The Monthly Researcher Spotlight is our new section highlighting the exciting work of the UK Biobank Research Analysis Platform user community. If you would like to be featured, email community@dnanexus.com.
This was originally published in the April 2023 UK Biobank RAP Newsletter. You can sign up for future installments here.
Dr. Karsten Suhre
Director Bioinformatics Core
Weill Cornell Medicine - Qatar
What are the focus and discovery highlights of your research?
My research focuses broadly on understanding the functioning of biological processes and how their dysregulation leads to the emergence of complex disorders, like diabetes and cardiovascular disease. In contrast to controlled intervention studies and cellular and animal models, I probe the variation of the human population to provide me with insights on how perturbations of biological systems can result in disease-relevant changes of the underlying pathways. As a bioinformatician I like working with big datasets – hence my interest in combining readouts from deep molecular phenotyping technologies, such a genome data, metabolomics and proteomics. Highlights of my work are being among the first to conduct genome-wide association (GWAS) studies with metabolomics and proteomics.
What are some of the key questions that you are looking to answer using UK Biobank data?
As conducting GWAS with omics datasets is almost routine these days, I am trying to go beyond mere genetic associations, aiming at getting a better understanding of how the different omics layers connect to each other, and which biological information is encoded between them.
How has the UK Biobank Research Analysis Platform (UKB-RAP) helped you perform your research?
UKB-RAP has been a game changer in terms of data access to me. Before (i.e., in other population studies), working with population scale data has always been a hassle, with many bureaucratic obstacles, inconsistencies between versions of data that different groups were using, politics about who is permitted to do what with the data, lack of documentation, etc. UKB-RAP is a very structured and democratized, and still very secure and rules-respecting way of accessing data and has made UKB an even greater resource than it had already been before.
Any tools or tutorials that you have developed that would be useful for the UKB-RAP community?
My colleagues from the Krumsiek lab at Weill Cornell in New York developed an R-tool for the structured analysis of metabolomics and proteomics data, which I have been using a lot to analyze UKB data. My own group performed a much smaller multi-omics study (compared to UKB) where we integrated data from 18 different platforms into a webserver that allows to connect traits measured on all platforms. This server can put omics associations identified using UKB data into the broader context of parameters that have (not yet!) been measured in UKB: If you are interested in working with the new OLINK data I can also (as shameless self-promotion) recommend our review paper.