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author:("Pedersen, olf")
1.  Metformin versus placebo in combination with insulin analogues in patients with type 2 diabetes mellitus—the randomised, blinded Copenhagen Insulin and Metformin Therapy (CIMT) trial 
BMJ Open  2016;6(2):e008376.
To assess the effect of metformin versus placebo both in combination with insulin analogue treatment on changes in carotid intima-media thickness (IMT) in patients with type 2 diabetes.
Design and setting
Investigator-initiated, randomised, placebo-controlled trial with a 2×3 factorial design conducted at eight hospitals in Denmark.
Participants and interventions
412 participants with type 2 diabetes (glycated haemoglobin (HbA1c) ≥7.5% (≥58 mmol/mol); body mass index >25 kg/m2) were in addition to open-labelled insulin treatment randomly assigned 1:1 to 18 months blinded metformin (1 g twice daily) versus placebo, aiming at an HbA1c ≤7.0% (≤53 mmol/mol).
The primary outcome was change in the mean carotid IMT (a marker of subclinical cardiovascular disease). HbA1c, insulin dose, weight and hypoglycaemic and serious adverse events were other prespecified outcomes.
Change in the mean carotid IMT did not differ significantly between the groups (between-group difference 0.012 mm (95% CI −0.003 to 0.026), p=0.11). HbA1c was more reduced in the metformin group (between-group difference −0.42% (95% CI −0.62% to −0.23%), p<0.001)), despite the significantly lower insulin dose at end of trial in the metformin group (1.04 IU/kg (95% CI 0.94 to 1.15)) compared with placebo (1.36 IU/kg (95% CI 1.23 to 1.51), p<0.001). The metformin group gained less weight (between-group difference −2.6 kg (95% CI −3.3 to −1.8), p<0.001). The groups did not differ with regard to number of patients with severe or non-severe hypoglycaemic or other serious adverse events, but the metformin group had more non-severe hypoglycaemic episodes (4347 vs 3161, p<0.001).
Metformin in combination with insulin did not reduce carotid IMT despite larger reduction in HbA1c, less weight gain, and smaller insulin dose compared with placebo plus insulin. However, the trial only reached 46% of the planned sample size and lack of power may therefore have affected our results.
Trial registration number
NCT00657943; Results.
PMCID: PMC4771973  PMID: 26916684
2.  Effects of biphasic, basal-bolus or basal insulin analogue treatments on carotid intima-media thickness in patients with type 2 diabetes mellitus: the randomised Copenhagen Insulin and Metformin Therapy (CIMT) trial 
BMJ Open  2016;6(2):e008377.
To assess the effect of 3 insulin analogue regimens on change in carotid intima-media thickness (IMT) in patients with type 2 diabetes.
Design and setting
Investigator-initiated, randomised, placebo-controlled trial with a 2×3 factorial design, conducted at 8 hospitals in Denmark.
Participants and interventions
Participants with type 2 diabetes (glycated haemoglobin (HbA1c)≥7.5% (≥58 mmol/mol), body mass index >25 kg/m2) were, in addition to metformin versus placebo, randomised to 18 months open-label biphasic insulin aspart 1–3 times daily (n=137) versus insulin aspart 3 times daily in combination with insulin detemir once daily (n=138) versus insulin detemir alone once daily (n=137), aiming at HbA1c≤7.0% (≤53 mmol/mol).
Primary outcome was change in mean carotid IMT (a marker of subclinical cardiovascular disease). HbA1c, insulin dose, weight, and hypoglycaemic and serious adverse events were other prespecified outcomes.
