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Your search keyword '"Krarup, Nikolaj T."' showing total 14 results
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14 results on '"Krarup, Nikolaj T."'

1. A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes

Author

Moltke, Ida, Grarup, Niels, Jørgensen, Marit E, Bjerregaard, Peter, Treebak, Jonas T, Fumagalli, Matteo, Korneliussen, Thorfinn S, Andersen, Marianne A, Nielsen, Thomas S, Krarup, Nikolaj T, Gjesing, Anette P, Zierath, Juleen R, Linneberg, Allan, Wu, Xueli, Sun, Guangqing, Jin, Xin, Al-Aama, Jumana, Wang, Jun, Borch-Johnsen, Knut, Pedersen, Oluf, Nielsen, Rasmus, Albrechtsen, Anders, and Hansen, Torben

Subjects
Biological Sciences, Genetics, Human Genome, Diabetes, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Adult, Blood Glucose, Codon, Nonsense, Diabetes Mellitus, Type 2, GTPase-Activating Proteins, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Genotype, Greenland, Humans, Insulin, Insulin Resistance, Middle Aged, Muscle, Skeletal, General Science & Technology
Abstract

The Greenlandic population, a small and historically isolated founder population comprising about 57,000 inhabitants, has experienced a dramatic increase in type 2 diabetes (T2D) prevalence during the past 25 years. Motivated by this, we performed association mapping of T2D-related quantitative traits in up to 2,575 Greenlandic individuals without known diabetes. Using array-based genotyping and exome sequencing, we discovered a nonsense p.Arg684Ter variant (in which arginine is replaced by a termination codon) in the gene TBC1D4 with an allele frequency of 17%. Here we show that homozygous carriers of this variant have markedly higher concentrations of plasma glucose (β = 3.8 mmol l(-1), P = 2.5 × 10(-35)) and serum insulin (β = 165 pmol l(-1), P = 1.5 × 10(-20)) 2 hours after an oral glucose load compared with individuals with other genotypes (both non-carriers and heterozygous carriers). Furthermore, homozygous carriers have marginally lower concentrations of fasting plasma glucose (β = -0.18 mmol l(-1), P = 1.1 × 10(-6)) and fasting serum insulin (β = -8.3 pmol l(-1), P = 0.0014), and their T2D risk is markedly increased (odds ratio (OR) = 10.3, P = 1.6 × 10(-24)). Heterozygous carriers have a moderately higher plasma glucose concentration 2 hours after an oral glucose load than non-carriers (β = 0.43 mmol l(-1), P = 5.3 × 10(-5)). Analyses of skeletal muscle biopsies showed lower messenger RNA and protein levels of the long isoform of TBC1D4, and lower muscle protein levels of the glucose transporter GLUT4, with increasing number of p.Arg684Ter alleles. These findings are concomitant with a severely decreased insulin-stimulated glucose uptake in muscle, leading to postprandial hyperglycaemia, impaired glucose tolerance and T2D. The observed effect sizes are several times larger than any previous findings in large-scale genome-wide association studies of these traits and constitute further proof of the value of conducting genetic association studies outside the traditional setting of large homogeneous populations.

Published
2014

2. Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

Author

Lohmueller, Kirk E, Sparsø, Thomas, Li, Qibin, Andersson, Ehm, Korneliussen, Thorfinn, Albrechtsen, Anders, Banasik, Karina, Grarup, Niels, Hallgrimsdottir, Ingileif, Kiil, Kristoffer, Kilpeläinen, Tuomas O, Krarup, Nikolaj T, Pers, Tune H, Sanchez, Gaston, Hu, Youna, DeGiorgio, Michael, Jørgensen, Torben, Sandbæk, Annelli, Lauritzen, Torsten, Brunak, Søren, Kristiansen, Karsten, Li, Yingrui, Hansen, Torben, Wang, Jun, Nielsen, Rasmus, and Pedersen, Oluf

Subjects
Biological Sciences, Genetics, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Published
2014

3. Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

Author

Lohmueller, Kirk E, Sparsø, Thomas, Li, Qibin, Andersson, Ehm, Korneliussen, Thorfinn, Albrechtsen, Anders, Banasik, Karina, Grarup, Niels, Hallgrimsdottir, Ingileif, Kiil, Kristoffer, Kilpeläinen, Tuomas O, Krarup, Nikolaj T, Pers, Tune H, Sanchez, Gaston, Hu, Youna, DeGiorgio, Michael, Jørgensen, Torben, Sandbæk, Annelli, Lauritzen, Torsten, Brunak, Søren, Kristiansen, Karsten, Li, Yingrui, Hansen, Torben, Wang, Jun, Nielsen, Rasmus, and Pedersen, Oluf

Subjects
Human Genome, Genetic Testing, Diabetes, Biotechnology, Cardiovascular, Genetics, Autoimmune Disease, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Computational Biology, Denmark, Diabetes Mellitus, Type 2, Exome, Genetic Association Studies, Genetic Variation, Genotype, High-Throughput Nucleotide Sequencing, Humans, Models, Statistical, Open Reading Frames, Polymorphism, Single Nucleotide, White People, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m(2) and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.

Published
2013

5. Variant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease

Author

Nioi, Paul, Sigurdsson, Asgeir, Thorleifsson, Gudmar, Helgason, Hannes, Agustsdottir, Arna B., Norddahl, Gudmundur L., Helgadottir, Anna, Magnusdottir, Audur, Jonasdottir, Aslaug, Gretarsdottir, Solveig, Jonsdottir, Ingileif, Steinthorsdottir, Valgerdur, Rafnar, Thorunn, Swinkels, Dorine W., Galesloot, Tessel E., Grarup, Niels, Jørgensen, Torben, Vestergaard, Henrik, Hansen, Torben, Lauritzen, Torsten, Linneberg, Allan, Friedrich, Nele, Krarup, Nikolaj T., Fenger, Mogens, Abildgaard, Ulrik, Hansen, Peter R., Galløe, Anders M., Braund, Peter S., Nelson, Christopher P., Hall, Alistair S., Williams, Michael J.A., van Rij, Andre M., Jones, Gregory T., Patel, Riyaz S., Levey, Allan I., Hayek, Salim, Shah, Svati H., Reilly, Muredach, Eyjolfsson, Gudmundur I., Sigurdardottir, Olof, Olafsson, Isleifur, Kiemeney, Lambertus A., Quyyumi, Arshed A., Rader, Daniel J., Kraus, William E., Samani, Nilesh J., Pedersen, Oluf, Thorgeirsson, Gudmundur, Masson, Gisli, Holm, Hilma, Gudbjartsson, Daniel, Sulem, Patrick, Thorsteinsdottir, Unnur, and Stefansson, Kari

Published
2016
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6. Arg82Cys Polymorphism of the Protein Nepmucin Implies a Role in HDL Metabolism.

Author

Metz, Sophia, Krarup, Nikolaj T, Bryrup, Thomas, Støy, Julie, Andersson, Ehm A, Christoffersen, Christina, Neville, Matt J, Christiansen, Malene R, Jonsson, Anna E, Witte, Daniel R, Kampmann, Ulla, Nielsen, Lars B, Jørgensen, Niklas R, Karpe, Fredrik, Grarup, Niels, Pedersen, Oluf, Kilpeläinen, Tuomas O, and Hansen, Torben

Subjects
HDL cholesterol, BLOOD lipids, METABOLISM, MEMBRANE proteins, BLOOD sugar
Abstract

Context Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG , is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive. Objective Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism. Methods We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status. Results A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB (P  = .004) and RbG studies (P  = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 (P  = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels. Conclusion Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation. [ABSTRACT FROM AUTHOR]

Published
2022
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8. The minor C-allele of rs2014355 in ACADS is associated with reduced insulin release following an oral glucose load

Author

Pisinger Charlotta, Lauritzen Torsten, Sandbæk Annelli, Andersson Åsa, Sandholt Camilla H, Krarup Nikolaj T, Justesen Johanne M, Banasik Karina, Hornbak Malene, Witte Daniel R, Sørensen Thorkild IA, Pedersen Oluf, and Hansen Torben

Subjects
Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (ACADS) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (ACADM) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D. Methods The variants were genotyped using KASPar® PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (nACADS = 4,324; nACADM = 4,337). The T2D-case-control study involved a total of ~8,300 Danish individuals (nACADS = 8,313; nACADM = 8,344). Results In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), P = 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), P = 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), P = 0.03), and with increased insulin sensitivity ISIMatsuda (β = 2.9% (0.5%;5.2%), P = 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, P = 0.21). rs11161510 of ACADM did not associate with any indices of glucose-stimulated insulin release or with T2D. Conclusions In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids.

