Journal/Magazine Articles

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This collection contains original research articles, review articles and case reports published in local and international peer reviewed journals by the staff members of the Faculty of Medicine

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    A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
    (American Society of Human Genetics., 2022) Ramdas, S.; Judd, J.; Graham, S.E.; Kanoni, S.; Wang, Y.; Surakka, I.; Wenz, B.; Clarke, S.L.; Chesi, A.; Wells, A.; Bhatti, K.F.; Vedantam, S.; Winkler, T.W.; Locke, A.E.; Marouli, E.; Zajac, G.J.M.; Wu, K.H.; Ntalla, I.; Hui, Q.; Klarin, D.; Hilliard, A.T.; Wang, Z.; Xue, C.; Thorleifsson, G.; Helgadottir, A.; Gudbjartsson, D.F.; Holm, H.; Olafsson, I.; Hwang, M.Y.; Han, S.; Akiyama, M.; Sakaue, S.; Terao, C.; Kanai, M.; Zhou, W.; Brumpton, B.M.; Rasheed, H.; Havulinna, A.S.; Veturi, Y.; Pacheco, J.A.; Rosenthal, E.A.; Lingren, T.; Feng, Q.; Kullo, I.J.; Narita, A.; Takayama, J.; Martin, H.C.; Hunt, K.A.; Trivedi, B.; Haessler, J.; Giulianini, F.; Bradford, Y.; Miller, J.E.; Campbell, A.; Lin, K.; Millwood, I.Y.; Rasheed, A.; Hindy, G.; Faul, J.D.; Zhao, W.; Weir, D.R.; Turman, C.; Huang, H.; Graff, M.; Choudhury, A.; Sengupta, D.; Mahajan, A.; Brown, M.R.; Zhang, W.; Yu, K.; Schmidt, E.M.; Pandit, A.; Gustafsson, S.; Yin, X.; Luan, J.; Zhao, J.H.; Matsuda, F.; Jang, H.M.; Yoon, K.; Gomez, C.M.; Pitsillides, A.; Hottenga, J.J.; Wood, A.R.; Ji, Y.; Gao, Z.; Haworth, S.; Mitchell, R.E.; Chai, J.F.; Aadahl, M.; Bjerregaard, A.A.; Yao, J.; Manichaikul, A.; JaneLee, W.; Hsiung, C.A.; Warren, H.R.; Ramirez, J.; Jensen, J.B.; Kårhus, L.; Goel, A.; Lleal, M.S.; Noordam, R.; Mauro, P.; Matteo, F.; McDaid, A.F.; Marques-Vidal, P.; Wielscher, M.; Trompet, S.; Sattar, N.; Møllehave, L.T.; Munz, M.; Zeng, L.; Huang, J.; Yang, B.; Poveda, A.; Kurbasic, A.; Schönherr, S.; Forer, L.; Scholz, M.; Galesloot, T.E.; Bradfield, J.P.; Ruotsalainen, S.E.; Daw, E.W.; Zmuda, J.M; Mitchell, J.S.; Fuchsberger, C.; Christensen, H.; Brody, J.A.; Le, P.; Feitosa, M.F.; Wojczynski, M.K.; Hemerich, D.; Preuss, M.; Mangino, M.; Christofidou, P.; Verweij, N.; Benjamins, J.W.; Engmann, J.; Noah, T.L.; Verma, A.; Slieker, R.C.; Lo, K.S.; Zilhao, N.R.; Kleber, M.E.; Delgado, G.E.; Huo, S.; Ikeda, D.D.; Iha, H.; Yang, J.; Liu, J.; Demirkan, A.; Leonard, H.L.; Marten,J.; Emmel, C.; Schmidt, B.; Smyth, L.J.; Cañadas-Garre, M.; Wang, C.; Nakatochi, M.; Wong, A.; Hutri-Kähönen , N.; Sim, X.; Xia, R.; Huerta-Chagoya, A.; Fernandez-Lopez, J.C.; Lyssenko, V; Nongmaithem, S.S.; Sankareswaran, A.; Irvin, M.R.; Oldmeadow, C.; Kim, H.N.; Ryu, S.; Timmers, P.R.H.J; Arbeeva, L.; Dorajoo, R.; Lange, L.A.; Prasad, G.; Lorés-Motta, L.; Pauper, M.; Long, J.; Li, X.; Theusch, E.; Takeuchi, F.; Spracklen, C.N.; Loukola, A.; Bollepalli, S.; Warner, S.C.; Wang, Y.X.; Wei, W.B.; Nutile, T.; Ruggiero, D.; Sung,Y.J.; Chen, S.; Liu, F.; Yang, J.; Kentistou, K.A.; Banas, B.; Morgan, A.; Meidtner, K.; Bielak, L.F.; Smith, J.A.; Hebbar, P.; Farmaki, A.E.; Hofer, E.; Lin, M.; Concas, M.P.; Vaccargiu, S.; Most, P.J.; Pitkänen, N.; Cade, B.E.; Laan, S.W.; Chitrala, K.N.; Weiss, S.; Bentley, A.R.; Doumatey, A.P.; Adeyemo, A.A.; Lee, J.Y.; Petersen, E.R.B.; Nielsen, A.A.; Choi, H.S.; Nethander, M.; Nethander, M.; Freitag-Wolf, S.; Southam, L.; Rayner, N.W.; Wang, C.A.; Lin, S.; Wang, J.S.; Couture, C.; Lyytikäinen, L.P.; Nikus, K.; Partida, G.C.; Vestergaard, H.; Hidalgo, B.; Giannakopoulou, O.; Cai, Q.; Obura, M.O.; Setten, J.; He, K.Y.; Tang, H.; Terzikhan, N.; Shin, J.H.; Jackson, R.D.; Reiner, A.P.; Martin, L.W.; Chen, Z.; Li, L.; Kawaguchi, T.; Thiery, J.; Bis, J.C.; Launer, L.J.; Li, H.; Nalls, M.A.; Raitakari, O.T.; Ichihara, S.; Wild, S.H.; Nelson, C.P.; Campbell, H.; Jäger, S.; Nabika, T.; Al-Mulla, F.; Niinikoski, H.; Braund, P.S.; Kolcic, I.; Kovacs, P.; Giardoglou, T.; Katsuya, T.; Kleijn, D.; Borst, G.J.; Kim, E.K.; Adams, H.H.H.; Ikram, M.A.; Zhu, X.; Asselbergs, F.W.; Kraaijeveld, A.O.; Beulens, J.W.J.; Shu, X.O.; Rallidis, L.S.; Pedersen, O.; Hansen, T.; Mitchell, P.; Hewitt, A.W.; Kähönen, M.; Pérusse, L.; Bouchard, C.; Tönjes, A.; Chen, Y.D.I; Pennell, C.E.; Mori, T.A.; Lieb, W.; Franke, A.; Ohlsson, C.; Mellström, D.; Cho, Y.S.; Lee, H.; Yuan, J.M.; Koh, W.P.; Rhee, S.Y.; Woo, J.T.; Heid, I.M.; Stark, K.J.; Zimmermann, M.E.; Völzke, H.; Homuth, G.; Homuth, G.; Evans, M.K.; Zonderman, A.B.; Polasek, O.; Pasterkamp, G.; Hoefer, I.E.; Redline, S.; Pahkala, K.; Oldehinkel, A.J.; Snieder, H.; Biino, G.; Schmidt, R.; Schmidt, H.; Bandinelli , S; Dedoussis, G.; Thanaraj, T.A.; Peyser, P.A.; Kato, N.; Schulze, M.B.; Girotto, G.; Böger, C.A.; Jung, B.; Joshi, P.K.; Bennett, D.A.; Jager, P.L.D.; Lu, X.; Mamakou, V.; Brown, M.; Caulfield, M.J.; Munroe, P.B.; Guo, X.; Ciullo, M.; Jonas, J.B.; Samani, N.J.; Kaprio, J.; Pajukanta, P.; Luna, T.T.; Salinas, C.A.A.; Adair, L.S.; Bechayda, S.A.; de Silva, H.J.; Wickremasinghe, A.R.; Krauss, R.M.; Wu, J.Y.; Zheng,W.; Hollander, A.I.; Bharadwaj, D.; Correa, A,; Wilson, J.G.; Lind, L.; Heng, C.K.; Nelson, A.E.; Golightly, Y.M.; Wilson, J.F.; Penninx, B.; Kim, H.L.; Attia, J.; Scott, R.J.; Rao, D.C.; Arnett, D.K.; Walker, M.; Scott, L.J.; Koistinen, H.A.; Chandak, G.R.; Mercader, J.M.; Villalpando, C.G.; Orozco, L.; Fornage, M.; Tai, E.S.; Dam, R.M.; Lehtimäki, T.; Chaturvedi, N.; Yokota, M.; Liu, J.; Reilly, D.F.; McKnight, A.J.; Kee, F.; Jöckel, K.H.; McCarthy, M.I.; Palmer, C.N.A.; Vitart, V.; Hayward, C.; Simonsick, E.; Duijn, C.M; Jin, Z.B.; Jin, Z.B.; Lu, F.; Hishigaki, H.; Lin, X.; März, W.; Gudnason, V.; Tardif, J.C.; Lettre, G.; Hart, L.M.T.; Elders, P.J.M.; Rader, D.J.; Loos, S.M.; Province, M.A.; Parra, E.J.; Cruz, M.; Psaty, B.M.; Brandslund, I.; Pramstaller, P.P.; Rotimi, C.N.; Christensen, K.; Ripatti, S.; Widén, E.; Hakonarson, H.; Grant, S.F.A.; Kiemeney, L.; de Graaf, J.; Loeffler, M.; Kronenberg, F.; Gu, D.; Erdmann, J.; Schunkert, H.; Franks,P.W.; Linneberg, A.; Jukema, J.W.; Khera, A.V.; Männikkö, M.; Jarvelin, M.R.; Kutalik, Z.; Francesco, C.; Kanamori, D.O.M.; Dijk, K.W.; Watkins, H.; Strachan, D.P.; Grarup, N.; Sever, P.; Poulter, N.; Sheu, W.H.H.; Rotter, J.I.; Dantoft, T.M.; Karpe, F.; Neville, M.J.; Timpson, N.J.; Cheng, C.Y.; Wong, T.Y.; Khor, C.C.; Li, H.; Sabanayagam, C.; Peters, A.; Gieger, C.; Hattersley, A.T.; Pedersen, N.L.; Magnusson, P.K.E.; Boomsma, D.I.; de Geus, E.J.C.; Cupples, L.A.; Meurs, J.B.J.; Ikram, A.; Ghanbari, M.; Larsen, P.G.; Huang, W.; Kim, Y.J.; Tabara, Y.; Wareham, N.J.; Langenberg, C.; Zeggini, E.; Tuomilehto, J.; Kuusisto, J.; Laakso, M.; Ingelsson, E.; Abecasis, G.; Chambers, J.C.; Kooner, J.S.; de Vries, P.S.; Morrison, A.C.; Hazelhurst, S.; Ramsay, M.; North, K.E.; Daviglus, M.; Kraft, P.; Martin, N.G.; Whitfield, J.B.; Abbas, S.; Saleheen, D.; Walters, R.G.; Holmes, M.V.; Black, C.; Smith, B.H.; Baras, A.; Justice, A.E.; Buring, J.E.; Ridker, P.M.; Chasman, D.I.; Kooperberg, C.; Tamiya, G.; Yamamoto, M.; Heel, D.A.; Trembath, R.C.; Wei, W.Q.; Jarvik, G.P.; Namjou, B.; Hayes, M.G.; Ritchie, M.D.; Jousilahti, P.; Salomaa, V.; Hveem, K.; Åsvold, B.O.; Kubo, M.; Kamatani, Y.; Okada, Y.; Murakami, Y.; Kim, B.J.; Thorsteinsdottir, U.; Stefansson, K.; Zhang, J.; Chen, Y.E.; Ho, Y.L.; Lynch, J.A.; Tsao, P.S.; Chang, K.M.; Cho, K.; O'Donnell, C.J.; Gaziano, J.M.; Wilson, P.; Mohlke, K.L.; Frayling, T.M.; Hirschhorn, J.N.; Kathiresan, S.; Boehnke, M.; Million Veterans Program; Global Lipids Genetics Consortium; Grant, S.; Natarajan, P.; Sun, Y.V.; Morris, A.P.; Deloukas, P.; Peloso, G.; Assimes, T.L.; Willer, C.J.; Zhu, X.; Brown, C.D.