Carotid IMT change did not differ between groups (biphasic −0.009 mm (95% CI −0.022 to 0.004), aspart+detemir 0.000 mm (95% CI −0.013 to 0.013), detemir −0.012 mm (95% CI −0.025 to 0.000)). HbA1c was more reduced with biphasic (−1.0% (95% CI −1.2 to −0.8)) compared with the aspart+detemir (−0.4% (95% CI −0.6 to −0.3)) and detemir (−0.3% (95% CI −0.4 to −0.1)) groups (p<0.001). Weight gain was higher in the biphasic (3.3 kg (95% CI 2.7 to 4.0) and aspart+detemir (3.2 kg (95% CI 2.6 to 3.9)) compared with the detemir group (1.9 kg (95% CI 1.3 to 2.6)). Insulin dose was higher with detemir (1.6 IU/kg/day (95% CI 1.4 to 1.8)) compared with biphasic (1.0 IU/kg/day (95% CI 0.9 to 1.1)) and aspart+detemir (1.1 IU/kg/day (95% CI 1.0 to 1.3)) (p<0.001). Number of participants with severe hypoglycaemia and serious adverse events did not differ.
Carotid IMT change did not differ between 3 insulin regimens despite differences in HbA1c, weight gain and insulin doses. The trial only reached 46% of planned sample size and lack of power may therefore have affected our results.
Trial registration number
PMCID: PMC4771974  PMID: 26916685
4.  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 ( provides a first global view of the genetic stability of the glycogenome and should serve as a tool for discovery of novel CDGs.
PMCID: PMC4351397  PMID: 25267602
damaging mutations; glycogenes; nonsynonymous mutations; nsSNV; MAF
5.  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.
PMCID: PMC4740377  PMID: 26833098
6.  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.
PMCID: PMC4740398  PMID: 26833246
7.  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.
PMCID: PMC4738362  PMID: 26818947
8.  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.
PMCID: PMC4719169  PMID: 26390057
9.  Multidisciplinary care of obese children and adolescents for one year reduces ectopic fat content in liver and skeletal muscle 
BMC Pediatrics  2015;15:196.
Ectopic fat deposition in liver and skeletal muscle tissue is related to cardiovascular disease risk and is a common metabolic complication in obese children. We evaluated the hypotheses of ectopic fat in these organs could be diminished following 1 year of multidisciplinary care specialized in childhood obesity, and whether this reduction would associate with changes in other markers of metabolic function.
This observational longitudinal study evaluated 40 overweight children and adolescents enrolled in a multidisciplinary treatment protocol at the Children’s Obesity Clinic, Holbæk, Denmark. The participants were assessed by anthropometry, fasting blood samples (HbA1c, glucose, insulin, lipids, and biochemical variables of liver function), and liver and muscle fat content assessed by magnetic resonance spectroscopy at enrollment and following an average of 12.2 months of care. Univariate linear regression models adjusted for age, sex, treatment duration, baseline degree of obesity, and pubertal developmental stage were used for investigating possible associations.
The standard deviation score (SDS) of baseline median body mass index (BMI) was 2.80 (range: 1.49–3.85) and the median age was 14 years (10–17). At the end of the observational period, the 40 children and adolescents (21 girls) significantly decreased their BMI SDS, liver fat, muscle fat, and visceral adipose tissue volume. The prevalence of hepatic steatosis changed from 28 to 20 % (p = 0.26) and the prevalence of muscular steatosis decreased from 75 to 45 % (p = 0.007).
Changes in liver and muscle fat were independent of changes in BMI SDS, baseline degree of obesity, duration of treatment, age, sex, and pubertal developmental stage.
A 1-year multidisciplinary intervention program in the setting of a childhood obesity outpatient clinic confers a biologically important reduction in liver and muscle fat; metabolic improvements that are independent of the magnitude of concurrent weight loss.
Trial registration registration number: NCT00928473, the Danish Childhood Obesity Biobank. Registered June 25, 2009.
Electronic supplementary material
The online version of this article (doi:10.1186/s12887-015-0513-6) contains supplementary material, which is available to authorized users.
