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1.  A glycogene mutation map for discovery of diseases of glycosylation 
Glycobiology  2014;25(2):211-224.
Glycosylation of proteins and lipids involves over 200 known glycosyltransferases (GTs), and deleterious defects in many of the genes encoding these enzymes cause disorders collectively classified as congenital disorders of glycosylation (CDGs). Most known CDGs are caused by defects in glycogenes that affect glycosylation globally. Many GTs are members of homologous isoenzyme families and deficiencies in individual isoenzymes may not affect glycosylation globally. In line with this, there appears to be an underrepresentation of disease-causing glycogenes among these larger isoenzyme homologous families. However, genome-wide association studies have identified such isoenzyme genes as candidates for different diseases, but validation is not straightforward without biomarkers. Large-scale whole-exome sequencing (WES) provides access to mutations in, for example, GT genes in populations, which can be used to predict and/or analyze functional deleterious mutations. Here, we constructed a draft of a functional mutational map of glycogenes, GlyMAP, from WES of a rather homogenous population of 2000 Danes. We cataloged all missense mutations and used prediction algorithms, manual inspection and in case of carbohydrate-active enzymes family GT27 experimental analysis of mutations to map deleterious mutations. GlyMAP (http://glymap.glycomics.ku.dk) provides a first global view of the genetic stability of the glycogenome and should serve as a tool for discovery of novel CDGs.
doi:10.1093/glycob/cwu104
PMCID: PMC4351397  PMID: 25267602
damaging mutations; glycogenes; nonsynonymous mutations; nsSNV; MAF
2.  Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels 
Kilpeläinen, Tuomas O. | Carli, Jayne F. Martin | Skowronski, Alicja A. | Sun, Qi | Kriebel, Jennifer | Feitosa, Mary F | Hedman, Åsa K. | Drong, Alexander W. | Hayes, James E. | Zhao, Jinghua | Pers, Tune H. | Schick, Ursula | Grarup, Niels | Kutalik, Zoltán | Trompet, Stella | Mangino, Massimo | Kristiansson, Kati | Beekman, Marian | Lyytikäinen, Leo-Pekka | Eriksson, Joel | Henneman, Peter | Lahti, Jari | Tanaka, Toshiko | Luan, Jian'an | Greco M, Fabiola Del | Pasko, Dorota | Renström, Frida | Willems, Sara M. | Mahajan, Anubha | Rose, Lynda M. | Guo, Xiuqing | Liu, Yongmei | Kleber, Marcus E. | Pérusse, Louis | Gaunt, Tom | Ahluwalia, Tarunveer S. | Ju Sung, Yun | Ramos, Yolande F. | Amin, Najaf | Amuzu, Antoinette | Barroso, Inês | Bellis, Claire | Blangero, John | Buckley, Brendan M. | Böhringer, Stefan | I Chen, Yii-Der | de Craen, Anton J. N. | Crosslin, David R. | Dale, Caroline E. | Dastani, Zari | Day, Felix R. | Deelen, Joris | Delgado, Graciela E. | Demirkan, Ayse | Finucane, Francis M. | Ford, Ian | Garcia, Melissa E. | Gieger, Christian | Gustafsson, Stefan | Hallmans, Göran | Hankinson, Susan E. | Havulinna, Aki S | Herder, Christian | Hernandez, Dena | Hicks, Andrew A. | Hunter, David J. | Illig, Thomas | Ingelsson, Erik | Ioan-Facsinay, Andreea | Jansson, John-Olov | Jenny, Nancy S. | Jørgensen, Marit E. | Jørgensen, Torben | Karlsson, Magnus | Koenig, Wolfgang | Kraft, Peter | Kwekkeboom, Joanneke | Laatikainen, Tiina | Ladwig, Karl-Heinz | LeDuc, Charles A. | Lowe, Gordon | Lu, Yingchang | Marques-Vidal, Pedro | Meisinger, Christa | Menni, Cristina | Morris, Andrew P. | Myers, Richard H. | Männistö, Satu | Nalls, Mike A. | Paternoster, Lavinia | Peters, Annette | Pradhan, Aruna D. | Rankinen, Tuomo | Rasmussen-Torvik, Laura J. | Rathmann, Wolfgang | Rice, Treva K. | Brent Richards, J | Ridker, Paul M. | Sattar, Naveed | Savage, David B. | Söderberg, Stefan | Timpson, Nicholas J. | Vandenput, Liesbeth | van Heemst, Diana | Uh, Hae-Won | Vohl, Marie-Claude | Walker, Mark | Wichmann, Heinz-Erich | Widén, Elisabeth | Wood, Andrew R. | Yao, Jie | Zeller, Tanja | Zhang, Yiying | Meulenbelt, Ingrid | Kloppenburg, Margreet | Astrup, Arne | Sørensen, Thorkild I. A. | Sarzynski, Mark A. | Rao, D. C. | Jousilahti, Pekka | Vartiainen, Erkki | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, André G. | Kajantie, Eero | Osmond, Clive | Palotie, Aarno | Eriksson, Johan G. | Heliövaara, Markku | Knekt, Paul B. | Koskinen, Seppo | Jula, Antti | Perola, Markus | Huupponen, Risto K. | Viikari, Jorma S. | Kähönen, Mika | Lehtimäki, Terho | Raitakari, Olli T. | Mellström, Dan | Lorentzon, Mattias | Casas, Juan P. | Bandinelli, Stefanie | März, Winfried | Isaacs, Aaron | van Dijk, Ko W. | van Duijn, Cornelia M. | Harris, Tamara B. | Bouchard, Claude | Allison, Matthew A. | Chasman, Daniel I. | Ohlsson, Claes | Lind, Lars | Scott, Robert A. | Langenberg, Claudia | Wareham, Nicholas J. | Ferrucci, Luigi | Frayling, Timothy M. | Pramstaller, Peter P. | Borecki, Ingrid B. | Waterworth, Dawn M. | Bergmann, Sven | Waeber, Gérard | Vollenweider, Peter | Vestergaard, Henrik | Hansen, Torben | Pedersen, Oluf | Hu, Frank B. | Eline Slagboom, P | Grallert, Harald | Spector, Tim D. | Jukema, J.W. | Klein, Robert J. | Schadt, Erik E | Franks, Paul W. | Lindgren, Cecilia M. | Leibel, Rudolph L. | Loos, Ruth J. F.
Nature Communications  2016;7:10494.
Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10−6 in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10−8) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
This meta-analysis of genome-wide association studies identifies four genetic loci associated with circulating leptin levels independent of adiposity. Examination in mouse adipose tissue explants provides functional support for the leptin-associated loci.
