👤 Leif Groop

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22
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4
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Also published as: L Groop, Leif C Groop, Per-Henrik Groop
articles
Anna Lessmark, Gad Hatem, Györgyi Kovacs +6 more · 2021 · Genes · MDPI · added 2026-04-24
Parent-of-origin effects (POE) and sex-specific parental effects have been reported for plasma lipid levels, and a strong relationship exists between dyslipidemia and obesity. We aim to explore whethe Show more
Parent-of-origin effects (POE) and sex-specific parental effects have been reported for plasma lipid levels, and a strong relationship exists between dyslipidemia and obesity. We aim to explore whether genetic variants previously reported to have an association to lipid traits also show POE on blood lipid levels and obesity. Families from the Botnia cohort and the Hungarian Transdanubian Biobank (HTB) were genotyped for 12 SNPs, parental origin of alleles were inferred, and generalized estimating equations were modeled to assess parental-specific associations with lipid traits and obesity. POE were observed for the variants at the Show less
📄 PDF DOI: 10.3390/genes13010091
DOCK7
Amra Jujić, Naeimeh Atabaki-Pasdar, Peter M Nilsson +16 more · 2020 · Diabetologia · Springer · added 2026-04-24
Evidence that glucose-dependent insulinotropic peptide (GIP) and/or the GIP receptor (GIPR) are involved in cardiovascular biology is emerging. We hypothesised that GIP has untoward effects on cardiov Show more
Evidence that glucose-dependent insulinotropic peptide (GIP) and/or the GIP receptor (GIPR) are involved in cardiovascular biology is emerging. We hypothesised that GIP has untoward effects on cardiovascular biology, in contrast to glucagon-like peptide 1 (GLP-1), and therefore investigated the effects of GIP and GLP-1 concentrations on cardiovascular disease (CVD) and mortality risk. GIP concentrations were successfully measured during OGTTs in two independent populations (Malmö Diet Cancer-Cardiovascular Cohort [MDC-CC] and Prevalence, Prediction and Prevention of Diabetes in Botnia [PPP-Botnia]) in a total of 8044 subjects. GLP-1 (n = 3625) was measured in MDC-CC. The incidence of CVD and mortality was assessed via national/regional registers or questionnaires. Further, a two-sample Mendelian randomisation (2SMR) analysis between the GIP pathway and outcomes (coronary artery disease [CAD] and myocardial infarction) was carried out using a GIP-associated genetic variant, rs1800437, as instrumental variable. An additional reverse 2SMR was performed with CAD as exposure variable and GIP as outcome variable, with the instrumental variables constructed from 114 known genetic risk variants for CAD. In meta-analyses, higher fasting levels of GIP were associated with risk of higher total mortality (HR[95% CI] = 1.22 [1.11, 1.35]; p = 4.5 × 10 In two prospective, community-based studies, elevated levels of GIP were associated with greater risk of all-cause and cardiovascular mortality within 5-9 years of follow-up, whereas GLP-1 levels were not associated with excess risk. Further studies are warranted to determine the cardiovascular effects of GIP per se. Show less
📄 PDF DOI: 10.1007/s00125-020-05093-9
GIPR
Geeti P Arora, Peter Almgren, Charlotte Brøns +4 more · 2018 · BMC medical genomics · BioMed Central · added 2026-04-24
Gestational diabetes (GDM) is a more common problem in India than in many other parts of the world but it is not known whether this is due to unique environmental factors or a unique genetic backgroun Show more
Gestational diabetes (GDM) is a more common problem in India than in many other parts of the world but it is not known whether this is due to unique environmental factors or a unique genetic background. To address this question we examined whether the same genetic variants associated with GDM and Type 2 Diabetes (T2D) in Caucasians also were associated with GDM in North Indian women. Five thousand one hundred pregnant women of gestational age 24-28 weeks from Punjab were studied by a 75 g oral glucose tolerance test (OGTT). GDM was diagnosed by both WHO1999 and 2013 criteria. 79 single nucleotide polymorphisms (SNPs) previously associated with T2D and glycemic traits (12 of them also with GDM) and 6 SNPs from previous T2D associations based on Indian population (some also with European) were genotyped on a Sequenom platform or using Taqman assays in DNA from 4018 women. In support of previous findings in Caucasian GDM, SNPs at KCJN11 and GRB14 loci were nominally associated with GDM1999 risk in Indian women (both p = 0.02). Notably, T2D risk alleles of the variant rs1552224 near CENTD2, rs11708067 in ADCY5 and rs11605924 in CRY2 genes associated with protection from GDM regardless of criteria applied (p < 0.025). SNPs rs7607980 near COBLL1 (p = 0.0001), rs13389219 near GRB14 (p = 0.026) and rs10423928 in the GIPR gene (p = 0.012) as well as the genetic risk score (GRS) for these previously shown insulin resistance loci here associated with insulin resistance defined by HOMA2-IR and showed a trend towards GDM. GRS comprised of 3 insulin secretion loci here associated with insulin secretion but not GDM. GDM in women from Punjab in Northern India shows a genetic component, seemingly driven by insulin resistance and secretion and partly shared with GDM in other parts of the world. Most previous T2D loci discovered in European studies did not associate with GDM in North India, indicative of different genetic etiology or alternately, differences in the linkage disequilibrium (LD) structure between populations in which the associated SNPs were identified and Northern Indian women. Interestingly some T2D risk variants were in fact indicative of being protective for GDM in these Indian women. Show less
