Search

Your search keyword '"Gnewuch, C"' showing total 13 results
Start Over Author "Gnewuch, C" Database OAIster
13 results on '"Gnewuch, C"'

1. Erratum: Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits (vol 15, pg 811, 2016)

Author

Teumer, A., Qi, Q., Nethander, M., Aschard, H., Bandinelli, S., Beekman, M., Berndt, S.I., Bidlingmaier, M., Broer, L., Cappola, A., Ceda, G.P., Chanock, S., Chen, M.-H., Chen, T.C., Chen, Y.-D.I., Chung, J., Del Greco Miglianico, F., Eriksson, J., Ferrucci, L., Friedrich, N., Gnewuch, C., Goodarzi, M.O., Grarup, N., Guo, T., Hammer, E., Hayes, R.B., Hicks, A.A., Hofman, A., Houwing-Duistermaat, J.J., Hu, F., Hunter, D.J., Husemoen, L.L., Isaacs, A., Jacobs, K.B., Janssen, J.A.M.J.L., Jansson, J.-O., Jehmlich, Nico, Johnson, S., Juul, A., Karlsson, M., Kilpelainen, T.O., Kovacs, P., Kraft, P., Li, C., Linneberg, A., Liu, Y., Loos, R.J.F., Lorentzon, M., Lu, Y., Maggio, M., Magi, R., Meigs, J., Mellström, D., Nauck, M., Newman, A.B., Pollak, M.N., Pramstaller, P.P., Prokopenko, I., Psaty, B.M., Reincke, M., Rimm, R.B., Rotter, J.I., Saint Pierre, A., Schurmann, C., Seshadri, S., Sjögren, K., Slagboom, P.E., Strickler, H.D., Stumvoll, M., Suh, Y., Sun, Q., Zhang, C., Svensson, J., Tanaka, T., Tare, A., Tönjes, A., Uh, H.-W., van Duijn, C., van Heemst, D., Vandenput, L., Vasan, R.S., Völker, U., Willems, S.M., Ohlsson, C., Wallaschofski, H., Kaplan, R.C., Teumer, A., Qi, Q., Nethander, M., Aschard, H., Bandinelli, S., Beekman, M., Berndt, S.I., Bidlingmaier, M., Broer, L., Cappola, A., Ceda, G.P., Chanock, S., Chen, M.-H., Chen, T.C., Chen, Y.-D.I., Chung, J., Del Greco Miglianico, F., Eriksson, J., Ferrucci, L., Friedrich, N., Gnewuch, C., Goodarzi, M.O., Grarup, N., Guo, T., Hammer, E., Hayes, R.B., Hicks, A.A., Hofman, A., Houwing-Duistermaat, J.J., Hu, F., Hunter, D.J., Husemoen, L.L., Isaacs, A., Jacobs, K.B., Janssen, J.A.M.J.L., Jansson, J.-O., Jehmlich, Nico, Johnson, S., Juul, A., Karlsson, M., Kilpelainen, T.O., Kovacs, P., Kraft, P., Li, C., Linneberg, A., Liu, Y., Loos, R.J.F., Lorentzon, M., Lu, Y., Maggio, M., Magi, R., Meigs, J., Mellström, D., Nauck, M., Newman, A.B., Pollak, M.N., Pramstaller, P.P., Prokopenko, I., Psaty, B.M., Reincke, M., Rimm, R.B., Rotter, J.I., Saint Pierre, A., Schurmann, C., Seshadri, S., Sjögren, K., Slagboom, P.E., Strickler, H.D., Stumvoll, M., Suh, Y., Sun, Q., Zhang, C., Svensson, J., Tanaka, T., Tare, A., Tönjes, A., Uh, H.-W., van Duijn, C., van Heemst, D., Vandenput, L., Vasan, R.S., Völker, U., Willems, S.M., Ohlsson, C., Wallaschofski, H., and Kaplan, R.C.