    A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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    Reference equations for evaluation of spirometry function tests in South Asia, and amongst south asians living in other countries
    (European Respiratory Society, 2022) Leong, W.Y.; Gupta, A.; Hasan, M.; Mahmood, S.; Siddiqui, S.; Ahmed, S.; Goon, I.Y.; Loh, M.; Mina, T.H.; Lam, B.; Yew, Y.W.; Ngeow, J.; Lee, J.; Lee, E.S.; Riboli, E.; Elliott, P.; Tan, G.P.; Chotirmall, S.H.; Wickremasinghe, A.R.; Kooner, J.S.; Khawaja, K.I.; Katulanda, P.; Mridha, M.K.; Jha, S.; Ranjit, M.A.; Pradeepa, G.; Kasturiratne, A.; Chambers, J.C.
    Background: There is little data to accurate interpretation of spirometry data in South Asia, a major global region with high reported burden for chronic respiratory disease. Method: We measured lung function in 7,453 healthy men and women aged over 18 years, from Bangladesh, North India, South India, Pakistan and Sri Lanka, as part of the South Asia Biobank study. We first assessed the accuracy of existing equations for predicting normal forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and FEV1/FVC ratio. We then used our data to derive (N=5589) and internally validate (N=1864) new prediction equations amongst South Asians, with further external validation amongst 339 healthy South Asians living in Singapore. Results: GLI2012 and NHANESIII consistently overestimated expiratory volumes (best fit GLI-African American, mean [sd] z-score (n=7453): FEV1 -0.94 [1.05]; FVC -0.91 [1.10]). Age, height and weight were strong predictors of lung function in our participants (p<0.001), and sex specific reference equations using these three variables were highly accurate in both internal validation (z-scores: FEV1 0.03 [0.99]; FVC 0.04 [0.97]; FEV1/FVC -0.03 [0.99]) and external validation (z-scores: FEV1 0.31 [0.99]; FVC 0.24 [0.97]; FEV1/FVC 0.16 [0.91]). Further adjustment for study regions improves the model fit, with highest accuracy for estimation of region specific lung function in South Asia. Conclusion: We present improved equations for predicting lung function in South Asians. These offer the opportunity to enhance diagnosis and management of acute and chronic lung diseases in this major global population.
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    Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
    (Nature Publishing Company, New York, 2022) Mahajan, A.; Spracklen, C.N.; Zhang, W.; Ng, M.C.Y.; Petty, L.E.; Kitajima, H.; Yu, G.Z.; Rüeger, S.; Speidel, L.; Kim, Y.J.; Horikoshi, M.; Mercader, J.M .; Taliun, D.; Moon, S.; Kwak, S.H.; Robertson, N.R.; Rayner, N.W.; Loh, M.; Kim, B.; Chiou, J.; Miguel-Escalada, I.; Parolo, P.D.B.; Lin, K.; Bragg, F.; Preuss, M.H.; Takeuchi, F.; Nano, J.; Guo, X.; Lamri, A.; Nakatoch, M.; Scott, R.A.; Lee, J.J.; Huerta-Chagoya, A.; Graff, M.; Chai, J.F.; Parra, E. J.; Yao, J.; Bielak, L.F.; Tabara, Y.; Hai, Y.; Steinthorsdottir, V.; Cook, J.P.; Kals, M.; Grarup, N.; Schmidt, E.M.; Pan, I.; Sofer, T.; Wuttke, M.; Sarnowski, C.; Gieger, C.; Nousome, D.; Trompet, S.; Long, J.; Sun, M.; Tong, L.; Chen, W.M.; Ahmad, M.; Noordam, R.; Lim, V.J.Y.; Tam, C.H.T.; Joo, Y.Y.; Chen, C.H.; Raffield, L.M.; Lecoeur, C.; Prins, B.P.; Nicolas, A.; Yanek, L.R.; Chen, G.; Jensen, R.A.; Tajuddin, S.; Kabagambe, E.K.; An, P.; Xiang, A.H.; Choi, H.S.; Cade, B.E.; Tan, J.; Flanagan, J.; Abaitua, F.; Adair, L.S.; Adeyemo, A.; Aguilar-Salinas, C.A.; Akiyama, M.; Anand, S.S.; Bertoni, A.; Bian, Z.; Bork-Jensen, J.; Brandslund, I.; Brody, J.A.; Brummett, C.M.; Buchanan, T.A.; Canouil, M.; Chan, J.C.N.; Chang, L.C.; Chee, M.L.; Chen, J.; Chen, S.H.; Chen, Y.T.; Chen, Z.; Chuang, L.M.; Cushman, M.; Das, S.K.; de