📄 PDF DOI: 10.1186/s12920-018-0380-8
GIPR
Stefan Amisten, Pontus Duner, Olof Asplund +3 more · 2018 · Journal of diabetes and its complications · Elsevier · added 2026-04-24
The impact of BL11282, an imidazoline receptor (NISCH) agonist, on potentiation of glucose-stimulated insulin secretion (GSIS) from isolated human non-diabetic (ND) and type 2 diabetic (T2D) islets wa Show more
The impact of BL11282, an imidazoline receptor (NISCH) agonist, on potentiation of glucose-stimulated insulin secretion (GSIS) from isolated human non-diabetic (ND) and type 2 diabetic (T2D) islets was investigated. Analysis of mRNA was performed by RNA-sequencing and qPCR. Insulin and cAMP by RIA and ELISA respectively. RNA-sequencing data revealed that NISCH is highly expressed in fat tissues, islets, liver and muscles, with eight detectable splice variants of transcripts in islets. NISCH had a positive correlation with GLP-1 (GLP1R) and GIP (GIPR) receptor transcripts. The expression of NISCH was confirmed by qPCR in human islets. NISCH and GLP1R were comparably higher expressed in mouse islets compared to human islets. GSIS was dose-dependently potentiated by BL11282 from incubated islets of ND and T2D human islet donors. The insulinotropic action of BL11282 was associated with increased cAMP. While the harmful effect of high glucose on reductive capacity of islet cells was enhanced by glibenclamide during long-term culture, it was counteracted by BL11282 or Bt2-cAMP. BL11282 also increased proliferation of INS-1 cells during long-time culture. Our data suggest that BL11282 potentiates GSIS by an action involving cAMP/PKA system and BL11282 could be an attractive insulinotropic and β-cell protective agent. Show less
no PDF DOI: 10.1016/j.jdiacomp.2018.06.010
GIPR
Viktoria Gusarova, Colm O'Dushlaine, Tanya M Teslovich +78 more · 2018 · Nature communications · Nature · added 2026-04-24
Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL Show more
Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85-0.92, p = 6.3 × 10 Show less
📄 PDF DOI: 10.1038/s41467-018-04611-z
ANGPTL4
Peter Almgren, Andreas Lindqvist, Ulrika Krus +14 more · 2017 · JCI insight · added 2026-04-24
The secretion of insulin and glucagon from the pancreas and the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) from the gastrointestinal tract is Show more
The secretion of insulin and glucagon from the pancreas and the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) from the gastrointestinal tract is essential for glucose homeostasis. Several novel treatment strategies for type 2 diabetes (T2D) mimic GLP-1 actions or inhibit incretin degradation (DPP4 inhibitors), but none is thus far aimed at increasing the secretion of endogenous incretins. In order to identify new potential therapeutic targets for treatment of T2D, we performed a meta-analysis of a GWAS and an exome-wide association study of circulating insulin, glucagon, GIP, and GLP-1 concentrations measured during an oral glucose tolerance test in up to 7,828 individuals. We identified 6 genome-wide significant functional loci associated with plasma incretin concentrations in or near the SLC5A1 (encoding SGLT1), GIPR, ABO, GLP2R, F13A1, and HOXD1 genes and studied the effect of these variants on mRNA expression in pancreatic islet and on metabolic phenotypes. Immunohistochemistry showed expression of GIPR, ABO, and HOXD1 in human enteroendocrine cells and expression of ABO in pancreatic islets, supporting a role in hormone secretion. This study thus provides candidate genes and insight into mechanisms by which secretion and breakdown of GIP and GLP-1 are regulated. Show less
no PDF DOI: 10.1172/jci.insight.93306
GIPR
Dajiang J Liu, Gina M Peloso, Haojie Yu +229 more · 2017 · Nature genetics · Nature · added 2026-04-24
Dajiang J Liu, Gina M Peloso, Haojie Yu, Adam S Butterworth, Xiao Wang, Anubha Mahajan, Danish Saleheen, Connor Emdin, Dewan Alam, Alexessander Couto Alves, Philippe Amouyel, Emanuele Di Angelantonio, Dominique Arveiler, Themistocles L Assimes, Paul L Auer, Usman Baber, Christie M Ballantyne, Lia E Bang, Marianne Benn, Joshua C Bis, Michael Boehnke, Eric Boerwinkle, Jette Bork-Jensen, Erwin P Bottinger, Ivan Brandslund, Morris Brown, Fabio Busonero, Mark J Caulfield, John C Chambers, Daniel I Chasman, Y Eugene Chen, Yii-der Ida Chen, Rajiv Chowdhury, Cramer Christensen, Audrey Y Chu, John M Connell, Francesco Cucca, L Adrienne Cupples, Scott M Damrauer, Gail Davies, Ian J Deary, George Dedoussis, Joshua C Denny, Anna Dominiczak, Marie-Pierre Dubé, Tapani Ebeling, Gudny Eiriksdottir, Tõnu Esko, Aliki-Eleni Farmaki, Mary F Feitosa, Marco Ferrario, Jean Ferrieres, Ian Ford, Myriam Fornage, Paul W Franks, Timothy M Frayling, Ruth Frikke-Schmidt, Lars G Fritsche, Philippe Frossard, Valentin Fuster, Santhi K Ganesh, Wei Gao, Melissa E Garcia, Christian Gieger, Franco Giulianini, Mark O Goodarzi, Harald Grallert, Niels Grarup, Leif Groop, Megan L Grove, Vilmundur Gudnason, Torben Hansen, Tamara B Harris, Caroline Hayward, Joel N Hirschhorn, Oddgeir L Holmen, Jennifer