Abstract

no abstract

Published
2017

2. Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

Author

Teumer, A. (Alexander), Qi, Q., Nethander, M. (Maria), Aschard, H. (Hugues), Bandinelli, S. (Stefania), Beekman, M. (Marian), Berndt, S.I. (Sonja), Bidlingmaier, M. (Martin), Broer, L. (Linda), Cappola, A.R. (Anne), Ceda, G.P. (Gian Paolo), Chanock, S.J. (Stephen), Chen, M.-H. (Ming-Huei), Chen, T.C. (Tai C.), Chen, Y.D. (Y.), Chung, J. (Jonathan), Del Greco Miglianico, F. (Fabiola), Eriksson, J. (Joel), Ferrucci, L. (Luigi), Friedrich, N. (Nele), Gnewuch, C. (Carsten), Goodarzi, M. (Mark), Grarup, N. (Niels), Guo, T. (Tingwei), Hammer, E. (Elke), Hayes, R.B. (Richard), Hicks, A.A. (Andrew), Hofman, A. (Albert), Houwing-Duistermaat, J.J. (Jeanine), Hu, F. (Frank), Hunter, D. (David), Husemoen, L.L.N. (Lise Lotte), Isaacs, A.J. (Aaron), Jacobs, K.B. (Kevin), Janssen, J.A.M.J.L. (Joop), Jansson, J.-O. (John-Olov), Jehmlich, N. (Nico), Johnson, S. (Simon), Juul, A. (Anders), Karlsson, M. (Magnus), Kilpeläinen, T.O. (Tuomas), Kovacs, P. (Peter), Kraft, P. (Peter), Li, C. (Chao), Linneberg, A. (Allan), Liu, Y. (YongMei), Loos, R.J.F. (Ruth), Lorentzon, M. (Mattias), Lu, Y. (Yingchang), Maggio, M. (Marcello), Mägi, R. (Reedik), Meigs, J.B. (James), Mellström, D. (Dan), Nauck, M. (Matthias), Newman, A.B. (Anne B.), Pollak, M.N. (Michael), Pramstaller, P.P. (Peter Paul), Prokopenko, I. (Inga), Psaty, B.M. (Bruce), Reincke, M. (Martin), Rimm, E.B. (Eric B.), Rotter, J.I. (Jerome I.), Saint Pierre, A. (Aude), Schurmann, C. (Claudia), Seshadri, S. (Sudha), Sjögren, K. (Klara), Slagboom, P.E. (Eline), Strickler, H.D. (Howard D.), Stumvoll, M. (Michael), Suh, Y. (Yousin), Sun, Q. (Qi), Zhang, C. (Cuilin), Svensson, J. (Johan), Tanaka, T. (Toshiko), Tare, A. (Archana), Tönjes, A. (Anke), Uh, H.-W. (Hae-Won), Duijn, C.M. (Cornelia) van, Heemst, D. (Diana) van, Vandenput, L. (Liesbeth), Vasan, R.S. (Ramachandran Srini), Völker, U. (Uwe), Willems, S.M. (Sara), Ohlsson, C. (Claes), Wallaschofski, H. (Henri), Kaplan, R.C. (Robert), Teumer, A. (Alexander), Qi, Q., Nethander, M. (Maria), Aschard, H. (Hugues), Bandinelli, S. (Stefania), Beekman, M. (Marian), Berndt, S.I. (Sonja), Bidlingmaier, M. (Martin), Broer, L. (Linda), Cappola, A.R. (Anne), Ceda, G.P. (Gian Paolo), Chanock, S.J. (Stephen), Chen, M.-H. (Ming-Huei), Chen, T.C. (Tai C.), Chen, Y.D. (Y.), Chung, J. (Jonathan), Del Greco Miglianico, F. (Fabiola), Eriksson, J. (Joel), Ferrucci, L. (Luigi), Friedrich, N. (Nele), Gnewuch, C. (Carsten), Goodarzi, M. (Mark), Grarup, N. (Niels), Guo, T. (Tingwei), Hammer, E. (Elke), Hayes, R.B. (Richard), Hicks, A.A. (Andrew), Hofman, A. (Albert), Houwing-Duistermaat, J.J. (Jeanine), Hu, F. (Frank), Hunter, D. (David), Husemoen, L.L.N. (Lise Lotte), Isaacs, A.J. (Aaron), Jacobs, K.B. (Kevin), Janssen, J.A.M.J.L. (Joop), Jansson, J.-O. (John-Olov), Jehmlich, N. (Nico), Johnson, S. (Simon), Juul, A. (Anders), Karlsson, M. (Magnus), Kilpeläinen, T.O. (Tuomas), Kovacs, P. (Peter), Kraft, P. (Peter), Li, C. (Chao), Linneberg, A. (Allan), Liu, Y. (YongMei), Loos, R.J.F. (Ruth), Lorentzon, M. (Mattias), Lu, Y. (Yingchang), Maggio, M. (Marcello), Mägi, R. (Reedik), Meigs, J.B. (James), Mellström, D. (Dan), Nauck, M. (Matthias), Newman, A.B. (Anne B.), Pollak, M.N. (Michael), Pramstaller, P.P. (Peter Paul), Prokopenko, I. (Inga), Psaty, B.M. (Bruce), Reincke, M. (Martin), Rimm, E.B. (Eric B.), Rotter, J.I. (Jerome I.), Saint Pierre, A. (Aude), Schurmann, C. (Claudia), Seshadri, S. (Sudha), Sjögren, K. (Klara), Slagboom, P.E. (Eline), Strickler, H.D. (Howard D.), Stumvoll, M. (Michael), Suh, Y. (Yousin), Sun, Q. (Qi), Zhang, C. (Cuilin), Svensson, J. (Johan), Tanaka, T. (Toshiko), Tare, A. (Archana), Tönjes, A. (Anke), Uh, H.-W. (Hae-Won), Duijn, C.M. (Cornelia) van, Heemst, D. (Diana) van, Vandenput, L. (Liesbeth), Vasan, R.S. (Ramachandran Srini), Völker, U. (Uwe), Willems, S.M. (Sara), Ohlsson, C. (Claes), Wallaschofski, H. (Henri), and Kaplan, R.C. (Robert)

