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Raffler, J. ; Römisch-Margl, W. ; Petersen, A.-K. ; Pagel, P.* ; Blöchl, F.* ; Hengstenberg, C.* ; Illig, T. ; Meisinger, C. ; Stark, K.* ; Wichmann, H.-E. ; Adamski, J. ; Gieger, C. ; Kastenmüller, G. ; Suhre, K.

Identification and MS-assisted interpretation of genetically influenced NMR signals in human plasma.

Genome Med. 5:13 (2013)
Verlagsversion Verlagsversion DOI PMC
Open Access Gold
Nuclear magnetic resonance spectroscopy (NMR) provides robust readouts of many metabolic parameters in one experiment. However, identification of clinically relevant markers in 1H NMR spectra is a major challenge. Association of NMR derived quantities with genetic variants can uncover biologically relevant metabolic traits. Using NMR data of plasma samples from 1,757 individuals from the KORA study together with 655,658 genetic variants, we show that ratios between NMR intensities at two chemical shift positions can provide informative and robust biomarkers. We report seven loci of genetic association with NMR derived traits (APOA1, CETP, CPS1, GCKR, FADS1, LIPC, PYROXD2) and characterize these traits biochemically using mass spectrometry. These ratios may now be used in clinical studies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Genome-wide Association ; Hdl-cholesterol Concentrations ; Type-2 Diabetes Risk ; Susceptibility Loci ; Triglyceride Levels ; Fasting Glucose ; Acid Intake ; Population ; Disease ; Metabolomics
ISSN (print) / ISBN 1756-994X
e-ISSN 1756-994X
Zeitschrift Genome Medicine
Quellenangaben Band: 5, Heft: 2, Seiten: , Artikelnummer: 13 Supplement: ,
Verlag BioMed Central
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Genetic Epidemiology (IGE)
Research Unit Molecular Epidemiology (AME)
Institute of Epidemiology II (EPI2)
Institute of Epidemiology (EPI)
Molekulare Endokrinologie und Metabolismus (MEM)