rs1052162 - ALMS1

Magnitude 2.2 · 1 study on file

Reported associations

• Mining the Unknown: A Systems Approach to Metabolite Identification Combining Genetic and Metabolic Information - Unknown journal (n.d.) · Unknown authors · PubMed 23093944

  ABSTRACT: Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these "unknown metabolites" is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical

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