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1. Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels

Author

Draisma, G. (Gerrit), Pool, R. (Reńe), Kobl, M. (Michael), Jansen, R. (Rick), Petersen, A.K., Vaarhorst, A.A.M. (Anika), Yet, I. (Idil), Haller, T. (Toomas), Demirkan, A. (Ayşe), Esko, T. (Tõnu), Zhu, G. (Gu), Böhringer, S. (Stefan), Beekman, M. (Marian), Klinken, J.B. (Jan Bert) van, Römisch-Margl, W. (Werner), Prehn, C. (Cornelia), Adamski, J. (Jerzy), De Craen, A.J.M. (Anton J. M.), Leeuwen, E.M. (Elisa) van, Amin, N. (Najaf), Dharuri, H. (Harish), Westra, H.J. (Harm-Jan), Franke, L. (Lude), Geus, E.J.C. (Eco) de, Hottenga, J.J. (Jouke Jan), Willemsen, G.A.H.M. (Gonneke), Henders, A.K. (Anjali), Montgomery, G.W. (Grant), Dimas, A.S. (Antigone), Whitfield, J.B. (John B.), Penninx, B.W.J.H. (Brenda), Spector, T.D. (Timothy), Metspalu, A. (Andres), Slagboom, P.E. (Eline), Van Dijk, K.W. (Ko Willems), Hoen, P.A.C. (Peter) 't, Strauch, K. (Konstantin), Martin, N.G. (Nicholas), Ommen, G.J. (Gert) van, Illig, T. (Thomas), Bell, J.T. (Jordana), Mangino, M. (Massimo), Suhre, K. (Karsten), McCarthy, M.I. (Mark), Gieger, C. (Christian), Isaacs, A. (Aaron), Duijn, C.M. (Cornelia) van, Boomsma, D.I. (Dorret), Draisma, G. (Gerrit), Pool, R. (Reńe), Kobl, M. (Michael), Jansen, R. (Rick), Petersen, A.K., Vaarhorst, A.A.M. (Anika), Yet, I. (Idil), Haller, T. (Toomas), Demirkan, A. (Ayşe), Esko, T. (Tõnu), Zhu, G. (Gu), Böhringer, S. (Stefan), Beekman, M. (Marian), Klinken, J.B. (Jan Bert) van, Römisch-Margl, W. (Werner), Prehn, C. (Cornelia), Adamski, J. (Jerzy), De Craen, A.J.M. (Anton J. M.), Leeuwen, E.M. (Elisa) van, Amin, N. (Najaf), Dharuri, H. (Harish), Westra, H.J. (Harm-Jan), Franke, L. (Lude), Geus, E.J.C. (Eco) de, Hottenga, J.J. (Jouke Jan), Willemsen, G.A.H.M. (Gonneke), Henders, A.K. (Anjali), Montgomery, G.W. (Grant), Dimas, A.S. (Antigone), Whitfield, J.B. (John B.), Penninx, B.W.J.H. (Brenda), Spector, T.D. (Timothy), Metspalu, A. (Andres), Slagboom, P.E. (Eline), Van Dijk, K.W. (Ko Willems), Hoen, P.A.C. (Peter) 't, Strauch, K. (Konstantin), Martin, N.G. (Nicholas), Ommen, G.J. (Gert) van, Illig, T. (Thomas), Bell, J.T. (Jordana), Mangino, M. (Massimo), Suhre, K. (Karsten), McCarthy, M.I. (Mark), Gieger, C. (Christian), Isaacs, A. (Aaron), Duijn, C.M. (Cornelia) van, and Boomsma, D.I. (Dorret)

Abstract

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platfo

Published
2015
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2. Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles

