Riccardo Marioni Research Group
Genetics and epigenetics of cognitive ageing
Section: Medical Genetics
Research in a Nutshell
I am a tenured Chancellor’s Fellow with a background in Epidemiology and Biostatistics. My primary research goal is to use computational models to understand the molecular mechanisms that underlie Alzheimer’s disease and to enhance prediction of the disease.
I have a passion for research into ageing and, in particular, examining the genetic and environmental contributions to health, cognitive ageing, and dementia. My group’s work is at the intersection of the biomedical and social sciences.
In recent years, much of my research has focused on DNA methylation – chemical changes to DNA that turn genes on and off and that can be added and removed over the lifespan. These methylation marks can be influenced by genes, lifestyle, and the environment, making them ideal candidates to help us understand the interaction between nature and nurture.
Much of my group’s work is carried out using data from population-based cohorts, such as Generation Scotland, the Lothian Birth Cohorts of 1921 and 1936, and UK Biobank.
|Dr Riccardo Marioni||Group Leader|
|Daniel McCartney||Postdoctoral Research Associate|
|Anna Stevenson||PhD Student|
|Daniel Simpson||PhD Student (co-supervised)|
|Robert Hillary||PhD Student|
|Kate Doust||PhD Student (co-supervised)|
|Eleanor Conole||WT Translational Neuroscience PhD programme (co-supervised)|
|Jure Mur||WT Translational Neuroscience PhD programme (co-supervised)|
Previous Team Members
Joeri Meijsen (2018 co-supervised), Anne Seeboth (2019) PhD Students
Olivia Hamilton (2017), Anders Jesperson (2018), Rebecca Madden (2018), Rebecca Lodge (2019), Jur Mur (2019), Tyler Saunders (2019). Wellcome Trust Translational Neuroscience PhD rotation projects
XiaoXiao Xie, 2018 MSc Bioinformatics
Dominique Ding (2016), Lichen Ma (2019) MSc Quantitative Genetics and Genome Analysis
Daniel Peng, 2016, MSc Cognitive Neuroscience
Jing Guo, 2015, MSc Quantitative Genetics and Genome Analysis
- Doctor Tamir Chandra, University of Edinburgh
- Professor Ian Deary, University of Edinburgh
- Doctor Kathy Evans, University of Edinburgh
- Professor Andrew McIntosh, University of Edinburgh
- Professor Craig Ritchie, University of Edinburgh
- Generation Scotland/STRADL research team, University of Edinburgh
- Lothian Birth Cohort research team, University of Edinburgh
- Professor Peter Visscher, University of Queensland
- Professor Naomi Wray, University of Queensland
- Professor Steve Hovath, UCLA
- Doctor Sarah Hagg, Karolinska Institutet
- Professor Caroline Relton, University of Bristol
- Doctor Matthew Robinson, University of Lausanne
Partners and Funders
- Gertrude Winifred Gear Fund, University of Edinburgh College of Medicine and Veterinary Medicine (£50,922) and Wellcome Trust Institutional Strategic Support Fund (£57,878). Epigenetic, structural brain MRI, and cognitive changes over the eighth decade. Duration: 01/03/16 - 01/12/16. Role: PI
- ESRC: Network Grant ES/N000382/1 (£199,513). INTERpreting epigenetic signatures in STudies of Early Life Adversity (InterStELA). PI: Dr Laura D Howe:University of Bristol. Duration: 01/10/2015 - 30/09/2017. Role: Co-I.
- ESRC: Research Grant ES/N000498/1 (£667,460). Epigenetics: Environment, Embodiment and Equality (E4). PI: Professor Caroline Relton: University of Bristol. Duration: 01/10/2015 - 30/09/2018. Role: Co-I (10% time commitment).
- NIH: U34 Research Grant ($953,566). The epiGenetIcs Leads to aGe-relAted diseases (GILGA-mesh) Network. PI: Professor Steve Horvath (UCLA). Duration: 01/10/2015 - 30/09/2018. Role: Co-I (15% time commitment, $32,400 sub-recipient award).
- Alzheimer's Research UK ARUK-PG2017B-10 (£166,833). Omics prediction of Alzheimer's disease. Duration : 01/10/2017 - 30/09/2020. Role: PI
- University of Edinburgh Pilot Grant, Centre for Cognitive Aging and Cognitive Epidemiology (£5,404). A non-invasive mouse DNA methylation age predictor for longitudinal studies. Duration: 01/10/2017 - 31/12/2018. Role: PI
Genetics, methylation, GWAS, prediction, ageing, cognitive decline