Abstract

The growth hormone/insulin-like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF-related proteins including IGF-I and IGF-binding protein-3 (IGFBP-3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through

Published
2016
Full Text
View/download PDF

3. Genomewide meta‐analysis identifies loci associated with IGF‐I and IGFBP‐3 levels with impact on age‐related traits

Author

Teumer, A., Qi, Q., Nethander, M., Aschard, H., Bandinelli, S., Beekman, M., Berndt, S.I., Bidlingmaier, M., Broer, L., Cappola, A., Ceda, G.P., Chanock, S., Chen, M.-H., Chen, T.C., Chen, Y.-D.I., Chung, J., Del Greco Miglianico, F., Eriksson, J., Ferrucci, L., Friedrich, N., Gnewuch, C., Goodarzi, M.O., Grarup, N., Guo, T., Hammer, E., Hayes, R.B., Hicks, A.A., Hofman, A., Houwing-Duistermaat, J.J., Hu, F., Hunter, D.J., Husemoen, L.L., Isaacs, A., Jacobs, K.B., Janssen, J.A.M.J.L., Jansson, J.-O., Jehmlich, Nico, Johnson, S., Juul, A., Karlsson, M., Kilpelainen, T.O., Kovacs, P., Kraft, P., Li, C., Linneberg, A., Liu, Y., Loos, R.J.F., Lorentzon, M., Lu, Y., Maggio, M., Magi, R., Meigs, J., Mellström, D., Nauck, M., Newman, A.B., Pollak, M.N., Pramstaller, P.P., Prokopenko, I., Psaty, B.M., Reincke, M., Rimm, R.B., Rotter, J.I., Saint Pierre, A., Schurmann, C., Seshadri, S., Sjögren, K., Slagboom, P.E., Strickler, H.D., Stumvoll, M., Suh, Y., Sun, Q., Zhang, C., Svensson, J., Tanaka, T., Tare, A., Tönjes, A., Uh, H.-W., van Duijn, C., van Heemst, D., Vandenput, L., Vasan, R.S., Völker, U., Willems, S.M., Ohlsson, C., Wallaschofski, H., Kaplan, R.C., Teumer, A., Qi, Q., Nethander, M., Aschard, H., Bandinelli, S., Beekman, M., Berndt, S.I., Bidlingmaier, M., Broer, L., Cappola, A., Ceda, G.P., Chanock, S., Chen, M.-H., Chen, T.C., Chen, Y.-D.I., Chung, J., Del Greco Miglianico, F., Eriksson, J., Ferrucci, L., Friedrich, N., Gnewuch, C., Goodarzi, M.O., Grarup, N., Guo, T., Hammer, E., Hayes, R.B., Hicks, A.A., Hofman, A., Houwing-Duistermaat, J.J., Hu, F., Hunter, D.J., Husemoen, L.L., Isaacs, A., Jacobs, K.B., Janssen, J.A.M.J.L., Jansson, J.-O., Jehmlich, Nico, Johnson, S., Juul, A., Karlsson, M., Kilpelainen, T.O., Kovacs, P., Kraft, P., Li, C., Linneberg, A., Liu, Y., Loos, R.J.F., Lorentzon, M., Lu, Y., Maggio, M., Magi, R., Meigs, J., Mellström, D., Nauck, M., Newman, A.B., Pollak, M.N., Pramstaller, P.P., Prokopenko, I., Psaty, B.M., Reincke, M., Rimm, R.B., Rotter, J.I., Saint Pierre, A., Schurmann, C., Seshadri, S., Sjögren, K., Slagboom, P.E., Strickler, H.D., Stumvoll, M., Suh, Y., Sun, Q., Zhang, C., Svensson, J., Tanaka, T., Tare, A., Tönjes, A., Uh, H.-W., van Duijn, C., van Heemst, D., Vandenput, L., Vasan, R.S., Völker, U., Willems, S.M., Ohlsson, C., Wallaschofski, H., and Kaplan, R.C.

