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1.  An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people 
Science (New York, N.Y.)  2012;337(6090):100-104.
Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (one every 17 bases) and geographically localized, such that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. Overall we conclude that, due to rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.
doi:10.1126/science.1217876
PMCID: PMC4319976  PMID: 22604722
2.  Beta amyloid and hyperphosphorylated tau deposits in the pancreas in type 2 diabetes 
Neurobiology of aging  2008;31(9):1503-1515.
Strong epidemiologic evidence suggests an association between Alzheimer disease (AD) and type 2 diabetes. To determine if amyloid beta (Aβ) and hyperphosphorylated tau occurs in type 2 diabetes, pancreas tissues from 21 autopsy cases (10 type 2 diabetes and 11 controls) were analyzed. APP and tau mRNAs were identified in human pancreas and in cultured insulinoma beta cells (INS-1) by RT-PCR. Prominent APP and tau bands were detected by Western blotting in pancreatic extracts. Aggregated Aβ, hyperphosphorylated tau, ubiquitin, apolipoprotein E, apolipoprotein(a), IB1/JIP-1 and JNK1 were detected in Langerhans islets in type 2 diabetic patients. Aβ was co-localized with amylin in islet amyloid deposits. In situ beta sheet formation of islet amyloid deposits was shown by infrared microspectroscopy (SIRMS). LPS increased APP in non-neuronal cells as well. We conclude that Aβ deposits and hyperphosphorylated tau are also associated with type 2 diabetes, highlighting common pathogenetic features in neurodegenerative disorders, including AD and type 2 diabetes and suggesting that Aβ deposits and hyperphosphorylated tau may also occur in other organs than the brain.
doi:10.1016/j.neurobiolaging.2008.08.019
PMCID: PMC4140193  PMID: 18950899
Alzheimer’s disease; Amylin; Beta amyloid; Apolipoprotein-E; Apolipoprotein-a; APP; LPS; Type 2 diabetes; IB1/JIP-1; JNK-1; Tau; Ubiquitin
3.  Genome-wide Linkage and Association Analyses to Identify Genes Influencing Adiponectin Levels: The GEMS Study 
Obesity (Silver Spring, Md.)  2009;17(4):737-744.
Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10−7). These two SNPs were in high linkage disequilibrium (r2 = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 × 10−5) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.
doi:10.1038/oby.2008.625
PMCID: PMC4028785  PMID: 19165155
4.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
5.  Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links 
PLoS Genetics  2014;10(2):e1004132.
Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on 1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10−8) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10−44) and lysine (rs8101881, P = 1.2×10−33), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.
Author Summary
The concentrations of small molecules known as metabolites, are subject to tight regulation in all organisms. Collectively, the metabolite concentrations make up the metabolome, which differs amongst individuals as a function of their environment and genetic makeup. In our study, we have further developed an untargeted approach to identify genetic factors affecting human metabolism. In this approach, we first identify all genetic variants that correlate with any of the measured metabolome features in a large set of individuals. For these variants, we then compute a profile of significance for association with all features, generating a signature that facilitates the expert or computational identification of the metabolite whose concentration is most likely affected by the genetic variant at hand. Our study replicated many of the previously reported genetically driven variations in human metabolism and revealed two new striking examples of genetic variations with a sizeable effect on the urine metabolome. Interestingly, in these two gene-metabolite pairs both the gene and the affected metabolite are related to human diseases – Crohn's disease in the first case, and kidney disease in the second. This highlights the connection between genetic predispositions, affected metabolites, and human health.
doi:10.1371/journal.pgen.1004132
PMCID: PMC3930510  PMID: 24586186
6.  Genetic variants influencing circulating lipid levels and risk of coronary artery disease 
Objectives
Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of LDL-c, HDL-c and triglycerides.
Methods and results
We combined genome-wide association data from eight studies, comprising up to 17,723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37,774 participants from eight populations and also in a population of Indian Asian descent. We also assessed the association between SNPs at lipid loci and risk of CAD in up to 9,633 cases and 38,684 controls.
We identified four novel genetic loci that showed reproducible associations with lipids (P values 1.6 × 10−8 to 3.1 × 10−10). These include a potentially functional SNP in the SLC39A8 gene for HDL-c, a SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-c and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with one or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (P values 1.1 × 10−3 to 1.2 × 10−9).
Conclusions
We have identified four novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-c, genetic loci mainly associated with circulating triglycerides and HDL-c are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.
doi:10.1161/ATVBAHA.109.201020
PMCID: PMC3891568  PMID: 20864672
lipids; lipoproteins; genetics; epidemiology
7.  A Comparison of Bayesian and Frequentist Approaches to Incorporating External Information for the Prediction of Prostate Cancer Risk 
Genetic epidemiology  2012;36(1):71-83.
We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates – one via a weighted PCa ‘risk’ score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.
doi:10.1002/gepi.21600
PMCID: PMC3791431  PMID: 22890972
prostate cancer; genetic clinical risk prediction; genetic scores; Bayesian logistic regression; predictive assessment
8.  Genetic loci influencing kidney function and chronic kidney disease in man 
Chambers, John C | Zhang, Weihua | Lord, Graham M | van der Harst, Pim | Lawlor, Debbie A | Sehmi, Joban S | Gale, Daniel P | Wass, Mark N | Ahmadi, Kourosh R | Bakker, Stephan JL | Beckmann, Jacqui | Bilo, Henk JG | Bochud, Murielle | Brown, Morris J | Caulfield, Mark J | Connell, John M C | Cook, Terence | Cotlarciuc, Ioana | Smith, George Davey | de Silva, Ranil | Deng, Guohong | Devuyst, Olivier | Dikkeschei, Lambert D. | Dimkovic, Nada | Dockrell, Mark | Dominiczak, Anna | Ebrahim, Shah | Eggermann, Thomas | Farrall, Martin | Ferrucci, Luigi | Floege, Jurgen | Forouhi, Nita G | Gansevoort, Ron T | Han, Xijin | Hedblad, Bo | van der Heide, Jaap J Homan | Hepkema, Bouke G | Hernandez-Fuentes, Maria | Hypponen, Elina | Johnson, Toby | de Jong, Paul E | Kleefstra, Nanne | Lagou, Vasiliki | Lapsley, Marta | Li, Yun | Loos, Ruth J F | Luan, Jian'an | Luttropp, Karin | Maréchal, Céline | Melander, Olle | Munroe, Patricia B | Nordfors, Louise | Parsa, Afshin | Penninx, Brenda W. | Perucha, Esperanza | Pouta, Anneli | Prokopenko, Inga | Roderick, Paul J | Ruokonen, Aimo | Samani, Nilesh | Sanna, Serena | Schalling, Martin | Schlessinger, David | Schlieper, Georg | Seelen, Marc AJ | Shuldiner, Alan R | Sjögren, Marketa | Smit, Johannes H. | Snieder, Harold | Soranzo, Nicole | Spector, Timothy D | Stenvinkel, Peter | Sternberg, Michael JE | Swaminathan, Ramasamyiyer | Tanaka, Toshiko | Ubink-Veltmaat, Lielith J. | Uda, Manuela | Vollenweider, Peter | Wallace, Chris | Waterworth, Dawn | Zerres, Klaus | Waeber, Gerard | Wareham, Nicholas J | Maxwell, Patrick H | McCarthy, Mark I | Jarvelin, Marjo-Riitta | Mooser, Vincent | Abecasis, Goncalo R | Lightstone, Liz | Scott, James | Navis, Gerjan | Elliott, Paul | Kooner., Jaspal S
Nature genetics  2010;42(5):373-375.
