👤 J Dupuis

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17
Articles
3
Name variants
Also published as: Josée Dupuis, Nina Dupuis
articles
Gina M Peloso, Dongyu Wang, Sabrina M Abbruzzese +25 more · 2026 · Journal of Alzheimer's disease : JAD · SAGE Publications · added 2026-04-24
BackgroundIdentifying genetic variants conferring resilience to Alzheimer's disease and related dementia (ADRD) may hold promise for developing therapeutics.ObjectiveTo determine genetic associations Show more
BackgroundIdentifying genetic variants conferring resilience to Alzheimer's disease and related dementia (ADRD) may hold promise for developing therapeutics.ObjectiveTo determine genetic associations with being dementia-free at age 85 (DF85).MethodsWe examined genetic associations, using whole genome sequencing data, with DF85 in three Trans-Omics for Precision Medicine cohorts and the Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium. We tested common variants individually and aggregation of rare (MAF ≤ 1%) coding and non-coding variants in DF85 participants (n = 3657) against individuals who were not DF85 (n = 20,010). We verified associations using a stricter control set who developed dementia before age 85 (n = 5552).ResultsWe observed an association at Show less
no PDF DOI: 10.1177/13872877261444302
APOE
Jordi Merino, Hassan S Dashti, Chloé Sarnowski +17 more · 2022 · Nature human behaviour · Nature · added 2026-04-24
Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a mult Show more
Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a multivariate genome-wide association analysis of overall variation in dietary intake to account for the correlation between dietary carbohydrate, fat and protein in 282,271 participants of European ancestry from the UK Biobank (n = 191,157) and Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 91,114), and identify 26 distinct genome-wide significant loci. Dietary intake signals map exclusively to specific brain regions and are enriched for genes expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons. We identified two main clusters of genetic variants for overall variation in dietary intake that were differently associated with obesity and coronary artery disease. These results enhance the biological understanding of interindividual differences in dietary intake by highlighting neural mechanisms, supporting functional follow-up experiments and possibly providing new avenues for the prevention and treatment of prevalent complex metabolic diseases. Show less
📄 PDF DOI: 10.1038/s41562-021-01182-w
KANSL1
Danielle E Haslam, Gina M Peloso, Melanie Guirette +53 more · 2021 · Circulation. Genomic and precision medicine · added 2026-04-24
ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the Data from Show more
ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; Our results identified genetic variants in the Show less
📄 PDF DOI: 10.1161/CIRCGEN.120.003288
MLXIPL
Nicola M McKeown, Hassan S Dashti, Jiantao Ma +47 more · 2018 · Diabetologia · Springer · added 2026-04-24
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormon Show more
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10 In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study). Show less
📄 PDF DOI: 10.1007/s00125-017-4475-0
MLXIPL
Nina Dupuis, Assia Fafouri, Aurélien Bayot +19 more · 2015 · Human molecular genetics · Oxford University Press · added 2026-04-24
Dymeclin is a Golgi-associated protein whose deficiency causes Dyggve-Melchior-Clausen syndrome (DMC, MIM #223800), a rare recessively inherited spondyloepimetaphyseal dysplasia consistently associate Show more