Silva, H.J.; Dedoussis, G.; Dimitrov, L.; Doumatey, A.P.; Du, S.; Duan, Q.; Eckardt, K.U.; Emery, L.S.; Evans, D.S.; Evans, M.K.; Fischer, K.; Floyd, J.S.; Ford, I.; Fornage, M.; Franco, O.H.; Frayling, T.M.; Freedman, B.I.; Fuchsberger, C.; Genter, P.; Gerstein, H.C.; Giedraitis, V.; Villalpando, C.G.; Villalpando, M.E.G.; Goodarzi, M.O.; Larsen, P.G.; Gorkin, D.; Gross, M.; Guo, Y.; Hackinger, S.; Han, S.; Hattersley, A.T.; Herder, C.; Howard, A.G.; Hsueh, W.; Huang, M.; Huang, W.; Hung, Y.; Hwang, M.Y.; Hwu, C.; Ichihara, S.; Ikram, M.A.; Ingelsson, M.; Islam, M.T.; Isono, M.; Jang, H.M.; Jasmine, F.; Jiang, G.; Jonas, J.B.; Jørgensen, M.E.; Jørgensen, T.; Kamatani, Y.; Kandeel, F.R.; Kasturiratne, A.; Katsuya, T.; Kaur, V.; Kawaguchi, T.; Keaton, J.M.; Kho, A.N.; Khor, C.C.; Kibriya, M.G.; Kim, D.H.; Kohara, K.; Kriebel, J.; Kronenberg, F.; Kuusisto, J.; Läll, K.; Lange, L.A.; Lee, M.; Lee, N.R.; Leong, A.; Li, L.; Li, Y.; Li-Gao, R.; Ligthart, S.; Lindgren, C.M.; Linneberg, A.; Liu, C.; Liu, J.; Locke, A.E.; Louie, T.; Luan, J.; Luk, A.O.; Luo, X.; Lv, J.; Lyssenko, V.; Mamakou, V.; Mani, K.R.; Meitinger, T.; Metspalu, A.; Morris, A.D.; Nadkarni, G.N.; Nadler, J.L.; Nalls, M.A.; Nayak, U.; Nongmaithem, S.S.; Ntalla, I.; Okada, Y.; Orozco, L.; Patel, S.R.; Pereira, M.A.; Peters, A.; Pirie, F.J.; Porneala, B.; Prasad, G.; Preissl, S.; Rasmussen-Torvik, L.J.; Reiner, A.P.; Roden, M.; Rohde, R.; Roll, K.; Sabanayagam, C.; Sander, M.; Sandow, K.; Sattar, N.; Schönherr, S.; Schurmann, C.; Shahriar, M.; Shi, J.; Shin, D.M.; Shriner, D.; Smith, J.A.; So, W.Y.; Stančáková, A.; Stilp, A.M.; Strauch, K.; Suzuki, K.; Takahashi, A.; Taylor, K.D.; Thorand, B.; Thorleifsson, G.; Thorsteinsdottir, U.; Tomlinson, B.; Torres, J.M.; Tsai, F.; Tuomilehto, J.; Tusie-Luna, T.; Udler, M.S.; Salgado, A.V.; Dam, R.M.; Klinken, J.B.; Varma, R.; Vujkovic, M.; Wacher-Rodarte, N.; Wheeler, E.; Whitsel, E.A.; Wickremasinghe, A.R.; Dijk, K.W.; Witte, D.R.; Yajnik, C.S; Yamamoto, K.; Yamauchi, T.; Yengo, L.; Yoon, K.; Yu, C.; Yuan, J.M.; Yusuf, S.; Zhang, L.; Zheng, W.; FinnGen; eMERGE Consortium; Leslie J Raffel; Igase, M.; Ipp, E.; Redline, S.; Cho, Y.S.; Lind, L.; Province, M.A.; Hanis, C.L.; Peyser, P.A.; Ingelsson, E.; Zonderman, A.B.; Psaty, B.M.; Wang, Y.; Rotimi, C.N.; Becker, D.M.; Matsuda, F.; Liu, Y.; Zeggini, E.; Yokota, M.; Rich, S.S.; Kooperberg, C.; Pankow, J.S.; Engert, J.C.; Chen, Y.I.; Froguel, P.; Wilson, J.G.; Sheu, W.H.H.; Kardia, S.L.R.; Wu, J.Y.; Hayes, M.G.; Ma, R.C.W.; Wong, T.Y.; Groop, L.; Mook-Kanamori, D.O.; Chandak, G.R.; Collins, F.S.; Bharadwaj, D.; Paré, G.; Sale, M.M.; Ahsan, H.; Motala, A.A.; Shu, X.O.; Park, K.S.; Jukema, J.W.; Cruz, M.; Cowdin, R.M.; Grallert, H.; Cheng, C.Y.; Bottinger, E.P.; Dehghan, A.; Tai, E.S.; Dupuis, J.; Kato, N.; Laakso, M.; Köttgen, A.; Koh, W.P.; Palmer, C.N.A.; Liu, S.; Abecasis, G.; Kooner, J.S.; Loos, R.J.F.; North, K.E.; Haiman, C.A.; Florez, J.C.; Saleheen, D.; Hansen, T.; Pedersen, O.; Mägi, R.; Langenberg, C.; Wareham, N.J.; Maeda, S.; Kadowaki, T.; Lee, J.; Millwood, I.Y.; Walters, R.G.; Stefansson, K.; Myers, S.R.; Ferrer, J.; Gaulton, K.J.; Meigs, J.B.; Mohlke, K.L.; Gloyn, A.L.; Bowden, D.W.; Below, J.E.; Chambers, J.C.; Sim, X.; Boehnke, M.; Rotter, J.I.; McCarthy, M.I.; Morris, A.P.
    We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
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    The Trans-ancestral genomic architecture of glycemic traits
    (Nature Pub. Co., 2021) Chen, J.; Spracklen, C.N.; Marenne, G.; Varshney, A.; Corbin, L.J.; Luan, J.; Willems, S.M.; Wu, Y.; Zhang, X.; Horikoshi, M.; Boutin, T.S.; Mägi, R.; Waage, J.; Li-Gao, R.; Chan, K.H.K; Yao, J.; Anasanti, M.D.; Chu, A.Y.; Claringbould, A.; Heikkinen, J.; Hong, J.; Hottenga, J.J.; Huo, S.; Kaakinen, M.A.; Louie, T.; März, W.; Moreno-Macias, H.; Ndungu, A.; Nelson, S.C.; Nolte, I.M.; North, K.E.; Raulerson, C.K.; Ray, D.; Rohde, R.; Rybin, D.; Schurmann, C.; Sim, X.; Southam, L.; Stewart, I.D.; Wang, C.A.; Wang, Y.; Wu, P.; Zhang, W.; Ahluwalia, T.S.; Appel, E.V.R.; Bielak, L.F.; Brody, J.A.; Burtt, N.P.; Cabrera, C.P.; Cade, B.E.; Chai, J.F.; Chai, X.; Chang, L.C.; Chen, C.H.; Chen, B.H.; Chitrala, K.N.; Chiu, Y.F.; De Haan, H.G.; Delgado, G.E.; Demirkan, A.; Duan, Q.; Engmann, J.; Fatumo, S.A.; Gayán, J.; Giulianini, F.; Gong, J.H.; Gustafsson, S.; Hai, Y.; Hartwig, F.P.; He, J.; Heianza, Y.; Huang, T.; Huerta-Chagoya, A.; Hwang, M.Y.; Jensen, R.A.; Kawaguchi, T.; Kentistou, K.A.; Kim, Y.J.; Kleber, M.E.; Kooner, I.K.; Lai, S.; Lange, L.A.; Langefeld, C.D.; Lauzon, M.; Li, M.; Ligthart, S.; Liu, J.; Loh, M.; Long, J.; Lyssenko, V.; Mangino, M.; Marzi, C.; Montasser, M.E.; Nag, A.; Nakatochi, M.; Noce, D.; Noordam, R.; Pistis, G.; Preuss, M.; Raffield, L.; Rasmussen-Torvik, L.J.; Rich, S.S.; Robertson, N.R.; Rueedi, R.; Ryan, K.; Sanna, S.; Saxena, R.; Schraut, K.E.; Sennblad, B.; Setoh, K.; Smith, A.V.; Sparsø, T.; Strawbridge, R.J.; Takeuchi, F.; Tan, J.; Trompet, S.; Van