Abstract

The growth hormone/insulin-like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF-related proteins including IGF-I and IGF-binding protein-3 (IGFBP-3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF-I and IGFBP-3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP-3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF-I and IGFBP-3 concentrations. The IGF-I-decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity-associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF-I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF-I- and IGFBP-3-associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF-I and IGFBP-3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity-associated loci.

Published
2016

4. Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

Author

Teumer, A, Qi, QB, Nethander, M, Aschard, H, Bandinelli, S, Beekman, M, Berndt, SI, Bidlingmaier, M, Broer, Linda, Cappola, A, Ceda, G P, Chanock, S, Chen, MH, Chen, T C, Chen, YDI, Chung, JW, Miglianico, F D, Eriksson, J, Ferrucci, L, Friedrich, N, Gnewuch, C, Goodarzi, MO, Grarup, N, Guo, T W, Hammer, E, Hayes, RB, Hicks, AA, Hofman, Bert, Houwing-Duistermaat, JJ, Hu, F, Hunter, DJ, Husemoen, LL, Isaacs, Aaron, Jacobs, KB, Janssen, J.A.M.J.L., Jansson, JO, Jehmlich, N, Johnson, S, Juul, A, Karlsson, M, Kilpelainen, TO, Kovacs, P, Kraft, P, Li, C, Linneberg, A, Liu, YM, Loos, RJF, Lorentzon, M, Lu, YC, Maggio, M, Magi, R, Meigs, J, Mellstrom, D, Nauck, M, Newman, AB, Pollak, MN, Pramstaller, PP, Prokopenko, I, Psaty, BM, Reincke, M, Rimm, EB, Rotter, JI, Saint Pierre, A, Schurmann, C, Seshadri, S, Sjogren, K, Slagboom, PE (Eline), Strickler, H D, Stumvoll, M, Suh, Y S, Sun, Q, Zhang, CL, Svensson, J, Tanaka, T, Tare, A, Tonjes, A, Uh, HW, Duijn, Cornelia, van Heemst, D, Vandenput, L, Vasan, RS, Volker, U, Willems, SM, Ohlsson, C, Wallaschofski, H, Kaplan, RC, Teumer, A, Qi, QB, Nethander, M, Aschard, H, Bandinelli, S, Beekman, M, Berndt, SI, Bidlingmaier, M, Broer, Linda, Cappola, A, Ceda, G P, Chanock, S, Chen, MH, Chen, T C, Chen, YDI, Chung, JW, Miglianico, F D, Eriksson, J, Ferrucci, L, Friedrich, N, Gnewuch, C, Goodarzi, MO, Grarup, N, Guo, T W, Hammer, E, Hayes, RB, Hicks, AA, Hofman, Bert, Houwing-Duistermaat, JJ, Hu, F, Hunter, DJ, Husemoen, LL, Isaacs, Aaron, Jacobs, KB, Janssen, J.A.M.J.L., Jansson, JO, Jehmlich, N, Johnson, S, Juul, A, Karlsson, M, Kilpelainen, TO, Kovacs, P, Kraft, P, Li, C, Linneberg, A, Liu, YM, Loos, RJF, Lorentzon, M, Lu, YC, Maggio, M, Magi, R, Meigs, J, Mellstrom, D, Nauck, M, Newman, AB, Pollak, MN, Pramstaller, PP, Prokopenko, I, Psaty, BM, Reincke, M, Rimm, EB, Rotter, JI, Saint Pierre, A, Schurmann, C, Seshadri, S, Sjogren, K, Slagboom, PE (Eline), Strickler, H D, Stumvoll, M, Suh, Y S, Sun, Q, Zhang, CL, Svensson, J, Tanaka, T, Tare, A, Tonjes, A, Uh, HW, Duijn, Cornelia, van Heemst, D, Vandenput, L, Vasan, RS, Volker, U, Willems, SM, Ohlsson, C, Wallaschofski, H, and Kaplan, RC