Chronic kidney disease (CKD), the result of permanent loss of kidney function, is a major global problem. We identify common genetic variants at chr2p12-p13, chr6q26, chr17q23 and chr19q13 associated with serum creatinine, a marker of kidney function (P=10−10 to 10−15). SNPs rs10206899 (near NAT8, chr2p12-p13) and rs4805834 (near SLC7A9, chr19q13) were also associated with CKD. Our findings provide new insight into metabolic, solute and drug-transport pathways underlying susceptibility to CKD.
doi:10.1038/ng.566
PMCID: PMC3748585  PMID: 20383145
9.  Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe 
Human Mutation  2012;33(7):1087-1098.
Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single nucleotide variants (SNVs), 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Amongst Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.
doi:10.1002/humu.22075
PMCID: PMC3370131  PMID: 22415848
LRRK2; Deep sequencing; novel variants; evolution; population genetics; genotype-phenotype associations
10.  Deep Resequencing Unveils Genetic Architecture of ADIPOQ and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation 
Diabetes  2012;61(5):1297-1301.
Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E–17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91–1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.
doi:10.2337/db11-0985
PMCID: PMC3331741  PMID: 22403302
11.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity 
Liu, Jason Z. | Tozzi, Federica | Waterworth, Dawn M. | Pillai, Sreekumar G. | Muglia, Pierandrea | Middleton, Lefkos | Berrettini, Wade | Knouff, Christopher W. | Yuan, Xin | Waeber, Gérard | Vollenweider, Peter | Preisig, Martin | Wareham, Nicholas J | Zhao, Jing Hua | Loos, Ruth J.F. | Barroso, Inês | Khaw, Kay-Tee | Grundy, Scott | Barter, Philip | Mahley, Robert | Kesaniemi, Antero | McPherson, Ruth | Vincent, John B. | Strauss, John | Kennedy, James L. | Farmer, Anne | McGuffin, Peter | Day, Richard | Matthews, Keith | Bakke, Per | Gulsvik, Amund | Lucae, Susanne | Ising, Marcus | Brueckl, Tanja | Horstmann, Sonja | Wichmann, H.-Erich | Rawal, Rajesh | Dahmen, Norbert | Lamina, Claudia | Polasek, Ozren | Zgaga, Lina | Huffman, Jennifer | Campbell, Susan | Kooner, Jaspal | Chambers, John C | Burnett, Mary Susan | Devaney, Joseph M. | Pichard, Augusto D. | Kent, Kenneth M. | Satler, Lowell | Lindsay, Joseph M. | Waksman, Ron | Epstein, Stephen | Wilson, James F. | Wild, Sarah H. | Campbell, Harry | Vitart, Veronique | Reilly, Muredach P. | Li, Mingyao | Qu, Liming | Wilensky, Robert | Matthai, William | Hakonarson, Hakon H. | Rader, Daniel J. | Franke, Andre | Wittig, Michael | Schäfer, Arne | Uda, Manuela | Terracciano, Antonio | Xiao, Xiangjun | Busonero, Fabio | Scheet, Paul | Schlessinger, David | St Clair, David | Rujescu, Dan | Abecasis, Gonçalo R. | Grabe, Hans Jörgen | Teumer, Alexander | Völzke, Henry | Petersmann, Astrid | John, Ulrich | Rudan, Igor | Hayward, Caroline | Wright, Alan F. | Kolcic, Ivana | Wright, Benjamin J | Thompson, John R | Balmforth, Anthony J. | Hall, Alistair S. | Samani, Nilesh J. | Anderson, Carl A. | Ahmad, Tariq | Mathew, Christopher G. | Parkes, Miles | Satsangi, Jack | Caulfield, Mark | Munroe, Patricia B. | Farrall, Martin | Dominiczak, Anna | Worthington, Jane | Thomson, Wendy | Eyre, Steve | Barton, Anne | Mooser, Vincent | Francks, Clyde | Marchini, Jonathan
Nature genetics  2010;42(5):436-440.
Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
doi:10.1038/ng.572
PMCID: PMC3612983  PMID: 20418889
12.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance 
Manning, Alisa K. | Hivert, Marie-France | Scott, Robert A. | Grimsby, Jonna L. | Bouatia-Naji, Nabila | Chen, Han | Rybin, Denis | Liu, Ching-Ti | Bielak, Lawrence F. | Prokopenko, Inga | Amin, Najaf | Barnes, Daniel | Cadby, Gemma | Hottenga, Jouke-Jan | Ingelsson, Erik | Jackson, Anne U. | Johnson, Toby | Kanoni, Stavroula | Ladenvall, Claes | Lagou, Vasiliki | Lahti, Jari | Lecoeur, Cecile | Liu, Yongmei | Martinez-Larrad, Maria Teresa | Montasser, May E. | Navarro, Pau | Perry, John R. B. | Rasmussen-Torvik, Laura J. | Salo, Perttu | Sattar, Naveed | Shungin, Dmitry | Strawbridge, Rona J. | Tanaka, Toshiko | van Duijn, Cornelia M. | An, Ping | de Andrade, Mariza | Andrews, Jeanette S. | Aspelund, Thor | Atalay, Mustafa | Aulchenko, Yurii | Balkau, Beverley | Bandinelli, Stefania | Beckmann, Jacques S. | Beilby, John P. | Bellis, Claire | Bergman, Richard N. | Blangero, John | Boban, Mladen | Boehnke, Michael | Boerwinkle, Eric | Bonnycastle, Lori L. | Boomsma, Dorret I. | Borecki, Ingrid B. | Böttcher, Yvonne | Bouchard, Claude | Brunner, Eric | Budimir, Danijela | Campbell, Harry | Carlson, Olga | Chines, Peter S. | Clarke, Robert | Collins, Francis S. | Corbatón-Anchuelo, Arturo | Couper, David | de Faire, Ulf | Dedoussis, George V | Deloukas, Panos | Dimitriou, Maria | Egan, Josephine M | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Eury, Elodie | Ferrucci, Luigi | Ford, Ian | Forouhi, Nita G. | Fox, Caroline S | Franzosi, Maria Grazia | Franks, Paul W | Frayling, Timothy M | Froguel, Philippe | Galan, Pilar | de Geus, Eco | Gigante, Bruna | Glazer, Nicole L. | Goel, Anuj | Groop, Leif | Gudnason, Vilmundur | Hallmans, Göran | Hamsten, Anders | Hansson, Ola | Harris, Tamara B. | Hayward, Caroline | Heath, Simon | Hercberg, Serge | Hicks, Andrew A. | Hingorani, Aroon | Hofman, Albert | Hui, Jennie | Hung, Joseph | Jarvelin, Marjo Riitta | Jhun, Min A. | Johnson, Paul C.D. | Jukema, J Wouter | Jula, Antti | Kao, W.H. | Kaprio, Jaakko | Kardia, Sharon L. R. | Keinanen-Kiukaanniemi, Sirkka | Kivimaki, Mika | Kolcic, Ivana | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Kyvik, Kirsten Ohm | Laakso, Markku | Lakka, Timo | Lannfelt, Lars | Lathrop, G Mark | Launer, Lenore J. | Leander, Karin | Li, Guo | Lind, Lars | Lindstrom, Jaana | Lobbens, Stéphane | Loos, Ruth J. F. | Luan, Jian’an | Lyssenko, Valeriya | Mägi, Reedik | Magnusson, Patrik K. E. | Marmot, Michael | Meneton, Pierre | Mohlke, Karen L. | Mooser, Vincent | Morken, Mario A. | Miljkovic, Iva | Narisu, Narisu | O’Connell, Jeff | Ong, Ken K. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Pankow, James S. | Peden, John F. | Pedersen, Nancy L. | Pehlic, Marina | Peltonen, Leena | Penninx, Brenda | Pericic, Marijana | Perola, Markus | Perusse, Louis | Peyser, Patricia A | Polasek, Ozren | Pramstaller, Peter P. | Province, Michael A. | Räikkönen, Katri | Rauramaa, Rainer | Rehnberg, Emil | Rice, Ken | Rotter, Jerome I. | Rudan, Igor | Ruokonen, Aimo | Saaristo, Timo | Sabater-Lleal, Maria | Salomaa, Veikko | Savage, David B. | Saxena, Richa | Schwarz, Peter | Seedorf, Udo | Sennblad, Bengt | Serrano-Rios, Manuel | Shuldiner, Alan R. | Sijbrands, Eric J.G. | Siscovick, David S. | Smit, Johannes H. | Small, Kerrin S. | Smith, Nicholas L. | Smith, Albert Vernon | Stančáková, Alena | Stirrups, Kathleen | Stumvoll, Michael | Sun, Yan V. | Swift, Amy J. | Tönjes, Anke | Tuomilehto, Jaakko | Trompet, Stella | Uitterlinden, Andre G. | Uusitupa, Matti | Vikström, Max | Vitart, Veronique | Vohl, Marie-Claude | Voight, Benjamin F. | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Watkins, Hugh | Wheeler, Eleanor | Widen, Elisabeth | Wild, Sarah H. | Willems, Sara M. | Willemsen, Gonneke | Wilson, James F. | Witteman, Jacqueline C.M. | Wright, Alan F. | Yaghootkar, Hanieh | Zelenika, Diana | Zemunik, Tatijana | Zgaga, Lina | Wareham, Nicholas J. | McCarthy, Mark I. | Barroso, Ines | Watanabe, Richard M. | Florez, Jose C. | Dupuis, Josée | Meigs, James B. | Langenberg, Claudia
Nature genetics  2012;44(6):659-669.
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
doi:10.1038/ng.2274
PMCID: PMC3613127  PMID: 22581228
13.  Variants in MTNR1B influence fasting glucose levels 
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J F | Manning, Alisa K | Jackson, Anne U | Aulchenko, Yurii | Potter, Simon C | Erdos, Michael R | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S | Bergman, Richard N | Bochud, Murielle | Bonnycastle, Lori L | Buchanan, Thomas A | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S | Crisponi, Laura | de Geus, Eco J C | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M | McCann, Owen T | Mohlke, Karen L | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G | Voight, Benjamin F | Waterworth, Dawn | Wichmann, H-Erich | Willemsen, Gonneke | Witteman, Jacqueline C M | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S | Peltonen, Leena | Groop, Leif C | Mooser, Vincent | Cupples, L Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M | Stefansson, Kari | McCarthy, Mark I | Wareham, Nicholas J | Meigs, James B | Abecasis, Gonçalo R
Nature genetics  2008;41(1):77-81.
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
doi:10.1038/ng.290
PMCID: PMC2682768  PMID: 19060907
14.  Plasma lipoprotein-associated phospholipase A2 activity in Alzheimer's disease, amnestic mild cognitive impairment, and cognitively healthy elderly subjects: a cross-sectional study 
Introduction
Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a circulating enzyme with pro-inflammatory and oxidative activities associated with cardiovascular disease and ischemic stroke. While high plasma Lp-PLA2 activity was reported as a risk factor for dementia in the Rotterdam study, no association between Lp-PLA2 mass and dementia or Alzheimer's disease (AD) was detected in the Framingham study. The objectives of the current study were to explore the relationship of plasma Lp-PLA2 activity with cognitive diagnoses (AD, amnestic mild cognitive impairment (aMCI), and cognitively healthy subjects), cardiovascular markers, cerebrospinal fluid (CSF) markers of AD, and apolipoprotein E (APOE) genotype.
Methods
Subjects with mild AD (n = 78) and aMCI (n = 59) were recruited from the Memory Clinic, University Hospital, Basel, Switzerland; cognitively healthy subjects (n = 66) were recruited from the community. Subjects underwent standardised medical, neurological, neuropsychological, imaging, genetic, blood and CSF evaluation. Differences in Lp-PLA2 activity between the cognitive diagnosis groups were tested with ANOVA and in multiple linear regression models with adjustment for covariates. Associations between Lp-PLA2 and markers of cardiovascular disease and AD were explored with Spearman's correlation coefficients.
Results
There was no significant difference in plasma Lp-PLA2 activity between AD (197.1 (standard deviation, SD 38.4) nmol/min/ml) and controls (195.4 (SD 41.9)). Gender, statin use and low-density lipoprotein cholesterol (LDL) were independently associated with Lp-PLA2 activity in multiple regression models. Lp-PLA2 activity was correlated with LDL and inversely correlated with high-density lipoprotein (HDL). AD subjects with APOE-ε4 had higher Lp-PLA2 activity (207.9 (SD 41.2)) than AD subjects lacking APOE-ε4 (181.6 (SD 26.0), P = 0.003) although this was attenuated by adjustment for LDL (P = 0.09). No strong correlations were detected for Lp-PLA2 activity and CSF markers of AD.