PMCID: PMC4696236  PMID: 26714769
Pediatric Obesity; Magnetic Resonance Spectroscopy; Skeletal Muscle; Non-alcoholic Fatty Liver Disease; Dyslipidemia; Glucose Metabolic Disorders; Child; Adolescent
10.  FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals 
Qi, Qibin | Kilpeläinen, Tuomas O. | Downer, Mary K. | Tanaka, Toshiko | Smith, Caren E. | Sluijs, Ivonne | Sonestedt, Emily | Chu, Audrey Y. | Renström, Frida | Lin, Xiaochen | Ängquist, Lars H. | Huang, Jinyan | Liu, Zhonghua | Li, Yanping | Asif Ali, Muhammad | Xu, Min | Ahluwalia, Tarunveer Singh | Boer, Jolanda M.A. | Chen, Peng | Daimon, Makoto | Eriksson, Johan | Perola, Markus | Friedlander, Yechiel | Gao, Yu-Tang | Heppe, Denise H.M. | Holloway, John W. | Houston, Denise K. | Kanoni, Stavroula | Kim, Yu-Mi | Laaksonen, Maarit A. | Jääskeläinen, Tiina | Lee, Nanette R. | Lehtimäki, Terho | Lemaitre, Rozenn N. | Lu, Wei | Luben, Robert N. | Manichaikul, Ani | Männistö, Satu | Marques-Vidal, Pedro | Monda, Keri L. | Ngwa, Julius S. | Perusse, Louis | van Rooij, Frank J.A. | Xiang, Yong-Bing | Wen, Wanqing | Wojczynski, Mary K | Zhu, Jingwen | Borecki, Ingrid B. | Bouchard, Claude | Cai, Qiuyin | Cooper, Cyrus | Dedoussis, George V. | Deloukas, Panos | Ferrucci, Luigi | Forouhi, Nita G. | Hansen, Torben | Christiansen, Lene | Hofman, Albert | Johansson, Ingegerd | Jørgensen, Torben | Karasawa, Shigeru | Khaw, Kay-Tee | Kim, Mi-Kyung | Kristiansson, Kati | Li, Huaixing | Lin, Xu | Liu, Yongmei | Lohman, Kurt K. | Long, Jirong | Mikkilä, Vera | Mozaffarian, Dariush | North, Kari | Pedersen, Oluf | Raitakari, Olli | Rissanen, Harri | Tuomilehto, Jaakko | van der Schouw, Yvonne T. | Uitterlinden, André G. | Zillikens, M. Carola | Franco, Oscar H. | Shyong Tai, E. | Ou Shu, Xiao | Siscovick, David S. | Toft, Ulla | Verschuren, W.M. Monique | Vollenweider, Peter | Wareham, Nicholas J. | Witteman, Jacqueline C.M. | Zheng, Wei | Ridker, Paul M. | Kang, Jae H. | Liang, Liming | Jensen, Majken K. | Curhan, Gary C. | Pasquale, Louis R. | Hunter, David J. | Mohlke, Karen L. | Uusitupa, Matti | Cupples, L. Adrienne | Rankinen, Tuomo | Orho-Melander, Marju | Wang, Tao | Chasman, Daniel I. | Franks, Paul W. | Sørensen, Thorkild I.A. | Hu, Frank B. | Loos, Ruth J. F. | Nettleton, Jennifer A. | Qi, Lu
Human Molecular Genetics  2014;23(25):6961-6972.
FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10−105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10−107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10−16), and relative weak associations with lower total energy intake (−6.4 [−10.1, −2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (−0.07 [−0.11, −0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10−9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.
PMCID: PMC4271061  PMID: 25104851
11.  Effect of Antibiotics on Gut Microbiota, Gut Hormones and Glucose Metabolism 
PLoS ONE  2015;10(11):e0142352.
The gut microbiota has been designated as an active regulator of glucose metabolism and metabolic phenotype in a number of animal and human observational studies. We evaluated the effect of removing as many bacteria as possible by antibiotics on postprandial physiology in healthy humans.
Meal tests with measurements of postprandial glucose tolerance and postprandial release of insulin and gut hormones were performed before, immediately after and 6 weeks after a 4-day, broad-spectrum, per oral antibiotic cocktail (vancomycin 500 mg, gentamycin 40 mg and meropenem 500 mg once-daily) in a group of 12 lean and glucose tolerant males. Faecal samples were collected for culture-based assessment of changes in gut microbiota composition.