Published
2011
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9. Interactions of Lipid Genetic Risk Scores With Estimates of Metabolic Health in a Danish Population.

Author

Justesen, Johanne M., Allin, Kristine H., Sandholt, Camilla H., Krarup, Nikolaj T., Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Borglykke, Anders, Linneberg, Allan, and Jørgensen, Torben

Subjects
LIPID metabolism disorders, GENETICS -- Risk factors, PROTEIN-lipid interactions, DISEASE risk factors
Abstract

Background--There are several well-established lifestyle factors influencing dyslipidemia and currently; 157 genetic susceptibility loci have been reported to be associated with serum lipid levels at genome-wide statistical significance. However, the interplay between lifestyle risk factors and these susceptibility loci has not been fully elucidated. We tested whether genetic risk scores (GRS) of lipid-associated single nucleotide polymorphisms associate with fasting serum lipid traits and whether the effects are modulated by lifestyle factors or estimates of metabolic health. Methods and Results--The single nucleotide polymorphisms were genotyped in 2 Danish cohorts: inter99 (n=5961) for discovery analyses and Health2006 (n=2565) for replication. On the basis of published effect sizes of single nucleotide polymorphisms associated with circulating fasting levels of total cholesterol, low-density lipoprotein-cholesterol, highdensity lipoprotein-cholesterol, or triglyceride, 4 weighted GRS were constructed. In a cross-sectional design, we investigated whether the effect of these weighted GRSs on lipid levels were modulated by diet, alcohol consumption, physical activity, and smoking or the individual metabolic health status as estimated from body mass index, waist circumference, and insulin resistance assessed using homeostasis model assessment of insulin resistance. All 4 lipid weighted GRSs associated strongly with their respective trait (from P=3.3×10-69 to P=1.1×10-123). We found interactions between the triglyceride weighted GRS and body mass index and waist circumference on fasting triglyceride levels in Inter99 and replicated these findings in Health2006 (Pinteraction=9.8×10-5 and 2.0×10-5, respectively, in combined analysis). Conclusions--Our findings suggest that individuals who are obese may be more susceptible to the cumulative genetic burden of triglyceride single nucleotide polymorphisms. Therefore, it is suggested that especially these genetically atrisk individuals may benefit more from targeted interventions aiming at obesity prevention. [ABSTRACT FROM AUTHOR]

Published
2015
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10. Bioinformatics-Driven Identification and Examination of Candidate Genes for Non-Alcoholic Fatty Liver Disease.

Author

Banasik, Karina, Justesen, Johanne M., Hornbak, Malene, Krarup, Nikolaj T., Gjesing, Anette P., Sandholt, Camilla H., Jensen, Thomas S., Grarup, Niels, Andersson, Åsa, Jørgensen, Torben, Witte, Daniel R., Sandbæk, Annelli, Lauritzen, Torsten, Thorens, Bernard, Brunak, Søren, Sørensen, Thorkild I. A., Pedersen, Oluf, and Hansen, Torben

Subjects
BIOINFORMATICS, GENES, LIVER diseases, FATTY liver, FATTY degeneration, PHENOTYPES, GENETICS, OBESITY, METABOLIC disorders
Abstract

Objective: Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes. Research Design and Methods: By integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twentyone tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS). Results: 273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations. Conclusions: Using a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS. [ABSTRACT FROM AUTHOR]

Published
2011
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11. The minor C-allele of rs2014355 in ACADS is associated with reduced insulin release following an oral glucose load.