Dymeclin is a Golgi-associated protein whose deficiency causes Dyggve-Melchior-Clausen syndrome (DMC, MIM #223800), a rare recessively inherited spondyloepimetaphyseal dysplasia consistently associated with postnatal microcephaly and intellectual disability. While the skeletal phenotype of DMC patients has been extensively described, very little is known about their cerebral anomalies, which result in brain growth defects and cognitive dysfunction. We used Dymeclin-deficient mice to determine the cause of microcephaly and to identify defective mechanisms at the cellular level. Brain weight and volume were reduced in all mutant mice from postnatal day 5 onward. Mutant mice displayed a narrowing of the frontal cortex, although cortical layers were normally organized. Interestingly, the corpus callosum was markedly thinner, a characteristic we also identified in DMC patients. Consistent with this, the myelin sheath was thinner, less compact and not properly rolled, while the number of mature oligodendrocytes and their ability to produce myelin basic protein were significantly decreased. Finally, cortical neurons from mutant mice and primary fibroblasts from DMC patients displayed substantially delayed endoplasmic reticulum to Golgi trafficking, which could be fully rescued upon Dymeclin re-expression. These findings indicate that Dymeclin is crucial for proper myelination and anterograde neuronal trafficking, two processes that are highly active during postnatal brain maturation. Show less
no PDF DOI: 10.1093/hmg/ddv038
DYM
Belinda K Cornes, Jennifer A Brody, Naghmeh Nikpoor +25 more · 2014 · Circulation. Cardiovascular genetics · added 2026-04-24
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In the Cohorts fo Show more
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced 5 gene regions at 11p11.2 to identify rare, potentially functional variants influencing fasting glucose or FI levels. Sequencing (mean depth, 38×) across 16.1 kb in 3566 individuals without diabetes mellitus identified 653 variants, 79.9% of which were rare (minor allele frequency <1%) and novel. We analyzed rare variants in 5 gene regions with FI or fasting glucose using the sequence kernel association test. At NR1H3, 53 rare variants were jointly associated with FI (P=2.73×10(-3)); of these, 7 were predicted to have regulatory function and showed association with FI (P=1.28×10(-3)). Conditioning on 2 previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are >2 independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; minor allele frequency=0.00068), contributed 20.6% to the overall sequence kernel association test score at NR1H3, lies in intron 2 of NR1H3, and is a predicted binding site for forkhead box A1 (FOXA1), a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity. Sequencing at 11p11.2-NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, seems to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity. Show less
📄 PDF DOI: 10.1161/CIRCGENETICS.113.000169
ACP2
Daan W Loth, María Soler Artigas, Sina A Gharib +157 more · 2014 · Nature genetics · Nature · added 2026-04-24
Daan W Loth, María Soler Artigas, Sina A Gharib, Louise V Wain, Nora Franceschini, Beate Koch, Tess D Pottinger, Albert Vernon Smith, Qing Duan, Chris Oldmeadow, Mi Kyeong Lee, David P Strachan, Alan L James, Jennifer E Huffman, Veronique Vitart, Adaikalavan Ramasamy, Nicholas J Wareham, Jaakko Kaprio, Xin-Qun Wang, Holly Trochet, Mika Kähönen, Claudia Flexeder, Eva Albrecht, Lorna M Lopez, Kim de Jong, Bharat Thyagarajan, Alexessander Couto Alves, Stefan Enroth, Ernst Omenaas, Peter K Joshi, Tove Fall, Ana Viñuela, Lenore J Launer, Laura R Loehr, Myriam Fornage, Guo Li, Jemma B Wilk, Wenbo Tang, Ani Manichaikul, Lies Lahousse, Tamara B Harris, Kari E North, Alicja R Rudnicka, Jennie Hui, Xiangjun Gu, Thomas Lumley, Alan F Wright, Nicholas D Hastie, Susan Campbell, Rajesh Kumar, Isabelle Pin, Robert A Scott, Kirsi H Pietiläinen, Ida Surakka, Yongmei Liu, Elizabeth G Holliday, Holger Schulz, Joachim Heinrich, Gail Davies, Judith M Vonk, Mary Wojczynski, Anneli Pouta, Asa Johansson, Sarah H Wild, Erik Ingelsson, Fernando Rivadeneira, Henry Völzke, Pirro G Hysi, Gudny Eiriksdottir, Alanna C Morrison, Jerome I Rotter, Wei Gao, Dirkje S Postma, Wendy B White, Stephen S Rich, Albert Hofman, Thor Aspelund, David Couper, Lewis J Smith, Bruce M Psaty, Kurt Lohman, Esteban G Burchard, André G Uitterlinden, Melissa Garcia, Bonnie R Joubert, Wendy L McArdle, A Bill Musk, Nadia Hansel, Susan R Heckbert, Lina Zgaga, Joyce B J van