Acute and dramatic reductions in the abundance of a representative set of gut bacteria was seen immediately following the antibiotic course, but no changes in postprandial glucose tolerance, insulin secretion or plasma lipid concentrations were found. Apart from an acute and reversible increase in peptide YY secretion, no changes were observed in postprandial gut hormone release.
As evaluated by selective cultivation of gut bacteria, a broad-spectrum 4-day antibiotics course with vancomycin, gentamycin and meropenem induced shifts in gut microbiota composition that had no clinically relevant short or long-term effects on metabolic variables in healthy glucose-tolerant males.
Trial Registration NCT01633762
PMCID: PMC4643023  PMID: 26562532
12.  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.
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.
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.
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).
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.
PMCID: PMC4642628  PMID: 26558825
Childhood obesity; Juvenile obesity; Single nucleotide polymorphism; Case-control study; Body mass index; BMI; Obesity
13.  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.
PMCID: PMC4562524  PMID: 26348622
14.  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 
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.
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.
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.
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
PMCID: PMC4553907  PMID: 26336608
Metabolic Syndrome; Genetics; Insulin Resistance; Gene Expression
15.  Dietary modulation of the gut microbiota – a randomised controlled trial in obese postmenopausal women 
The British Journal of Nutrition  2015;114(3):406-417.
The gut microbiota has been implicated in obesity and its progression towards metabolic disease. Dietary interventions that target the gut microbiota have been suggested to improve metabolic health. The aim of the present study was to investigate the effect of interventions with Lactobacillus paracasei F19 or flaxseed mucilage on the gut microbiota and metabolic risk markers in obesity. A total of fifty-eight obese postmenopausal women were randomised to a single-blinded, parallel-group intervention of 6-week duration, with a daily intake of either L. paracasei F19 (9·4 × 1010 colony-forming units), flaxseed mucilage (10 g) or placebo. Quantitative metagenomic analysis of faecal DNA was performed to identify the changes in the gut microbiota. Diet-induced changes in metabolic markers were explored using adjusted linear regression models. The intake of flaxseed mucilage over 6 weeks led to a reduction in serum C-peptide and insulin release during an oral glucose tolerance test (P< 0·05) and improved insulin sensitivity measured by Matsuda index (P< 0·05). Comparison of gut microbiota composition at baseline and after 6 weeks of intervention with flaxseed mucilage showed alterations in abundance of thirty-three metagenomic species (P< 0·01), including decreased relative abundance of eight Faecalibacterium species. These changes in the microbiota could not explain the effect of flaxseed mucilage on insulin sensitivity. The intake of L. paracasei F19 did not modulate metabolic markers compared with placebo. In conclusion, flaxseed mucilage improves insulin sensitivity and alters the gut microbiota; however, the improvement in insulin sensitivity was not mediated by the observed changes in relative abundance of bacterial species.
PMCID: PMC4531470  PMID: 26134388
Gut microbiota; Probiotics; Flaxseed mucilage; Obesity-related disease; Metagenomics
16.  1H-MRS Measured Ectopic Fat in Liver and Muscle in Danish Lean and Obese Children and Adolescents 
PLoS ONE  2015;10(8):e0135018.
This cross sectional study aims to investigate the associations between ectopic lipid accumulation in liver and skeletal muscle and biochemical measures, estimates of insulin resistance, anthropometry, and blood pressure in lean and overweight/obese children.
Fasting plasma glucose, serum lipids, serum insulin, and expressions of insulin resistance, anthropometry, blood pressure, and magnetic resonance spectroscopy of liver and muscle fat were obtained in 327 Danish children and adolescents aged 8–18 years.