Huffman, Yong Huo, Kristian Hveem, Sehrish Jabeen, Anne U Jackson, Johanna Jakobsdottir, Marjo-Riitta Jarvelin, Gorm B Jensen, Marit E Jørgensen, J Wouter Jukema, Johanne M Justesen, Pia R Kamstrup, Stavroula Kanoni, Fredrik Karpe, Frank Kee, Amit V Khera, Derek Klarin, Heikki A Koistinen, Jaspal S Kooner, Charles Kooperberg, Kari Kuulasmaa, Johanna Kuusisto, Markku Laakso, Timo Lakka, Claudia Langenberg, Anne Langsted, Lenore J Launer, Torsten Lauritzen, David C M Liewald, Li An Lin, Allan Linneberg, Ruth J F Loos, Yingchang Lu, Xiangfeng Lu, Reedik Mägi, Anders Malarstig, Ani Manichaikul, Alisa K Manning, Pekka Mäntyselkä, Eirini Marouli, Nicholas G D Masca, Andrea Maschio, James B Meigs, Olle Melander, Andres Metspalu, Andrew P Morris, Alanna C Morrison, Antonella Mulas, Martina Müller-Nurasyid, Patricia B Munroe, Matt J Neville, Jonas B Nielsen, Sune F Nielsen, Børge G Nordestgaard, Jose M Ordovas, Roxana Mehran, Christoper J O'Donnell, Marju Orho-Melander, Cliona M Molony, Pieter Muntendam, Sandosh Padmanabhan, Colin N A Palmer, Dorota Pasko, Aniruddh P Patel, Oluf Pedersen, Markus Perola, Annette Peters, Charlotta Pisinger, Giorgio Pistis, Ozren Polasek, Neil Poulter, Bruce M Psaty, Daniel J Rader, Asif Rasheed, Rainer Rauramaa, Dermot F Reilly, Alex P Reiner, Frida Renström, Stephen S Rich, Paul M Ridker, John D Rioux, Neil R Robertson, Dan M Roden, Jerome I Rotter, Igor Rudan, Veikko Salomaa, Nilesh J Samani, Serena Sanna, Naveed Sattar, Ellen M Schmidt, Robert A Scott, Peter Sever, Raquel S Sevilla, Christian M Shaffer, Xueling Sim, Suthesh Sivapalaratnam, Kerrin S Small, Albert V Smith, Blair H Smith, Sangeetha Somayajula, Lorraine Southam, Timothy D Spector, Elizabeth K Speliotes, John M Starr, Kathleen E Stirrups, Nathan Stitziel, Konstantin Strauch, Heather M Stringham, Praveen Surendran, Hayato Tada, Alan R Tall, Hua Tang, Jean-Claude Tardif, Kent D Taylor, Stella Trompet, Philip S Tsao, Jaakko Tuomilehto, Anne Tybjaerg-Hansen, Natalie R van Zuydam, Anette Varbo, Tibor V Varga, Jarmo Virtamo, Melanie Waldenberger, Nan Wang, Nick J Wareham, Helen R Warren, Peter E Weeke, Joshua Weinstock, Jennifer Wessel, James G Wilson, Peter W F Wilson, Ming Xu, Hanieh Yaghootkar, Robin Young, Eleftheria Zeggini, He Zhang, Neil S Zheng, Weihua Zhang, Yan Zhang, Wei Zhou, Yanhua Zhou, Magdalena Zoledziewska, Charge Diabetes Working Group, EPIC-InterAct Consortium, EPIC-CVD Consortium, GOLD Consortium, VA Million Veteran Program, Joanna M M Howson, John Danesh, Mark I McCarthy, Chad A Cowan, Goncalo Abecasis, Panos Deloukas, Kiran Musunuru, Cristen J Willer, Sekar Kathiresan Show less
We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated w Show more
We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD. Show less
📄 PDF DOI: 10.1038/ng.3977
ANGPTL4
Lisa M Berglund, Valeriya Lyssenko, Claes Ladenvall +30 more · 2016 · Diabetes · added 2026-04-24
Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone with extrapancreatic effects beyond glycemic control. Here we demonstrate unexpected effects of GIP signaling in the vasculatu Show more
Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone with extrapancreatic effects beyond glycemic control. Here we demonstrate unexpected effects of GIP signaling in the vasculature. GIP induces the expression of the proatherogenic cytokine osteopontin (OPN) in mouse arteries via local release of endothelin-1 and activation of CREB. Infusion of GIP increases plasma OPN concentrations in healthy individuals. Plasma endothelin-1 and OPN concentrations are positively correlated in patients with critical limb ischemia. Fasting GIP concentrations are higher in individuals with a history of cardiovascular disease (myocardial infarction, stroke) when compared with control subjects. GIP receptor (GIPR) and OPN mRNA levels are higher in carotid endarterectomies from patients with symptoms (stroke, transient ischemic attacks, amaurosis fugax) than in asymptomatic patients, and expression associates with parameters that are characteristic of unstable and inflammatory plaques (increased lipid accumulation, macrophage infiltration, and reduced smooth muscle cell content). While GIPR expression is predominantly endothelial in healthy arteries from humans, mice, rats, and pigs, remarkable upregulation is observed in endothelial and smooth muscle cells upon culture conditions, yielding a "vascular disease-like" phenotype. Moreover, the common variant rs10423928 in the GIPR gene is associated with increased risk of stroke in patients with type 2 diabetes. Show less
no PDF DOI: 10.2337/db15-0122
GIPR
Petr Volkov, Anders H Olsson, Linn Gillberg +9 more · 2016 · PloS one · PLOS · added 2026-04-24
Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wi Show more
Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes. Show less
📄 PDF DOI: 10.1371/journal.pone.0157776
ADCY3
Emma Ahlqvist, Peter Osmark, Tiina Kuulasmaa +22 more · 2013 · Diabetes · added 2026-04-24
Low-grade inflammation in obesity is associated with accumulation of the macrophage-derived cytokine osteopontin (OPN) in adipose tissue and induction of local as well as systemic insulin resistance. Show more
