2 |
The trans-ancestral genomic architecture of glycemic traits.
|
|
|
|
BASE
|
|
Show details
|
|
3 |
The trans-ancestral genomic architecture of glycemic traits.
|
|
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, KHK; 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, EVR; 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, SJL; 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, EJC; 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.; Lin, S.Y.; Lindström, J.; Linneberg, A.; 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, PRHJ; 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, SLR; 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.; Lin, X.; Lind, L.; Lindgren, C.; Liu, S.; Loos, RJF; Magnusson, PKE; 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, CNA; 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, TIA; 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, TGM; 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, SCJ; Mohlke, K.L.; Langenberg, C.; Wheeler, E.; Morris, A.P.; Barroso, I.
|
|
In: Nature genetics, vol. 53, no. 6, pp. 840-860 (2021)
|
|
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.
|
|
Keyword:
Alleles; Blood Glucose/genetics; Epigenesis; European Continental Ancestry Group/genetics; Gene Expression Profiling; Genetic; Genome; Genome-Wide Association Study; Glycated Hemoglobin A/metabolism; Heritable; Human; Humans; Multifactorial Inheritance/genetics; Physical Chromosome Mapping; Quantitative Trait; Quantitative Trait Loci/genetics
|
|
URL: https://serval.unil.ch/notice/serval:BIB_53C688CA509F http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_53C688CA509F9 https://serval.unil.ch/resource/serval:BIB_53C688CA509F.P001/REF.pdf https://doi.org/10.1038/s41588-021-00852-9
|
|
BASE
|
|
Hide details
|
|
4 |
Relationship between subacute brain activity and aphasia recovery
|
|
|
|
BASE
|
|
Show details
|
|
6 |
A Comparison of NAL and DSL Prescriptive Methods for Pediatric Hearing Aid Fittings: Estimates of Speech Intelligibility, Loudness, and Safety
|
|
|
|
In: ETSU Faculty Works (2012)
|
|
BASE
|
|
Show details
|
|
7 |
Modulation of N400 in chronic non-fluent aphasia using low frequency Repetitive Transcranial Magnetic Stimulation (rTMS)
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Improved language performance subsequent to low-frequency rTMS in patients with chronic non-fluent aphasia post-stroke
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Differentiating Cantonese-Speaking Preschool Children With and Without SLI Using MLU and lexical Diversity (D)
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Early Oral Language Markers of Poor Reading Performance in Hong Kong Chinese Children
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Assessing Cantonese-speaking children with language difficulties from the perspective of evidence-based practice: Current practice and future directions
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Morphosyntactic deficits in Cantonese-speaking children with specific language impairment
|
|
|
|
BASE
|
|
Show details
|
|
13 |
Are our medical graduates in New Zealand safe and accurate in ECG interpretation?
|
|
|
|
In: http://www.nzma.org.nz/journal/122-1292/3536/ (2009)
|
|
BASE
|
|
Show details
|
|
14 |
Quantitative analysis of translation revision:contrastive corpus research on native English and Chinese translationese
|
|
|
|
BASE
|
|
Show details
|
|
15 |
What's in a word? Morphological awareness and vocabulary knowledge in three languages
|
|
|
|
In: Applied Psycholinguistics, 01-07-2008 (2008)
|
|
BASE
|
|
Show details
|
|
16 |
Student Perceptions of Chemistry Laboratory Learning Environments, Student-Teacher Interactions and Attitudes in Secondary School Gifted Education Classes in Singapore.
|
|
|
|
BASE
|
|
Show details
|
|
17 |
and then gives the learner the telegraphic and diagrammatic representations of the problem, which are more
|
|
|
|
In: http://www.csie.cyut.edu.tw/~shwu/publication/Wong C and E 2005.pdf (2004)
|
|
BASE
|
|
Show details
|
|
|
|