In 287 overweight/obese children, the prevalences of hepatic and muscular steatosis were 31% and 68%, respectively, whereas the prevalences in 40 lean children were 3% and 10%, respectively. A multiple regression analysis adjusted for age, sex, body mass index z-score (BMI SDS), and pubertal development showed that the OR of exhibiting dyslipidemia was 4.2 (95%CI: [1.8; 10.2], p = 0.0009) when hepatic steatosis was present. Comparing the simultaneous presence of hepatic and muscular steatosis with no presence of steatosis, the OR of exhibiting dyslipidemia was 5.8 (95%CI: [2.0; 18.6], p = 0.002). No significant associations between muscle fat and dyslipidemia, impaired fasting glucose, or blood pressure were observed.
Liver and muscle fat, adjusted for age, sex, BMI SDS, and pubertal development, associated to BMI SDS and glycosylated hemoglobin, while only liver fat associated to visceral and subcutaneous adipose tissue and intramyocellular lipid associated inversely to high density lipoprotein cholesterol.
Hepatic steatosis is associated with dyslipidemia and liver and muscle fat depositions are linked to obesity-related metabolic dysfunctions, especially glycosylated hemoglobin, in children and adolescents, which suggest an increased cardiovascular disease risk.
PMCID: PMC4529156  PMID: 26252778
17.  Pleiotropic genes for metabolic syndrome and inflammation 
Molecular genetics and metabolism  2014;112(4):317-338.
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.
PMCID: PMC4122618  PMID: 24981077
18.  Associations of the Inflammatory Marker YKL-40 with Measures of Obesity and Dyslipidaemia in Individuals at High Risk of Type 2 Diabetes 
PLoS ONE  2015;10(7):e0133672.
Circulating levels of the inflammatory marker YKL-40 are elevated in cardiovascular disease and obesity-related type 2 diabetes (T2D), and serum YKL-40 levels are related to elements of dyslipidaemia.
We aimed to investigate the associations between serum YKL-40 and obesity-related traits in a Danish sample of non-diabetic relatives to T2D patients and, furthermore, to estimate the heritability of YKL-40.
Research Design and Methods
324 non-diabetic individuals with family relation to a T2D patient were included in the study. The participants underwent oral- and intravenous glucose tolerance tests for estimation of glucose tolerance and surrogate measures of insulin sensitivity. Anthropometric measures were retrieved and biochemical measures of the plasma lipid profile and serum YKL-40 levels were obtained. Association-analyses between serum YKL-40 and obesity-related traits and estimates of the narrow sense heritability of YKL-40 were based on a polygenic variance component model.
Fasting serum levels of YKL-40 were positively associated with waist-hip-ratio (p<0.001) and fasting plasma triglyceride levels (p<0.001). None of the insulin sensitivity indexes were significantly associated with YKL-40. According to the AE model, the familiality-estimate h2 of YKL-40 was 0.45 (SE 0.13). When the ACE-model was applied, the heritability-estimate h2 of YKL-40 did not reach statistical significance.
Our results suggest a role of serum YKL-40 in obesity-related low grade inflammation, but do not indicate that YKL-40 is directly involved in the development of T2D.
PMCID: PMC4510434  PMID: 26197239
19.  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.
PMCID: PMC4030103  PMID: 24296717
20.  The gut microbiome in cardio-metabolic health 
Genome Medicine  2015;7(1):33.
With the prevalence of cardio-metabolic disorders reaching pandemic proportions, the search for modifiable causative factors has intensified. One such potential factor is the vast microbial community inhabiting the human gastrointestinal tract, the gut microbiota. For the past decade evidence has accumulated showing the association of distinct changes in gut microbiota composition and function with obesity, type 2 diabetes and cardiovascular disease. Although causality in humans and the pathophysiological mechanisms involved have yet to be decisively established, several studies have demonstrated that the gut microbiota, as an environmental factor influencing the metabolic state of the host, is readily modifiable through a variety of interventions. In this review we provide an overview of the development of the gut microbiome and its compositional and functional changes in relation to cardio-metabolic disorders, and give an update on recent progress in how this could be exploited in microbiota-based therapeutics.
Electronic supplementary material
The online version of this article (doi:10.1186/s13073-015-0157-z) contains supplementary material, which is available to authorized users.