den Akker, E.; Van der Most, P.J.; Verweij, N.; Vogel, M.; Wang, H.; Wang, C.; Wang, N.; Warren, H.R.; Wen, W.; Wilsgaard, T.; Wong, A.; Wood, A.R.; Xie, T.; Zafarmand, M.H.; Zhao, J.H.; Zhao, W.; Amin, N.; Arzumanyan, Z.; Astrup, A.; Bakker, S.J.L.; Baldassarre, D.; Beekman, M.; Bergman, R.N.; Bertoni, A.; Blüher, M.; Bonnycastle, L.L.; Bornstein, S.R.; Bowden, D.W.; Cai, Q.; Campbell, A.; Campbell, H.; Chang, Y.C.; de Geus, E.J.C.; Dehghan, A.; Du, S.; Eiriksdottir, G.; Farmaki, A.E.; Frånberg, M.; Fuchsberger, C.; Gao, Y.; Gjesing, A.P.; Goel, A.; Han, S.; Hartman, C.A.; Herder, C.; Hicks, A.A.; Hsieh, C.H.; Hsueh, W.A.; Ichihara, S.; Igase, M.; Ikram, M.A.; Johnson, W.C.; Jørgensen, M.E.; Joshi, P.K.; Kalyani, R.R.; Kandeel, F.R.; Katsuya, T.; Khor, C.C.; Kiess, W.; Kolcic, I.; Kuulasmaa, T.; Kuusisto, J.; Läll, K.; Lam, K.; Lawlor, D.A.; Lee, N.R.; Lemaitre, R.N.; Li, H.; Lifelines Cohort Study; Lin, S.Y.; Lindström, J.; Linneberg, A.; Liu, J.; Lorenzo, C.; Matsubara, T.; Matsuda, F.; Mingrone, G.; Mooijaart, S.; Moon, S.; Nabika, T.; Nadkarni, G.N.; Nadler, J.L.; Nelis, M.; Neville, M.J.; Norris, J.M.; Ohyagi, Y.; Peters, A.; Peyser, P.A.; Polasek, O.; Qi, Q.; Raven, D.; Reilly, D.F.; Reiner, A.; Rivideneira, F.; Roll, K.; Rudan, I.; Sabanayagam, C.; Sandow, K.; Sattar, N.; Schürmann, A.; Shi, J.; Stringham, H.M.; Taylor, K.D.; Teslovich, T.M.; Thuesen, B.; Timmers, P.R.H.J.; Tremoli, E.; Tsai, M.Y.; Uitterlinden, A.; van Dam, R.M.; van Heemst, D.; van Hylckama Vlieg, A.; van Vliet-Ostaptchouk, J.V.; Vangipurapu, J.; Vestergaard, H.; Wang, T.; Willems van Dijk, K.; Zemunik, T.; Abecasis, G.R.; Adair, L.S.; Aguilar-Salinas, C.A.; Alarcón-Riquelme, M.E.; An, P.; Aviles-Santa, L.; Becker, D.M.; Beilin, L.J.; Bergmann, S.; Bisgaard, H.; Black, C.; Boehnke, M.; Boerwinkle, E.; Böhm, B.O.; Bønnelykke, K.; Boomsma, D.I.; Bottinger, E.P.; Buchanan, T.A.; Canouil, M.; Caulfield, M.J.; Chambers, J.C.; Chasman, D.I.; Chen, Y.I.; Cheng, C.Y.; Collins, F.S.; Correa, A.; Cucca, F.; de Silva, H.J.; Dedoussis, G.; Elmståhl, S.; Evans, M.K.; Ferrannini, E.; Ferrucci, L.; Florez, J.C.; Franks, P.W.; Frayling, T.M.; Froguel, P.; Gigante, B.; Goodarzi, M.O.; Gordon-Larsen, P.; Grallert, H.; Grarup, N.; Grimsgaard, S.; Groop, L.; Gudnason, V.; Guo, X.; Hamsten, A.; Hansen, T.; Hayward, C.; Heckbert, S.R.; Horta, B.L.; Huang, W.; Ingelsson, E.; James, P.S.; Jarvelin, M.R.; Jonas, J.B.; Jukema, J.W.; Kaleebu, P.; Kaplan, R.; Kardia, S.L.R.; Kato, N.; Keinanen-Kiukaanniemi, S.M.; Kim, B.J.; Kivimaki, M.; Koistinen, H.A.; Kooner, J.S.; Körner, A.; Kovacs, P.; Kuh, D.; Kumari, M.; Kutalik, Z.; Laakso, M.; Lakka, T.A.; Launer, L.J.; Leander, K.; Li, H.; Lin, X.; Lind, L.; Lindgren, C.; Liu, S.; Loos, R.J.F.; Magnusson, P.K.E.; Mahajan, A.; Metspalu, A.; Mook-Kanamori, D.O.; Mori, T.A.; Munroe, P.B.; Njølstad, I.; O'Connell, J.R.; Oldehinkel, A.J.; Ong, K.K.; Padmanabhan, S.; Palmer, C.N.A.; Palmer, N.D.; Pedersen, O.; Pennell, C.E.; Porteous, D.J.; Pramstaller, P.P.; Province, M.A.; Psaty, B.M.; Qi, L.; Raffel, L.J.; Rauramaa, R.; Redline, S.; Ridker, P.M.; Rosendaal, F.R.; Saaristo, T.E.; Sandhu, M.; Saramies, J.; Schneiderman, N.; Schwarz, P.; Scott, L.J.; Selvin, E.; Sever, P.; Shu, X.O.; Slagboom, P.E.; Small, K.S.; Smith, B.H.; Snieder, H.; Sofer, T.; Sørensen, T.I.A.; Spector, T.D.; Stanton, A.; Steves, C.J.; Stumvoll, M.; Sun, L.; Tabara, Y.; Tai, E.S.; Timpson, N.J.; Tönjes, A.; Tuomilehto, J.; Tusie, T.; Uusitupa, M.; van der Harst, P.; van Duijn, C.; Vitart, V.; Vollenweider, P.; Vrijkotte, T.G.M.; Wagenknecht, L.E.; Walker, M.; Wang, Y.X.; Wareham, N.J.; Watanabe, R.M.; Watkins, H.; Wei, W.B.; Wickremasinghe, A.R.; Willemsen, G.; Wilson, J.F.; Wong, T.Y.; Wu, J.Y.; Xiang, A.H.; Yanek, L.R.; Yengo, L.; Yokota, M.; Zeggini, E.; Zheng, W.; Zonderman, A.B.; Rotter, J.I.; Gloyn, A.L.; McCarthy, M.I.; Dupuis, J.; Meigs, J.B.; Scott, R.A.; Prokopenko, I.; Leong, A.; Liu, C.T.; Parker, S.C.J.; Mohlke, K.L.; Langenberg, C.; Wheeler, E.; Morris, A.P.; Barroso, I.; Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) Collaborators.
