What we do

In the Statistical Genetics Group, we are interested in the development of statistical methodologies in order to decipher the genetic architecture of complex human traits related to obesity. To do this, we efficiently combine large-scale genome-wide association studies (GWAS) with various -omics data. Our methods improve genetic fine-mapping, reveal gene-environment interactions, dissect genetic subtypes of obesity, enhance causal effect estimation and detect various statistical artefacts. Furthermore, we are involved in large consortia researching the genetic basis of anthropometric traits (GIANT) and longevity (LifeGen).

Find out more about the Group’s activities

Highlights 2019

Main publications 2019

  • Porcu E et al.
    Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
    Nat Comms, doi: 10.1038/s41467-019-10936-0
  • Timmers PR et al.
    Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances
    eLife, doi: 10.7554/eLife.39856
  • Marouli E et al.
    Mendelian randomisation analyses find pulmonary factors mediate the effect of height on coronary artery disease
    Comm Biol, doi: 10.1038/s42003-019-0361-2

Members

epfl lausanne

Zoltán Kutalik
Statistical Genetics Group
CHUV / University of Lausanne
Group Webpage

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Domain(s) of activity:

  • Genes and genomes
  • Systems biology
  • Biostatistics
  • Epigenetics
  • GWAS
  • Human genetics
  • Mathematical modelling
  • Metabolomics
  • Personalised medicine
  • Population genetics
  • Transcriptomics

Domain(s) of application:

  • Medicine and health

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