Published
2016

5. 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
Full Text
View/download PDF

6. Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations

Author

Demirkan, A. (Ayşe), Duijn, C.M. (Cornelia) van, Ugocsai, P. (Peter), Isaacs, A.J. (Aaron), Pramstaller, P.P. (Peter Paul), Liebisch, G. (Gerhard), Wilson, J.F. (James), 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), Nelson, C.P. (Christopher P.), Preuss, M. (Michael), Bis, J.C. (Joshua), O'Donnell, C.J. (Christopher), Franceschini, N. (Nora), 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), Demirkan, A. (Ayşe), Duijn, C.M. (Cornelia) van, Ugocsai, P. (Peter), Isaacs, A.J. (Aaron), Pramstaller, P.P. (Peter Paul), Liebisch, G. (Gerhard), Wilson, J.F. (James), 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), Nelson, C.P. (Christopher P.), Preuss, M. (Michael), Bis, J.C. (Joshua), O'Donnell, C.J. (Christopher), Franceschini, N. (Nora), 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

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10 -204) and 10 loci for sphingolipids (smallest P-value = 3.10×10 -57). After a correction for multiple comparisons (P-value&2.2×10 -9), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nin

Published
2012
Full Text
View/download PDF

7. Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations

Author

Demirkan, Ayse, Duijn, Cornelia, Ugocsai, P, Isaacs, Aaron, Pramstaller, PP, Liebisch, G, Wilson, JF, Johansson, A, Rudan, I, Aulchenko, YS, Kirichenko, AV, Janssens, Cecile, Jansen, RC, Gnewuch, C, Domingues, FS, Pattaro, C, Wild, SH, Jonasson, I, Polasek, O, Zorkoltseva, IV, Hofman, Bert, Karssen, Lennart, Struchalin, M, Floyd, J, Igl, W, Biloglav, Z, Broer, Linda, Pfeufer, A, Pichler, I, Campbell, S, Zaboli, G, Kolcic, I, Rivadeneira, Fernando, Huffman, J, Hastie, ND, Uitterlinden, André, Franke, L, Franklin, CS, Vitart, V, Nelson, CP, Preuss, M, Bis, JC, O'Donnell, CJ, Franceschini, N, Witteman, JCM, Axenovich, T, Oostra, Ben, Meitinger, T, Hicks, AA, Hayward, C, Wright, AF, Gyllensten, U, Campbell, H, Schmitz, G, Demirkan, Ayse, Duijn, Cornelia, Ugocsai, P, Isaacs, Aaron, Pramstaller, PP, Liebisch, G, Wilson, JF, Johansson, A, Rudan, I, Aulchenko, YS, Kirichenko, AV, Janssens, Cecile, Jansen, RC, Gnewuch, C, Domingues, FS, Pattaro, C, Wild, SH, Jonasson, I, Polasek, O, Zorkoltseva, IV, Hofman, Bert, Karssen, Lennart, Struchalin, M, Floyd, J, Igl, W, Biloglav, Z, Broer, Linda, Pfeufer, A, Pichler, I, Campbell, S, Zaboli, G, Kolcic, I, Rivadeneira, Fernando, Huffman, J, Hastie, ND, Uitterlinden, André, Franke, L, Franklin, CS, Vitart, V, Nelson, CP, Preuss, M, Bis, JC, O'Donnell, CJ, Franceschini, N, Witteman, JCM, Axenovich, T, Oostra, Ben, Meitinger, T, Hicks, AA, Hayward, C, Wright, AF, Gyllensten, U, Campbell, H, and Schmitz, G

Abstract

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88 x 10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10 x 10(-57)). After a correction for multiple comparisons (P-value, 2.2 x 10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study iden