    ABSTRACT: Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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    A large-scale multi-ancestry genome-wide study accounting for smoking behavior identifies multiple significant loci for blood pressure
    (University of Chicago Press, 2018) Sung, Y.J.; Winkler, T.W.; de Las Fuentes, L.; Bentley, A.R.; Brown, M.R.; Kraja, A.T.; Schwander, K.; Ntalla, I.; Guo, X.; Franceschini, N.; Lu, Y.; Cheng, C.Y.; Sim, X.; Vojinovic, D.; Marten, J.; Musani, S.K.; Li, C.; Feitosa, M.F.; Kilpelainen, T.O.; Richard, M.A.; Noordam, R.; Aslibekyan, S.; Aschard, H.; Bartz, T.M.; Dorajoo, R.; Liu, Y.; Manning, A.K.; Rankinen, T.; Smith, A.V.; Tajuddin, S.M.; Tayo, B.O.; Warren, H.R.; Zhao, W.; Zhou, Y.; Matoba, N.; Sofer, T.; Alver, M.; Amini, M.; Boissel, M.; Chai, J.F.; Chen, X.; Divers, J.; Gandin, I.; Gao, C.; Giulianini, F.; Goel, A.; Harris, S.E.; Hatwig, F.P.; Horimoto, A.R.V.R.; Hsu, F.C.; Jackson, A.U.; Kahonen, M.; Kasturiratne, A.; Kuhnel, B.; Leander, K.; Lee, W.J.; Lin, K.H.; an Luan, J.; McKenzie, C.A.; Meian, H.; Nelson, C.P.; Rauramaa, R.; Schupf, N.; Scott, R.A.; Sheu, W.H.H.; Stancakova, A.; Takeuchi, F.; van der Most, P.J.; Varga, T.V.; Wang, H.; Wang, Y.; Ware, E.B.; Weiss, S.; Wen, W.; Yanek, L.R.; Zhang, W.; Zhao, J.H.; Afag, S.; Alfred, T.; Amin, N.; Arking, D.; Aung, T.; Barr, R.G.; Bielak, L.F.; Boerwincle, E.; Bottinger, E.P.; Braund, P.S.; Brody, J.A.; Broeckel, U.; Cabrera, C.P.; Cade, B.; Caizheng, Y.; Campbell, A.; Canouil, M.; Chakravarti, A.; CHARGE Neurology Working Group; Chauhan, G.; Christensen, K.; Cocca, M.; COGENT-Kidney Consortium; Collins, F.S.; Connel, J.M.; de Mutsert, R.; de Silva, H.J.; Debette, S.; Dorr, M.; Duan, Q.; Eaton, C.B.; Ehret, G.; Evangelou, E.; FAul, J.D.; Fisher, V.A.; Forouhi, N.G.; Franco, O.H.; Friedlander, Y.; Gao, H.; GIANT Consortium; Gigante, B.; Graff, M.; Gu, C.C.; Gu, D.; Gupta, P.; Hagenaars, S.P.; Harris, T.B.; He, J.; Heikkinen, S.; Heng, C.K.; Hirata, M.; Hofman., A.; Howard, B.V.; Hunt, S.; Irvin, M.R.; Jia, Y.; Joehanes, R.; Justice, A.E.; Katsuya, T.; Kaufman, J,; Kerrison, N.D.; Khor, C.C.; Koh, W.P.; Koistinen, H.A.; Komulainen, P.; Kooperberg, C.; Krieger, J.E.; Kubo, M.; Kuusisto, J.; Lanefeld, C.D.; Langenberg, C.; Launer, L.J.; Lehne, B.; Lewis, C.E.; Li, Y.; Lifelines Cohort Study; Lim, S.H.; Lin, S.; Liu, C.T.; Liu, J.; Liu, J.; Liu, K.; Liu, Y.; Loh, M.; Lohmann, K.K.; Long, J.; Louie, T.; Magi, R.; Mahajan, A.; Meitinger, T.; Metspalu, A.; Milani, L.; Momozawa, Y.; Morris, A.P.; Mosley, T.H.Jr.; Munson, P.; Murray, A.D.; Nalls, M.A.; Nasri, U.; Norris, J.M.; North, K.; Ogunniyi, A.; Padmanabhan, S.; Palmas, W.R.; Palmer, N.D.; Pankow, J.S.; Pedersen, N.L.; Peters, A.; Peyser, P.A.; Polasek, O.; Raitakari, O.T.; Renstrom, F.; Rice, T.K.; Ridker, P.M.; Robino, A.; Robinson, J.G.; Rose, L.M.; Rudan, I.; Salako, B.L.; Sandow, K.; Schmidt, C.O.; Schreiner, P.J.; Scott, W.R.; Seshadri, S.; Sever, P.; Sitlani, C.M.; Smith, J.A.; Snieder, H.; Starr, J.M.; Strauch, K.; Tang, H.; Taylor, K.D.; Teo, Y.Y.; Tham, Y.C.; Uitterlineden, A.G.; Waldenberger, M.; Wang, L.; Wang, Y.X.; Wei, W.B.; Williams, C.; Wilson, G.; Wojczynski, M.K.; Yao, J.; Yuan, J.M.; Zonderman, A.B.; Becker, D.M.; Boehnke, M.; Bowden, D.W.; Chambers, J.C.; Chen, Y.I.; de Faire, U.; Deary, I.J.; Esco, T.; Farrall, M.; Forrester, T.; Franks, P.W.; Freedman, B.I.; Froguel, P.; Gasparini, P.; Gieger, C.; Horta, B.L.; Hung, Y.J.; Jonas, J.B.; Kato, N.; Kooner, J.S.; Laakso, M.; Lehtimaki, T.; Liang, K.W.; Magnusson, P.K.E.; Newman, A.B.; Oldehinkel, A.J.; Pereira, A.C.; Redline, S.; Rettig, R.; Samani, N.J.; Scott, J.; Shu, X.O.; van der Harst, P.; Wagenknecht, L.E.; Wareham, N.J.; Watkins, H.; Weir, D.R.; Wickremasinghe, A.R.; Wu, T.; Zheng, W.; Kamatani, Y.; Laurie, C.C.; Bouchard, C.; Cooper, R.S.; Evans, M.K.; Gudnason, V.; Kardia, S.L.R.; Kritchevsky, S.B.; Levy, D.; O'Connell, J.R.; Psaty, B.M.; van Dam, R.M.; Sims, M.; Arnett, D.K.; Mook-Kanamori, D.O.; Kelly, T.N.; Fox, E.R.; Hayward, C.; Fornage, M.; Rotimi, C.N.; Province, M.A.; van Dujin, C.M.; Tai, E.S.; Wong, T.Y.; Loos, R.J.F.; Reiner, A.P.; Rotter, J.I.; Zhu, X.; Bierut, L.J.; Gauderman, W.J.; Caulfield, M.J.; Elliott, P.; Rice, K.; Munroe, P.B.; Morrison, A.C.; Cupples, L.A.; Rao., D.C.; Chasman, D.I.
    Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10-8) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10-8). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).
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    Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity
    (Nature Publishing Group, 2017) Whal, S.; Drong, A.; Lehne, B.; Loh, M.; Scott, W.R.; Kunze, S.; Tsai, P.C.; Ried, J.S.; Zhang, W.; Yang, Y.; Tan, S.; Fiorito, G.; Franke, L.; Guarrera, S.; Kasela, S.; Kriebel, J.; Richmond, R.C.; Adamo, M.; Afzal, U.; Ala-Korpela, M.; Albeetti, B.; Ammerpohl, O.; Apperley, J.F.; Beekman, M.; Bertazzi, P.A.; Black, S.L.; Blancher, C.; Bonder, M.J.; Brosch, M.; Carstensen-Kirberg, M.; de Craen, A.J.; de Lusignan, S.; Dehghan, A.; Elkalaawy, M.; Fischer, K.; Franco, O.H.; Gaunt, T.R.; Hampe, J.; Hashemi, M.; Isaacs, A.; Jenkinson, A.; Jha, S.; Kato, N.; Krogh, V.; Laffan, M.; Meisinger, C.; Meitinger, T.; Mok, Z.Y.; Motta, V.; Ng, H.K.; Nikolakopoulou, Z.; Nteliopoulos, G.; Panico, S.; Pervjakova, N.; Prokisch, H.; Rathmann, W.; Roden, M.; Rota, F.; Rozario, M.A.; Sandling, J.K.; Schafmayer, C.; Schramm, K.; Siebert, R.; Slagboom, P.E.; Soininen, P.; Stolk, L.; Strauch, K.; Tai, E.S.; Tarantini, L.; Thorand, B.; Tigchelaar, E.F.; Tumino, R.; Uitterlinden, A.G.; van Duijn, C.; van Meurs, J.B.; Vineis, P.; Wickremasinghe, A.R.; Wijmenga, C.; Yang, T.P.; Yuan, W.; Zhernakova, A.; Batterham, R.L.; Smith, G.D.; Deloukas, P.; Heijmans, B.T.; Herder, C.; Hofman, A.; Lindgren, C.M.; Milani, L.; van der Harst, P.; Peters, A.; Illig, T.; Relton, C.L.; Waldenberger, M.; Järvelin, M.R.; Bollati, V.; Soong, R.; Spector, T.D.; Scott, J.; McCarthy, M.I.; Elliott, P.; Bell, J.T.; Matullo, G.; Gieger, C.; Kooner, J.S.; Grallert, H.; Chambers, J.C.
    Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances. Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation, a key regulator of gene expression and molecular phenotype. Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 × 10-7, range P = 9.2 × 10-8 to 6.0 × 10-46; n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 × 10-6, range P = 5.5 × 10-6 to 6.1 × 10-35, n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07-2.56); P = 1.1 × 10-54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.