Conclusion
Plasma Lp-PLA2 was not associated with a diagnosis of AD or aMCI in this cross-sectional study. The main clinical correlates of Lp-PLA2 activity in AD, aMCI and cognitively healthy subjects were variables associated with lipid metabolism.
doi:10.1186/alzrt154
PMCID: PMC3580460  PMID: 23217243
15.  Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma 
Chambers, John C | Zhang, Weihua | Sehmi, Joban | Li, Xinzhong | Wass, Mark N | Van der Harst, Pim | Holm, Hilma | Sanna, Serena | Kavousi, Maryam | Baumeister, Sebastian E | Coin, Lachlan J | Deng, Guohong | Gieger, Christian | Heard-Costa, Nancy L | Hottenga, Jouke-Jan | Kühnel, Brigitte | Kumar, Vinod | Lagou, Vasiliki | Liang, Liming | Luan, Jian’an | Vidal, Pedro Marques | Leach, Irene Mateo | O’Reilly, Paul F | Peden, John F | Rahmioglu, Nilufer | Soininen, Pasi | Speliotes, Elizabeth K | Yuan, Xin | Thorleifsson, Gudmar | Alizadeh, Behrooz Z | Atwood, Larry D | Borecki, Ingrid B | Brown, Morris J | Charoen, Pimphen | Cucca, Francesco | Das, Debashish | de Geus, Eco J C | Dixon, Anna L | Döring, Angela | Ehret, Georg | Eyjolfsson, Gudmundur I | Farrall, Martin | Forouhi, Nita G | Friedrich, Nele | Goessling, Wolfram | Gudbjartsson, Daniel F | Harris, Tamara B | Hartikainen, Anna-Liisa | Heath, Simon | Hirschfield, Gideon M | Hofman, Albert | Homuth, Georg | Hyppönen, Elina | Janssen, Harry L A | Johnson, Toby | Kangas, Antti J | Kema, Ido P | Kühn, Jens P | Lai, Sandra | Lathrop, Mark | Lerch, Markus M | Li, Yun | Liang, T Jake | Lin, Jing-Ping | Loos, Ruth J F | Martin, Nicholas G | Moffatt, Miriam F | Montgomery, Grant W | Munroe, Patricia B | Musunuru, Kiran | Nakamura, Yusuke | O’Donnell, Christopher J | Olafsson, Isleifur | Penninx, Brenda W | Pouta, Anneli | Prins, Bram P | Prokopenko, Inga | Puls, Ralf | Ruokonen, Aimo | Savolainen, Markku J | Schlessinger, David | Schouten, Jeoffrey N L | Seedorf, Udo | Sen-Chowdhry, Srijita | Siminovitch, Katherine A | Smit, Johannes H | Spector, Timothy D | Tan, Wenting | Teslovich, Tanya M | Tukiainen, Taru | Uitterlinden, Andre G | Van der Klauw, Melanie M | Vasan, Ramachandran S | Wallace, Chris | Wallaschofski, Henri | Wichmann, H-Erich | Willemsen, Gonneke | Würtz, Peter | Xu, Chun | Yerges-Armstrong, Laura M | Abecasis, Goncalo R | Ahmadi, Kourosh R | Boomsma, Dorret I | Caulfield, Mark | Cookson, William O | van Duijn, Cornelia M | Froguel, Philippe | Matsuda, Koichi | McCarthy, Mark I | Meisinger, Christa | Mooser, Vincent | Pietiläinen, Kirsi H | Schumann, Gunter | Snieder, Harold | Sternberg, Michael J E | Stolk, Ronald P | Thomas, Howard C | Thorsteinsdottir, Unnur | Uda, Manuela | Waeber, Gérard | Wareham, Nicholas J | Waterworth, Dawn M | Watkins, Hugh | Whitfield, John B | Witteman, Jacqueline C M | Wolffenbuttel, Bruce H R | Fox, Caroline S | Ala-Korpela, Mika | Stefansson, Kari | Vollenweider, Peter | Völzke, Henry | Schadt, Eric E | Scott, James | Järvelin, Marjo-Riitta | Elliott, Paul | Kooner, Jaspal S
Nature genetics  2011;43(11):1131-1138.
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
doi:10.1038/ng.970
PMCID: PMC3482372  PMID: 22001757
16.  Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure 
Wain, Louise V | Verwoert, Germaine C | O’Reilly, Paul F | Shi, Gang | Johnson, Toby | Johnson, Andrew D | Bochud, Murielle | Rice, Kenneth M | Henneman, Peter | Smith, Albert V | Ehret, Georg B | Amin, Najaf | Larson, Martin G | Mooser, Vincent | Hadley, David | Dörr, Marcus | Bis, Joshua C | Aspelund, Thor | Esko, Tõnu | Janssens, A Cecile JW | Zhao, Jing Hua | Heath, Simon | Laan, Maris | Fu, Jingyuan | Pistis, Giorgio | Luan, Jian’an | Arora, Pankaj | Lucas, Gavin | Pirastu, Nicola | Pichler, Irene | Jackson, Anne U | Webster, Rebecca J | Zhang, Feng | Peden, John F | Schmidt, Helena | Tanaka, Toshiko | Campbell, Harry | Igl, Wilmar | Milaneschi, Yuri | Hotteng, Jouke-Jan | Vitart, Veronique | Chasman, Daniel I | Trompet, Stella | Bragg-Gresham, Jennifer L | Alizadeh, Behrooz Z | Chambers, John C | Guo, Xiuqing | Lehtimäki, Terho | Kühnel, Brigitte | Lopez, Lorna M | Polašek, Ozren | Boban, Mladen | Nelson, Christopher P | Morrison, Alanna C | Pihur, Vasyl | Ganesh, Santhi K | Hofman, Albert | Kundu, Suman | Mattace-Raso, Francesco US | Rivadeneira, Fernando | Sijbrands, Eric JG | Uitterlinden, Andre G | Hwang, Shih-Jen | Vasan, Ramachandran S | Wang, Thomas J | Bergmann, Sven | Vollenweider, Peter | Waeber, Gérard | Laitinen, Jaana | Pouta, Anneli | Zitting, Paavo | McArdle, Wendy L | Kroemer, Heyo K | Völker, Uwe | Völzke, Henry | Glazer, Nicole L | Taylor, Kent D | Harris, Tamara B | Alavere, Helene | Haller, Toomas | Keis, Aime | Tammesoo, Mari-Liis | Aulchenko, Yurii | Barroso, Inês | Khaw, Kay-Tee | Galan, Pilar | Hercberg, Serge | Lathrop, Mark | Eyheramendy, Susana | Org, Elin | Sõber, Siim | Lu, Xiaowen | Nolte, Ilja M | Penninx, Brenda W | Corre, Tanguy | Masciullo, Corrado | Sala, Cinzia | Groop, Leif | Voight, Benjamin