Published
2012

8. A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level

Author

Pattaro, C. (Cristian), Grandi, A. (Alessandro) de, Vitart, V. (Veronique), Hayward, C. (Caroline), Franke, A. (Andre), Aulchenko, Y.S. (Yurii), Johansson, A. (Åsa), Wild, S.H. (Sarah), Melville, S.A. (Scott), Isaacs, A.J. (Aaron), Polasek, O. (Ozren), Ellinghaus, D. (David), Kolcic, I. (Ivana), Nöthlings, U. (Ute), Zgaga, L. (Lina), Zemunik, T. (Tatijana), Gnewuch, C. (Carsten), Schreiber, S. (Stefan), Campbell, S. (Susan), Hastie, N. (Nick), Boban, M. (Mladen), Meitinger, T. (Thomas), Oostra, B.A. (Ben), Riegler, P. (Peter), Minelli, C. (Cosetta), Wright, A.F. (Alan), Campbell, H. (Harry), Duijn, C.M. (Cornelia) van, Gyllensten, U. (Ulf), Wilson, J.F. (James), Krawczak, M. (Michael), Rudan, I. (Igor), Pramstaller, P.P. (Peter Paul), Pattaro, C. (Cristian), Grandi, A. (Alessandro) de, Vitart, V. (Veronique), Hayward, C. (Caroline), Franke, A. (Andre), Aulchenko, Y.S. (Yurii), Johansson, A. (Åsa), Wild, S.H. (Sarah), Melville, S.A. (Scott), Isaacs, A.J. (Aaron), Polasek, O. (Ozren), Ellinghaus, D. (David), Kolcic, I. (Ivana), Nöthlings, U. (Ute), Zgaga, L. (Lina), Zemunik, T. (Tatijana), Gnewuch, C. (Carsten), Schreiber, S. (Stefan), Campbell, S. (Susan), Hastie, N. (Nick), Boban, M. (Mladen), Meitinger, T. (Thomas), Oostra, B.A. (Ben), Riegler, P. (Peter), Minelli, C. (Cosetta), Wright, A.F. (Alan), Campbell, H. (Harry), Duijn, C.M. (Cornelia) van, Gyllensten, U. (Ulf), Wilson, J.F. (James), Krawczak, M. (Michael), Rudan, I. (Igor), and Pramstaller, P.P. (Peter Paul)

Abstract

Background: Serum creatinine (SCR) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in SCR level is explicable by genetic factors.Methods: We performed a meta-analysis of genome-wide association studies of SCR undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence f

Published
2010
Full Text
View/download PDF

9. Modeling of environmental effects in genome-wide association studies identifies SLC2A2 and HP as novel loci influencing serum cholesterol levels

Author

Igl, W. (Wilmar), Johansson, A. (Åsa), Wilson, J.F. (James), Wild, S.H. (Sarah), Polasek, O. (Ozren), Hayward, C. (Caroline), Vitart, V. (Veronique), Hastie, N. (Nick), Rudan, P. (Pavao), Gnewuch, C. (Carsten), Schmitz, G. (Gerd), Meitinger, T. (Thomas), Pramstaller, P.P. (Peter Paul), Hicks, A.A. (Andrew), Oostra, B.A. (Ben), Duijn, C.M. (Cornelia) van, Rudan, I. (Igor), Wright, A.F. (Alan), Campbell, H. (Harry), Gyllensten, U. (Ulf), Igl, W. (Wilmar), Johansson, A. (Åsa), Wilson, J.F. (James), Wild, S.H. (Sarah), Polasek, O. (Ozren), Hayward, C. (Caroline), Vitart, V. (Veronique), Hastie, N. (Nick), Rudan, P. (Pavao), Gnewuch, C. (Carsten), Schmitz, G. (Gerd), Meitinger, T. (Thomas), Pramstaller, P.P. (Peter Paul), Hicks, A.A. (Andrew), Oostra, B.A. (Ben), Duijn, C.M. (Cornelia) van, Rudan, I. (Igor), Wright, A.F. (Alan), Campbell, H. (Harry), and Gyllensten, U. (Ulf)

Abstract

Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWA

Published
2010
Full Text
View/download PDF

10. Modeling of Environmental Effects in Genome-Wide Association Studies Identifies SLC2A2 and HP as Novel Loci Influencing Serum Cholesterol Levels

Author

Igl, W, Johansson, A, Wilson, JF, Wild, SH, Polasek, O, Hayward, C, Vitart, V, Hastie, N, Rudan, P, Gnewuch, C, Schmitz, G, Meitinger, T, Pramstaller, PP, Hicks, AA, Oostra, Ben, Duijn, Cornelia, Rudan, I, Wright, A, Campbell, H, Gyllensten, U, Igl, W, Johansson, A, Wilson, JF, Wild, SH, Polasek, O, Hayward, C, Vitart, V, Hastie, N, Rudan, P, Gnewuch, C, Schmitz, G, Meitinger, T, Pramstaller, PP, Hicks, AA, Oostra, Ben, Duijn, Cornelia, Rudan, I, Wright, A, Campbell, H, and Gyllensten, U

Abstract

Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (N-SE = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (N-NS = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (p(SE,unadjusted) = 3.6x10(-5), p(SE,adjusted) = 2.26x10(-6), p(NS,unadjusted) = 0.047) in the SLC2A2 ( Glucose transporter type 2) and rs2000999 (p(SE,unadjusted) = 1.1x10(-3), p(SE,adjusted) = 3.8x10(-4), p(NS,unadjusted) = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci.