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    Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation
    (Nature Publishing Company, 2015) Kato, N.; Loh, M.; Takeuchi, F.; Verweij, N.; Wang, X.; Zhang, W.; Kelly, T.N.; Saleheen, D.; Lehne, B.; Leach, I.M.; Drong, A.W.; Abbott, J.; Wahl, S.; Tan, S.T.; Scott, W.R.; Campanella, G.; Chadeau-Hyam, M.; Afzal, U.; Ahluwalia, T.S.; Bonder, M.J.; Chen, P.; Dehghan, A.; Edwards, T.L.; Esko, T.; Go, M.J.; Harris, S.E.; Hartiala, J.; Kasela, S.; Kasturiratne, A.; Khor, C.C.; Kleber, M.E.; Li, H.; Mok, Z.Y.; Nakatochi, M.; Sapari, N.S.; Saxena, R.; Stewart, A.F.; Stolk, L.; Tabara, Y.; Teh, A.L.; Wu, Y.; Wu, J.Y.; Zhang, Y.; Aits, I.; Da Silva Couto Alves, A.; Das, S.; Dorajoo, R.; Hopewell, J.C.; Kim, Y.K.; Koivula, R.W.; Luan, J.; Lyytikäinen, L.P.; Nguyen, Q.N.; Pereira, M.A.; Postmus, I.; Raitakari, O.T.; Bryan, M.S.; Scott, R.A.; Sorice, R.; Tragante, V.; Traglia, M.; White, J.; Yamamoto, K.; Zhang, Y.; Adair, L.S.; Ahmed, A.; Akiyama, K.; Asif, R.; Aung, T.; Barroso, I.; Bjonnes, A.; Braun, T.R.; Cai, H.; Chang, L.C.; Chen, C.H.; Cheng, C.Y.; Chong, Y.S.; Collins, R.; Courtney, R.; Davies, G.; Delgado, G.; Do, L.D.; Doevendans, P.A.; Gansevoort, R.T.; Gao, Y.T.; Grammer, T.B.; Grarup, N.; Grewal, J.; Gu, D.; Wander, G.S.; Hartikainen, A.L.; Hazen, S.L.; He, J.; Heng, C.K.; Hixson, J.E.; Hofman, A.; Hsu, C.; Huang, W.; Husemoen, L.L.; Hwang, J.Y.; Ichihara, S.; Igase, M.; Isono, M.; Justesen, J.M.; Katsuya, T.; Kibriya, M.G.; Kim, Y.J.; Kishimoto, M.; Koh, W.P.; Kohara, K.; Kumari, M.; Kwek, K.; Lee, N.R.; Lee, J.; Liao, J.; Lieb, W.; Liewald, D.C.; Matsubara, T.; Matsushita, Y.; Meitinger, T.; Mihailov, E.; Milani, L.; Mills, R.; Mononen, N.; Müller-Nurasyid, M.; Nabika, T.; Nakashima, E.; Ng, H.K.; Nikus, K.; Nutile, T.; Ohkubo, T.; Ohnaka, K.; Parish, S.; Paternoster, L.; Peng, H.; Peters, A.; Pham, S.T.; Pinidiyapathirage, M.J.; Rahman, M.; Rakugi, H.; Rolandsson, O.; Rozario, M.A.; Ruggiero, D.; Sala, C.F.; Sarju, R.; Shimokawa, K.; Snieder, H.; Sparso, T.; Spiering, W.; Starr, J.M.; Stott, D.J.; Stram, D.O.; Sugiyama, T.; Szymczak, S.; Tang, W.H.; Tong, L.; Trompet, S.; Turjanmaa, V.; Ueshima, H.; Uitterlinden, A.G.; Umemura, S.; Vaarasmaki, M.; van Dam, R.M.; van Gilst, W.H.; van Veldhuisen, D.J.; Viikari, J.S.; Waldenberger, M.; Wang, Y.; Wang, A.; Wilson, R.; Wong, T.Y.; Xiang, Y.B.; Yamaguchi, S.; Ye, X.; Young, R.D.; Young, T.L.; Yuan, J.M.; Zhou, X.; Asselbergs, F.W.; Ciullo, M.; Clarke, R.; Deloukas, P.; Franke, A.; Franks, P.W.; Franks, S.; Friedlander, Y.; Gross, M.D.; Guo, Z.; Hansen, T.; Jarvelin, M.R.; Jorgensen, T.; Jukema, J.W.; Kähönen, M.; Kajio, H.; Kivimaki, M.; Lee, J.Y.; Lehtimäki, T.; Linneberg, A.; Miki, T.; Pedersen, O.; Samani, N.J.; Sorensen, T.I.; Takayanagi, R.; Toniolo, D.; BIOS-consortium; CARDIo GRAMplusCD; LifeLines Cohort Study; InterAct Consortium; Ahsan, H.; Allayee, H.; Chen, Y.T.; Danesh, J.; Deary, I.J.; Franco, O.H.; Franke, L.; Heijman, B.T.; Holbrook, J.D.; Isaacs, A.; Kim, B.J.; Lin, X.; Liu, J.; März, W.; Metspalu, A.; Mohlke, K.L.; Sanghera, D.K.; Shu, X.O.; van Meurs, J.B.; Vithana, E.; Wickremasinghe, A.R.; Wijmenga, C.; Wolffenbuttel, B.H.; Yokota, M.; Zheng, W.; Zhu, D.; Vineis, P.; Kyrtopoulos, S.A.; Kleinjans, J.C.; McCarthy, M.I.; Soong, R.; Gieger, C.; Scott, J.; Teo, Y.Y.; He, J.; Elliott, P.; Tai, E.S.; van der Harst, P.; Kooner, J.S.; Chambers, J.C.
    We carried out a trans-ancestry genome-wide association and replication study of blood pressurephenotypes 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 DNAmethylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNAmethylation 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.
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    Genome-wide association study in individuals of South Asian ancestry identifies six new type-2 diabetes susceptibility loci
    (Nature Publishing Company, 2011) Kooner, J.S.; Saleheen, D.; Sim, X.; Sehmi, J.; Zhang, W.; Frossard, P.; Been, L.F.; Chia, K.S.; Dimas, A.S.; Hassanali, N.; Jafar, T.; Jowett, J.B.; Li, X.; Radha, V.; Rees, S.D.; Takeuchi, F.; Young, R.; Aung, T.; Basit, A.; Chidambaram, M.; Das, D.; Grundberg, E.; Hedman, A.K.; Hydrie, Z.I.; Islam, M.; Khor, C.C.; Kowlessur, S.; Kristensen, M.M.; Liju, S.; Lim, W.Y.; Matthews, D.R.; Liu, J.; Morris, A.P.; Nica, A.C.; Pinidiyapathirage, M.J.; Prokopenko, I.; Rasheed, A.; Samuel, M.; Shah, N.; Shera, A.S.; Small, K.S.; Suo, C.; Wickremasinghe, A.R.; Wong, T.Y.; Yang, M.; Zhang, F.
    We carried out a genome-wide association study of type-2 diabetes (T2D) in individuals of South Asian ancestry. Our discovery set included 5,561 individuals with T2D (cases) and 14,458 controls drawn from studies in London, Pakistan and Singapore. We identified 20 independent SNPs associated with T2D at P < 10(-4) for testing in a replication sample of 13,170 cases and 25,398 controls, also all of South Asian ancestry. In the combined analysis, we identified common genetic variants at six loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) newly associated with T2D (P = 4.1 × 10(-8) to P = 1.9 × 10(-11)). SNPs at GRB14 were also associated with insulin sensitivity (P = 5.0 × 10(-4)), and SNPs at ST6GAL1 and HNF4A were also associated with pancreatic beta-cell function (P = 0.02 and P = 0.001, respectively). Our findings provide additional insight into mechanisms underlying T2D and show the potential for new discovery from genetic association studies in South Asians, a population with increased susceptibility to T2D.