Low-grade inflammation in obesity is associated with accumulation of the macrophage-derived cytokine osteopontin (OPN) in adipose tissue and induction of local as well as systemic insulin resistance. Since glucose-dependent insulinotropic polypeptide (GIP) is a strong stimulator of adipogenesis and may play a role in the development of obesity, we explored whether GIP directly would stimulate OPN expression in adipose tissue and thereby induce insulin resistance. GIP stimulated OPN protein expression in a dose-dependent fashion in rat primary adipocytes. The level of OPN mRNA was higher in adipose tissue of obese individuals (0.13 ± 0.04 vs. 0.04 ± 0.01, P < 0.05) and correlated inversely with measures of insulin sensitivity (r = -0.24, P = 0.001). A common variant of the GIP receptor (GIPR) (rs10423928) gene was associated with a lower amount of the exon 9-containing isoform required for transmembrane activity. Carriers of the A allele with a reduced receptor function showed lower adipose tissue OPN mRNA levels and better insulin sensitivity. Together, these data suggest a role for GIP not only as an incretin hormone but also as a trigger of inflammation and insulin resistance in adipose tissue. Carriers of the GIPR rs10423928 A allele showed protective properties via reduced GIP effects. Identification of this unprecedented link between GIP and OPN in adipose tissue might open new avenues for therapeutic interventions. Show less
📄 PDF DOI: 10.2337/db12-0976
GIPR
Weijia Xie, Andrew R Wood, Valeriya Lyssenko +24 more · 2013 · Diabetes · added 2026-04-24
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel m Show more
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits. Show less
📄 PDF DOI: 10.2337/db12-0876
CPS1
A Albrechtsen, N Grarup, Y Li +105 more · 2013 · Diabetologia · Springer · added 2026-04-24
Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) Show more
Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits. Show less
📄 PDF DOI: 10.1007/s00125-012-2756-1
MACF1
Emily Sonestedt, Valeriya Lyssenko, Ulrika Ericson +4 more · 2012 · The Journal of clinical endocrinology and metabolism · added 2026-04-24
A common genetic variant (rs10423928, A-allele) in the glucose-dependent insulinotropic polypeptide receptor gene (GIPR) is associated with decreased insulin secretion. Glucose-dependent insulinotropi Show more
A common genetic variant (rs10423928, A-allele) in the glucose-dependent insulinotropic polypeptide receptor gene (GIPR) is associated with decreased insulin secretion. Glucose-dependent insulinotropic polypeptide is secreted after food consumption and gipr knockout mice fed a high-fat diet are protected against obesity and disturbances in glucose homeostasis. Our objective was to examine the interactions between rs10423928 and macronutrients and fiber intakes on body mass index and type 2 diabetes risk. Among nondiabetic subjects in the Swedish population-based Malmö Diet and Cancer cohort (n = 24,840; 45-74 yr), 1541 diabetes cases were identified during 12 yr of follow-up. Dietary intakes were assessed using a diet history method. Incident type 2 diabetes was identified through registers. There was no indication that dietary intakes significantly modify the association between GIPR genotype and body mass index (P interaction >0.08). We observed significant interactions between GIPR genotype and quintiles of carbohydrate (P = 0.0005) and fat intake (P = 0.0006) on incident type 2 diabetes. The TT-genotype carriers within the highest compared with the lowest carbohydrate quintile were at 23% (95% confidence interval = 5-39%) decreased type 2 diabetes risk. In contrast, AA-genotype carriers in the highest compared with the lowest fat quintile were at 69% (95% confidence interval = 29-86%) decreased risk. Our prospective, observational study indicates that the type 2 diabetes risk by dietary intake of carbohydrate and fat may be dependent on GIPR genotype. In line with results in gipr knockout mice, AA-genotype carriers consuming high-fat low-carbohydrate diets had reduced type 2 diabetes risk, whereas high-carbohydrate low-fat diets benefitted the two thirds of population homozygous for the T-allele. Show less
no PDF DOI: 10.1210/jc.2011-2444
GIPR
Nicola Santoro, Clarence K Zhang, Hongyu Zhao +10 more · 2012 · Hepatology (Baltimore, Md.) · Wiley · added 2026-04-24
Recently, the single nucleotide polymorphism (SNP) identified as rs1260326, in the glucokinase regulatory protein (GCKR), was associated with hypertriglyceridemia in adults. Because accumulation of tr Show more
Recently, the single nucleotide polymorphism (SNP) identified as rs1260326, in the glucokinase regulatory protein (GCKR), was associated with hypertriglyceridemia in adults. Because accumulation of triglycerides in hepatocytes represents the hallmark of steatosis, we aimed to investigate whether this variant might be associated with fatty liver (hepatic fat content, HFF%). Moreover, because recently rs738409 in the PNPLA3 and rs2854116 in the APOC3 were associated with fatty liver, we explored how the GCKR SNP and these two variants jointly influence hepatosteatosis. We studied 455 obese children and adolescents (181 Caucasians, 139 African Americans, and 135 Hispanics). All underwent an oral glucose tolerance test and fasting lipoprotein subclasses measurement by proton nuclear magnetic resonance. A subset of 142 children underwent a fast gradient magnetic resonance imaging to measure the HFF%. The rs1260326 was associated with elevated triglycerides (Caucasians P = 0.00014; African Americans P = 0.00417), large very low-density lipoprotein (VLDL) (Caucasians P = 0.001; African Americans, P = 0.03), and with fatty liver (Caucasians P = 0.034; African Americans P = 0.00002; and Hispanics P = 0.016). The PNPLA3, but not the APOC3 rs2854116 SNP, was associated with fatty liver but not with triglyceride levels. There was a joint effect between the PNPLA3 and GCKR SNPs, explaining 32% of HFF% variance in Caucasians (P = 0.00161), 39.0% in African Americans (P = 0.00000496), and 15% in Hispanics (P = 0.00342). The rs1260326 in GCKR is associated with hepatic fat accumulation along with large VLDL and triglyceride levels. GCKR and PNPLA3 act together to convey susceptibility to fatty liver in obese youths. Show less