Published
2010

11. A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level

Author

Pattaro, C, De Grandi, A, Vitart, V, Hayward, C, Franke, A, Aulchenko, YS, Johansson, A, Wild, SH, Melville, SA, Isaacs, Aaron, Polasek, O, Ellinghaus, D, Kolcic, I, Nothlings, U, Zgaga, L, Zemunik, T, Gnewuch, C, Schreiber, S, Campbell, S, Hastie, N, Boban, M, Meitinger, T, Oostra, Ben, Riegler, P, Minelli, C, Wright, AF, Campbell, H, Duijn, Cornelia, Gyllensten, U, Wilson, JF, Krawczak, M, Rudan, I, Pramstaller, PP, Pattaro, C, De Grandi, A, Vitart, V, Hayward, C, Franke, A, Aulchenko, YS, Johansson, A, Wild, SH, Melville, SA, Isaacs, Aaron, Polasek, O, Ellinghaus, D, Kolcic, I, Nothlings, U, Zgaga, L, Zemunik, T, Gnewuch, C, Schreiber, S, Campbell, S, Hastie, N, Boban, M, Meitinger, T, Oostra, Ben, Riegler, P, Minelli, C, Wright, AF, Campbell, H, Duijn, Cornelia, Gyllensten, U, Wilson, JF, Krawczak, M, Rudan, I, and Pramstaller, PP

Abstract

Background: Serum creatinine (S-CR) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in SCR level is explicable by genetic factors. Methods: We performed a meta-analysis of genome-wide association studies of SCR undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence for an association with SCR (candidate loci) were replicated in two additional population-based samples ('replication cohorts'). Results: After the discovery meta-analysis, 29 loci were selected for replication. Association between SCR level and polymorphisms in the collagen type XXII alpha 1 (COL22A1) gene, on chromosome 8, and in the synaptotagmin-1 (SYT1) gene, on chromosome 12, were successfully replicated in the replication cohorts (p value = 1.0 x 10(-6) and 1.7 x 10(-4), respectively). Evidence of association was also found for polymorphisms in a locus including the gamma-aminobutyric acid receptor rho-2 (GABRR2) gene and the ubiquitin-conjugating enzyme E2-J1 (UBE2J1) gene (replication p value = 3.6 x 10(-3)). Previously reported findings, associating glomerular filtration rate with SNPs in the uromodulin (UMOD) gene and in the schroom family member 3 (SCHROOM3) gene were also replicated. Conclusions: While confirming earlier results, our study provides new insights in the understanding of the genetic basis of serum creatinine regulatory processes. In particular, the association with the genes SYT1 and GABRR2 corroborate previous findings that highlighted a possible role of the neurotransmitters GABA(A) receptors in the regulation of the glomerular basement membrane and a possible interaction between GABA(A)receptors and synaptotagmin-I at the podocyte level.