F | Melander, Olle | O’Donnell, Christopher J | Salomaa, Veikko | d’Adamo, Adamo Pio | Fabretto, Antonella | Faletra, Flavio | Ulivi, Sheila | Del Greco, M Fabiola | Facheris, Maurizio | Collins, Francis S | Bergman, Richard N | Beilby, John P | Hung, Joseph | Musk, A William | Mangino, Massimo | Shin, So-Youn | Soranzo, Nicole | Watkins, Hugh | Goel, Anuj | Hamsten, Anders | Gider, Pierre | Loitfelder, Marisa | Zeginigg, Marion | Hernandez, Dena | Najjar, Samer S | Navarro, Pau | Wild, Sarah H | Corsi, Anna Maria | Singleton, Andrew | de Geus, Eco JC | Willemsen, Gonneke | Parker, Alex N | Rose, Lynda M | Buckley, Brendan | Stott, David | Orru, Marco | Uda, Manuela | van der Klauw, Melanie M | Zhang, Weihua | Li, Xinzhong | Scott, James | Chen, Yii-Der Ida | Burke, Gregory L | Kähönen, Mika | Viikari, Jorma | Döring, Angela | Meitinger, Thomas | Davies, Gail | Starr, John M | Emilsson, Valur | Plump, Andrew | Lindeman, Jan H | ’t Hoen, Peter AC | König, Inke R | Felix, Janine F | Clarke, Robert | Hopewell, Jemma C | Ongen, Halit | Breteler, Monique | Debette, Stéphanie | DeStefano, Anita L | Fornage, Myriam | Mitchell, Gary F | Smith, Nicholas L | Holm, Hilma | Stefansson, Kari | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Samani, Nilesh J | Preuss, Michael | Rudan, Igor | Hayward, Caroline | Deary, Ian J | Wichmann, H-Erich | Raitakari, Olli T | Palmas, Walter | Kooner, Jaspal S | Stolk, Ronald P | Jukema, J Wouter | Wright, Alan F | Boomsma, Dorret I | Bandinelli, Stefania | Gyllensten, Ulf B | Wilson, James F | Ferrucci, Luigi | Schmidt, Reinhold | Farrall, Martin | Spector, Tim D | Palmer, Lyle J | Tuomilehto, Jaakko | Pfeufer, Arne | Gasparini, Paolo | Siscovick, David | Altshuler, David | Loos, Ruth JF | Toniolo, Daniela | Snieder, Harold | Gieger, Christian | Meneton, Pierre | Wareham, Nicholas J | Oostra, Ben A | Metspalu, Andres | Launer, Lenore | Rettig, Rainer | Strachan, David P | Beckmann, Jacques S | Witteman, Jacqueline CM | Erdmann, Jeanette | van Dijk, Ko Willems | Boerwinkle, Eric | Boehnke, Michael | Ridker, Paul M | Jarvelin, Marjo-Riitta | Chakravarti, Aravinda | Abecasis, Goncalo R | Gudnason, Vilmundur | Newton-Cheh, Christopher | Levy, Daniel | Munroe, Patricia B | Psaty, Bruce M | Caulfield, Mark J | Rao, Dabeeru C | Tobin, Martin D | Elliott, Paul | van Duijn, Cornelia M
Nature genetics  2011;43(10):1005-1011.
Numerous genetic loci influence systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans 1-3. We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N=74,064) and follow-up studies (N=48,607), we identified at genome-wide significance (P= 2.7×10-8 to P=2.3×10-13) four novel PP loci (at 4q12 near CHIC2/PDGFRAI, 7q22.3 near PIK3CG, 8q24.12 in NOV, 11q24.3 near ADAMTS-8), two novel MAP loci (3p21.31 in MAP4, 10q25.3 near ADRB1) and one locus associated with both traits (2q24.3 near FIGN) which has recently been associated with SBP in east Asians. For three of the novel PP signals, the estimated effect for SBP was opposite to that for DBP, in contrast to the majority of common SBP- and DBP-associated variants which show concordant effects on both traits. These findings indicate novel genetic mechanisms underlying blood pressure variation, including pathways that may differentially influence SBP and DBP.
doi:10.1038/ng.922
PMCID: PMC3445021  PMID: 21909110
17.  Genome-wide association study identifies two loci strongly affecting transferrin glycosylation 
Human Molecular Genetics  2011;20(18):3710-3717.
Polysaccharide sidechains attached to proteins play important roles in cell–cell and receptor–ligand interactions. Variation in the carbohydrate component has been extensively studied for the iron transport protein transferrin, because serum levels of the transferrin isoforms asialotransferrin + disialotransferrin (carbohydrate-deficient transferrin, CDT) are used as biomarkers of excessive alcohol intake. We conducted a genome-wide association study to assess whether genetic factors affect CDT concentration in serum. CDT was measured in three population-based studies: one in Switzerland (CoLaus study, n = 5181) and two in Australia (n = 1509, n = 775). The first cohort was used as the discovery panel and the latter ones served as replication. Genome-wide single-nucleotide polymorphism (SNP) typing data were used to identify loci with significant associations with CDT as a percentage of total transferrin (CDT%). The top three SNPs in the discovery panel (rs2749097 near PGM1 on chromosome 1, and missense polymorphisms rs1049296, rs1799899 in TF on chromosome 3) were successfully replicated , yielding genome-wide significant combined association with CDT% (P = 1.9 × 10−9, 4 × 10−39, 5.5 × 10−43, respectively) and explain 5.8% of the variation in CDT%. These allelic effects are postulated to be caused by variation in availability of glucose-1-phosphate as a precursor of the glycan (PGM1), and variation in transferrin (TF) structure.
