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We are interested in understanding factors that define our ageing ‘trajectories’, which diseases we likely to develop and how to predict and prevent them from developing.

We already know a lot about genetic predispositions, environmental factors and (not always healthy) habits that could lead to development of various diseases. However, our current knowledge can only predict a very small proportion of disease-associated risks as they result from complex interplay between genes, environment and lifestyle. We argue that a holistic modelling of multilevel (from genomes and transcriptomes to phenotype) can help to decode this complexity and help personalized disease prognostics.

Our main research topics include:

  • Study of disease-related polymorphic genomic regions missing from known genome reference (pangenomics)
  • Integration of data from multiple omics layers for better understanding of mechanisms and development of chronic lung diseases and cancer (proteogenomics)
  • Studying ageing trajectories and their connections to disease onset using physiological and molecular phenotypes in large cohorts and biobanks (e.g. LifeLines)
Relevance

Our research and benefits to society

We perform several research projects aimed to improve our understanding of human diseases:

  • Identification of disease genes
    The currently incomplete genome reference and gene annotation result in our oversight of important factors playing roles in disease susceptibility and progression. Our pangenome study is aimed to complete the missing part of our genomes that may be related to onset of chronic lung diseases, different cancer types and other diseases.
  • Multi-level characterization of human diseases
    Many ongoing large-scale projects investigate single type of molecular data (e.g. genes, RNAs or proteins) in large cohorts of patients, identifying common features of the disease studied. We develop computational methods for integration of multiple data types from individual patients to learn more about molecular underpinnings of the disease in personalized manner.
  • Study ageing trajectories that lead to diseases
    We are using data from large populations to study ageing-related changes on physiological and molecular levels and their relation to diseases. Our results should confirm known and discover new factors that postpone or accelerate disease onset.

Contact

Small profile photo of V. Guryev
Victor Guryev Team leader, PhD, computational biologist

Genome structure and ageing
Internal postcode FA50
Antonius Deusinglaan 1
9713AV Groningen
The Netherlands