What can large-scale metabolomic and genetic profiling of population biobanks tell us about common disease?
For our next talk, in the BDI/CHG (gen)omics Seminar series, on 23 January, 9:30-10:30 am at the Big Data Institute (BDI), we will be hearing from Dr Luke Jostins-Dean, Sir Henry Dale Fellow, Kennedy institute of Rheumatology and Dr Eirini Trichia, Senior Statistical Epidemiologist, NDPH . We’re delighted to host Luke and Eirini in what promises to be a great talk!
Date: 23 January
Time: 9:30-10:30 am
Location: Big Data Institute Seminar Room 1
Talk 1: 9:30am – 9:50am
Dr Luke Jostins-Dean
Predicting common diseases in large biobanks with metabolic and polygenic risk scores
In this talk I will discuss recent work from the Nightingale Health Insights research group, using high-throughput NMR profiling to measure hundreds of metabolites and metabolic parameters in the UK Biobank. I will discuss our recently completed analysis validating combined metabolic and genomic risk prediction for incidence of 12 common diseases. I will describe how these predictions change over time in longitudinal samples, how they can track changes in risk, the behavioural and environmental drivers of these changes, and how they relate to (static) genetics-only predictions. I will also discuss applications of metabolomic risk scores to predict disease progression in inflammatory disease, and to shed light on the mechanisms of monogenic diseases. Finally, I will discuss how these risk predictions are being used in the clinic to help guide regular health checks in Finland.
Bio: Dr Luke Jostins-Dean is a group leader at the Kennedy Institute of Rheumatology, and Principal Scientist at Nightingale Health UK. His research focuses on developing statistical approaches to leverage genetic, metagenomic and metabolomic profiling to understand and predict the onset and progression of common diseases.
Talk 2: 9:50am – 10:10am
Dr Eirini Trichia
Leveraging physiological and metabolomic traits to understand the genetic basis of type 2 diabetes in a Mexican population.
Type 2 diabetes (T2D) is a physiologically heterogeneous disease that is common in Mexico. In the Mexico City Prospective Study (MCPS) the excess mortality risk associated with previously-diagnosed diabetes accounted for one third of all deaths before age 75. However, Mexican participants remain underrepresented in genetic studies of T2D. To address this gap and characterise the genetic architecture of diabetes in this Mexican population with high relatedness and admixture, we conducted a genome-wide association study (GWAS) of previously-diagnosed type 2 diabetes among 125,042 adults (19,431 cases). Regression models were adjusted for age, sex and admixture (first seven principal components). Conditional analyses yielded 86 independent variants. To better understand the potential mechanisms through which the 86 variants are linked to diabetes risk, we leveraged information from physiological traits, NMR metabolomics, and diseases from MCPS to perform a phenome-wise association study and a subsequent physiological clustering analysis of the variants. We enhanced this analysis using glycaemic traits from the MAGIC consortium. Known T2D variants were assigned to previously-specified clusters, while most of the potentially novel variants mapped within or close to clusters related to insulin secretion and/or insulin action. Our work highlights the need for genetic discovery efforts in understudied populations such as Mexico, a highly-admixed population, where diabetes is common and a major contributor to mortality.
Dr Eirini Trichia is a Senior Statistical Epidemiologist at the Nuffield Department of Public Health, working on the Mexico City Prospective Study. Her background is in nutritional epidemiology and public health, and her work focuses on multiomic epidemiological analysis of large-scale cohort data to understand adiposity, cardiovascular health and diabetes.
————————————————————————————————————————————————————————-
All members of the University are welcome to join, please let reception at BDI know you’re here for the seminar and sign-in. We hope you can join us!
We also now have a mailing list –
To be added, ping genomics_bdi_whg-subscribe@mailist.ox.ac.uk (with any message), you should get a bounce-back with three options to confirm your subscription. Follow any of those options, and with a bit of luck you should be signed up!
As a reminder, the gen)omics seminar series runs every other Tuesday morning and is intended to increase interaction between individuals working in genomics across Oxford. We encourage in-person attendance where possible. There is time for discussion over, tea, coffee and pastries after the talks.
Hybrid Option:
Please note that these meetings are closed meetings and only open to members of the University of Oxford to encourage sharing of new and unpublished data. Please respect our speakers and do not share the link with anyone outside of the university. The aim of these seminars is to increase interaction between people working in Genomics across the University so we encourage in person attendance wherever possible.
Microsoft Teams meeting –
Meeting ID: 394 946 941 997
Passcode: wKaucw
————————————————————————————————————————————————————-
If you wish to know more or receive information related to trainings and events at BDI, please subscribe by emailing bdi-announce-subscribe@maillist.ox.ac.uk. You’ll then receive an email from SYMPA and once you reply you’ll be on the list!
Date:
23 January 2024, 9:30 (Tuesday, 2nd week, Hilary 2024)
Venue:
Big Data Institute, Old Road Campus OX3 7LF
Venue Details:
Seminar room 1
Speakers:
Eirini Trichia (University of Oxford),
Dr Luke Jostins-Dean (University of Oxford)
Organising department:
Big Data Institute (NDPH)
Organisers:
Nicola Whiffin (University of Oxford),
Duncan Palmer (University of Oxford)
Organiser contact email address:
sumeeta.maheshwari@ndph.ox.ac.uk
Part of:
BDI/CHG Genomics Seminar Series
Booking required?:
Not required
Cost:
free
Audience:
Members of the University only
Editor:
Sumeeta Maheshwari