📄 PDF DOI: 10.1002/hep.24806
APOC3
Valeriya Lyssenko, Lena Eliasson, Olga Kotova +36 more · 2011 · Diabetes · added 2026-04-24
The incretin hormone GIP (glucose-dependent insulinotropic polypeptide) promotes pancreatic β-cell function by potentiating insulin secretion and β-cell proliferation. Recently, a combined analysis of Show more
The incretin hormone GIP (glucose-dependent insulinotropic polypeptide) promotes pancreatic β-cell function by potentiating insulin secretion and β-cell proliferation. Recently, a combined analysis of several genome-wide association studies (Meta-analysis of Glucose and Insulin-Related Traits Consortium [MAGIC]) showed association to postprandial insulin at the GIP receptor (GIPR) locus. Here we explored mechanisms that could explain the protective effects of GIP on islet function. Associations of GIPR rs10423928 with metabolic and anthropometric phenotypes in both nondiabetic (N = 53,730) and type 2 diabetic individuals (N = 2,731) were explored by combining data from 11 studies. Insulin secretion was measured both in vivo in nondiabetic subjects and in vitro in islets from cadaver donors. Insulin secretion was also measured in response to exogenous GIP. The in vitro measurements included protein and gene expression as well as measurements of β-cell viability and proliferation. The A allele of GIPR rs10423928 was associated with impaired glucose- and GIP-stimulated insulin secretion and a decrease in BMI, lean body mass, and waist circumference. The decrease in BMI almost completely neutralized the effect of impaired insulin secretion on risk of type 2 diabetes. Expression of GIPR mRNA was decreased in human islets from carriers of the A allele or patients with type 2 diabetes. GIP stimulated osteopontin (OPN) mRNA and protein expression. OPN expression was lower in carriers of the A allele. Both GIP and OPN prevented cytokine-induced reduction in cell viability (apoptosis). In addition, OPN stimulated cell proliferation in insulin-secreting cells. These findings support β-cell proliferative and antiapoptotic roles for GIP in addition to its action as an incretin hormone. Identification of a link between GIP and OPN may shed new light on the role of GIP in preservation of functional β-cell mass in humans. Show less
📄 PDF DOI: 10.2337/db10-1532
GIPR
Rona J Strawbridge, Josée Dupuis, Inga Prokopenko +105 more · 2011 · Diabetes · added 2026-04-24
Rona J Strawbridge, Josée Dupuis, Inga Prokopenko, Adam Barker, Emma Ahlqvist, Denis Rybin, John R Petrie, Mary E Travers, Nabila Bouatia-Naji, Antigone S Dimas, Alexandra Nica, Eleanor Wheeler, Han Chen, Benjamin F Voight, Jalal Taneera, Stavroula Kanoni, John F Peden, Fabiola Turrini, Stefan Gustafsson, Carina Zabena, Peter Almgren, David J P Barker, Daniel Barnes, Elaine M Dennison, Johan G Eriksson, Per Eriksson, Elodie Eury, Lasse Folkersen, Caroline S Fox, Timothy M Frayling, Anuj Goel, Harvest F Gu, Momoko Horikoshi, Bo Isomaa, Anne U Jackson, Karen A Jameson, Eero Kajantie, Julie Kerr-Conte, Teemu Kuulasmaa, Johanna Kuusisto, Ruth J F Loos, Jian'an Luan, Konstantinos Makrilakis, Alisa K Manning, María Teresa Martínez-Larrad, Narisu Narisu, Maria Nastase Mannila, John Ohrvik, Clive Osmond, Laura Pascoe, Felicity Payne, Avan A Sayer, Bengt Sennblad, Angela Silveira, Alena Stancáková, Kathy Stirrups, Amy J Swift, Ann-Christine Syvänen, Tiinamaija Tuomi, Ferdinand M van 't Hooft, Mark Walker, Michael N Weedon, Weijia Xie, Björn Zethelius, DIAGRAM Consortium, GIANT Consortium, MuTHER Consortium, CARDIoGRAM Consortium, C4D Consortium, Halit Ongen, Anders Mälarstig, Jemma C Hopewell, Danish Saleheen, John Chambers, Sarah Parish, John Danesh, Jaspal Kooner, Claes-Göran Ostenson, Lars Lind, Cyrus C Cooper, Manuel Serrano-Ríos, Ele Ferrannini, Tom J Forsen, Robert Clarke, Maria Grazia Franzosi, Udo Seedorf, Hugh Watkins, Philippe Froguel, Paul Johnson, Panos Deloukas, Francis S Collins, Markku Laakso, Emmanouil T Dermitzakis, Michael Boehnke, Mark I McCarthy, Nicholas J Wareham, Leif Groop, François Pattou, Anna L Gloyn, George V Dedoussis, Valeriya Lyssenko, James B Meigs, Inês Barroso, Richard M Watanabe, Erik Ingelsson, Claudia Langenberg, Anders Hamsten, Jose C Florez Show less
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diab Show more
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis. Show less
no PDF DOI: 10.2337/db11-0415
VPS13C
Elizabeth K Speliotes, Cristen J Willer, Sonja I Berndt +374 more · 2010 · Nature genetics · Nature · added 2026-04-24