doi:10.1093/hmg/ddr272
PMCID: PMC3159549  PMID: 21665994
18.  Meta-analyses identify 13 novel loci associated with age at menopause and highlights DNA repair and immune pathways 
Stolk, Lisette | Perry, John RB | Chasman, Daniel I | He, Chunyan | Mangino, Massimo | Sulem, Patrick | Barbalic, Maja | Broer, Linda | Byrne, Enda M | Ernst, Florian | Esko, Tõnu | Franceschini, Nora | Gudbjartsson, Daniel F | Hottenga, Jouke-Jan | Kraft, Peter | McArdle, Patick F | Porcu, Eleonora | Shin, So-Youn | Smith, Albert V | van Wingerden, Sophie | Zhai, Guangju | Zhuang, Wei V | Albrecht, Eva | Alizadeh, Behrooz Z | Aspelund, Thor | Bandinelli, Stefania | Lauc, Lovorka Barac | Beckmann, Jacques S | Boban, Mladen | Boerwinkle, Eric | Broekmans, Frank J | Burri, Andrea | Campbell, Harry | Chanock, Stephen J | Chen, Constance | Cornelis, Marilyn C | Corre, Tanguy | Coviello, Andrea D | d’Adamo, Pio | Davies, Gail | de Faire, Ulf | de Geus, Eco JC | Deary, Ian J | Dedoussis, George VZ | Deloukas, Panagiotis | Ebrahim, Shah | Eiriksdottir, Gudny | Emilsson, Valur | Eriksson, Johan G | Fauser, Bart CJM | Ferreli, Liana | Ferrucci, Luigi | Fischer, Krista | Folsom, Aaron R | Garcia, Melissa E | Gasparini, Paolo | Gieger, Christian | Glazer, Nicole | Grobbee, Diederick E | Hall, Per | Haller, Toomas | Hankinson, Susan E | Hass, Merli | Hayward, Caroline | Heath, Andrew C | Hofman, Albert | Ingelsson, Erik | Janssens, A Cecile JW | Johnson, Andrew D | Karasik, David | Kardia, Sharon LR | Keyzer, Jules | Kiel, Douglas P | Kolcic, Ivana | Kutalik, Zoltán | Lahti, Jari | Lai, Sandra | Laisk, Triin | Laven, Joop SE | Lawlor, Debbie A | Liu, Jianjun | Lopez, Lorna M | Louwers, Yvonne V | Magnusson, Patrik KE | Marongiu, Mara | Martin, Nicholas G | Klaric, Irena Martinovic | Masciullo, Corrado | McKnight, Barbara | Medland, Sarah E | Melzer, David | Mooser, Vincent | Navarro, Pau | Newman, Anne B | Nyholt, Dale R | Onland-Moret, N. Charlotte | Palotie, Aarno | Paré, Guillaume | Parker, Alex N | Pedersen, Nancy L | Peeters, Petra HM | Pistis, Giorgio | Plump, Andrew S | Polasek, Ozren | Pop, Victor JM | Psaty, Bruce M | Räikkönen, Katri | Rehnberg, Emil | Rotter, Jerome I | Rudan, Igor | Sala, Cinzia | Salumets, Andres | Scuteri, Angelo | Singleton, Andrew | Smith, Jennifer A | Snieder, Harold | Soranzo, Nicole | Stacey, Simon N | Starr, John M | Stathopoulou, Maria G | Stirrups, Kathleen | Stolk, Ronald P | Styrkarsdottir, Unnur | Sun, Yan V | Tenesa, Albert | Thorand, Barbara | Toniolo, Daniela | Tryggvadottir, Laufey | Tsui, Kim | Ulivi, Sheila | van Dam, Rob M | van der Schouw, Yvonne T | van Gils, Carla H | van Nierop, Peter | Vink, Jacqueline M | Visscher, Peter M | Voorhuis, Marlies | Waeber, Gérard | Wallaschofski, Henri | Wichmann, H Erich | Widen, Elisabeth | Gent, Colette JM Wijnands-van | Willemsen, Gonneke | Wilson, James F | Wolffenbuttel, Bruce HR | Wright, Alan F | Yerges-Armstrong, Laura M | Zemunik, Tatijana | Zgaga, Lina | Zillikens, M. Carola | Zygmunt, Marek | Arnold, Alice M | Boomsma, Dorret I | Buring, Julie E. | Crisponi, Laura | Demerath, Ellen W | Gudnason, Vilmundur | Harris, Tamara B | Hu, Frank B | Hunter, David J | Launer, Lenore J | Metspalu, Andres | Montgomery, Grant W | Oostra, Ben A | Ridker, Paul M | Sanna, Serena | Schlessinger, David | Spector, Tim D | Stefansson, Kari | Streeten, Elizabeth A | Thorsteinsdottir, Unnur | Uda, Manuela | Uitterlinden, André G | van Duijn, Cornelia M | Völzke, Henry | Murray, Anna | Murabito, Joanne M | Visser, Jenny A | Lunetta, Kathryn L
Nature Genetics  2012;44(3):260-268.
To identify novel loci for age at natural menopause, we performed a meta-analysis of 22 genome-wide association studies in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 new age at natural menopause loci (P < 5 × 10−8). The new loci included genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG, PRIM1) and immune function (IL11, NLRP11, BAT2). Gene-set enrichment pathway analyses using the full GWAS dataset identified exodeoxyribonuclease, NFκB signalling and mitochondrial dysfunction as biological processes related to timing of menopause.
doi:10.1038/ng.1051
PMCID: PMC3288642  PMID: 22267201
19.  Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study 
Voight, Benjamin F | Peloso, Gina M | Orho-Melander, Marju | Frikke-Schmidt, Ruth | Barbalic, Maja | Jensen, Majken K | Hindy, George | Hólm, Hilma | Ding, Eric L | Johnson, Toby | Schunkert, Heribert | Samani, Nilesh J | Clarke, Robert | Hopewell, Jemma C | Thompson, John F | Li, Mingyao | Thorleifsson, Gudmar | Newton-Cheh, Christopher | Musunuru, Kiran | Pirruccello, James P | Saleheen, Danish | Chen, Li | Stewart, Alexandre FR | Schillert, Arne | Thorsteinsdottir, Unnur | Thorgeirsson, Gudmundur | Anand, Sonia | Engert, James C | Morgan, Thomas | Spertus, John | Stoll, Monika | Berger, Klaus | Martinelli, Nicola | Girelli, Domenico | McKeown, Pascal P | Patterson, Christopher C | Epstein, Stephen E | Devaney, Joseph | Burnett, Mary-Susan | Mooser, Vincent | Ripatti, Samuli | Surakka, Ida | Nieminen, Markku S | Sinisalo, Juha | Lokki, Marja-Liisa | Perola, Markus | Havulinna, Aki | de Faire, Ulf | Gigante, Bruna | Ingelsson, Erik | Zeller, Tanja | Wild, Philipp | de Bakker, Paul I W | Klungel, Olaf H | Maitland-van der Zee, Anke-Hilse | Peters, Bas J M | de Boer, Anthonius | Grobbee, Diederick E | Kamphuisen, Pieter W | Deneer, Vera H M | Elbers, Clara C | Onland-Moret, N Charlotte | Hofker, Marten H | Wijmenga, Cisca | Verschuren, WM Monique | Boer, Jolanda MA | van der Schouw, Yvonne T | Rasheed, Asif | Frossard, Philippe | Demissie, Serkalem | Willer, Cristen | Do, Ron | Ordovas, Jose M | Abecasis, Gonçalo R | Boehnke, Michael | Mohlke, Karen L | Daly, Mark J | Guiducci, Candace | Burtt, Noël P | Surti, Aarti | Gonzalez, Elena | Purcell, Shaun | Gabriel, Stacey | Marrugat, Jaume | Peden, John | Erdmann, Jeanette | Diemert, Patrick | Willenborg, Christina | König, Inke R | Fischer, Marcus | Hengstenberg, Christian | Ziegler, Andreas | Buysschaert, Ian | Lambrechts, Diether | Van de Werf, Frans | Fox, Keith A | El Mokhtari, Nour Eddine | Rubin, Diana | Schrezenmeir, Jürgen | Schreiber, Stefan | Schäfer, Arne | Danesh, John | Blankenberg, Stefan | Roberts, Robert | McPherson, Ruth | Watkins, Hugh | Hall, Alistair S | Overvad, Kim | Rimm, Eric | Boerwinkle, Eric | Tybjaerg-Hansen, Anne | Cupples, L Adrienne | Reilly, Muredach P | Melander, Olle | Mannucci, Pier M | Ardissino, Diego | Siscovick, David | Elosua, Roberto | Stefansson, Kari | O'Donnell, Christopher J | Salomaa, Veikko | Rader, Daniel J | Peltonen, Leena | Schwartz, Stephen M | Altshuler, David | Kathiresan, Sekar
Lancet  2012;380(9841):572-580.
