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Your search keyword '"Gjesing, Anette P."' showing total 4 results
Start Over Author "Gjesing, Anette P." Publisher escholarship, university of california
4 results on '"Gjesing, Anette P."'

1. A saturated map of common genetic variants associated with human height

Author

Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U, Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D, Graham, Sarah E, Mukamel, Ronen E, Spracklen, Cassandra N, Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H, Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E, Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S, Akiyama, Masato, Allison, Matthew A, Alvarez, Marcus, Andersen, Mette K, Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F, Bollepalli, Sailalitha, Bonnycastle, Lori L, Bork-Jensen, Jette, Bradfield, Jonathan P, Bradford, Yuki, Braund, Peter S, Brody, Jennifer A, Burgdorf, Kristoffer S, Cade, Brian E, Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E Warwick, Degenhard, Frauke, Delgado, Graciela E, Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B, Engmann, Jorgen E, Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D, Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E, Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P, Goel, Anuj, Gordon, Scott D, Gorski, Mathias, Grove, Jakob, and Guo, Xiuqing

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Humans, Body Height, Gene Frequency, Genome, Human, Genome-Wide Association Study, Haplotypes, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Europe, Sample Size, Phenotype, Chromosome Mapping, 23andMe Research Team, VA Million Veteran Program, DiscovEHR, eMERGE, Lifelines Cohort Study, PRACTICAL Consortium, Understanding Society Scientific Group, General Science & Technology
Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

2. A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Author

Manning, Alisa, Highland, Heather M, Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A, Mahajan, Anubha, Locke, Adam E, Cingolani, Pablo, Pers, Tune H, Viñuela, Ana, Brown, Andrew A, Wu, Ying, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R, Gaulton, Kyle J, Im, Hae Kyung, Teslovich, Tanya M, Blackwell, Thomas W, Bork-Jensen, Jette, Burtt, Noël P, Chen, Yuhui, Green, Todd, Hartl, Christopher, Kang, Hyun Min, Kumar, Ashish, Ladenvall, Claes, Ma, Clement, Moutsianas, Loukas, Pearson, Richard D, Perry, John RB, Rayner, N William, Robertson, Neil R, Scott, Laura J, van de Bunt, Martijn, Eriksson, Johan G, Jula, Antti, Koskinen, Seppo, Lehtimäki, Terho, Palotie, Aarno, Raitakari, Olli T, Jacobs, Suzanne BR, Wessel, Jennifer, Chu, Audrey Y, Scott, Robert A, Goodarzi, Mark O, Blancher, Christine, Buck, Gemma, Buck, David, Chines, Peter S, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Trakalo, Joseph, Banks, Eric, Carey, Jason, Carneiro, Mauricio O, DePristo, Mark, Farjoun, Yossi, Fennell, Timothy, Goldstein, Jacqueline I, Grant, George, Hrabé de Angelis, Martin, Maguire, Jared, Neale, Benjamin M, Poplin, Ryan, Purcell, Shaun, Schwarzmayr, Thomas, Shakir, Khalid, Smith, Joshua D, Strom, Tim M, Wieland, Thomas, Lindstrom, Jaana, Brandslund, Ivan, Christensen, Cramer, Surdulescu, Gabriela L, Lakka, Timo A, Doney, Alex SF, Nilsson, Peter, Wareham, Nicholas J, Langenberg, Claudia, Varga, Tibor V, Franks, Paul W, Rolandsson, Olov, Rosengren, Anders H, and Farook, Vidya S

Subjects
Genetics, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Black or African American, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Fasting, Finland, Gene Frequency, Genetic Predisposition to Disease, Genotype, Hispanic or Latino, Humans, Insulin, Insulin Resistance, Odds Ratio, Proto-Oncogene Proteins c-akt, White People, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Published
2017

3. Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Author

Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A, Highland, Heather M, Locke, Adam E, Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J, Teslovich, Tanya M, Rayner, N William, Robertson, Neil R, Beer, Nicola L, Rundle, Jana K, Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noël P, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Syvänen, Ann-Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I, Blangero, John, Cox, Nancy J, Duggirala, Ravindranath, Hanis, Craig L, Seielstad, Mark, Wilson, James G, Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L, Doney, Alex SF, Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jørgensen, Marit E, Jørgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D, Morris, Andrew D, Palmer, Colin NA, Collins, Francis S, Mohlke, Karen L, Bergman, Richard N, Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M, Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C, Morris, Andrew P, Altshuler, David, Meigs, James B, Boehnke, Michael, McCarthy, Mark I, Lindgren, Cecilia M, Gloyn, Anna L, and T2D-GENES consortium and GoT2D consortium

Subjects
T2D-GENES consortium and GoT2D consortium, Humans, Diabetes Mellitus, Type 2, Insulin, Glucose-6-Phosphatase, Blood Glucose, Receptors, Glucagon, Glycemic Index, Gene Frequency, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Exome, Glucagon-Like Peptide-1 Receptor, Diabetes Mellitus, Type 2, Receptors, Glucagon, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P

Published
2015

4. 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

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