Author

Hornbak, Malene, Banasik, Karina, Justesen, Johanne M., Krarup, Nikolaj T., Sandholt, Camilla H., Andersson, Äsa, Sandbæk, Annelli, Lauritzen, Torsten, Pisinger, Charlotta, Witte, Daniel R., Sørensen, Thorkild I. A., Pedersen, Oluf, and Hansen, Torben

Subjects
INSULIN, GLUCOSE, GENOMES, COENZYMES, TYPE 2 diabetes
Abstract

Background: A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (ACADS) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (ACADM) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D. Methods: The variants were genotyped using KASPar® PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (nACADS = 4,324; nACADM = 4,337). The T2D-case-control study involved a total of ∼8,300 Danish individuals (nACADS = 8,313; nACADM = 8,344). Results: In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), P = 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), P = 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), P = 0.03), and with increased insulin sensitivity ISIMatsuda (β = 2.9% (0.5%;5.2%), P = 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, P = 0.21). rs11161510 of ACADM did not associate with any indices of glucose-stimulated insulin release or with T2D. Conclusions: In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids. [ABSTRACT FROM AUTHOR]

Published
2011
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12. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Author

Winkler, Thomas W., Justice, Anne E., Graff, Mariaelisa, Barata, Llilda, Feitosa, Mary F., Chu, Su, Czajkowski, Jacek, Esko, Tõnu, Fall, Tove, Kilpeläinen, Tuomas O., Lu, Yingchang, Mägi, Reedik, Mihailov, Evelin, Pers, Tune H., Rüeger, Sina, Teumer, Alexander, Ehret, Georg B., Ferreira, Teresa, Heard-Costa, Nancy L., Karjalainen, Juha, Lagou, Vasiliki, Mahajan, Anubha, Neinast, Michael D., Prokopenko, Inga, Simino, Jeannette, Teslovich, Tanya M., Jansen, Rick, Westra, Harm-Jan, White, Charles C., Absher, Devin, Ahluwalia, Tarunveer S., Ahmad, Shafqat, Albrecht, Eva, Alves, Alexessander Couto, Bragg-Gresham, Jennifer L., de Craen, Anton J. M., Bis, Joshua C., Bonnefond, Amélie, Boucher, Gabrielle, Cadby, Gemma, Cheng, Yu-Ching, Chiang, Charleston W. K., Delgado, Graciela, Demirkan, Ayse, Dueker, Nicole, Eklund, Niina, Eiriksdottir, Gudny, Eriksson, Joel, Feenstra, Bjarke, Fischer, Krista, Frau, Francesca, Galesloot, Tessel E., Geller, Frank, Goel, Anuj, Gorski, Mathias, Grammer, Tanja B., Gustafsson, Stefan, Haitjema, Saskia, Hottenga, Jouke-Jan, Huffman, Jennifer E., Jackson, Anne U., Jacobs, Kevin B., Johansson, Åsa, Kaakinen, Marika, Kleber, Marcus E., Lahti, Jari, Leach, Irene Mateo, Lehne, Benjamin, Liu, Youfang, Lo, Ken Sin, Lorentzon, Mattias, Luan, Jian'an, Madden, Pamela A. F., Mangino, Massimo, McKnight, Barbara, Medina-Gomez, Carolina, Monda, Keri L., Montasser, May E., Müller, Gabriele, Müller-Nurasyid, Martina, Nolte, Ilja M., Panoutsopoulou, Kalliope, Pascoe, Laura, Paternoster, Lavinia, Rayner, Nigel W., Renström, Frida, Rizzi, Federica, Rose, Lynda M., Ryan, Kathy A., Salo, Perttu, Sanna, Serena, Scharnagl, Hubert, Shi, Jianxin, Smith, Albert