Elizabeth K Speliotes, Cristen J Willer, Sonja I Berndt, Keri L Monda, Gudmar Thorleifsson, Anne U Jackson, Hana Lango Allen, Cecilia M Lindgren, Jian'an Luan, Reedik Mägi, Joshua C Randall, Sailaja Vedantam, Thomas W Winkler, Lu Qi, Tsegaselassie Workalemahu, Iris M Heid, Valgerdur Steinthorsdottir, Heather M Stringham, Michael N Weedon, Eleanor Wheeler, Andrew R Wood, Teresa Ferreira, Robert J Weyant, Ayellet V Segrè, Karol Estrada, Liming Liang, James Nemesh, Ju-Hyun Park, Stefan Gustafsson, Tuomas O Kilpeläinen, Jian Yang, Nabila Bouatia-Naji, Tõnu Esko, Mary F Feitosa, Zoltán Kutalik, Massimo Mangino, Soumya Raychaudhuri, Andre Scherag, Albert Vernon Smith, Ryan Welch, Jing Hua Zhao, Katja K Aben, Devin M Absher, Najaf Amin, Anna L Dixon, Eva Fisher, Nicole L Glazer, Michael E Goddard, Nancy L Heard-Costa, Volker Hoesel, Jouke-Jan Hottenga, Asa Johansson, Toby Johnson, Shamika Ketkar, Claudia Lamina, Shengxu Li, Miriam F Moffatt, Richard H Myers, Narisu Narisu, John R B Perry, Marjolein J Peters, Michael Preuss, Samuli Ripatti, Fernando Rivadeneira, Camilla Sandholt, Laura J Scott, Nicholas J Timpson, Jonathan P Tyrer, Sophie van Wingerden, Richard M Watanabe, Charles C White, Fredrik Wiklund, Christina Barlassina, Daniel I Chasman, Matthew N Cooper, John-Olov Jansson, Robert W Lawrence, Niina Pellikka, Inga Prokopenko, Jianxin Shi, Elisabeth Thiering, Helene Alavere, Maria T S Alibrandi, Peter Almgren, Alice M Arnold, Thor Aspelund, Larry D Atwood, Beverley Balkau, Anthony J Balmforth, Amanda J Bennett, Yoav Ben-Shlomo, Richard N Bergman, Sven Bergmann, Heike Biebermann, Alexandra I F Blakemore, Tanja Boes, Lori L Bonnycastle, Stefan R Bornstein, Morris J Brown, Thomas A Buchanan, Fabio Busonero, Harry Campbell, Francesco P Cappuccio, Christine Cavalcanti-Proença, Yii-der Ida Chen, Chih-Mei Chen, Peter S Chines, Robert Clarke, Lachlan Coin, John Connell, Ian N M Day, Martin den Heijer, Jubao Duan, Shah Ebrahim, Paul Elliott, Roberto Elosua, Gudny Eiriksdottir, Michael R Erdos, Johan G Eriksson, Maurizio F Facheris, Stephan B Felix, Pamela Fischer-Posovszky, Aaron R Folsom, Nele Friedrich, Nelson B Freimer, Mao Fu, Stefan Gaget, Pablo V Gejman, Eco J C Geus, Christian Gieger, Anette P Gjesing, Anuj Goel, Philippe Goyette, Harald Grallert, Jürgen Grässler, Danielle M Greenawalt, Christopher J Groves, Vilmundur Gudnason, Candace Guiducci, Anna-Liisa Hartikainen, Neelam Hassanali, Alistair S Hall, Aki S Havulinna, Caroline Hayward, Andrew C Heath, Christian Hengstenberg, Andrew A Hicks, Anke Hinney, Albert Hofman, Georg Homuth, Jennie Hui, Wilmar Igl, Carlos Iribarren, Bo Isomaa, Kevin B Jacobs, Ivonne Jarick, Elizabeth Jewell, Ulrich John, Torben Jørgensen, Pekka Jousilahti, Antti Jula, Marika Kaakinen, Eero Kajantie, Lee M Kaplan, Sekar Kathiresan, Johannes Kettunen, Leena Kinnunen, Joshua W Knowles, Ivana Kolcic, Inke R König, Seppo Koskinen, Peter Kovacs, Johanna Kuusisto, Peter Kraft, Kirsti Kvaløy, Jaana Laitinen, Olivier Lantieri, Chiara Lanzani, Lenore J Launer, Cecile Lecoeur, Terho Lehtimäki, Guillaume Lettre, Jianjun Liu, Marja-Liisa Lokki, Mattias Lorentzon, Robert N Luben, Barbara Ludwig, MAGIC, Paolo Manunta, Diana Marek, Michel Marre, Nicholas G Martin, Wendy L McArdle, Anne McCarthy, Barbara McKnight, Thomas Meitinger, Olle Melander, David Meyre, Kristian Midthjell, Grant W Montgomery, Mario A Morken, Andrew P Morris, Rosanda Mulic, Julius S Ngwa, Mari Nelis, Matt J Neville, Dale R Nyholt, Christopher J O'Donnell, Stephen O'Rahilly, Ken K Ong, Ben Oostra, Guillaume Paré, Alex N Parker, Markus Perola, Irene Pichler, Kirsi H Pietiläinen, Carl G P Platou, Ozren Polasek, Anneli Pouta, Suzanne Rafelt, Olli Raitakari, Nigel W Rayner, Martin Ridderstråle, Winfried Rief, Aimo Ruokonen, Neil R Robertson, Peter Rzehak, Veikko Salomaa, Alan R Sanders, Manjinder S Sandhu, Serena Sanna, Jouko Saramies, Markku J Savolainen, Susann Scherag, Sabine Schipf, Stefan Schreiber, Heribert Schunkert, Kaisa Silander, Juha Sinisalo, David S Siscovick, Jan H Smit, Nicole Soranzo, Ulla Sovio, Jonathan Stephens, Ida Surakka, Amy J Swift, Mari-Liis Tammesoo, Jean-Claude Tardif, Maris Teder-Laving, Tanya M Teslovich, John R Thompson, Brian Thomson, Anke Tönjes, Tiinamaija Tuomi, Joyce B J van Meurs, Gert-Jan van Ommen, Vincent Vatin, Jorma Viikari, Sophie Visvikis-Siest, Veronique Vitart, Carla I G Vogel, Benjamin F Voight, Lindsay L Waite, Henri Wallaschofski, G Bragi Walters, Elisabeth Widen, Susanna Wiegand, Sarah H Wild, Gonneke Willemsen, Daniel R Witte, Jacqueline C Witteman, Jianfeng Xu, Qunyuan Zhang, Lina Zgaga, Andreas Ziegler, Paavo Zitting, John P Beilby, I Sadaf Farooqi, Johannes Hebebrand, Heikki V Huikuri, Alan L James, Mika Kähönen, Douglas F Levinson, Fabio Macciardi, Markku S Nieminen, Claes Ohlsson, Lyle J Palmer, Paul M Ridker, Michael Stumvoll, Jacques S Beckmann, Heiner Boeing, Eric Boerwinkle, Dorret I Boomsma, Mark J Caulfield, Stephen J Chanock, Francis S Collins, L Adrienne Cupples, George Davey Smith, Jeanette Erdmann, Philippe Froguel, Henrik Grönberg, Ulf Gyllensten, Per Hall, Torben Hansen, Tamara B Harris, Andrew T Hattersley, Richard B Hayes, Joachim Heinrich, Frank B Hu, Kristian Hveem, Thomas Illig, Marjo-Riitta Jarvelin, Jaakko Kaprio, Fredrik Karpe, Kay-Tee Khaw, Lambertus A Kiemeney, Heiko Krude, Markku Laakso, Debbie A Lawlor, Andres Metspalu, Patricia B Munroe, Willem H Ouwehand, Oluf Pedersen, Brenda W Penninx, Annette Peters, Peter P Pramstaller, Thomas Quertermous, Thomas Reinehr, Aila Rissanen, Igor Rudan, Nilesh J Samani, Peter E H Schwarz, Alan R Shuldiner, Timothy D Spector, Jaakko Tuomilehto, Manuela Uda, André Uitterlinden, Timo T Valle, Martin Wabitsch, Gérard Waeber, Nicholas J Wareham, Hugh Watkins, PROCARDIS Consortium, James F Wilson, Alan F Wright, M Carola Zillikens, Nilanjan Chatterjee, Steven A McCarroll, Shaun Purcell, Eric E Schadt, Peter M Visscher, Themistocles L Assimes, Ingrid B Borecki, Panos Deloukas, Caroline S Fox, Leif C Groop, Talin Haritunians, David J Hunter, Robert C Kaplan, Karen L Mohlke, Jeffrey R O'Connell, Leena Peltonen, David Schlessinger, David P Strachan, Cornelia M Van Duijn, H-Erich Wichmann, Timothy M Frayling, Unnur Thorsteinsdottir, Gonçalo R Abecasis, Inês Barroso, Michael Boehnke, Kari Stefansson, Kari E North, Mark I McCarthy, Joel N Hirschhorn, Erik Ingelsson, Ruth J F Loos Show less