Summary
Background
High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal.
Methods
We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol.
Findings
Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10−13) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10−10).
Interpretation
Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction.
Funding
US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.
doi:10.1016/S0140-6736(12)60312-2
PMCID: PMC3419820  PMID: 22607825
20.  Effects of particulate matter on inflammatory markers in the general adult population 
Background
Particulate air pollution is associated with increased risk of cardiovascular disease and stroke. Although the precise mechanisms underlying this association are still unclear, the induction of systemic inflammation following particle inhalation represents a plausible mechanistic pathway.
Methods
We used baseline data from the CoLaus Study including 6183 adult participants residing in Lausanne, Switzerland. We analyzed the association of short-term exposure to PM10 (on the day of examination visit) with continuous circulating serum levels of high-sensitive C-reactive protein (hs-CRP), interleukin 1-beta (IL-1β), interleukin 6 (IL-6), and tumor-necrosis-factor alpha (TNF-α) by robust linear regressions, controlling for potential confounding factors and assessing effect modification.
Results
In adjusted analyses, for every 10 μg/m3 elevation in PM10, IL-1ß increased by 0.034 (95 % confidence interval, 0.007-0.060) pg/mL, IL-6 by 0.036 (0.015-0.057) pg/mL, and TNF-α by 0.024 (0.013-0.035) pg/mL, whereas no significant association was found with hs-CRP levels.
Conclusions
Short-term exposure to PM10 was positively associated with higher levels of circulating IL-1ß, IL-6 and TNF-α in the adult general population. This positive association suggests a link between air pollution and cardiovascular risk, although further studies are needed to clarify the mechanistic pathway linking PM10 to cardiovascular risk.
doi:10.1186/1743-8977-9-24
PMCID: PMC3464812  PMID: 22769230
High-sensitive C-reactive protein (hs-CRP); Interleukin 1-beta (IL-1β); Interleukin 6 (IL-6); Tumor-necrosis-factor alpha (TNF-α); Air pollution
21.  Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort 
BMC Genomics  2012;13:241.
Background
Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets.
Results
Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs.
Conclusion
Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.
doi:10.1186/1471-2164-13-241
PMCID: PMC3464625  PMID: 22702538
22.  Six Novel Susceptibility Loci for Early-Onset Androgenetic Alopecia and Their Unexpected Association with Common Diseases 
PLoS Genetics  2012;8(5):e1002746.
Androgenetic alopecia (AGA) is a highly heritable condition and the most common form of hair loss in humans. Susceptibility loci have been described on the X chromosome and chromosome 20, but these loci explain a minority of its heritable variance. We conducted a large-scale meta-analysis of seven genome-wide association studies for early-onset AGA in 12,806 individuals of European ancestry. While replicating the two AGA loci on the X chromosome and chromosome 20, six novel susceptibility loci reached genome-wide significance (p = 2.62×10−9–1.01×10−12). Unexpectedly, we identified a risk allele at 17q21.31 that was recently associated with Parkinson's disease (PD) at a genome-wide significant level. We then tested the association between early-onset AGA and the risk of PD in a cross-sectional analysis of 568 PD cases and 7,664 controls. Early-onset AGA cases had significantly increased odds of subsequent PD (OR = 1.28, 95% confidence interval: 1.06–1.55, p = 8.9×10−3). Further, the AGA susceptibility alleles at the 17q21.31 locus are on the H1 haplotype, which is under negative selection in Europeans and has been linked to decreased fertility. Combining the risk alleles of six novel and two established susceptibility loci, we created a genotype risk score and tested its association with AGA in an additional sample. Individuals in the highest risk quartile of a genotype score had an approximately six-fold increased risk of early-onset AGA [odds ratio (OR) = 5.78, p = 1.4×10−88]. Our results highlight unexpected associations between early-onset AGA, Parkinson's disease, and decreased fertility, providing important insights into the pathophysiology of these conditions.
Author Summary
While most genome-wide association studies (GWAS) focus on the identification of susceptibility loci for a specific disease, this hypothesis-free approach also enables the identification of unexpected associations between different diseases by taking advantage of the previously published GWAS associations. Androgenetic Alopecia (AGA, also known as male pattern baldness) is the most common type of hair loss in humans. Parkinson's disease is reported to occur more commonly in men than in women; however, there are no studies investigating the link between AGA and Parkinson's disease. Here, we show that a specific genetic locus, chromosome 17q21.31, which is associated with Parkinson's disease, is also a susceptibility locus for early-onset AGA. We further investigate the association between early-onset AGA and Parkinson's disease, irrespective of genotype, directly in a large-scale web-based study. We find that men with early-onset AGA have 28% higher risk of developing Parkinson's disease. The early-onset AGA locus on chromosome 17q21.31 has also been linked to decreased fertility previously. Future studies of this locus may implicate novel biological pathways affecting these three conditions.
doi:10.1371/journal.pgen.1002746
PMCID: PMC3364959  PMID: 22693459
23.  Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals 
Dastani, Zari | Hivert, Marie-France | Timpson, Nicholas | Perry, John R. B. | Yuan, Xin | Scott, Robert A. | Henneman, Peter | Heid, Iris M. | Kizer, Jorge R. | Lyytikäinen, Leo-Pekka | Fuchsberger, Christian | Tanaka, Toshiko | Morris, Andrew P. | Small, Kerrin | Isaacs, Aaron | Beekman, Marian | Coassin, Stefan | Lohman, Kurt | Qi, Lu | Kanoni, Stavroula | Pankow, James S. | Uh, Hae-Won | Wu, Ying | Bidulescu, Aurelian | Rasmussen-Torvik, Laura J. | Greenwood, Celia M. T. | Ladouceur, Martin | Grimsby, Jonna | Manning, Alisa K. | Liu, Ching-Ti | Kooner, Jaspal | Mooser, Vincent E. | Vollenweider, Peter | Kapur, Karen A. | Chambers, John | Wareham, Nicholas J. | Langenberg, Claudia | Frants, Rune | Willems-vanDijk, Ko | Oostra, Ben A. | Willems, Sara M. | Lamina, Claudia | Winkler, Thomas W. | Psaty, Bruce M. | Tracy, Russell P. | Brody, Jennifer | Chen, Ida | Viikari, Jorma | Kähönen, Mika | Pramstaller, Peter P. | Evans, David M. | St. Pourcain, Beate | Sattar, Naveed | Wood, Andrew R. | Bandinelli, Stefania | Carlson, Olga D. | Egan, Josephine M. | Böhringer, Stefan | van Heemst, Diana | Kedenko, Lyudmyla | Kristiansson, Kati | Nuotio, Marja-Liisa | Loo, Britt-Marie | Harris, Tamara | Garcia, Melissa | Kanaya, Alka | Haun, Margot | Klopp, Norman | Wichmann, H.-Erich | Deloukas, Panos | Katsareli, Efi | Couper, David J. | Duncan, Bruce B. | Kloppenburg, Margreet | Adair, Linda S. | Borja, Judith B. | Wilson, James G. | Musani, Solomon | Guo, Xiuqing | Johnson, Toby | Semple, Robert | Teslovich, Tanya M. | Allison, Matthew A. | Redline, Susan | Buxbaum, Sarah G. | Mohlke, Karen L. | Meulenbelt, Ingrid | Ballantyne, Christie M. | Dedoussis, George V. | Hu, Frank B. | Liu, Yongmei | Paulweber, Bernhard | Spector, Timothy D. | Slagboom, P. Eline | Ferrucci, Luigi | Jula, Antti | Perola, Markus | Raitakari, Olli | Florez, Jose C. | Salomaa, Veikko | Eriksson, Johan G. | Frayling, Timothy M. | Hicks, Andrew A. | Lehtimäki, Terho | Smith, George Davey | Siscovick, David S. | Kronenberg, Florian | van Duijn, Cornelia | Loos, Ruth J. F. | Waterworth, Dawn M. | Meigs, James B. | Dupuis, Josee | Richards, J. Brent
PLoS Genetics  2012;8(3):e1002607.