doi:10.1038/ncomms10494
PMCID: PMC4740377  PMID: 26833098
3.  New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk 
Lu, Yingchang | Day, Felix R. | Gustafsson, Stefan | Buchkovich, Martin L. | Na, Jianbo | Bataille, Veronique | Cousminer, Diana L. | Dastani, Zari | Drong, Alexander W. | Esko, Tõnu | Evans, David M. | Falchi, Mario | Feitosa, Mary F. | Ferreira, Teresa | Hedman, Åsa K. | Haring, Robin | Hysi, Pirro G. | Iles, Mark M. | Justice, Anne E. | Kanoni, Stavroula | Lagou, Vasiliki | Li, Rui | Li, Xin | Locke, Adam | Lu, Chen | Mägi, Reedik | Perry, John R. B. | Pers, Tune H. | Qi, Qibin | Sanna, Marianna | Schmidt, Ellen M. | Scott, William R. | Shungin, Dmitry | Teumer, Alexander | Vinkhuyzen, Anna A. E. | Walker, Ryan W. | Westra, Harm-Jan | Zhang, Mingfeng | Zhang, Weihua | Zhao, Jing Hua | Zhu, Zhihong | Afzal, Uzma | Ahluwalia, Tarunveer Singh | Bakker, Stephan J. L. | Bellis, Claire | Bonnefond, Amélie | Borodulin, Katja | Buchman, Aron S. | Cederholm, Tommy | Choh, Audrey C. | Choi, Hyung Jin | Curran, Joanne E. | de Groot, Lisette C. P. G. M. | De Jager, Philip L. | Dhonukshe-Rutten, Rosalie A. M. | Enneman, Anke W. | Eury, Elodie | Evans, Daniel S. | Forsen, Tom | Friedrich, Nele | Fumeron, Frédéric | Garcia, Melissa E. | Gärtner, Simone | Han, Bok-Ghee | Havulinna, Aki S. | Hayward, Caroline | Hernandez, Dena | Hillege, Hans | Ittermann, Till | Kent, Jack W. | Kolcic, Ivana | Laatikainen, Tiina | Lahti, Jari | Leach, Irene Mateo | Lee, Christine G. | Lee, Jong-Young | Liu, Tian | Liu, Youfang | Lobbens, Stéphane | Loh, Marie | Lyytikäinen, Leo-Pekka | Medina-Gomez, Carolina | Michaëlsson, Karl | Nalls, Mike A. | Nielson, Carrie M. | Oozageer, Laticia | Pascoe, Laura | Paternoster, Lavinia | Polašek, Ozren | Ripatti, Samuli | Sarzynski, Mark A. | Shin, Chan Soo | Narančić, Nina Smolej | Spira, Dominik | Srikanth, Priya | Steinhagen-Thiessen, Elisabeth | Sung, Yun Ju | Swart, Karin M. A. | Taittonen, Leena | Tanaka, Toshiko | Tikkanen, Emmi | van der Velde, Nathalie | van Schoor, Natasja M. | Verweij, Niek | Wright, Alan F. | Yu, Lei | Zmuda, Joseph M. | Eklund, Niina | Forrester, Terrence | Grarup, Niels | Jackson, Anne U. | Kristiansson, Kati | Kuulasmaa, Teemu | Kuusisto, Johanna | Lichtner, Peter | Luan, Jian'an | Mahajan, Anubha | Männistö, Satu | Palmer, Cameron D. | Ried, Janina S. | Scott, Robert A. | Stancáková, Alena | Wagner, Peter J. | Demirkan, Ayse | Döring, Angela | Gudnason, Vilmundur | Kiel, Douglas P. | Kühnel, Brigitte | Mangino, Massimo | Mcknight, Barbara | Menni, Cristina | O'Connell, Jeffrey R. | Oostra, Ben A. | Shuldiner, Alan R. | Song, Kijoung | Vandenput, Liesbeth | van Duijn, Cornelia M. | Vollenweider, Peter | White, Charles C. | Boehnke, Michael | Boettcher, Yvonne | Cooper, Richard S. | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Hingorani, Aroon | Jørgensen, Torben | Jousilahti, Pekka | Kivimaki, Mika | Kumari, Meena | Laakso, Markku | Langenberg, Claudia | Linneberg, Allan | Luke, Amy | Mckenzie, Colin A. | Palotie, Aarno | Pedersen, Oluf | Peters, Annette | Strauch, Konstantin | Tayo, Bamidele O. | Wareham, Nicholas J. | Bennett, David A. | Bertram, Lars | Blangero, John | Blüher, Matthias | Bouchard, Claude | Campbell, Harry | Cho, Nam H. | Cummings, Steven R. | Czerwinski, Stefan A. | Demuth, Ilja | Eckardt, Rahel | Eriksson, Johan G. | Ferrucci, Luigi | Franco, Oscar H. | Froguel, Philippe | Gansevoort, Ron T. | Hansen, Torben | Harris, Tamara B. | Hastie, Nicholas | Heliövaara, Markku | Hofman, Albert | Jordan, Joanne M. | Jula, Antti | Kähönen, Mika | Kajantie, Eero | Knekt, Paul B. | Koskinen, Seppo | Kovacs, Peter | Lehtimäki, Terho | Lind, Lars | Liu, Yongmei | Orwoll, Eric S. | Osmond, Clive | Perola, Markus | Pérusse, Louis | Raitakari, Olli T. | Rankinen, Tuomo | Rao, D. C. | Rice, Treva K. | Rivadeneira, Fernando | Rudan, Igor | Salomaa, Veikko | Sørensen, Thorkild I. A. | Stumvoll, Michael | Tönjes, Anke | Towne, Bradford | Tranah, Gregory J. | Tremblay, Angelo | Uitterlinden, André G. | van der Harst, Pim | Vartiainen, Erkki | Viikari, Jorma S. | Vitart, Veronique | Vohl, Marie-Claude | Völzke, Henry | Walker, Mark | Wallaschofski, Henri | Wild, Sarah | Wilson, James F. | Yengo, Loïc | Bishop, D. Timothy | Borecki, Ingrid B. | Chambers, John C. | Cupples, L. Adrienne | Dehghan, Abbas | Deloukas, Panos | Fatemifar, Ghazaleh | Fox, Caroline | Furey, Terrence S. | Franke, Lude | Han, Jiali | Hunter, David J. | Karjalainen, Juha | Karpe, Fredrik | Kaplan, Robert C. | Kooner, Jaspal S. | McCarthy, Mark I. | Murabito, Joanne M. | Morris, Andrew P. | Bishop, Julia A. N. | North, Kari E. | Ohlsson, Claes | Ong, Ken K. | Prokopenko, Inga | Richards, J. Brent | Schadt, Eric E. | Spector, Tim D. | Widén, Elisabeth | Willer, Cristen J. | Yang, Jian | Ingelsson, Erik | Mohlke, Karen L. | Hirschhorn, Joel N. | Pospisilik, John Andrew | Zillikens, M. Carola | Lindgren, Cecilia | Kilpeläinen, Tuomas Oskari | Loos, Ruth J. F.
Nature Communications  2016;7:10495.
To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10−8), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
A genome-wide association meta-analysis study here shows novel genetic loci to be associated to body fat percentage, and describes cross-phenotype association that further demonstrate a close relationship between adiposity and cardiovascular disease risk.
doi:10.1038/ncomms10495
PMCID: PMC4740398  PMID: 26833246
4.  Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes 
Nature Communications  2016;7:10531.
Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P<5 × 10−8), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P<0.007). These results indicate that expansion of single ethnic GWAS is still useful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but also for common loci across different ethnicities.
Here, Imamura et al. conduct meta-analysis of genome-wide association studies to identify novel susceptibility loci for type 2 diabetes (T2D) in the Japanese population. By doing so, this study shows that both ethnicity-specific and ethnically-shared genetic loci can contribute to T2D risk.