Author

Dharuri, H. (Harish), Henneman, P. (Peter), Demirkan, A. (Ayşe), Klinken, J.B. (Jan) van, Mook-Kanamori, D.O. (Dennis), Wang-Sattler, R. (Rui), Gieger, C. (Christian), Adamski, J. (Jerzy), Hettne, K.M. (Kristina), Roos, M. (Marco), Suhre, K. (Karsten), Duijn, C.M. (Cornelia) van, Willems van Dijk, J.A.P. (Ko), Hoen, P.A.C. (Peter) 't, Ugocsai, P. (Peter), Isaacs, A.J. (Aaron), Pramstaller, P.P. (Peter Paul), Liebisch, G. (Gerhard), Wilson, J.F. (James F), Johansson, A. (Åsa), Rudan, I. (Igor), Aulchenko, Y.S. (Yurii), Kirichenko, A.V. (Anatoly), Janssens, A.C.J.W. (Cécile), Jansen, R.C. (Ritsert), Gnewuch, C. (Carsten), Domingues, I. (Inês), Pattaro, C. (Cristian), Wild, S.H. (Sarah), Jonasson, I. (Inger), Polasek, O. (Ozren), Zorkoltseva, I.V. (Irina), Hofman, A. (Albert), Karssen, L.C. (Lennart), Struchalin, M.V. (Maksim), Floyd, J. (Jamie), Igl, W. (Wilmar), Biloglav, Z. (Zrinka), Broer, L. (Linda), Pfeufer, A. (Arne), Pichler, I. (Irene), Campbell, S. (Susan), Zaboli, G. (Ghazal), Kolcic, I. (Ivana), Rivadeneira Ramirez, F. (Fernando), Huffman, J.E. (Jennifer), Hastie, N. (Nick), Uitterlinden, A.G. (André), Franke, L. (Lude), Franklin, C.S. (Christopher), Vitart, V. (Veronique), Witteman, J.C.M. (Jacqueline), Axenovich, T.I. (Tatiana), Oostra, B.A. (Ben), Meitinger, T. (Thomas), Hicks, A.A. (Andrew), Hayward, C. (Caroline), Wright, A.F. (Alan), Gyllensten, U. (Ulf), Campbell, H. (Harry), Schmitz, G. (Gerd), Dharuri, H. (Harish), Henneman, P. (Peter), Demirkan, A. (Ayşe), Klinken, J.B. (Jan) van, Mook-Kanamori, D.O. (Dennis), Wang-Sattler, R. (Rui), Gieger, C. (Christian), Adamski, J. (Jerzy), Hettne, K.M. (Kristina), Roos, M. (Marco), Suhre, K. (Karsten), Duijn, C.M. (Cornelia) van, Willems van Dijk, J.A.P. (Ko), Hoen, P.A.C. (Peter) 't, Ugocsai, P. (Peter), Isaacs, A.J. (Aaron), Pramstaller, P.P. (Peter Paul), Liebisch, G. (Gerhard), Wilson, J.F. (James F), Johansson, A. (Åsa), Rudan, I. (Igor), Aulchenko, Y.S. (Yurii), Kirichenko, A.V. (Anatoly), Janssens, A.C.J.W. (Cécile), Jansen, R.C. (Ritsert), Gnewuch, C. (Carsten), Domingues, I. (Inês), Pattaro, C. (Cristian), Wild, S.H. (Sarah), Jonasson, I. (Inger), Polasek, O. (Ozren), Zorkoltseva, I.V. (Irina), Hofman, A. (Albert), Karssen, L.C. (Lennart), Struchalin, M.V. (Maksim), Floyd, J. (Jamie), Igl, W. (Wilmar), Biloglav, Z. (Zrinka), Broer, L. (Linda), Pfeufer, A. (Arne), Pichler, I. (Irene), Campbell, S. (Susan), Zaboli, G. (Ghazal), Kolcic, I. (Ivana), Rivadeneira Ramirez, F. (Fernando), Huffman, J.E. (Jennifer), Hastie, N. (Nick), Uitterlinden, A.G. (André), Franke, L. (Lude), Franklin, C.S. (Christopher), Vitart, V. (Veronique), Witteman, J.C.M. (Jacqueline), Axenovich, T.I. (Tatiana), Oostra, B.A. (Ben), Meitinger, T. (Thomas), Hicks, A.A. (Andrew), Hayward, C. (Caroline), Wright, A.F. (Alan), Gyllensten, U. (Ulf), Campbell, H. (Harry), and Schmitz, G. (Gerd)

Abstract

Background: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWA

Published
2013
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3. Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations