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10−4). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10−3, n = 22,044), increased triglycerides (p = 2.6×10−14, n = 93,440), increased waist-to-hip ratio (p = 1.8×10−5, n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10−3, n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10−13, n = 96,748) and decreased BMI (p = 1.4×10−4, n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
Author Summary
Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.
doi:10.1371/journal.pgen.1002607
PMCID: PMC3315470  PMID: 22479202
24.  Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile 
Kilpeläinen, Tuomas O | Zillikens, M Carola | Stančáková, Alena | Finucane, Francis M | Ried, Janina S | Langenberg, Claudia | Zhang, Weihua | Beckmann, Jacques S | Luan, Jian’an | Vandenput, Liesbeth | Styrkarsdottir, Unnur | Zhou, Yanhua | Smith, Albert Vernon | Zhao, Jing-Hua | Amin, Najaf | Vedantam, Sailaja | Shin, So Youn | Haritunians, Talin | Fu, Mao | Feitosa, Mary F | Kumari, Meena | Halldorsson, Bjarni V | Tikkanen, Emmi | Mangino, Massimo | Hayward, Caroline | Song, Ci | Arnold, Alice M | Aulchenko, Yurii S | Oostra, Ben A | Campbell, Harry | Cupples, L Adrienne | Davis, Kathryn E | Döring, Angela | Eiriksdottir, Gudny | Estrada, Karol | Fernández-Real, José Manuel | Garcia, Melissa | Gieger, Christian | Glazer, Nicole L | Guiducci, Candace | Hofman, Albert | Humphries, Steve E | Isomaa, Bo | Jacobs, Leonie C | Jula, Antti | Karasik, David | Karlsson, Magnus K | Khaw, Kay-Tee | Kim, Lauren J | Kivimäki, Mika | Klopp, Norman | Kühnel, Brigitte | Kuusisto, Johanna | Liu, Yongmei | Ljunggren, Östen | Lorentzon, Mattias | Luben, Robert N | McKnight, Barbara | Mellström, Dan | Mitchell, Braxton D | Mooser, Vincent | Moreno, José Maria | Männistö, Satu | O’Connell, Jeffery R | Pascoe, Laura | Peltonen, Leena | Peral, Belén | Perola, Markus | Psaty, Bruce M | Salomaa, Veikko | Savage, David B | Semple, Robert K | Skaric-Juric, Tatjana | Sigurdsson, Gunnar | Song, Kijoung S | Spector, Timothy D | Syvänen, Ann-Christine | Talmud, Philippa J | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Uitterlinden, André G | van Duijn, Cornelia M | Vidal-Puig, Antonio | Wild, Sarah H | Wright, Alan F | Clegg, Deborah J | Schadt, Eric | Wilson, James F | Rudan, Igor | Ripatti, Samuli | Borecki, Ingrid B | Shuldiner, Alan R | Ingelsson, Erik | Jansson, John-Olov | Kaplan, Robert C | Gudnason, Vilmundur | Harris, Tamara B | Groop, Leif | Kiel, Douglas P | Rivadeneira, Fernando | Walker, Mark | Barroso, Inês | Vollenweider, Peter | Waeber, Gérard | Chambers, John C | Kooner, Jaspal S | Soranzo, Nicole | Hirschhorn, Joel N | Stefansson, Kari | Wichmann, H-Erich | Ohlsson, Claes | O’Rahilly, Stephen | Wareham, Nicholas J | Speliotes, Elizabeth K | Fox, Caroline S | Laakso, Markku | Loos, Ruth J F
Nature Genetics  2011;43(8):753-760.
Genome-wide association studies have identified 32 loci associated with body mass index (BMI), a measure that does not allow distinguishing lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ~2.5 million SNPs and body fat percentage from 36,626 individuals, and followed up the 14 most significant (P<10−6) independent loci in 39,576 individuals. We confirmed the previously established adiposity locus in FTO (P=3×10−26), and identified two new loci associated with body fat percentage, one near IRS1 (P=4×10−11) and one near SPRY2 (P=3×10−8). Both loci harbour genes with a potential link to adipocyte physiology, of which the locus near IRS1 shows an intriguing association pattern. The body-fat-decreasing allele associates with decreased IRS1 expression and with an impaired metabolic profile, including decreased subcutaneous-to-visceral fat ratio, increased insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease, and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.
doi:10.1038/ng.866
PMCID: PMC3262230  PMID: 21706003
25.  An 18-kDa Translocator Protein (TSPO) polymorphism explains differences in binding affinity of the PET radioligand PBR28 
[11C]PBR28 binds the 18-kDa Translocator Protein (TSPO) and is used in positron emission tomography (PET) to detect microglial activation. However, quantitative interpretations of signal are confounded by large interindividual variability in binding affinity, which displays a trimodal distribution compatible with a codominant genetic trait. Here, we tested directly for an underlying genetic mechanism to explain this. Binding affinity of PBR28 was measured in platelets isolated from 41 human subjects and tested for association with polymorphisms in TSPO and genes encoding other proteins in the TSPO complex. Complete agreement was observed between the TSPO Ala147Thr genotype and PBR28 binding affinity phenotype (P value=3.1 × 10−13). The TSPO Ala147Thr polymorphism predicts PBR28 binding affinity in human platelets. As all second-generation TSPO PET radioligands tested hitherto display a trimodal distribution in binding affinity analogous to PBR28, testing for this polymorphism may allow quantitative interpretation of TSPO PET studies with these radioligands.
doi:10.1038/jcbfm.2011.147
PMCID: PMC3323305  PMID: 22008728
Ala147Thr; PBR28; polymorphism; radioligand binding; TSPO

Results 1-25 (70)