doi:10.1038/ncomms10531
PMCID: PMC4738362  PMID: 26818947
5.  Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation 
Kato, Norihiro | Loh, Marie | Takeuchi, Fumihiko | Verweij, Niek | Wang, Xu | Zhang, Weihua | Kelly, Tanika N | Saleheen, Danish | Lehne, Benjamin | Leach, Irene Mateo | Drong, Alexander W | Abbott, James | Wahl, Simone | Tan, Sian-Tsung | Scott, William R | Campanella, Gianluca | Chadeau-Hyam, Marc | Afzal, Uzma | Ahluwalia, Tarunveer S | Bonder, Marc Jan | Chen, Peng | Dehghan, Abbas | Edwards, Todd L | Esko, Tõnu | Go, Min Jin | Harris, Sarah E | Hartiala, Jaana | Kasela, Silva | Kasturiratne, Anuradhani | Khor, Chiea-Chuen | Kleber, Marcus E | Li, Huaixing | Yu Mok, Zuan | Nakatochi, Masahiro | Sapari, Nur Sabrina | Saxena, Richa | Stewart, Alexandre F R | Stolk, Lisette | Tabara, Yasuharu | Teh, Ai Ling | Wu, Ying | Wu, Jer-Yuarn | Zhang, Yi | Aits, Imke | Da Silva Couto Alves, Alexessander | Das, Shikta | Dorajoo, Rajkumar | Hopewell, Jemma C | Kim, Yun Kyoung | Koivula, Robert W | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Nguyen, Quang N | Pereira, Mark A | Postmus, Iris | Raitakari, Olli T | Bryan, Molly Scannell | Scott, Robert A | Sorice, Rossella | Tragante, Vinicius | Traglia, Michela | White, Jon | Yamamoto, Ken | Zhang, Yonghong | Adair, Linda S | Ahmed, Alauddin | Akiyama, Koichi | Asif, Rasheed | Aung, Tin | Barroso, Inês | Bjonnes, Andrew | Braun, Timothy R | Cai, Hui | Chang, Li-Ching | Chen, Chien-Hsiun | Cheng, Ching-Yu | Chong, Yap-Seng | Collins, Rory | Courtney, Regina | Davies, Gail | Delgado, Graciela | Do, Loi D | Doevendans, Pieter A | Gansevoort, Ron T | Gao, Yu-Tang | Grammer, Tanja B | Grarup, Niels | Grewal, Jagvir | Gu, Dongfeng | Wander, Gurpreet S | Hartikainen, Anna-Liisa | Hazen, Stanley L | He, Jing | Heng, Chew-Kiat | Hixson, James E | Hofman, Albert | Hsu, Chris | Huang, Wei | Husemoen, Lise L N | Hwang, Joo-Yeon | Ichihara, Sahoko | Igase, Michiya | Isono, Masato | Justesen, Johanne M | Katsuya, Tomohiro | Kibriya, Muhammad G | Kim, Young Jin | Kishimoto, Miyako | Koh, Woon-Puay | Kohara, Katsuhiko | Kumari, Meena | Kwek, Kenneth | Lee, Nanette R | Lee, Jeannette | Liao, Jiemin | Lieb, Wolfgang | Liewald, David C M | Matsubara, Tatsuaki | Matsushita, Yumi | Meitinger, Thomas | Mihailov, Evelin | Milani, Lili | Mills, Rebecca | Mononen, Nina | Müller-Nurasyid, Martina | Nabika, Toru | Nakashima, Eitaro | Ng, Hong Kiat | Nikus, Kjell | Nutile, Teresa | Ohkubo, Takayoshi | Ohnaka, Keizo | Parish, Sarah | Paternoster, Lavinia | Peng, Hao | Peters, Annette | Pham, Son T | Pinidiyapathirage, Mohitha J | Rahman, Mahfuzar | Rakugi, Hiromi | Rolandsson, Olov | Ann Rozario, Michelle | Ruggiero, Daniela | Sala, Cinzia F | Sarju, Ralhan | Shimokawa, Kazuro | Snieder, Harold | Sparsø, Thomas | Spiering, Wilko | Starr, John M | Stott, David J | Stram, Daniel O | Sugiyama, Takao | Szymczak, Silke | Tang, W H Wilson | Tong, Lin | Trompet, Stella | Turjanmaa, Väinö | Ueshima, Hirotsugu | Uitterlinden, André G | Umemura, Satoshi | Vaarasmaki, Marja | van Dam, Rob M | van Gilst, Wiek H | van Veldhuisen, Dirk J | Viikari, Jorma S | Waldenberger, Melanie | Wang, Yiqin | Wang, Aili | Wilson, Rory | Wong, Tien-Yin | Xiang, Yong-Bing | Yamaguchi, Shuhei | Ye, Xingwang | Young, Robin D | Young, Terri L | Yuan, Jian-Min | Zhou, Xueya | Asselbergs, Folkert W | Ciullo, Marina | Clarke, Robert | Deloukas, Panos | Franke, Andre | Franks, Paul W | Franks, Steve | Friedlander, Yechiel | Gross, Myron D | Guo, Zhirong | Hansen, Torben | Jarvelin, Marjo-Riitta | Jørgensen, Torben | Jukema, J Wouter | kähönen, Mika | Kajio, Hiroshi | Kivimaki, Mika | Lee, Jong-Young | Lehtimäki, Terho | Linneberg, Allan | Miki, Tetsuro | Pedersen, Oluf | Samani, Nilesh J | Sørensen, Thorkild I A | Takayanagi, Ryoichi | Toniolo, Daniela | Ahsan, Habibul | Allayee, Hooman | Chen, Yuan-Tsong | Danesh, John | Deary, Ian J | Franco, Oscar H | Franke, Lude | Heijman, Bastiaan T | Holbrook, Joanna D | Isaacs, Aaron | Kim, Bong-Jo | Lin, Xu | Liu, Jianjun | März, Winfried | Metspalu, Andres | Mohlke, Karen L | Sanghera, Dharambir K | Shu, Xiao-Ou | van Meurs, Joyce B J | Vithana, Eranga | Wickremasinghe, Ananda R | Wijmenga, Cisca | Wolffenbuttel, Bruce H W | Yokota, Mitsuhiro | Zheng, Wei | Zhu, Dingliang | Vineis, Paolo | Kyrtopoulos, Soterios A | Kleinjans, Jos C S | McCarthy, Mark I | Soong, Richie | Gieger, Christian | Scott, James | Teo, Yik-Ying | He, Jiang | Elliott, Paul | Tai, E Shyong | van der Harst, Pim | Kooner, Jaspal S | Chambers, John C
Nature genetics  2015;47(11):1282-1293.
We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10−11 to 5.0 × 10−21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10−6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.
doi:10.1038/ng.3405
PMCID: PMC4719169  PMID: 26390057
6.  Common variants in LEPR, IL6, AMD1, and NAMPT do not associate with risk of juvenile and childhood obesity in Danes: a case–control study 
BMC Medical Genetics  2015;16:105.
Background
Childhood obesity is a highly heritable disorder, for which the underlying genetic architecture is largely unknown. Four common variants involved in inflammatory-adipokine triggering (IL6 rs2069845, LEPR rs1137100, NAMPT rs3801266, and AMD1 rs2796749) have recently been associated with obesity and related traits in Indian children. The current study aimed to examine the effect of these variants on risk of childhood/juvenile onset obesity and on obesity-related quantitative traits in two Danish cohorts.
Methods
Genotype information was obtained for 1461 young Caucasian men from the Genetics of Overweight Young Adults (GOYA) study (overweight/obese: 739 and normal weight: 722) and the Danish Childhood Obesity Biobank (TDCOB; overweight/obese: 1022 and normal weight: 650).
Overweight/obesity was defined as having a body mass index (BMI) ≥25 kg/m2; among children and youths, this cut-off was defined using age and sex-specific cut-offs corresponding to an adult body mass index ≥25 kg/m2. Risk of obesity was assessed using a logistic regression model whereas obesity-related quantitative measures were analyzed using a general linear model (based on z-scores) stratifying on the case status and adjusting for age and gender. Meta-analyses were performed using the fixed effects model.
Results
No statistically significant association with childhood/juvenile obesity was found for any of the four gene variants among the individual or combined analyses (rs2069845 OR: 0.94 CI: 0.85–1.04; rs1137100 OR: 1.01 CI: 0.90–1.14; rs3801266: 0.96 CI: 0.84–1.10; rs2796749 OR: 1.02 CI: 0.90–1.15; p > 0.05). However, among normal weight children and juvenile men, the LEPR rs1137100 A-allele significantly associated with lower BMI (β = −0.12, p = 0.0026).
Conclusions
The IL6, LEPR, NAMPT, and AMD1 gene variants previously found to associate among Indian children did not associate with risk of obesity or obesity-related quantitative measures among Caucasian children and juvenile men from Denmark.
doi:10.1186/s12881-015-0253-3
PMCID: PMC4642628  PMID: 26558825
Childhood obesity; Juvenile obesity; Single nucleotide polymorphism; Case-control study; Body mass index; BMI; Obesity
7.  Comparative Analyses of QTLs Influencing Obesity and Metabolic Phenotypes in Pigs and Humans 
PLoS ONE  2015;10(9):e0137356.
The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genome-wide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.
doi:10.1371/journal.pone.0137356
PMCID: PMC4562524  PMID: 26348622
8.  Reduced CD300LG mRNA tissue expression, increased intramyocellular lipid content and impaired glucose metabolism in healthy male carriers of Arg82Cys in CD300LG: a novel genometabolic cross-link between CD300LG and common metabolic phenotypes 
Background
CD300LG rs72836561 (c.313C>T, p.Arg82Cys) has in genetic-epidemiological studies been associated with the lipoprotein abnormalities of the metabolic syndrome. CD300LG belongs to the CD300-family of membrane-bound molecules which have the ability to recognize and interact with extracellular lipids. We tested whether this specific polymorphism results in abnormal lipid accumulation in skeletal muscle and liver and other indices of metabolic dysfunction.
Methods
40 healthy men with a mean age of 55 years were characterized metabolically including assessment of insulin sensitivity by the hyperinsulinemic euglycemic clamp, intrahepatic lipid content (IHLC) and intramyocellular lipid content (IMCL) by MR spectroscopy, and β-cell function by an intravenous glucose tolerance test. Changes in insulin signaling and CD300LG mRNA expression were determined by western blotting and quantitative PCR in muscle and adipose tissue.