Vernon, Southam, Lorraine, Stančáková, Alena, Steinthorsdottir, Valgerdur, Strawbridge, Rona J., Sung, Yun Ju, Tachmazidou, Ioanna, Tanaka, Toshiko, Thorleifsson, Gudmar, Trompet, Stella, Pervjakova, Natalia, Tyrer, Jonathan P., Vandenput, Liesbeth, van der Laan, Sander W, van der Velde, Nathalie, van Setten, Jessica, van Vliet-Ostaptchouk, Jana V., Verweij, Niek, Vlachopoulou, Efthymia, Waite, Lindsay L., Wang, Sophie R., Wang, Zhaoming, Wild, Sarah H., Willenborg, Christina, Wilson, James F., Wong, Andrew, Yang, Jian, Yengo, Loïc, Yerges-Armstrong, Laura M., Yu, Lei, Zhang, Weihua, Zhao, Jing Hua, Andersson, Ehm A., Bakker, Stephan J. L., Baldassarre, Damiano, Banasik, Karina, Barcella, Matteo, Barlassina, Cristina, Bellis, Claire, Benaglio, Paola, Blangero, John, Blüher, Matthias, Bonnet, Fabrice, Bonnycastle, Lori L., Boyd, Heather A., Bruinenberg, Marcel, Buchman, Aron S, Campbell, Harry, Chen, Yii-Der Ida, Chines, Peter S., Claudi-Boehm, Simone, Cole, John, Collins, Francis S., de Geus, Eco J. C., de Groot, Lisette C. P. G. M., Dimitriou, Maria, Duan, Jubao, Enroth, Stefan, Eury, Elodie, Farmaki, Aliki-Eleni, Forouhi, Nita G., Friedrich, Nele, Gejman, Pablo V., Gigante, Bruna, Glorioso, Nicola, Go, Alan S., Gottesman, Omri, Gräßler, Jürgen, Grallert, Harald, Grarup, Niels, Gu, Yu-Mei, Broer, Linda, Ham, Annelies C., Hansen, Torben, Harris, Tamara B., Hartman, Catharina A., Hassinen, Maija, Hastie, Nicholas, Hattersley, Andrew T., Heath, Andrew C., Henders, Anjali K., Hernandez, Dena, Hillege, Hans, Holmen, Oddgeir, Hovingh, Kees G, Hui, Jennie, Husemoen, Lise L., Hutri-Kähönen, Nina, Hysi, Pirro G., Illig, Thomas, De Jager, Philip L., Jalilzadeh, Shapour, Jørgensen, Torben, Jukema, J. Wouter, Juonala, Markus, Kanoni, Stavroula, Karaleftheri, Maria, Khaw, Kay Tee, Kinnunen, Leena, Kittner, Steven J., Koenig, Wolfgang, Kolcic, Ivana, Kovacs, Peter, Krarup, Nikolaj T., Kratzer, Wolfgang, Krüger, Janine, Kuh, Diana, Kumari, Meena, Kyriakou, Theodosios, Langenberg, Claudia, Lannfelt, Lars, Lanzani, Chiara, Lotay, Vaneet, Launer, Lenore J., Leander, Karin, Lindström, Jaana, Linneberg, Allan, Liu, Yan-Ping, Lobbens, Stéphane, Luben, Robert, Lyssenko, Valeriya, Männistö, Satu, Magnusson, Patrik K., McArdle, Wendy L., Menni, Cristina, Merger, Sigrun, Milani, Lili, Montgomery, Grant W., Morris, Andrew P., Narisu, Narisu, Nelis, Mari, Ong, Ken K., Palotie, Aarno, Pérusse, Louis, Pichler, Irene, Pilia, Maria G., Pouta, Anneli, Rheinberger, Myriam, Ribel-Madsen, Rasmus, Richards, Marcus, Rice, Kenneth M., Rice, Treva K., Rivolta, Carlo, Salomaa, Veikko, Sanders, Alan R., Sarzynski, Mark A., Scholtens, Salome, Scott, Robert A., Scott, William R., Sebert, Sylvain, Sengupta, Sebanti, Sennblad, Bengt, Seufferlein, Thomas, Silveira, Angela, Slagboom, P. Eline, Smit, Jan H., Sparsø, Thomas H., Stirrups, Kathleen, Stolk, Ronald P., Stringham, Heather M., Swertz, Morris A, Swift, Amy J., Syvänen, Ann-Christine, Tan, Sian-Tsung, Thorand, Barbara, Tönjes, Anke, Tremblay, Angelo, Tsafantakis, Emmanouil, van der Most, Peter J., Völker, Uwe, Vohl, Marie-Claude, Vonk, Judith M., Waldenberger, Melanie, Walker, Ryan