Meurs, Pau Navarro, Igor Rudan, Yeon-Mok Oh, Susan Redline, Deborah L Jarvis, Jing Hua Zhao, Taina Rantanen, George T O'Connor, Samuli Ripatti, Rodney J Scott, Stefan Karrasch, Harald Grallert, Nathan C Gaddis, John M Starr, Cisca Wijmenga, Ryan L Minster, David J Lederer, Juha Pekkanen, Ulf Gyllensten, Harry Campbell, Andrew P Morris, Sven Gläser, Christopher J Hammond, Kristin M Burkart, John Beilby, Stephen B Kritchevsky, Vilmundur Gudnason, Dana B Hancock, O Dale Williams, Ozren Polasek, Tatijana Zemunik, Ivana Kolcic, Marcy F Petrini, Matthias Wjst, Woo Jin Kim, David J Porteous, Generation Scotland, Blair H Smith, Anne Viljanen, Markku Heliövaara, John R Attia, Ian Sayers, Regina Hampel, Christian Gieger, Ian J Deary, H Marike Boezen, Anne Newman, Marjo-Riitta Jarvelin, James F Wilson, Lars Lind, Bruno H Stricker, Alexander Teumer, Timothy D Spector, Erik Melén, Marjolein J Peters, Leslie A Lange, R Graham Barr, Ken R Bracke, Fien M Verhamme, Joohon Sung, Pieter S Hiemstra, Patricia A Cassano, Akshay Sood, Caroline Hayward, Josée Dupuis, Ian P Hall, Guy G Brusselle, Martin D Tobin, Stephanie J London Show less
Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analys Show more
Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease. Show less
📄 PDF DOI: 10.1038/ng.3011
HSD17B12
Aldi T Kraja, Daniel I Chasman, Kari E North +76 more · 2014 · Molecular genetics and metabolism · Elsevier · added 2026-04-24
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular Show more
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation. Show less
📄 PDF DOI: 10.1016/j.ymgme.2014.04.007
MACF1
Nina Dupuis, Sophie Lebon, Manoj Kumar +4 more · 2013 · Human mutation · Wiley · added 2026-04-24
Smith-McCort dysplasia (SMC) is a rare autosomal recessive spondylo-epi-metaphyseal dysplasia with skeletal features identical to those of Dyggve-Melchior-Clausen syndrome (DMC) but with normal intell Show more
Smith-McCort dysplasia (SMC) is a rare autosomal recessive spondylo-epi-metaphyseal dysplasia with skeletal features identical to those of Dyggve-Melchior-Clausen syndrome (DMC) but with normal intelligence and no microcephaly. Although both syndromes were shown to result from mutations in the DYM gene, which encodes the Golgi protein DYMECLIN, a few SMC patients remained negative in DYM mutation screening. Recently, autozygosity mapping and exome sequencing in a large SMC family have allowed the identification of a missense mutation in RAB33B, another Golgi protein involved in retrograde transport of Golgi vesicles. Here, we report a novel RAB33B mutation in a second SMC case that leads to a marked reduction of the protein as shown by Western blot and immunofluorescence. These data confirm the genetic heterogeneity of SMC dysplasia and highlight the role of Golgi transport in the pathogenesis of SMC and DMC syndromes. Show less
no PDF DOI: 10.1002/humu.22235
DYM
C-T Liu, M C Y Ng, D Rybin +37 more · 2012 · Diabetologia · Springer · added 2026-04-24
Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European a Show more
Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European ancestry (EuA) populations in 5,984 non-diabetic AfAs. We meta-analysed SNP associations with fasting glucose (FG) or insulin (FI) in AfAs from five cohorts in the Candidate Gene Association Resource. We: (1) calculated allele frequency differences, variations in linkage disequilibrium (LD), fixation indices (F(st)s) and integrated haplotype scores (iHSs); (2) tested EuA SNPs in AfAs; and (3) interrogated within ± 250 kb around each EuA SNP in AfAs. Allele frequency differences ranged from 0.6% to 54%. F(st) exceeded 0.15 at 6/16 loci, indicating modest population differentiation. All iHSs were <2, suggesting no recent positive selection. For 18 SNPs, all directions of effect were the same and 95% CIs of association overlapped when comparing EuA with AfA. For 17 of 18 loci, at least one SNP was nominally associated with FG in AfAs. Four loci were significantly associated with FG (GCK, p = 5.8 × 10(-8); MTNR1B, p = 8.5 × 10(-9); and FADS1, p = 2.2 × 10(-4)) or FI (GCKR, p = 5.9 × 10(-4)). At GCK and MTNR1B the EuA and AfA SNPs represented the same signal, while at FADS1, and GCKR, the EuA and best AfA SNPs were weakly correlated (r(2) <0.2), suggesting allelic heterogeneity for association with FG at these loci. Few glycaemic SNPs showed strict evidence of transferability from EuA to AfAs. Four loci were significantly associated in both AfAs and those with EuA after accounting for varying LD across ancestral groups, with new signals emerging to aid fine-mapping. Show less