Results
Compared with the 20 controls (CC carriers), the 20 CT carriers (polymorphism carriers) had higher IMCL (p=0.045), a reduced fasting forearm glucose uptake (p=0.011), a trend toward lower M-values during the clamp; 6.0 mg/kg/min vs 7.1 (p=0.10), and higher IHLC (p=0.10). CT carriers had lower CD300LG mRNA expression and CD300LG expression in muscle correlated with IMCL (β=−0.35, p=0.046), forearm glucose uptake (β=0.37, p=0.03), and tended to correlate with the M-value (β=0.33, p=0.06), independently of CD300LG genotype. β-cell function was unaffected.
Conclusions
The CD300LG polymorphism was associated with decreased CD300LG mRNA expression in muscle and adipose tissue, increased IMCL, and abnormalities of glucose metabolism. CD300LG mRNA levels correlated with IMCL and forearm glucose uptake. These findings link a specific CD300LG polymorphism with features of the metabolic syndrome suggesting a role for CD300LG in the regulation of common metabolic traits.
Trial registration number
NCT01571609.
doi:10.1136/bmjdrc-2015-000095
PMCID: PMC4553907  PMID: 26336608
Metabolic Syndrome; Genetics; Insulin Resistance; Gene Expression
9.  Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility 
Wessel, Jennifer | Chu, Audrey Y. | Willems, Sara M. | Wang, Shuai | Yaghootkar, Hanieh | Brody, Jennifer A. | Dauriz, Marco | Hivert, Marie-France | Raghavan, Sridharan | Lipovich, Leonard | Hidalgo, Bertha | Fox, Keolu | Huffman, Jennifer E. | An, Ping | Lu, Yingchang | Rasmussen-Torvik, Laura J. | Grarup, Niels | Ehm, Margaret G. | Li, Li | Baldridge, Abigail S. | Stančáková, Alena | Abrol, Ravinder | Besse, Céline | Boland, Anne | Bork-Jensen, Jette | Fornage, Myriam | Freitag, Daniel F. | Garcia, Melissa E. | Guo, Xiuqing | Hara, Kazuo | Isaacs, Aaron | Jakobsdottir, Johanna | Lange, Leslie A. | Layton, Jill C. | Li, Man | Zhao, Jing Hua | Meidtner, Karina | Morrison, Alanna C. | Nalls, Mike A. | Peters, Marjolein J. | Sabater-Lleal, Maria | Schurmann, Claudia | Silveira, Angela | Smith, Albert V. | Southam, Lorraine | Stoiber, Marcus H. | Strawbridge, Rona J. | Taylor, Kent D. | Varga, Tibor V. | Allin, Kristine H. | Amin, Najaf | Aponte, Jennifer L. | Aung, Tin | Barbieri, Caterina | Bihlmeyer, Nathan A. | Boehnke, Michael | Bombieri, Cristina | Bowden, Donald W. | Burns, Sean M. | Chen, Yuning | Chen, Yii-Der I. | Cheng, Ching-Yu | Correa, Adolfo | Czajkowski, Jacek | Dehghan, Abbas | Ehret, Georg B. | Eiriksdottir, Gudny | Escher, Stefan A. | Farmaki, Aliki-Eleni | Frånberg, Mattias | Gambaro, Giovanni | Giulianini, Franco | III, William A. Goddard | Goel, Anuj | Gottesman, Omri | Grove, Megan L. | Gustafsson, Stefan | Hai, Yang | Hallmans, Göran | Heo, Jiyoung | Hoffmann, Per | Ikram, Mohammad K. | Jensen, Richard A. | Jørgensen, Marit E. | Jørgensen, Torben | Karaleftheri, Maria | Khor, Chiea C. | Kirkpatrick, Andrea | Kraja, Aldi T. | Kuusisto, Johanna | Lange, Ethan M. | Lee, I.T. | Lee, Wen-Jane | Leong, Aaron | Liao, Jiemin | Liu, Chunyu | Liu, Yongmei | Lindgren, Cecilia M. | Linneberg, Allan | Malerba, Giovanni | Mamakou, Vasiliki | Marouli, Eirini | Maruthur, Nisa M. | Matchan, Angela | McKean, Roberta | McLeod, Olga | Metcalf, Ginger A. | Mohlke, Karen L. | Muzny, Donna M. | Ntalla, Ioanna | Palmer, Nicholette D. | Pasko, Dorota | Peter, Andreas | Rayner, Nigel W. | Renström, Frida | Rice, Ken | Sala, Cinzia F. | Sennblad, Bengt | Serafetinidis, Ioannis | Smith, Jennifer A. | Soranzo, Nicole | Speliotes, Elizabeth K. | Stahl, Eli A. | Stirrups, Kathleen | Tentolouris, Nikos | Thanopoulou, Anastasia | Torres, Mina | Traglia, Michela | Tsafantakis, Emmanouil | Javad, Sundas | Yanek, Lisa R. | Zengini, Eleni | Becker, Diane M. | Bis, Joshua C. | Brown, James B. | Cupples, L. Adrienne | Hansen, Torben | Ingelsson, Erik | Karter, Andrew J. | Lorenzo, Carlos | Mathias, Rasika A. | Norris, Jill M. | Peloso, Gina M. | Sheu, Wayne H.-H. | Toniolo, Daniela | Vaidya, Dhananjay | Varma, Rohit | Wagenknecht, Lynne E. | Boeing, Heiner | Bottinger, Erwin P. | Dedoussis, George | Deloukas, Panos | Ferrannini, Ele | Franco, Oscar H. | Franks, Paul W. | Gibbs, Richard A. | Gudnason, Vilmundur | Hamsten, Anders | Harris, Tamara B. | Hattersley, Andrew T. | Hayward, Caroline | Hofman, Albert | Jansson, Jan-Håkan | Langenberg, Claudia | Launer, Lenore J. | Levy, Daniel | Oostra, Ben A. | O'Donnell, Christopher J. | O'Rahilly, Stephen | Padmanabhan, Sandosh | Pankow, James S. | Polasek, Ozren | Province, Michael A. | Rich, Stephen S. | Ridker, Paul M | Rudan, Igor | Schulze, Matthias B. | Smith, Blair H. | Uitterlinden, André G. | Walker, Mark | Watkins, Hugh | Wong, Tien Y. | Zeggini, Eleftheria | Scotland, Generation | Laakso, Markku | Borecki, Ingrid B. | Chasman, Daniel I. | Pedersen, Oluf | Psaty, Bruce M. | Tai, E. Shyong | van Duijn, Cornelia M. | Wareham, Nicholas J. | Waterworth, Dawn M. | Boerwinkle, Eric | Kao, WH Linda | Florez, Jose C. | Loos, Ruth J.F. | Wilson, James G. | Frayling, Timothy M. | Siscovick, David S. | Dupuis, Josée | Rotter, Jerome I. | Meigs, James B. | Scott, Robert A. | Goodarzi, Mark O.
Nature communications  2015;6:5897.
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol L−1, p=3.4×10−12), T2D risk (OR[95%CI]=0.86[0.76-0.96], p=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose−1, p=0.048), but higher 2-h glucose (β=0.16±0.05 mmol L−1, p=4.3×10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8×10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol L−1, p=1.3×10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
doi:10.1038/ncomms6897
PMCID: PMC4311266  PMID: 25631608
10.  Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity 
Diabetes  2014;63(6):2158-2171.
Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
doi:10.2337/db13-0949
PMCID: PMC4030103  PMID: 24296717
11.  The Type 2 Diabetes Risk Allele of TMEM154-rs6813195 Associates with Decreased Beta Cell Function in a Study of 6,486 Danes 
PLoS ONE  2015;10(3):e0120890.
Objectives
A trans-ethnic meta-analysis of type 2 diabetes genome-wide association studies has identified seven novel susceptibility variants in or near TMEM154, SSR1/RREB1, FAF1, POU5F1/TCF19, LPP, ARL15 and ABCB9/MPHOSPH9. The aim of our study was to investigate associations between these novel risk variants and type 2 diabetes and pre-diabetic traits in a Danish population-based study with measurements of plasma glucose and serum insulin after an oral glucose tolerance test in order to elaborate on the physiological impact of the variants.
Methods
Case-control analyses were performed in up to 5,777 patients with type 2 diabetes and 7,956 individuals with normal fasting glucose levels. Quantitative trait analyses were performed in up to 5,744 Inter99 participants naïve to glucose-lowering medication. Significant associations between TMEM154-rs6813195 and the beta cell measures insulinogenic index and disposition index and between FAF1-rs17106184 and 2-hour serum insulin levels were selected for further investigation in additional Danish studies and results were combined in meta-analyses including up to 6,486 Danes.