W., Wennauer, Roman, Widén, Elisabeth, Willemsen, Gonneke, Wilsgaard, Tom, Wright, Alan F., Zillikens, M. Carola, van Dijk, Suzanne C., van Schoor, Natasja M., Asselbergs, Folkert W., de Bakker, Paul I. W., Beckmann, Jacques S., Beilby, John, Bennett, David A., Bergman, Richard N., Bergmann, Sven, Böger, Carsten A., Boehm, Bernhard O., Boerwinkle, Eric, Boomsma, Dorret I., Bornstein, Stefan R., Bottinger, Erwin P., Bouchard, Claude, Chambers, John C., Chanock, Stephen J., Chasman, Daniel I., Cucca, Francesco, Cusi, Daniele, Dedoussis, George, Erdmann, Jeanette, Eriksson, Johan G., Evans, Denis A., de Faire, Ulf, Farrall, Martin, Ferrucci, Luigi, Ford, Ian, Franke, Lude, Franks, Paul W., Froguel, Philippe, Gansevoort, Ron T., Gieger, Christian, Grönberg, Henrik, Gudnason, Vilmundur, Gyllensten, Ulf, Hall, Per, Hamsten, Anders, van der Harst, Pim, Hayward, Caroline, Heliövaara, Markku, Hengstenberg, Christian, Hicks, Andrew A, Hingorani, Aroon, Hofman, Albert, Hu, Frank, Huikuri, Heikki V., Hveem, Kristian, James, Alan L., Jordan, Joanne M., Jula, Antti, Kähönen, Mika, Kajantie, Eero, Kathiresan, Sekar, Kiemeney, Lambertus A. L. M., Kivimaki, Mika, Knekt, Paul B., Koistinen, Heikki A., Kooner, Jaspal S., Koskinen, Seppo, Kuusisto, Johanna, Maerz, Winfried, Martin, Nicholas G, Laakso, Markku, Lakka, Timo A., Lehtimäki, Terho, Lettre, Guillaume, Levinson, Douglas F., Lind, Lars, Lokki, Marja-Liisa, Mäntyselkä, Pekka, Melbye, Mads, Metspalu, Andres, Mitchell, Braxton D., Moll, Frans L., Murray, Jeffrey C., Musk, Arthur W., Nieminen, Markku S., Njølstad, Inger, Ohlsson, Claes, Oldehinkel, Albertine J., Oostra, Ben A., Palmer, Lyle J, Pankow, James S., Pasterkamp, Gerard, Pedersen, Nancy L., Pedersen, Oluf, Penninx, Brenda W., Perola, Markus, Peters, Annette, Polašek, Ozren, Pramstaller, Peter P., Psaty, Bruce M., Qi, Lu, Quertermous, Thomas, Raitakari, Olli T., Rankinen, Tuomo, Rauramaa, Rainer, Ridker, Paul M., Rioux, John D., Rivadeneira, Fernando, Rotter, Jerome I., Rudan, Igor, den Ruijter, Hester M., Saltevo, Juha, Sattar, Naveed, Schunkert, Heribert, Schwarz, Peter E. H., Shuldiner, Alan R., Sinisalo, Juha, Snieder, Harold, Sørensen, Thorkild I. A., Spector, Tim D., Staessen, Jan A., Stefania, Bandinelli, Thorsteinsdottir, Unnur, Stumvoll, Michael, Tardif, Jean-Claude, Tremoli, Elena, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, Verbeek, André L. M., Vermeulen, Sita H., Viikari, Jorma S., Vitart, Veronique, Völzke, Henry, Vollenweider, Peter, Waeber, Gérard, Walker, Mark, Wallaschofski, Henri, Wareham, Nicholas J., Watkins, Hugh, Zeggini, Eleftheria, Chakravarti, Aravinda, Clegg, Deborah J., Cupples, L. Adrienne, Gordon-Larsen, Penny, Jaquish, Cashell E., Rao, D. C., Abecasis, Goncalo R., Assimes, Themistocles L., Barroso, Inês, Berndt, Sonja I., Boehnke, Michael, Deloukas, Panos, Fox, Caroline S., Groop, Leif C., Hunter, David J., Ingelsson, Erik, Kaplan, Robert C., McCarthy, Mark I., Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Hirschhorn, Joel N., Lindgren, Cecilia M., Heid, Iris M., North, Kari E., Borecki, Ingrid B., Kutalik, Zoltán, and Loos, Ruth J. F.

Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Published
2015
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13. The Arg82Cys Polymorphism of the Protein Nepmucin Implies a Role in HDL Metabolism.

Author

Metz S, Krarup NT, Bryrup T, Støy J, Andersson EA, Christoffersen C, Neville MJ, Christiansen MR, Jonsson AE, Witte DR, Kampmann U, Nielsen LB, Jørgensen NR, Karpe F, Grarup N, Pedersen O, Kilpeläinen TO, and Hansen T

Abstract

Context: Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG , is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive., Objective: Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism., Methods: We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status., Results: A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB ( P  = .004) and RbG studies ( P  = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 ( P  = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels., Conclusion: Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.)

Published
2022
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14. Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author

Winkler TW, Justice AE, Graff M, Barata L, Feitosa MF, Chu S, Czajkowski J, Esko T, Fall T, Kilpeläinen TO, Lu Y, Mägi R, Mihailov E, Pers TH, Rüeger S, Teumer A, Ehret GB, Ferreira T, Heard-Costa NL, Karjalainen J, Lagou V, Mahajan A, Neinast MD, Prokopenko I, Simino J, Teslovich TM, Jansen R, Westra HJ, White CC, Absher D, Ahluwalia TS, Ahmad S, Albrecht E, Alves AC, Bragg-Gresham JL, de Craen AJ, Bis JC, Bonnefond A, Boucher G, Cadby G, Cheng YC, Chiang CW, Delgado G, Demirkan A, Dueker N, Eklund N, Eiriksdottir G, Eriksson J, Feenstra B, Fischer K, Frau F, Galesloot TE, Geller F, Goel A, Gorski M, Grammer TB, Gustafsson S, Haitjema S, Hottenga JJ, Huffman JE, Jackson AU, Jacobs KB, Johansson Å, Kaakinen M, Kleber ME, Lahti J, Mateo Leach I, Lehne B, Liu Y, Lo KS, Lorentzon M, Luan J, Madden PA, Mangino M, McKnight B, Medina-Gomez C, Monda KL, Montasser ME, Müller G, Müller-Nurasyid M, Nolte IM, Panoutsopoulou K, Pascoe L, Paternoster L, Rayner NW, Renström F, Rizzi F, Rose LM, Ryan KA, Salo P, Sanna S, Scharnagl H, Shi J, Smith AV, Southam L, Stančáková A, Steinthorsdottir V, Strawbridge RJ, Sung YJ, Tachmazidou I, Tanaka T, Thorleifsson G, Trompet S, Pervjakova N, Tyrer JP, Vandenput L, van der Laan SW, van der Velde N, van Setten J, van Vliet-Ostaptchouk JV, Verweij N, Vlachopoulou E, Waite LL, Wang SR, Wang Z, Wild SH, Willenborg C, Wilson JF, Wong A, Yang J, Yengo L, Yerges-Armstrong LM, Yu L, Zhang W, Zhao JH, Andersson EA, Bakker SJ, Baldassarre D, Banasik K, Barcella M, Barlassina C, Bellis C, Benaglio P, Blangero J, Blüher M, Bonnet F, Bonnycastle LL, Boyd HA, Bruinenberg M, Buchman AS, Campbell H, Chen YI, Chines PS, Claudi-Boehm S, Cole J, Collins FS, de Geus EJ, de Groot LC, Dimitriou M, Duan J, Enroth S, Eury E, Farmaki AE, Forouhi NG, Friedrich N, Gejman PV, Gigante B, Glorioso N, Go AS, Gottesman O, Gräßler J, Grallert H, Grarup N, Gu YM, Broer L, Ham AC, Hansen T, Harris TB, Hartman CA, Hassinen M, Hastie N, Hattersley AT, Heath AC, Henders AK, Hernandez D, Hillege H, Holmen O, Hovingh KG, Hui