Genetic Association Studies and Mendelian Randomisation
Mendelian randomisation studies have become increasingly popular in the past decade following the growth in availability of genome-wide data.
Initially this one-day course will cover basic concepts behind genetic association studies with focus on Genome-Wide Association Studies (GWAS).
The practical component will take participants through quality controlling genetic datasets as well as using the latest statistical methods and software to analyse and visualise results for genome-wide data.
The second part of the course will then focus on Mendelian Randomisation (MR), and more specifically using genetic variants identified through GWAS to estimate the causal relationship of a non-genetic risk factor on an outcome of interest.
The practicals will be implemented in PLINK, HAPLOVIEW, R and Stata.
|Time Activity Led by|
|09:00-09:30||Registration and coffee|
|09:30-10:15||Introduction to genetic association studies and genome-wide association studies||Ghazaleh Fatemifar|
|10:30-11:45||Practical: Genome-wide association studies||Ghazaleh Fatemifar|
|12:45-13:30||Introduction to Mendelian randomisation||Michail Katsoulis|
|13:30-14:15||Mendelian randomisation using individual-level data||Michail Katsoulis|
|14:30-15:15||Practical: Mendelian randomisation using individual-level data||Michail Katsoulis, Victoria Allan, Caroline Dale|
Two-sample Mendelian randomisation
Practical: two-sample Mendelian randomisation
Michail Katsoulis, Victoria Allan
- Dr Ghazaleh Fatemifar (Lead Tutor)
Ghazaleh has a background in genetic epidemiology. Her research is focused on using genome-wide association studies to identify instruments for Mendelian randomisation.
She recently moved to the Farr Institute of Health Informatics Research London in order to perform genetic analyses using electronic heath records.
- Dr Michail Katsoulis (Lead Tutor)
Michail holds a BSc in Applied Mathematical and Physical Sciences (2006), an MSc in Statistics (2007) and a PhD in Epidemiology (2015).
He worked at the Hellenic Health Foundation and the University of Athens for 7 years (2008-2015) before joining the Farr Institute of Health Informatics Research London as a Medical Statistician (Research Associate) in December 2015.
His research interests include interaction and mediation analysis, Mendelian randomisation and application of causal inference methods to deal with time-dependent confounding.
- Ms Victoria Allan
Victoria is a PhD student at the UCL Institute of Health Informatics.
Her PhD centres on the use of electronic health records to better understand risk factors associated with the common heart rhythm disorder atrial fibrillation.
- Dr Caroline Dale
Caroline, a UCL Springboard Population Science Fellow, works as a genetic epidemiologist at the Farr Institute of Health Informatics Research London. She is interested in using Mendelian Randomisation (MR) to investigate the impact of environmental risk factors on chronic morbidities of older age.
She has previously worked with international collaborations looking at the impact of alcohol and adiposity (BMI, waist:hip) on cardiovascular disease using multi-SNP instruments and methods to address pleiotropy. Currently, she is working on a project using MR in half a million UK Biobank participants to analyse the effect of alcohol consumption on a range of outcomes including dementia.
She has also worked as an epidemiologist within the UCL-London School of Hygiene & Tropical Medicine-Edinburgh-Bristol (UCLEB) consortium since 2011. The consortium included 14 British prospective studies whose main aim is to integrate different OMICs platforms (e.g. genomics, NMR and metabolomics) to improve understanding of disease aetiology, drug-targets, risk prediction and prognosis. Before taking on this role, she worked as a Research Fellow with the British Women’s Heart & Health Study. She completed both an MSc in Demography & Health and a PhD in Epidemiology at the London School of Hygiene & Tropical Medicine in 2011.