Results
We confirmed associations with type 2 diabetes for five of the seven SNPs (TMEM154-rs6813195, FAF1-rs17106184, POU5F1/TCF19-rs3130501, ARL15-rs702634 and ABCB9/MPHOSPH9-rs4275659). The type 2 diabetes risk C-allele of TMEM154-rs6813195 associated with decreased disposition index (n=5,181, β=-0.042, p=0.012) and insulinogenic index (n=5,181, β=-0.032, p=0.043) in Inter99 and these associations remained significant in meta-analyses including four additional Danish studies (disposition index n=6,486, β=-0.042, p=0.0044; and insulinogenic index n=6,486, β=-0.037, p=0.0094). The type 2 diabetes risk G-allele of FAF1-rs17106184 associated with increased levels of 2-hour serum insulin (n=5,547, β=0.055, p=0.017) in Inter99 and also when combining effects with three additional Danish studies (n=6,260, β=0.062, p=0.0040).
Conclusion
Studies of type 2 diabetes intermediary traits suggest the diabetogenic impact of the C-allele of TMEM154-rs6813195 is mediated through reduced beta cell function. The impact of the diabetes risk G-allele of FAF1-rs17106184 on increased 2-hour insulin levels is however unexplained.
doi:10.1371/journal.pone.0120890
PMCID: PMC4370672  PMID: 25799151
12.  Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility 
Wessel, Jennifer | Chu, Audrey Y | Willems, Sara M | Wang, Shuai | Yaghootkar, Hanieh | Brody, Jennifer A | Dauriz, Marco | Hivert, Marie-France | Raghavan, Sridharan | Lipovich, Leonard | Hidalgo, Bertha | Fox, Keolu | Huffman, Jennifer E | An, Ping | Lu, Yingchang | Rasmussen-Torvik, Laura J | Grarup, Niels | Ehm, Margaret G | Li, Li | Baldridge, Abigail S | Stančáková, Alena | Abrol, Ravinder | Besse, Céline | Boland, Anne | Bork-Jensen, Jette | Fornage, Myriam | Freitag, Daniel F | Garcia, Melissa E | Guo, Xiuqing | Hara, Kazuo | Isaacs, Aaron | Jakobsdottir, Johanna | Lange, Leslie A | Layton, Jill C | Li, Man | Hua Zhao, Jing | Meidtner, Karina | Morrison, Alanna C | Nalls, Mike A | Peters, Marjolein J | Sabater-Lleal, Maria | Schurmann, Claudia | Silveira, Angela | Smith, Albert V | Southam, Lorraine | Stoiber, Marcus H | Strawbridge, Rona J | Taylor, Kent D | Varga, Tibor V | Allin, Kristine H | Amin, Najaf | Aponte, Jennifer L | Aung, Tin | Barbieri, Caterina | Bihlmeyer, Nathan A | Boehnke, Michael | Bombieri, Cristina | Bowden, Donald W | Burns, Sean M | Chen, Yuning | Chen, Yii-DerI | Cheng, Ching-Yu | Correa, Adolfo | Czajkowski, Jacek | Dehghan, Abbas | Ehret, Georg B | Eiriksdottir, Gudny | Escher, Stefan A | Farmaki, Aliki-Eleni | Frånberg, Mattias | Gambaro, Giovanni | Giulianini, Franco | Goddard, William A | Goel, Anuj | Gottesman, Omri | Grove, Megan L | Gustafsson, Stefan | Hai, Yang | Hallmans, Göran | Heo, Jiyoung | Hoffmann, Per | Ikram, Mohammad K | Jensen, Richard A | Jørgensen, Marit E | Jørgensen, Torben | Karaleftheri, Maria | Khor, Chiea C | Kirkpatrick, Andrea | Kraja, Aldi T | Kuusisto, Johanna | Lange, Ethan M | Lee, I T | Lee, Wen-Jane | Leong, Aaron | Liao, Jiemin | Liu, Chunyu | Liu, Yongmei | Lindgren, Cecilia M | Linneberg, Allan | Malerba, Giovanni | Mamakou, Vasiliki | Marouli, Eirini | Maruthur, Nisa M | Matchan, Angela | McKean-Cowdin, Roberta | McLeod, Olga | Metcalf, Ginger A | Mohlke, Karen L | Muzny, Donna M | Ntalla, Ioanna | Palmer, Nicholette D | Pasko, Dorota | Peter, Andreas | Rayner, Nigel W | Renström, Frida | Rice, Ken | Sala, Cinzia F | Sennblad, Bengt | Serafetinidis, Ioannis | Smith, Jennifer A | Soranzo, Nicole | Speliotes, Elizabeth K | Stahl, Eli A | Stirrups, Kathleen | Tentolouris, Nikos | Thanopoulou, Anastasia | Torres, Mina | Traglia, Michela | Tsafantakis, Emmanouil | Javad, Sundas | Yanek, Lisa R | Zengini, Eleni | Becker, Diane M | Bis, Joshua C | Brown, James B | Adrienne Cupples, L | Hansen, Torben | Ingelsson, Erik | Karter, Andrew J | Lorenzo, Carlos | Mathias, Rasika A | Norris, Jill M | Peloso, Gina M | Sheu, Wayne H.-H. | Toniolo, Daniela | Vaidya, Dhananjay | Varma, Rohit | Wagenknecht, Lynne E | Boeing, Heiner | Bottinger, Erwin P | Dedoussis, George | Deloukas, Panos | Ferrannini, Ele | Franco, Oscar H | Franks, Paul W | Gibbs, Richard A | Gudnason, Vilmundur | Hamsten, Anders | Harris, Tamara B | Hattersley, Andrew T | Hayward, Caroline | Hofman, Albert | Jansson, Jan-Håkan | Langenberg, Claudia | Launer, Lenore J | Levy, Daniel | Oostra, Ben A | O'Donnell, Christopher J | O'Rahilly, Stephen | Padmanabhan, Sandosh | Pankow, James S | Polasek, Ozren | Province, Michael A | Rich, Stephen S | Ridker, Paul M | Rudan, Igor | Schulze, Matthias B | Smith, Blair H | Uitterlinden, André G | Walker, Mark | Watkins, Hugh | Wong, Tien Y | Zeggini, Eleftheria | Laakso, Markku | Borecki, Ingrid B | Chasman, Daniel I | Pedersen, Oluf | Psaty, Bruce M | Shyong Tai, E | van Duijn, Cornelia M | Wareham, Nicholas J | Waterworth, Dawn M | Boerwinkle, Eric | Linda Kao, W H | Florez, Jose C | Loos, Ruth J.F. | Wilson, James G | Frayling, Timothy M | Siscovick, David S | Dupuis, Josée | Rotter, Jerome I | Meigs, James B | Scott, Robert A | Goodarzi, Mark O
Nature Communications  2015;6:5897.
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=−0.09±0.01 mmol l−1, P=3.4 × 10−12), T2D risk (OR[95%CI]=0.86[0.76–0.96], P=0.010), early insulin secretion (β=−0.07±0.035 pmolinsulin mmolglucose−1, P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l−1, P=4.3 × 10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l−1, P=1.3 × 10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
Both rare and common variants contribute to the aetiology of complex traits such as type 2 diabetes (T2D). Here, the authors examine the effect of coding variation on glycaemic traits and T2D, and identify low-frequency variation in GLP1R significantly associated with these traits.