PMCID: PMC4378584  PMID: 25825594
21.  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.
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.
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.
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).
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.
PMCID: PMC4370672  PMID: 25799151
22.  Impact of PTBP1 rs11085226 on glucose-stimulated insulin release in adult Danes 
BMC Medical Genetics  2015;16:17.
The variant rs11085226 (G) within the gene encoding polypyrimidine tract binding protein 1 (PTBP1) was reported to associate with reduced insulin release determined by an oral glucose tolerance test (OGTT) as well as an intravenous glucose tolerance test (IVGTT). The aim of the present study was to validate the association of the rs11085226 G-allele of PTBP1 with previously investigated OGTT- and IVGTT-derived diabetes-related metabolic quantitative phenotypes, to conduct exploratory analyses of additional measures of beta-cell function, and to further investigate a potential association with type 2 diabetes.
PTBP1 rs11085226 was genotyped in 20,911 individuals of Danish Caucasian ethnicity ascertained from 9 study samples. Case control analysis was performed on 5,634 type 2 diabetic patients and 11,319 individuals having a normal fasting glucose level as well as 4,641 glucose tolerant controls, respectively. Quantitative trait analyses were performed in up to 13,605 individuals subjected to an OGTT or blood samples obtained after an overnight fast, as well as in 596 individuals subjected to an IVGTT.
Analyses of fasting and OGTT-derived quantitative traits did not show any significant associations with the PTBP1 rs11085226 variant. Meta-analysis of IVGTT-derived quantitative traits showed a nominally significant association between the variant and reduced beta-cell responsiveness to glucose (β = −0.1 mmol · kg−1 · min−1; 95% CI: −0.200.20 – −0.024; P = 0.01) assuming a dominant model of inheritance, but failed to replicate a previously reported association with area under the curve (AUC) for insulin. Case control analysis did not show an association of the PTBP1 rs11085226 variant with type 2 diabetes.
Despite failure to replicate the previously reported associations of PTBP1 rs11085226 with OGTT- and IVGTT-derived measures of beta-cell function, we did find a nominally significant association with reduced beta-cell responsiveness to glucose during an IVGTT, a trait not previously investigated, leaving the potential influence of this variant in PTBP1 on glucose stimulated insulin release open for further investigation. However, the present study does not support the hypothesis that the variant confers risk of type 2 diabetes.
Electronic supplementary material
The online version of this article (doi:10.1186/s12881-015-0160-7) contains supplementary material, which is available to authorized users.
PMCID: PMC4422140  PMID: 25927630
Polypyrimidine tract binding protein 1; Type 2 diabetes; Beta-cell function; Genetics; Insulin release
23.  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.
PMCID: PMC4311266  PMID: 25631608
24.  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.
PMCID: PMC4311266  PMID: 25631608
25.  Novel variation and de novo mutation rates in population-wide de novo assembled Danish trios 
Nature Communications  2015;6:5969.
Building a population-specific catalogue of single nucleotide variants (SNVs), indels and structural variants (SVs) with frequencies, termed a national pan-genome, is critical for further advancing clinical and public health genetics in large cohorts. Here we report a Danish pan-genome obtained from sequencing 10 trios to high depth (50 × ). We report 536k novel SNVs and 283k novel short indels from mapping approaches and develop a population-wide de novo assembly approach to identify 132k novel indels larger than 10 nucleotides with low false discovery rates. We identify a higher proportion of indels and SVs than previous efforts showing the merits of high coverage and de novo assembly approaches. In addition, we use trio information to identify de novo mutations and use a probabilistic method to provide direct estimates of 1.27e−8 and 1.5e−9 per nucleotide per generation for SNVs and indels, respectively.
The generation of a national pan-genome, a population-specific catalogue of genetic variation, may advance the impact of clinical genetics studies. Here the Besenbacher et al. carry out deep sequencing and de novo assembly of 10 parent–child trios to generate a Danish pan-genome that provides insight into structural variation, de novo mutation rates and variant calling.
PMCID: PMC4309431  PMID: 25597990

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