Metabolomics in Epidemiology

This internal course is only open to invited University of Bristol staff, postgraduate students and selected collaborators.

Course dates

26-27 October 2016.

Course duration: 2 days (approximately 11 hours of lectures and 3 hours of practicals).
Registration will start at 9.00am on the first day, the course will finish by 4.15pm on the final day.

Course tutors

Professor Mika Ala-Korpela (course organiser), Professor Debbie Lawlor, Dr Peter Würtz, Dr Pasi Soininen, Antti Kangas, Qin Wang.

Course aims and objectives

This course is an introductory course on omics sciences, particularly quantitative metabolomics, and their current and future role in epidemiology and medicine. It is aimed at familiarising participants with the basis and applications and integration of various omics disciplines. The focus will be in quantitative metabolomics, but a brief introduction, e.g., to genomics and transcriptomics will be given in the light of integration of multiple omics data sets and domains in systems epidemiology research. An overview on experimental issues as well as data characterisation and analyses is given with respect to key quantitative NMR and mass spec metabolomics methodologies. The focus is on the role of metabolomics and its applications, but in general systems epidemiology thinking remains on the background with an emphasis on understanding the relation between various omics spaces and the importance of their integration in modern epidemiology. The concept of “big data” will be introduced in relation to systems epidemiology and medicine. The role and concept of biobanking will be introduced and linked with electronic health records. Several exemplars of the above mentioned concepts are illustrated in real epidemiological research applications, including genetic background of systemic metabolism (so-called genome-wide association study approach) and how genetics, metabolomics and big data can enhance drug development.

By the end of the course participants should be able to:

  • understand the role of metabolomics among other ‘omics sciences in epidemiology;
  • understand the pros and cons of NMR spectroscopy and mass spectrometry in epidemiology;
  • be familiar with the current status of metabolomics applications in epidemiology;
  • appreciate the potential value of biobanks in understanding complex diseases and multiple omics data in drug development;
  • have a realistic outlook on systems epidemiology and medicine;
  • know the basics of using R in analysing epidemiological metabolomics data and appreciate the importance of data visualisations.

Who the course is intended for

Invited University of Bristol staff, postgraduate students and selected collaborators who are interested in applying omics sciences in epidemiology. Participants are required to have a basic background in medical statistics and epidemiology, and knowledge of the basics of R software.

Course outline

Day 1
Overview on metabolomics in epidemiology.
Metabolomics among the other omics’. 
Metabolic profiling in epidemiology.

Day 2
Key quantitative metabolomics methodologies in epidemiology.
The role of data visualisation for understanding complex data.
Recent metabolomics highlights from scientific literature. 
Basics of using R in epidemiological metabolomics. 

Recommended reading: It would be helpful for attendees to familiarise themselves with the following papers in advance of the course:

  • Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches Niiranen, T. J., & Vasan, R. S. (2016). Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches. Expert Review of Cardiovascular Therapy, 14(7), 855–869.
  • Quantitative high-throughput metabolomics: a new era in epidemiology and genetics. Ala-Korpela, M., Kangas, A. J., & Soininen, P. (2012). Quantitative high-throughput metabolomics: a new era in epidemiology and genetics. Genome Medicine, 4(4), 36.

Please note: The following software will be used on the course - R (; version 3.3.1 or newer. This course will be held in a computer lab, you will not need to bring a laptop.  

Internal Booking

Please note bookings for this course have now closed.

Very good practical tips - great insights. I REALLY enjoyed the visualization and the R sessions, as they provided some hands-on materials.

Course feedback, October 2016

Course fees

Please note that we do not charge fees for pilot courses, nor do these count against your allocation of free course places.

More information on course fees, fee waivers and reduced prices.

Course venue

School of Social and Community Medicine
Canynge Hall
39 Whatley Road
United Kingdom

Map and directions

Lunch and refreshments

Coffee, tea, fruit and biscuits will be available to all students. Please let us know if you have any dietary requirements.


Information about accommodation.


For further information please email