doi:10.1038/ncomms6897
PMCID: PMC4311266  PMID: 25631608
13.  Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus 
Mahajan, Anubha | Sim, Xueling | Ng, Hui Jin | Manning, Alisa | Rivas, Manuel A. | Highland, Heather M. | Locke, Adam E. | Grarup, Niels | Im, Hae Kyung | Cingolani, Pablo | Flannick, Jason | Fontanillas, Pierre | Fuchsberger, Christian | Gaulton, Kyle J. | Teslovich, Tanya M. | Rayner, N. William | Robertson, Neil R. | Beer, Nicola L. | Rundle, Jana K. | Bork-Jensen, Jette | Ladenvall, Claes | Blancher, Christine | Buck, David | Buck, Gemma | Burtt, Noël P. | Gabriel, Stacey | Gjesing, Anette P. | Groves, Christopher J. | Hollensted, Mette | Huyghe, Jeroen R. | Jackson, Anne U. | Jun, Goo | Justesen, Johanne Marie | Mangino, Massimo | Murphy, Jacquelyn | Neville, Matt | Onofrio, Robert | Small, Kerrin S. | Stringham, Heather M. | Syvänen, Ann-Christine | Trakalo, Joseph | Abecasis, Goncalo | Bell, Graeme I. | Blangero, John | Cox, Nancy J. | Duggirala, Ravindranath | Hanis, Craig L. | Seielstad, Mark | Wilson, James G. | Christensen, Cramer | Brandslund, Ivan | Rauramaa, Rainer | Surdulescu, Gabriela L. | Doney, Alex S. F. | Lannfelt, Lars | Linneberg, Allan | Isomaa, Bo | Tuomi, Tiinamaija | Jørgensen, Marit E. | Jørgensen, Torben | Kuusisto, Johanna | Uusitupa, Matti | Salomaa, Veikko | Spector, Timothy D. | Morris, Andrew D. | Palmer, Colin N. A. | Collins, Francis S. | Mohlke, Karen L. | Bergman, Richard N. | Ingelsson, Erik | Lind, Lars | Tuomilehto, Jaakko | Hansen, Torben | Watanabe, Richard M. | Prokopenko, Inga | Dupuis, Josee | Karpe, Fredrik | Groop, Leif | Laakso, Markku | Pedersen, Oluf | Florez, Jose C. | Morris, Andrew P. | Altshuler, David | Meigs, James B. | Boehnke, Michael | McCarthy, Mark I. | Lindgren, Cecilia M. | Gloyn, Anna L.
PLoS Genetics  2015;11(1):e1004876.
Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
Author Summary
Understanding how FI and FG levels are regulated is important because their derangement is a feature of T2D. Despite recent success from GWAS in identifying regions of the genome influencing glycemic traits, collectively these loci explain only a small proportion of trait variance. Unlocking the biological mechanisms driving these associations has been challenging because the vast majority of variants map to non-coding sequence, and the genes through which they exert their impact are largely unknown. In the current study, we sought to increase our understanding of the physiological pathways influencing both traits using exome-array genotyping in up to 33,231 non-diabetic individuals to identify coding variants and consequently genes associated with either FG or FI levels. We identified novel association signals for both traits including the receptor for GLP-1 agonists which are a widely used therapy for T2D. Furthermore, we identified coding variants at several GWAS loci which point to the genes underlying these association signals. Importantly, we found that multiple coding variants in G6PC2 result in a loss of protein function and lower fasting glucose levels.
doi:10.1371/journal.pgen.1004876
PMCID: PMC4307976  PMID: 25625282
14.  Blood Pressure Levels in Male Carriers of Arg82Cys in CD300LG 
PLoS ONE  2014;9(10):e109646.
The genetics of hypertension has been scrutinized in large-scale genome-wide association studies (GWAS) with a large number of common genetic variants identified, each exerting subtle effects on disease susceptibility. An amino acid polymorphism, p.Arg82Cys, in CD300LG was recently found to be associated with fasting HDL-cholesterol and triglyceride levels. The polymorphism has not been detected in hypertension GWAS potentially due to its low frequency, but CD300LG has been linked to blood pressure as CD300LG knockout mice have changes in blood pressure. Twenty-four-hour ambulatory blood pressure was obtained in human CD300LG CT-carriers to follow up on these observations.
Methods
Twenty healthy male CD300LG rs72836561 CT-carriers matched for age and BMI with 20 healthy male CC-carriers. Office blood pressure, 24-hour ambulatory blood pressure, carotid intima-media thickness (CIMT), and fasting blood samples were evaluated. The clinical study was combined with a genetic-epidemiological study to replicate the association between blood pressure and CD300LG Arg82Cys in 2,637 men and 3,249 women.
Results
CT-carriers had a higher 24-hour ambulatory systolic blood pressure (122 mmHg versus 115; p = 0.01) and diastolic blood pressure (77 mmHg versus 72; p<0.01) compared with CC-carriers. There were no differences in CIMT between the two groups. Metalloproteinase-9 level was higher in CT-carriers than in CC-carriers (P<0.01). However, no association between office blood pressure and CD300LG genotype was detected in the genetic-epidemiological study.
Conclusions
Although 24-hour blood pressure, measured with a sensitive method, in a small sample of CD300LG rs72836561 CT-carriers was higher than in CC-carriers, this did not translate into significant differences in office blood pressure in a larger cohort. This discrepancy which may reflect differences in methodological approach, underlines the importance of performing replication studies in a larger clinical context, but a formal rejection of a relation between blood pressure and CD300LG requires measurement of 24-hour ambulatory blood pressure in a larger cohort.
doi:10.1371/journal.pone.0109646
PMCID: PMC4196928  PMID: 25314291
15.  Genome-wide association study identifies a sequence variant within the DAB2IP gene conferring susceptibility to abdominal aortic aneurysm 
Gretarsdottir, Solveig | Baas, Annette F | Thorleifsson, Gudmar | Holm, Hilma | den Heijer, Martin | de Vries, Jean-Paul P M | Kranendonk, Steef E | Zeebregts, Clark J A M | van Sterkenburg, Steven M | Geelkerken, Robert H | van Rij, Andre M | Williams, Michael J A | Boll, Albert P M | Kostic, Jelena P | Jonasdottir, Adalbjorg | Jonasdottir, Aslaug | Walters, G Bragi | Masson, Gisli | Sulem, Patrick | Saemundsdottir, Jona | Mouy, Magali | Magnusson, Kristinn P | Tromp, Gerard | Elmore, James R | Sakalihasan, Natzi | Limet, Raymond | Defraigne, Jean-Olivier | Ferrell, Robert E | Ronkainen, Antti | Ruigrok, Ynte M | Wijmenga, Cisca | Grobbee, Diederick E | Shah, Svati H | Granger, Christopher B | Quyyumi, Arshed A | Vaccarino, Viola | Patel, Riyaz S | Zafari, A Maziar | Levey, Allan I | Austin, Harland | Girelli, Domenico | Pignatti, Pier Franco | Olivieri, Oliviero | Martinelli, Nicola | Malerba, Giovanni | Trabetti, Elisabetta | Becker, Lewis C | Becker, Diane M | Reilly, Muredach P | Rader, Daniel J | Mueller, Thomas | Dieplinger, Benjamin | Haltmayer, Meinhard | Urbonavicius, Sigitas | Lindblad, Bengt | Gottsäter, Anders | Gaetani, Eleonora | Pola, Roberto | Wells, Philip | Rodger, Marc | Forgie, Melissa | Langlois, Nicole | Corral, Javier | Vicente, Vicente | Fontcuberta, Jordi | España, Francisco | Grarup, Niels | Jørgensen, Torben | Witte, Daniel R | Hansen, Torben | Pedersen, Oluf | Aben, Katja K | de Graaf, Jacqueline | Holewijn, Suzanne | Folkersen, Lasse | Franco-Cereceda, Anders | Eriksson, Per | Collier, David A | Stefansson, Hreinn | Steinthorsdottir, Valgerdur | Rafnar, Thorunn | Valdimarsson, Einar M | Magnadottir, Hulda B | Sveinbjornsdottir, Sigurlaug | Olafsson, Isleifur | Magnusson, Magnus Karl | Palmason, Robert | Haraldsdottir, Vilhelmina | Andersen, Karl | Onundarson, Pall T | Thorgeirsson, Gudmundur | Kiemeney, Lambertus A | Powell, Janet T | Carey, David J | Kuivaniemi, Helena | Lindholt, Jes S | Jones, Gregory T | Kong, Augustine | Blankensteijn, Jan D | Matthiasson, Stefan E | Thorsteinsdottir, Unnur | Stefansson, Kari
Nature genetics  2010;42(8):692-697.