Author

Kolz, M. (Melanie), Johnson, T. (Toby), Sanna, S. (Serena), Teumer, A. (Alexander), Vitart, V. (Veronique), Perola, M. (Markus), Mangino, M. (Massimo), Albrecht, E. (Eva), Wallace, C. (Chris), Farrall, M. (Martin), Johansson, A. (Åsa), Dimas, A.S. (Antigone), Aulchenko, Y.S. (Yurii), Beckmann, J.S. (Jacques), Bergmann, S.M. (Sven), Bochud, M. (Murielle), Brown, M.J. (Morris), Campbell, H. (Harry), Connell, J. (John), Dominiczak, A. (Anna), Homuth, G. (Georg), Lamina, C. (Claudia), McCarthy, M.I. (Mark), Meitinger, T. (Thomas), Mooser, V. (Vincent), Munroe, P. (Patricia), Nauck, M. (Matthias), Peden, J. (John), Prokisch, H. (Holger), Salo, P. (Perttu), Salomaa, V. (Veikko), Samani, N.J. (Nilesh), Schlessinger, D. (David), Uda, M. (Manuela), Waeber, G. (Gérard), Waterworth, D. (Dawn), Wang-Sattler, R. (Rui), Wright, A.F. (Alan), Adamski, J. (Jerzy), Whitfield, J.B. (John), Gyllensten, U. (Ulf), Wilson, J.F. (James), Rudan, I. (Igor), Pramstaller, P.P. (Peter Paul), Watkins, H. (Hugh), Doering, A. (Angela), Wichmann, H.E. (Erich), Spector, T.D. (Timothy), Peltonen, L. (Leena Johanna), Völzke, H. (Henry), Nagaraja, R. (Ramaiah), Vollenweider, P. (Peter), Caulfield, M. (Mark), Illig, T. (Thomas), Gieger, C. (Christian), Völker, U. (Uwe), Kolz, M. (Melanie), Johnson, T. (Toby), Sanna, S. (Serena), Teumer, A. (Alexander), Vitart, V. (Veronique), Perola, M. (Markus), Mangino, M. (Massimo), Albrecht, E. (Eva), Wallace, C. (Chris), Farrall, M. (Martin), Johansson, A. (Åsa), Dimas, A.S. (Antigone), Aulchenko, Y.S. (Yurii), Beckmann, J.S. (Jacques), Bergmann, S.M. (Sven), Bochud, M. (Murielle), Brown, M.J. (Morris), Campbell, H. (Harry), Connell, J. (John), Dominiczak, A. (Anna), Homuth, G. (Georg), Lamina, C. (Claudia), McCarthy, M.I. (Mark), Meitinger, T. (Thomas), Mooser, V. (Vincent), Munroe, P. (Patricia), Nauck, M. (Matthias), Peden, J. (John), Prokisch, H. (Holger), Salo, P. (Perttu), Salomaa, V. (Veikko), Samani, N.J. (Nilesh), Schlessinger, D. (David), Uda, M. (Manuela), Waeber, G. (Gérard), Waterworth, D. (Dawn), Wang-Sattler, R. (Rui), Wright, A.F. (Alan), Adamski, J. (Jerzy), Whitfield, J.B. (John), Gyllensten, U. (Ulf), Wilson, J.F. (James), Rudan, I. (Igor), Pramstaller, P.P. (Peter Paul), Watkins, H. (Hugh), Doering, A. (Angela), Wichmann, H.E. (Erich), Spector, T.D. (Timothy), Peltonen, L. (Leena Johanna), Völzke, H. (Henry), Nagaraja, R. (Ramaiah), Vollenweider, P. (Peter), Caulfield, M. (Mark), Illig, T. (Thomas), Gieger, C. (Christian), and Völker, U. (Uwe)

Abstract

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10-201), ABCG2 (p = 3.1×10-26), SLC17A1 (p = 3.0×10-14), SLC22A11 (p = 6.7×10-14), SLC22A12 (p = 2.0×10-9), SLC16A9 (p = 1.1×10-8), GCKR (p = 1.4×10-9), LRRC16A (p = 8.5×10-9), and near PDZK1 (p = 2.7×10-9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10-26) and propionyl-L-carnitine (p = 5.0×10-8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10-57and p = 8.1×10-54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.

Published
2009
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