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between bod Show more
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less
📄 PDF DOI: 10.1038/ng.686
GIPR
Erik Ingelsson, Claudia Langenberg, Marie-France Hivert +65 more · 2010 · Diabetes · added 2026-04-24
OBJECTIVE Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin process Show more
OBJECTIVE Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084). RESULTS The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 x 10(-71)). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction. CONCLUSIONS Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes. Show less
📄 PDF DOI: 10.2337/db09-1568
GIPR
Richa Saxena, Marie-France Hivert, Claudia Langenberg +153 more · 2010 · Nature genetics · Nature · added 2026-04-24
Richa Saxena, Marie-France Hivert, Claudia Langenberg, Toshiko Tanaka, James S Pankow, Peter Vollenweider, Valeriya Lyssenko, Nabila Bouatia-Naji, Josée Dupuis, Anne U Jackson, W H Linda Kao, Man Li, Nicole L Glazer, Alisa K Manning, Jian'an Luan, Heather M Stringham, Inga Prokopenko, Toby Johnson, Niels Grarup, Trine W Boesgaard, Cécile Lecoeur, Peter Shrader, Jeffrey O'Connell, Erik Ingelsson, David J Couper, Kenneth Rice, Kijoung Song, Camilla H Andreasen, Christian Dina, Anna Köttgen, Olivier Le Bacquer, François Pattou, Jalal Taneera, Valgerdur Steinthorsdottir, Denis Rybin, Kristin Ardlie, Michael Sampson, Lu Qi, Mandy van Hoek, Michael N Weedon, Yurii S Aulchenko, Benjamin F Voight, Harald Grallert, Beverley Balkau, Richard N Bergman, Suzette J Bielinski, Amelie Bonnefond, Lori L Bonnycastle, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Thomas A Buchanan, Suzannah J Bumpstead, Christine Cavalcanti-Proença, Guillaume Charpentier, Yii-der Ida Chen, Peter S Chines, Francis S Collins, Marilyn Cornelis, Gabriel J Crawford, Jerome Delplanque, Alex Doney, Josephine M Egan, Michael R Erdos, Mathieu Firmann, Nita G Forouhi, Caroline S Fox, Mark O Goodarzi, Jürgen Graessler, Aroon Hingorani, Bo Isomaa, Torben Jørgensen, Mika Kivimaki, Peter Kovacs, Knut Krohn, Meena Kumari, Torsten Lauritzen, Claire Lévy-Marchal, Vladimir Mayor, Jarred B McAteer, David Meyre, Braxton D Mitchell, Karen L Mohlke, Mario A Morken, Narisu Narisu, Colin N A Palmer, Ruth Pakyz, Laura Pascoe, Felicity Payne, Daniel Pearson, Wolfgang Rathmann, Annelli Sandbaek, Avan Aihie Sayer, Laura J Scott, Stephen J Sharp, Eric Sijbrands, Andrew Singleton, David S Siscovick, Nicholas L Smith, Thomas Sparsø, Amy J Swift, Holly Syddall, Gudmar Thorleifsson, Anke Tönjes, Tiinamaija Tuomi, Jaakko Tuomilehto, Timo T Valle, Gérard Waeber, Andrew Walley, Dawn M Waterworth, Eleftheria Zeggini, Jing Hua Zhao, GIANT Consortium, MAGIC Investigators, Thomas Illig, H Erich Wichmann, James F Wilson, Cornelia van Duijn, Frank B Hu, Andrew D Morris, Timothy M Frayling, Andrew T Hattersley, Unnur Thorsteinsdottir, Kari Stefansson, Peter Nilsson, Ann-Christine Syvänen, Alan R Shuldiner, Mark Walker, Stefan R Bornstein, Peter Schwarz, Gordon H Williams, David M Nathan, Johanna Kuusisto, Markku Laakso, Cyrus Cooper, Michael Marmot, Luigi Ferrucci, Vincent Mooser, Michael Stumvoll, Ruth J F Loos, David Altshuler, Bruce M Psaty, Jerome I Rotter, Eric Boerwinkle, Torben Hansen, Oluf Pedersen, Jose C Florez, Mark I McCarthy, Michael Boehnke, Inês Barroso, Robert Sladek, Philippe Froguel, James B Meigs, Leif Groop, Nicholas J Wareham, Richard M Watanabe Show less
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studi Show more
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)). Show less
📄 PDF DOI: 10.1038/ng.521
GIPR
Josée Dupuis, Claudia Langenberg, Inga Prokopenko +305 more · 2010 · Nature genetics · Nature · added 2026-04-24
Josée Dupuis, Claudia Langenberg, Inga Prokopenko, Richa Saxena, Nicole Soranzo, Anne U Jackson, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Anna L Gloyn, Cecilia M Lindgren, Reedik Mägi, Andrew P Morris, Joshua Randall, Toby Johnson, Paul Elliott, Denis Rybin, Gudmar Thorleifsson, Valgerdur Steinthorsdottir, Peter Henneman, Harald Grallert, Abbas Dehghan, Jouke Jan Hottenga, Christopher S Franklin, Pau Navarro, Kijoung Song, Anuj Goel, John R B Perry, Josephine M Egan, Taina Lajunen, Niels Grarup, Thomas Sparsø, Alex Doney, Benjamin F Voight, Heather M Stringham, Man Li, Stavroula Kanoni, Peter Shrader, Christine Cavalcanti-Proença, Meena Kumari, Lu Qi, Nicholas J Timpson, Christian Gieger, Carina Zabena, Ghislain Rocheleau, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Felicity Payne, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Kristin Ardlie, Yavuz Ariyurek, Beverley Balkau, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Rafn Benediktsson, Amanda J Bennett, Sven Bergmann, Murielle Bochud, Eric Boerwinkle, Amélie Bonnefond, Lori L Bonnycastle, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Guillaume Charpentier, Yii-der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Marilyn Cornelis, Gabe