We performed a genome-wide association study on 1,292 individuals with abdominal aortic aneurysms (AAAs) and 30,503 controls from Iceland and The Netherlands, with a follow-up of top markers in up to 3,267 individuals with AAAs and 7,451 controls. The A allele of rs7025486 on 9q33 was found to associate with AAA, with an odds ratio (OR) of 1.21 and P = 4.6 × 10−10. In tests for association with other vascular diseases, we found that rs7025486[A] is associated with early onset myocardial infarction (OR = 1.18, P = 3.1 × 10−5), peripheral arterial disease (OR = 1.14, P = 3.9 × 10−5) and pulmonary embolism (OR = 1.20, P = 0.00030), but not with intracranial aneurysm or ischemic stroke. No association was observed between rs7025486[A] and common risk factors for arterial and venous diseases—that is, smoking, lipid levels, obesity, type 2 diabetes and hypertension. Rs7025486 is located within DAB2IP, which encodes an inhibitor of cell growth and survival.
doi:10.1038/ng.622
PMCID: PMC4157066  PMID: 20622881
16.  Variation and association to diabetes in 2000 full mtDNA sequences mined from an exome study in a Danish population 
European Journal of Human Genetics  2014;22(8):1040-1045.
In this paper, we mine full mtDNA sequences from an exome capture data set of 2000 Danes, showing that it is possible to get high-quality full-genome sequences of the mitochondrion from this resource. The sample includes 1000 individuals with type 2 diabetes and 1000 controls. We characterise the variation found in the mtDNA sequence in Danes and relate the variation to diabetes risk as well as to several blood phenotypes of the controls but find no significant associations. We report 2025 polymorphisms, of which 393 have not been reported previously. These 393 mutations are both very rare and estimated to be caused by very recent mutations but individuals with type 2 diabetes do not possess more of these variants. Population genetics analysis using Bayesian skyline plot shows a recent history of rapid population growth in the Danish population in accordance with the fact that >40% of variable sites are observed as singletons.
doi:10.1038/ejhg.2013.282
PMCID: PMC4350597  PMID: 24448545
diabetes; mtDNA; population history
17.  Loss-of-function mutations in SLC30A8 protect against type 2 diabetes 
Flannick, Jason | Thorleifsson, Gudmar | Beer, Nicola L. | Jacobs, Suzanne B. R. | Grarup, Niels | Burtt, Noël P. | Mahajan, Anubha | Fuchsberger, Christian | Atzmon, Gil | Benediktsson, Rafn | Blangero, John | Bowden, Don W. | Brandslund, Ivan | Brosnan, Julia | Burslem, Frank | Chambers, John | Cho, Yoon Shin | Christensen, Cramer | Douglas, Desirée A. | Duggirala, Ravindranath | Dymek, Zachary | Farjoun, Yossi | Fennell, Timothy | Fontanillas, Pierre | Forsén, Tom | Gabriel, Stacey | Glaser, Benjamin | Gudbjartsson, Daniel F. | Hanis, Craig | Hansen, Torben | Hreidarsson, Astradur B. | Hveem, Kristian | Ingelsson, Erik | Isomaa, Bo | Johansson, Stefan | Jørgensen, Torben | Jørgensen, Marit Eika | Kathiresan, Sekar | Kong, Augustine | Kooner, Jaspal | Kravic, Jasmina | Laakso, Markku | Lee, Jong-Young | Lind, Lars | Lindgren, Cecilia M | Linneberg, Allan | Masson, Gisli | Meitinger, Thomas | Mohlke, Karen L | Molven, Anders | Morris, Andrew P. | Potluri, Shobha | Rauramaa, Rainer | Ribel-Madsen, Rasmus | Richard, Ann-Marie | Rolph, Tim | Salomaa, Veikko | Segrè, Ayellet V. | Skärstrand, Hanna | Steinthorsdottir, Valgerdur | Stringham, Heather M. | Sulem, Patrick | Tai, E Shyong | Teo, Yik Ying | Teslovich, Tanya | Thorsteinsdottir, Unnur | Trimmer, Jeff K. | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Vaziri-Sani, Fariba | Voight, Benjamin F. | Wilson, James G. | Boehnke, Michael | McCarthy, Mark I. | Njølstad, Pål R. | Pedersen, Oluf | Groop, Leif | Cox, David R. | Stefansson, Kari | Altshuler, David
Nature genetics  2014;46(4):357-363.
Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets1,2,3, yet none are described for type 2 diabetes (T2D). Through sequencing or genotyping ~150,000 individuals across five ethnicities, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8)4 and harbors a common variant (p.Trp325Arg) associated with T2D risk, glucose, and proinsulin levels5–7. Collectively, protein-truncating variant carriers had 65% reduced T2D risk (p=1.7×10−6), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34SerfsX50) demonstrated reduced glucose levels (−0.17 s.d., p=4.6×10−4). The two most common protein-truncating variants (p.Arg138X and p.Lys34SerfsX50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested reduced zinc transport increases T2D risk8,9, yet phenotypic heterogeneity was observed in rodent Slc30a8 knockouts10–15. Contrastingly, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, proposing ZnT8 inhibition as a therapeutic strategy in T2D prevention.
doi:10.1038/ng.2915
PMCID: PMC4051628  PMID: 24584071
18.  Studies of association of AGPAT6 variants with type 2 diabetes and related metabolic phenotypes in 12,068 Danes 
BMC Medical Genetics  2013;14:113.
Background
Type 2 diabetes, obesity and insulin resistance are characterized by hypertriglyceridemia and ectopic accumulation of lipids in liver and skeletal muscle. AGPAT6 encodes a novel glycerol-3 phosphate acyltransferase, GPAT4, which catalyzes the first step in the de novo triglyceride synthesis. AGPAT6-deficient mice show lower weight and resistance to diet- and genetically induced obesity. Here, we examined whether common or low-frequency variants in AGPAT6 associate with type 2 diabetes or related metabolic traits in a Danish population.
Methods
Eleven variants selected by a candidate gene approach capturing the common and low-frequency variation of AGPAT6 were genotyped in 12,068 Danes from four study populations of middle-aged individuals. The case–control study involved 4,638 type 2 diabetic and 5,934 glucose-tolerant individuals, while studies of quantitative metabolic traits were performed in 5,645 non-diabetic participants of the Inter99 Study.
Results
None of the eleven AGPAT6 variants were robustly associated with type 2 diabetes in the Danish case–control study. Moreover, none of the AGPAT6 variants showed association with measures of obesity (waist circumference and BMI), serum lipid concentrations, fasting or 2-h post-glucose load levels of plasma glucose and serum insulin, or estimated indices of insulin secretion or insulin sensitivity.
Conclusions
Common and low-frequency variants in AGPAT6 do not significantly associate with type 2 diabetes susceptibility, or influence related phenotypic traits such as obesity, dyslipidemia or indices of insulin sensitivity or insulin secretion in the population studied.
doi:10.1186/1471-2350-14-113
PMCID: PMC4231429  PMID: 24156295
Type 2 diabetes; Genetics; Insulin resistance; Human; Lipid droplets; AGPAT6; GPAT4
19.  Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry 
PLoS Genetics  2013;9(7):e1003607.
Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
Author Summary
We undertook analyses in 111,421 adults of European descent to examine whether physical activity diminishes the genetic risk of obesity predisposed by 12 single nucleotide polymorphisms, as previously reported in a study of 20,000 UK adults (Li et al, PLoS Med. 2010). Although the study by Li et al is widely cited, the original report has not been replicated to our knowledge. Therefore, we sought to confirm or refute the original study's findings in a combined analysis of 111,421 adults. Our analyses yielded a statistically significant interaction effect (Pinteraction = 0.015), confirming the original study's results; we also identified an interaction between the FTO locus and physical activity (Pinteraction = 0.003), verifying previous analyses (Kilpelainen et al, PLoS Med., 2010), and we detected a novel interaction between the SEC16B locus and physical activity (Pinteraction = 0.025). We also examined the power constraints of interaction analyses, thereby demonstrating that sources of within- and between-study heterogeneity and the manner in which data are treated can inhibit the detection of interaction effects in meta-analyses that combine many cohorts with varying characteristics. This suggests that combining many small studies that have measured environmental exposures differently may be relatively inefficient for the detection of gene × environment interactions.
doi:10.1371/journal.pgen.1003607
PMCID: PMC3723486  PMID: 23935507
20.  Genetic Architecture of Vitamin B12 and Folate Levels Uncovered Applying Deeply Sequenced Large Datasets 
PLoS Genetics  2013;9(6):e1003530.
Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B12 and folate measurements, respectively. We found six novel loci associating with serum B12 (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B12 and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimer's disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations.
