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The genetics of cognitive ageing: neuromodulators and prefrontal cortex

Primary Supervisor: Dr Magdalena Chechlacz, School of Psychology & Centre for Human Brain Health

Secondary supervisor: Professor Georgios Gkoutos, Institute of Cancer and Genomic Sciences & Centre for Computational Biology, Dr Peter Hansen, School of Psychology & Centre for Human Brain Health

PhD project title: The genetics of cognitive ageing: neuromodulators and prefrontal cortex

University of Registration: University of Birmingham

Project outline:

Neuromodulators including dopamine, noradrenaline, serotonin, and acetylcholine have been implicated in numerous cognitive functions and behaviours. Across the life-span neuromodulators, maintain functional dynamics among large-scale brain networks controlling cognitive performance. Neuromodulators originate from subcortically-located neurons, which have widely distributed cortical projections, densely terminating within the prefrontal cortex (PFC). Recent research suggests that genetic variation, leading to either elevated or decreased levels of neuromodulators in the PFC, have impact on the functional dynamics of the cognitive control networks, and underlie inter-individual variability in numerous cognitive abilities. The proposed MIBTP project is centred on the idea that similar genetic influences on the PFC, and associated brain networks, underlay the widely reported but poorly understood heterogeneity in cognitive ageing.

While some older adults retain high levels of mental capacity, many undergo slow gradual drop in cognitive functioning, and some experience sharp cognitive decline hindering their ability to undertake basic daily activities. Cognitive decline in old age is known to be associated with decreased network efficiency triggered by reduced connectivity within highly specialized networks, including the prefrontal cognitive control networks. The proposed project will explore the idea that advantageous genetic make-up, enhancing neuromodulation across lifespan, supports maintaining higher efficiency of the prefrontal cognitive control networks, translating into better-preserved cognition in older adults.

The observed heterogeneity in cognitive ageing affects not only overall rate of cognitive decline but also inter- and intra-individual variability across different cognitive domains. Crucially cognitive ageing is thought to be associated with cognitive de-differentiation i.e., increased correlations between different cognitive functions. Consequently, many studies exploring genetic influences on age-related cognitive decline focus on phenotypes representing general cognitive abilities rather than on one specific cognitive function. By focusing on phenotypes represented not by cognitive performance but measures of network connectivity, specifically the PFC connectivity, the project will take into account both inter-individual variability across different cognitive functions and cognitive de-differentiation when examining genetic influences on cognitive ageing. Unlike prior genetic research in cognitive ageing, which predominantly focused on linking genetic variance to behavioural performance using either candidate gene or genome-wide association study approaches, the proposed work will investigate polygenic effects on the network connectivity by employing pathway and gene-set analysis methods. Specifically, to gain further insights into heritability of cognitive ageing, this project will examine the impact of genetic variance affecting common neuromodulators (dopamine, noradrenaline, serotonin and acetylcholine) on differences in the connectivity of the prefrontal cognitive control networks in the old age. This project will be conducted using UK Biobank Resources, genetic and neuroimaging data from the Brain Imaging Cohort (19,000 datasets), under the approved project 29447. By systematically examining the association between genetic variability in neuromodulator systems and the PFC connectivity, this project will further our understanding of the mechanisms of cognitive ageing.


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BBSRC Strategic Research Priority: Integrated Understanding of Health: Ageing

Techniques that will be undertaken during the project:

  • Programming Skills (e.g., Bash, Python, Matlab, R)
  • Advances statistical and machine learning analyses
  • Functional and Structural connectivity analysis (advanced brain imaging analysis methods)
  • Genetic analysis: GWAS, gene-set/pathway analysis

Contact: Dr Magda Chechlacz, University of Birmingham