Published
2010

12. Genetic determinants of circulating sphingolipid concentrations in European populations

Author

Hicks, A.A. (Andrew), Pramstaller, P.P. (Peter Paul), Johansson, A. (Åsa), Vitart, V. (Veronique), Rudan, I. (Igor), Ugocsai, P. (Peter), Aulchenko, Y.S. (Yurii), Franklin, C.S. (Christopher), Liebisch, G. (Gerhard), Jonasson, I. (Inger), Zorkoltseva, I.V. (Irina), Pattaro, C. (Cristian), Hayward, C. (Caroline), Isaacs, A.J. (Aaron), Hengstenberg, C. (Christian), Campbell, S. (Susan), Gnewuch, C. (Carsten), Janssens, A.C.J.W. (Cécile), Kirichenko, A.V. (Anatoly), König, I.R. (Inke), Marroni, F. (Fabio), Polasek, O. (Ozren), Demirkan, A. (Ayşe), Kolcic, I. (Ivana), Schwienbacher, C. (Christine), Igl, W. (Wilmar), Biloglav, Z. (Zrinka), Witteman, J.C.M. (Jacqueline), Pichler, I. (Irene), Zaboli, G. (Ghazal), Axenovich, T.I. (Tatiana), Peters, A. (Annette), Schreiber, S. (Stefan), Wichmann, H.E. (Heinz Erich), Erdmann, J. (Jeanette), Schunkert, H. (Heribert), Hastie, N. (Nick), Oostra, B.A. (Ben), Wild, S.H. (Sarah), Meitinger, T. (Thomas), Gyllensten, U. (Ulf), Tikka-Kleemola, P. (Päivi), Wilson, J.F. (James), Wright, A.F. (Alan), Schmitz, G. (Gerd), Hicks, A.A. (Andrew), Pramstaller, P.P. (Peter Paul), Johansson, A. (Åsa), Vitart, V. (Veronique), Rudan, I. (Igor), Ugocsai, P. (Peter), Aulchenko, Y.S. (Yurii), Franklin, C.S. (Christopher), Liebisch, G. (Gerhard), Jonasson, I. (Inger), Zorkoltseva, I.V. (Irina), Pattaro, C. (Cristian), Hayward, C. (Caroline), Isaacs, A.J. (Aaron), Hengstenberg, C. (Christian), Campbell, S. (Susan), Gnewuch, C. (Carsten), Janssens, A.C.J.W. (Cécile), Kirichenko, A.V. (Anatoly), König, I.R. (Inke), Marroni, F. (Fabio), Polasek, O. (Ozren), Demirkan, A. (Ayşe), Kolcic, I. (Ivana), Schwienbacher, C. (Christine), Igl, W. (Wilmar), Biloglav, Z. (Zrinka), Witteman, J.C.M. (Jacqueline), Pichler, I. (Irene), Zaboli, G. (Ghazal), Axenovich, T.I. (Tatiana), Peters, A. (Annette), Schreiber, S. (Stefan), Wichmann, H.E. (Heinz Erich), Erdmann, J. (Jeanette), Schunkert, H. (Heribert), Hastie, N. (Nick), Oostra, B.A. (Ben), Wild, S.H. (Sarah), Meitinger, T. (Thomas), Gyllensten, U. (Ulf), Tikka-Kleemola, P. (Päivi), Wilson, J.F. (James), Wright, A.F. (Alan), and Schmitz, G. (Gerd)

Abstract

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipidmetabolismare being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic b-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matchedmetabolite ratiosmeasured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08610266. The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of th

Published
2009
Full Text
View/download PDF

13. Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations

Author

Hicks, AA, Pramstaller, PP, Johansson, A, Vitart, V, Rudan, I, Ugocsai, P, Aulchenko, Yuriy, Franklin, CS, Liebisch, G, Erdmann, J, Jonasson, I, Zorkoltseva, IV, Pattaro, C, Hayward, C, Isaacs, Aaron, Hengstenberg, C, Campbell, S, Gnewuch, C, Janssens, Cecile, Kirichenko, AV, Konig, IR, Marroni, F, Polasek, O, Demirkan, Ayse, Kolcic, I, Schwienbacher, C, Igl, W, Biloglav, Z, Witteman, JCM, Pichler, I, Zaboli, G, Axenovich, TI, Peters, A, Schreiber, S, Wichmann, HE, Schunkert, H, Hastie, N, Oostra, Ben, Wild, SH, Meitinger, T, Gyllensten, U, Duijn, Cornelia, Wilson, JF, Wright, A, Schmitz, G, Campbell, H, Hicks, AA, Pramstaller, PP, Johansson, A, Vitart, V, Rudan, I, Ugocsai, P, Aulchenko, Yuriy, Franklin, CS, Liebisch, G, Erdmann, J, Jonasson, I, Zorkoltseva, IV, Pattaro, C, Hayward, C, Isaacs, Aaron, Hengstenberg, C, Campbell, S, Gnewuch, C, Janssens, Cecile, Kirichenko, AV, Konig, IR, Marroni, F, Polasek, O, Demirkan, Ayse, Kolcic, I, Schwienbacher, C, Igl, W, Biloglav, Z, Witteman, JCM, Pichler, I, Zaboli, G, Axenovich, TI, Peters, A, Schreiber, S, Wichmann, HE, Schunkert, H, Hastie, N, Oostra, Ben, Wild, SH, Meitinger, T, Gyllensten, U, Duijn, Cornelia, Wilson, JF, Wright, A, Schmitz, G, and Campbell, H

Abstract

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08 x 10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested f

Published
2009

Catalog

Books, media, physical & digital resources
See catalog results