Author Summary
Genome-wide association studies have in recent years revealed a wealth of common variants associated with common diseases and phenotypes. We took advantage of the advances in sequencing technologies to study the association of low frequency and rare variants in conjunction with common variants with serum levels of vitamin B12 (B12) and folate in Icelanders and Danes. We found 18 independent signals in 13 loci associated with serum B12 or folate levels. Interestingly, 13 of the 18 identified variants are coding and 11 of the 13 target genes have known functions related to B12 and folate pathways. These data indicate that the target genes at all of the loci have been identified. Epidemiological studies have shown a relationship between serum B12 and folate levels and the risk of cardiovascular diseases, cancers, and Alzheimer's disease. We investigated association between the identified variants and these diseases but did not find consistent association.
doi:10.1371/journal.pgen.1003530
PMCID: PMC3674994  PMID: 23754956
22.  No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels 
Scott, Robert A. | Chu, Audrey Y. | Grarup, Niels | Manning, Alisa K. | Hivert, Marie-France | Shungin, Dmitry | Tönjes, Anke | Yesupriya, Ajay | Barnes, Daniel | Bouatia-Naji, Nabila | Glazer, Nicole L. | Jackson, Anne U. | Kutalik, Zoltán | Lagou, Vasiliki | Marek, Diana | Rasmussen-Torvik, Laura J. | Stringham, Heather M. | Tanaka, Toshiko | Aadahl, Mette | Arking, Dan E. | Bergmann, Sven | Boerwinkle, Eric | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brunner, Eric | Bumpstead, Suzannah J. | Brage, Soren | Carlson, Olga D. | Chen, Han | Chen, Yii-Der Ida | Chines, Peter S. | Collins, Francis S. | Couper, David J. | Dennison, Elaine M. | Dowling, Nicole F. | Egan, Josephine S. | Ekelund, Ulf | Erdos, Michael R. | Forouhi, Nita G. | Fox, Caroline S. | Goodarzi, Mark O. | Grässler, Jürgen | Gustafsson, Stefan | Hallmans, Göran | Hansen, Torben | Hingorani, Aroon | Holloway, John W. | Hu, Frank B. | Isomaa, Bo | Jameson, Karen A. | Johansson, Ingegerd | Jonsson, Anna | Jørgensen, Torben | Kivimaki, Mika | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Laakso, Markku | Lecoeur, Cécile | Lévy-Marchal, Claire | Li, Guo | Loos, Ruth J.F. | Lyssenko, Valeri | Marmot, Michael | Marques-Vidal, Pedro | Morken, Mario A. | Müller, Gabriele | North, Kari E. | Pankow, James S. | Payne, Felicity | Prokopenko, Inga | Psaty, Bruce M. | Renström, Frida | Rice, Ken | Rotter, Jerome I. | Rybin, Denis | Sandholt, Camilla H. | Sayer, Avan A. | Shrader, Peter | Schwarz, Peter E.H. | Siscovick, David S. | Stančáková, Alena | Stumvoll, Michael | Teslovich, Tanya M. | Waeber, Gérard | Williams, Gordon H. | Witte, Daniel R. | Wood, Andrew R. | Xie, Weijia | Boehnke, Michael | Cooper, Cyrus | Ferrucci, Luigi | Froguel, Philippe | Groop, Leif | Kao, W.H. Linda | Vollenweider, Peter | Walker, Mark | Watanabe, Richard M. | Pedersen, Oluf | Meigs, James B. | Ingelsson, Erik | Barroso, Inês | Florez, Jose C. | Franks, Paul W. | Dupuis, Josée | Wareham, Nicholas J. | Langenberg, Claudia
Diabetes  2012;61(5):1291-1296.
Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
doi:10.2337/db11-0973
PMCID: PMC3331745  PMID: 22415877
23.  What Is the Contribution of Two Genetic Variants Regulating VEGF Levels to Type 2 Diabetes Risk and to Microvascular Complications? 
PLoS ONE  2013;8(2):e55921.
Vascular endothelial growth factor (VEGF) is a key chemokine involved in tissue growth and organ repair processes, particularly angiogenesis. Elevated circulating VEGF levels are believed to play a role in type 2 diabetes (T2D) microvascular complications, especially diabetic retinopathy. Recently, a genome-wide association study identified two common single nucleotide polymorphisms (SNPs; rs6921438 and rs10738760) explaining nearly half of the variance in circulating VEGF levels. Considering the putative contribution of VEGF to T2D and its complications, we aimed to assess the effect of these VEGF-related SNPs on the risk of T2D, nephropathy and retinopathy, as well as on variation in related traits.
SNPs were genotyped in several case-control studies: French and Danish T2D studies (Ncases = 6,920-Ncontrols = 3,875 and Ncases = 3,561-Ncontrols = 2,623; respectively), two French studies one for diabetic nephropathy (Ncases = 1,242-Ncontrols = 860) and the other for diabetic retinopathy (Ncases = 1,336-Ncontrols = 1,231). The effects of each SNP on quantitative traits were analyzed in a French general population-based cohort (N = 4,760) and two French T2D studies (N = 3,480). SNP associations were assessed using logistic or linear regressions.
In the French population, we found an association between the G-allele of rs6921438, shown to increase circulating VEGF levels, and increased T2D risk (OR = 1.15; P = 3.7×10−5). Furthermore, the same allele was associated with higher glycated hemoglobin levels (β = 0.02%; P = 9.2×10−3). However, these findings were not confirmed in the Danes. Conversely, the SNP rs10738760 was not associated with T2D in the French or Danish populations. Despite having adequate statistical power, we did not find any significant effects of rs6921438 or rs10738760 on diabetic microvascular complications or the variation in related traits in T2D patients.
In spite of their impact on the variance in circulating VEGF, we did not find any association between SNPs rs6921438 and rs10738760, and the risk of T2D, diabetic nephropathy or retinopathy. The link between VEGF and T2D and its complications might be indirect and more complex than expected.
doi:10.1371/journal.pone.0055921
PMCID: PMC3566098  PMID: 23405237
24.  Genetic Variant SCL2A2 Is Associated with Risk of Cardiovascular Disease – Assessing the Individual and Cumulative Effect of 46 Type 2 Diabetes Related Genetic Variants 
PLoS ONE  2012;7(11):e50418.
Aim
To assess the individual and combined effect of 46 type 2 diabetes related risk alleles on incidence of a composite CVD endpoint.
Methods
Data from the first Danish MONICA study (N = 3523) and the Inter99 study (N = 6049) was used. Using Cox proportional hazard regression the individual effect of each risk allele on incident CVD was analyzed. Risk was presented as hazard ratios (HR) per risk allele.
Results
During 80,859 person years 1441 incident cases of CVD (fatal and non-fatal) occurred in the MONICA study. In Inter99 942 incident cases were observed during 61,239 person years.
In the Danish MONICA study four gene variants were significantly associated with incident CVD independently of known diabetes status at baseline; SLC2A2 rs11920090 (HR 1.147, 95% CI 1.027–1.283 , P = 0.0154), C2CD4A rs7172432 (1.112, 1.027–1.205 , P = 0.0089), GCKR rs780094 (1.094, 1.007–1.188 , P = 0.0335) and C2CD4B rs11071657 (1.092, 1.007–1.183 , P = 0.0323). The genetic score was significantly associated with increased risk of CVD (1.025, 1.010–1.041, P = 0.0016). In Inter99 two gene variants were associated with risk of CVD independently of diabetes; SLC2A2 (HR 1.180, 95% CI 1.038–1.341 P = 0.0116) and FTO (0.909, 0.827–0.998, P = 0.0463). Analysing the two populations together we found SLC2A2 rs11920090 (HR 1.164, 95% CI 1.070–1.267, P = 0.0004) meeting the Bonferroni corrected threshold for significance. GCKR rs780094 (1.076, 1.010–1.146, P = 0.0229), C2CD4B rs11071657 (1.067, 1.003–1.135, P = 0.0385) and NOTCH2 rs10923931 (1.104 (1.001 ; 1.217 , P = 0.0481) were found associated with CVD without meeting the corrected threshold. The genetic score was significantly associated with increased risk of CVD (1.018, 1.006–1.031, P = 0.0043).
Conclusions
This study showed that out of the 46 genetic variants examined only the minor risk allele of SLC2A2 rs11920090 was significantly (P = 0.0005) associated with a composite endpoint of incident CVD below the threshold for statistical significance corrected for multiple testing. This potential pathway needs further exploration.
doi:10.1371/journal.pone.0050418
PMCID: PMC3503928  PMID: 23185617

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