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Fields & Applications Clinical, Mass Spectrometry, Genomics & DNA Analysis, Metabolomics & Lipidomics, Proteomics, Translational Science

Mapping the Molecular Landscape

Researchers have combined 18 distinct omics technologies to create a molecular map of human physiology, with a particular focus on diabetes subtypes. The study, conducted as part of the Qatar Metabolomics Study of Diabetes (QMDiab), analyzed 391 participants, integrating data from various omics layers – including genomics, proteomics, metabolomics, and glycomics – across blood, urine, and saliva samples, generating a dataset that included 6,300 individual molecular data.

This allowed the researchers to identify distinct molecular signatures associated with different diabetes subtypes, where specific metabolite profiles were linked to type 1 and type 2 diabetes. Additionally, glycomics data revealed variations in glycan structures associated with diabetic conditions. 

"Our idea was to bring together everything we have learned over more than a decade of multiomics research to create a comprehensive molecular model of the human body and its processes," said senior author Karsten Suhre, professor of physiology and biophysics and a member of the Englander Institute of Precision Medicine, in a press release

The researchers have also made their data publicly accessible through an interactive web tool, COmics, which allows other scientists to explore the molecular networks and generate new hypotheses.

"This reference tool is free to access and use by researchers who want to investigate how the human body works at the molecular level and also for the formation of hypotheses to test with experimentation,” said Suhre. 

First author Anna Halama, assistant professor of research in physiology and biophysics, said: “Our integrative omics approach provides an overview of the interrelationships between different molecular traits and their association with a person's phenotype – their observable traits, such as their physical appearance, biochemical processes and behaviors. The scale of the data integrated within the COmics web-tool enables access to hundreds of thousands of pathways and associations for researchers to explore, giving huge potential for discovery and investigation.”

Image credit: Suhre/Halama Labs

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