📄 PDF DOI: 10.1007/s00125-012-2656-4
FADS1
Abbas Dehghan, Josée Dupuis, Maja Barbalic +111 more · 2011 · Circulation · added 2026-04-24
Abbas Dehghan, Josée Dupuis, Maja Barbalic, Joshua C Bis, Gudny Eiriksdottir, Chen Lu, Niina Pellikka, Henri Wallaschofski, Johannes Kettunen, Peter Henneman, Jens Baumert, David P Strachan, Christian Fuchsberger, Veronique Vitart, James F Wilson, Guillaume Paré, Silvia Naitza, Megan E Rudock, Ida Surakka, Eco J C de Geus, Behrooz Z Alizadeh, Jack Guralnik, Alan Shuldiner, Toshiko Tanaka, Robert Y L Zee, Renate B Schnabel, Vijay Nambi, Maryam Kavousi, Samuli Ripatti, Matthias Nauck, Nicholas L Smith, Albert V Smith, Jouko Sundvall, Paul Scheet, Yongmei Liu, Aimo Ruokonen, Lynda M Rose, Martin G Larson, Ron C Hoogeveen, Nelson B Freimer, Alexander Teumer, Russell P Tracy, Lenore J Launer, Julie E Buring, Jennifer F Yamamoto, Aaron R Folsom, Eric J G Sijbrands, James Pankow, Paul Elliott, John F Keaney, Wei Sun, Antti-Pekka Sarin, João D Fontes, Sunita Badola, Brad C Astor, Albert Hofman, Anneli Pouta, Karl Werdan, Karin H Greiser, Oliver Kuss, Henriette E Meyer zu Schwabedissen, Joachim Thiery, Yalda Jamshidi, Ilja M Nolte, Nicole Soranzo, Timothy D Spector, Henry Völzke, Alexander N Parker, Thor Aspelund, David Bates, Lauren Young, Kim Tsui, David S Siscovick, Xiuqing Guo, Jerome I Rotter, Manuela Uda, David Schlessinger, Igor Rudan, Andrew A Hicks, Brenda W Penninx, Barbara Thorand, Christian Gieger, Joe Coresh, Gonneke Willemsen, Tamara B Harris, Andre G Uitterlinden, Marjo-Riitta Järvelin, Kenneth Rice, Dörte Radke, Veikko Salomaa, Ko Willems Van Dijk, Eric Boerwinkle, Ramachandran S Vasan, Luigi Ferrucci, Quince D Gibson, Stefania Bandinelli, Harold Snieder, Dorret I Boomsma, Xiangjun Xiao, Harry Campbell, Caroline Hayward, Peter P Pramstaller, Cornelia M Van Duijn, Leena Peltonen, Bruce M Psaty, Vilmundur Gudnason, Paul M Ridker, Georg Homuth, Wolfgang Koenig, Christie M Ballantyne, Jacqueline C M Witteman, Emelia J Benjamin, Markus Perola, Daniel I Chasman Show less
C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP leve Show more
C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP levels. We performed a genome-wide association analysis of CRP in 66 185 participants from 15 population-based studies. We sought replication for the genome-wide significant and suggestive loci in a replication panel comprising 16 540 individuals from 10 independent studies. We found 18 genome-wide significant loci, and we provided evidence of replication for 8 of them. Our results confirm 7 previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome (APOC1, HNF1A, LEPR, GCKR, HNF4A, and PTPN2) or the immune system (CRP, IL6R, NLRP3, IL1F10, and IRF1) or that reside in regions previously not known to play a role in chronic inflammation (PPP1R3B, SALL1, PABPC4, ASCL1, RORA, and BCL7B). We found a significant interaction of body mass index with LEPR (P<2.9×10(-6)). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained ≈5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease. We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation. Show less
no PDF DOI: 10.1161/CIRCULATIONAHA.110.948570
PABPC4
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
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
Nancy L Heard-Costa, M Carola Zillikens, Keri L Monda +58 more · 2009 · PLoS genetics · PLOS · added 2026-04-24
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association a Show more
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity. Show less
no PDF DOI: 10.1371/journal.pgen.1000539
NRXN3