Crawford, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Christian Dina, Michael R Erdos, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Caroline S Fox, Rune Frants, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Christopher J Groves, Scott Grundy, Rhian Gwilliam, Ulf Gyllensten, Samy Hadjadj, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Neelam Hassanali, Caroline Hayward, Simon C Heath, Serge Hercberg, Christian Herder, Andrew A Hicks, David R Hillman, Aroon D Hingorani, Albert Hofman, Jennie Hui, Joe Hung, Bo Isomaa, Paul R V Johnson, Torben Jørgensen, Antti Jula, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Valeriya Lyssenko, Robert Mahley, Massimo Mangino, Alisa K Manning, María Teresa Martínez-Larrad, Jarred B McAteer, Laura J McCulloch, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Mario A Morken, Sutapa Mukherjee, Silvia Naitza, Narisu Narisu, Matthew J Neville, Ben A Oostra, Marco Orrù, Ruth Pakyz, Colin N A Palmer, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Markus Perola, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Bruce M Psaty, Wolfgang Rathmann, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Michael Roden, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Laura J Scott, Udo Seedorf, Stephen J Sharp, Beverley Shields, Gunnar Sigurethsson, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Toshiko Tanaka, Barbara Thorand, Jean Tichet, Anke Tönjes, Tiinamaija Tuomi, André G Uitterlinden, Ko Willems Van Dijk, Mandy van Hoek, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, G Bragi Walters, Kim L Ward, Hugh Watkins, Michael N Weedon, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Eleftheria Zeggini, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, DIAGRAM Consortium, GIANT Consortium, Global BPgen Consortium, Ingrid B Borecki, Ruth J F Loos, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Andrew T Hattersley, Kaisa Silander, Veikko Salomaa, George Davey Smith, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, George V Dedoussis, Manuel Serrano-Ríos, Andrew D Morris, Lars Lind, Lyle J Palmer, Frank B Hu, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, James S Pankow, Michael J Sampson, Johanna Kuusisto, Markku Laakso, Torben Hansen, Oluf Pedersen, Peter Paul Pramstaller, H Erich Wichmann, Thomas Illig, Igor Rudan, Alan F Wright, Michael Stumvoll, Harry Campbell, James F Wilson, Anders Hamsten on behalf of Procardis Consortium, MAGIC Investigators, Richard N Bergman, Thomas A Buchanan, Francis S Collins, Karen L Mohlke, Jaakko Tuomilehto, Timo T Valle, David Altshuler, Jerome I Rotter, David S Siscovick, Brenda W J H Penninx, Dorret I Boomsma, Panos Deloukas, Timothy D Spector, Timothy M Frayling, Luigi Ferrucci, Augustine Kong, Unnur Thorsteinsdottir, Kari Stefansson, Cornelia M Van Duijn, Yurii S Aulchenko, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Dawn M Waterworth, Peter Vollenweider, Leena Peltonen, Vincent Mooser, Goncalo R Abecasis, Nicholas J Wareham, Robert Sladek, Philippe Froguel, Richard M Watanabe, James B Meigs, Leif Groop, Michael Boehnke, Mark I McCarthy, Jose C Florez, Inês Barroso Show less
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, Show more
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less
📄 PDF DOI: 10.1038/ng.520
FADS1
Sekar Kathiresan, Cristen J Willer, Gina M Peloso +58 more · 2009 · Nature genetics · Nature · added 2026-04-24
Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these Show more
Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 x 10(-8)), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10(-15) for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia. Show less
📄 PDF DOI: 10.1038/ng.291
FADS1
Sekar Kathiresan, Olle Melander, Candace Guiducci +23 more · 2008 · Nature genetics · Nature · added 2026-04-24
Blood concentrations of lipoproteins and lipids are heritable risk factors for cardiovascular disease. Using genome-wide association data from three studies (n = 8,816 that included 2,758 individuals Show more
Blood concentrations of lipoproteins and lipids are heritable risk factors for cardiovascular disease. Using genome-wide association data from three studies (n = 8,816 that included 2,758 individuals from the Diabetes Genetics Initiative specific to the current paper as well as 1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables reported in a companion paper in this issue) and targeted replication association analyses in up to 18,554 independent participants, we show that common SNPs at 18 loci are reproducibly associated with concentrations of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and/or triglycerides. Six of these loci are new (P < 5 x 10(-8) for each new locus). Of the six newly identified chromosomal regions, two were associated with LDL cholesterol (1p13 near CELSR2, PSRC1 and SORT1 and 19p13 near CILP2 and PBX4), one with HDL cholesterol (1q42 in GALNT2) and five with triglycerides (7q11 near TBL2 and MLXIPL, 8q24 near TRIB1, 1q42 in GALNT2, 19p13 near CILP2 and PBX4 and 1p31 near ANGPTL3). At 1p13, the LDL-associated SNP was also strongly correlated with CELSR2, PSRC1, and SORT1 transcript levels in human liver, and a proxy for this SNP was recently shown to affect risk for coronary artery disease. Understanding the molecular, cellular and clinical consequences of the newly identified loci may inform therapy and clinical care. Show less
📄 PDF DOI: 10.1038/ng.75
MLXIPL