies into populations are commonplace. These provide insight into the link between genetic changes and the probability of developing a specific disease, the rate of disease progression, and response to therapy. Though many researchers, government agencies and pharmaceutical companies are beginning to take note of the results of these studies, more can be done to use the mutational outcomes to direct lab work, produce drug targets and better understand the mechanisms behind disease development.
Dr Georgina Menzies is using advanced in silico techniques to study the structural impact mutations from these genetic studies have on proteins. The results from these studies will be used to make hypotheses into functional effects with the hope that these will be used to direct wet lab research, provide possible drug targets and drive dementia research forward.
The long-term goal is to characterise coding mutations in neurodegenerative disease. This will be achieved by creating protein models which contain the amino acid changes of novel genetic variants and using these to make functional predictions. Outcomes from this research will provide new insight on the impact of mutations associated with neurodegenerative diseases and accelerate the path towards translation.
Main objectives and research goals:
The main aim of Georgina’s research is to translate the genetics coming out of large-scale studies - identifying promising panels of mutations and performing structural analysis - to make better hypotheses into functional changes and direct further molecular biology-based research.
Within UK DRI:
- Thomas Lancaster, UK DRI at Cardiff
Computational biology, coding mutations, molecular dynamics
6. Key publications
Menzies GE, Sims R & Williams J. Molecular Dynamics simulations of Alzheimer’s variants, R47H and R62H, in TREM2 provide evidence for structural alterations behind functional changes. bioRxiv preprint 2019 doi: https://doi.org/10.1101/536540
Escott-Price, V, Bracher-Smith, M, Menzies, G, Walters, J, Kirov, G, Owen, MJ. and O'Donovan, MC. Genetic liability to schizophrenia is negatively associated with educational attainment in UK Biobank. Molecular Psychiatry 2019; doi: 10.1038/s41380-018-0328-6
Kunkle et al., Meta-analysis of genetic association with diagnosed Alzheimer's disease identifies novel risk loci and implicates Aβ, Tau, immunity and lipid processing. Nature Genetics 2019; 51: 414–430
Grozeva, D., Saad, S., Menzies, G. E., & Sims, R. (2019). Benefits and Challenges of Rare Genetic Variation in Alzheimer’s Disease. Current Genetic Medicine Reports, 7(1), 53-62.
Legge, S. E., Jones, H. J., Kendall, K. M., Pardiñas, A. F., Menzies, G., Bracher-Smith, M., ... & Savage, J. E. (2019). Genetic association study of psychotic experiences in UK Biobank. BioRxiv, 583468.