J, Husemoen LL, Hutri-Kähönen N, Hysi PG, Illig T, De Jager PL, Jalilzadeh S, Jørgensen T, Jukema JW, Juonala M, Kanoni S, Karaleftheri M, Khaw KT, Kinnunen L, Kittner SJ, Koenig W, Kolcic I, Kovacs P, Krarup NT, Kratzer W, Krüger J, Kuh D, Kumari M, Kyriakou T, Langenberg C, Lannfelt L, Lanzani C, Lotay V, Launer LJ, Leander K, Lindström J, Linneberg A, Liu YP, Lobbens S, Luben R, Lyssenko V, Männistö S, Magnusson PK, McArdle WL, Menni C, Merger S, Milani L, Montgomery GW, Morris AP, Narisu N, Nelis M, Ong KK, Palotie A, Pérusse L, Pichler I, Pilia MG, Pouta A, Rheinberger M, Ribel-Madsen R, Richards M, Rice KM, Rice TK, Rivolta C, Salomaa V, Sanders AR, Sarzynski MA, Scholtens S, Scott RA, Scott WR, Sebert S, Sengupta S, Sennblad B, Seufferlein T, Silveira A, Slagboom PE, Smit JH, Sparsø TH, Stirrups K, Stolk RP, Stringham HM, Swertz MA, Swift AJ, Syvänen AC, Tan ST, Thorand B, Tönjes A, Tremblay A, Tsafantakis E, van der Most PJ, Völker U, Vohl MC, Vonk JM, Waldenberger M, Walker RW, Wennauer R, Widén E, Willemsen G, Wilsgaard T, Wright AF, Zillikens MC, van Dijk SC, van Schoor NM, Asselbergs FW, de Bakker PI, Beckmann JS, Beilby J, Bennett DA, Bergman RN, Bergmann S, Böger CA, Boehm BO, Boerwinkle E, Boomsma DI, Bornstein SR, Bottinger EP, Bouchard C, Chambers JC, Chanock SJ, Chasman DI, Cucca F, Cusi D, Dedoussis G, Erdmann J, Eriksson JG, Evans DA, de Faire U, Farrall M, Ferrucci L, Ford I, Franke L, Franks PW, Froguel P, Gansevoort RT, Gieger C, Grönberg H, Gudnason V, Gyllensten U, Hall P, Hamsten A, van der Harst P, Hayward C, Heliövaara M, Hengstenberg C, Hicks AA, Hingorani A, Hofman A, Hu F, Huikuri HV, Hveem K, James AL, Jordan JM, Jula A, Kähönen M, Kajantie E, Kathiresan S, Kiemeney LA, Kivimaki M, Knekt PB, Koistinen HA, Kooner JS, Koskinen S, Kuusisto J, Maerz W, Martin NG, Laakso M, Lakka TA, Lehtimäki T, Lettre G, Levinson DF, Lind L, Lokki ML, Mäntyselkä P, Melbye M, Metspalu A, Mitchell BD, Moll FL, Murray JC, Musk AW, Nieminen MS, Njølstad I, Ohlsson C, Oldehinkel AJ, Oostra BA, Palmer LJ, Pankow JS, Pasterkamp G, Pedersen NL, Pedersen O, Penninx BW, Perola M, Peters A, Polašek O, Pramstaller PP, Psaty BM, Qi L, Quertermous T, Raitakari OT, Rankinen T, Rauramaa R, Ridker PM, Rioux JD, Rivadeneira F, Rotter JI, Rudan I, den Ruijter HM, Saltevo J, Sattar N, Schunkert H, Schwarz PE, Shuldiner AR, Sinisalo J, Snieder H, Sørensen TI, Spector TD, Staessen JA, Stefania B, Thorsteinsdottir U, Stumvoll M, Tardif JC, Tremoli E, Tuomilehto J, Uitterlinden AG, Uusitupa M, Verbeek AL, Vermeulen SH, Viikari JS, Vitart V, Völzke H, Vollenweider P, Waeber G, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Zeggini E, Chakravarti A, Clegg DJ, Cupples LA, Gordon-Larsen P, Jaquish CE, Rao DC, Abecasis GR, Assimes TL, Barroso I, Berndt SI, Boehnke M, Deloukas P, Fox CS, Groop LC, Hunter DJ, Ingelsson E, Kaplan RC, McCarthy MI, Mohlke KL, O'Connell JR, Schlessinger D, Strachan DP, Stefansson K, van Duijn CM, Hirschhorn JN, Lindgren CM, Heid IM, North KE, Borecki IB, Kutalik Z, and Loos RJ

Abstract

[This corrects the article DOI: 10.1371/journal.pgen.1005378.].

Published
2016
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