Publication Information (EuropePMC) | |
Title | The trans-ancestral genomic architecture of glycemic traits. |
PubMed ID | 34059833(Europe PMC) |
doi | 10.1038/s41588-021-00852-9 |
Publication Date | May 31, 2021 |
Journal | Nat Genet |
Author(s) | Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J, Willems SM, Wu Y, Zhang X, Horikoshi M, Boutin TS, Mägi R, Waage J, Li-Gao R, Chan KHK, Yao J, Anasanti MD, Chu AY, Claringbould A, Heikkinen J, Hong J, Hottenga JJ, Huo S, Kaakinen MA, Louie T, März W, Moreno-Macias H, Ndungu A, Nelson SC, Nolte IM, North KE, Raulerson CK, Ray D, Rohde R, Rybin D, Schurmann C, Sim X, Southam L, Stewart ID, Wang CA, Wang Y, Wu P, Zhang W, Ahluwalia TS, Appel EVR, Bielak LF, Brody JA, Burtt NP, Cabrera CP, Cade BE, Chai JF, Chai X, Chang LC, Chen CH, Chen BH, Chitrala KN, Chiu YF, de Haan HG, Delgado GE, Demirkan A, Duan Q, Engmann J, Fatumo SA, Gayán J, Giulianini F, Gong JH, Gustafsson S, Hai Y, Hartwig FP, He J, Heianza Y, Huang T, Huerta-Chagoya A, Hwang MY, Jensen RA, Kawaguchi T, Kentistou KA, Kim YJ, Kleber ME, Kooner IK, Lai S, Lange LA, Langefeld CD, Lauzon M, Li M, Ligthart S, Liu J, Loh M, Long J, Lyssenko V, Mangino M, Marzi C, Montasser ME, Nag A, Nakatochi M, Noce D, Noordam R, Pistis G, Preuss M, Raffield L, Rasmussen-Torvik LJ, Rich SS, Robertson NR, Rueedi R, Ryan K, Sanna S, Saxena R, Schraut KE, Sennblad B, Setoh K, Smith AV, Sparsø T, Strawbridge RJ, Takeuchi F, Tan J, Trompet S, van den Akker E, van der Most PJ, Verweij N, Vogel M, Wang H, Wang C, Wang N, Warren HR, Wen W, Wilsgaard T, Wong A, Wood AR, Xie T, Zafarmand MH, Zhao JH, Zhao W, Amin N, Arzumanyan Z, Astrup A, Bakker SJL, Baldassarre D, Beekman M, Bergman RN, Bertoni A, Blüher M, Bonnycastle LL, Bornstein SR, Bowden DW, Cai Q, Campbell A, Campbell H, Chang YC, de Geus EJC, Dehghan A, Du S, Eiriksdottir G, Farmaki AE, Frånberg M, Fuchsberger C, Gao Y, Gjesing AP, Goel A, Han S, Hartman CA, Herder C, Hicks AA, Hsieh CH, Hsueh WA, Ichihara S, Igase M, Ikram MA, Johnson WC, Jørgensen ME, Joshi PK, Kalyani RR, Kandeel FR, Katsuya T, Khor CC, Kiess W, Kolcic I, Kuulasmaa T, Kuusisto J, Läll K, Lam K, Lawlor DA, Lee NR, Lemaitre RN, Li H, Lifelines Cohort Study, Lin SY, Lindström J, Linneberg A, Liu J, Lorenzo C, Matsubara T, Matsuda F, Mingrone G, Mooijaart S, Moon S, Nabika T, Nadkarni GN, Nadler JL, Nelis M, Neville MJ, Norris JM, Ohyagi Y, Peters A, Peyser PA, Polasek O, Qi Q, Raven D, Reilly DF, Reiner A, Rivideneira F, Roll K, Rudan I, Sabanayagam C, Sandow K, Sattar N, Schürmann A, Shi J, Stringham HM, Taylor KD, Teslovich TM, Thuesen B, Timmers PRHJ, Tremoli E, Tsai MY, Uitterlinden A, van Dam RM, van Heemst D, van Hylckama Vlieg A, van Vliet-Ostaptchouk JV, Vangipurapu J, Vestergaard H, Wang T, Willems van Dijk K, Zemunik T, Abecasis GR, Adair LS, Aguilar-Salinas CA, Alarcón-Riquelme ME, An P, Aviles-Santa L, Becker DM, Beilin LJ, Bergmann S, Bisgaard H, Black C, Boehnke M, Boerwinkle E, Böhm BO, Bønnelykke K, Boomsma DI, Bottinger EP, Buchanan TA, Canouil M, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Cheng CY, Collins FS, Correa A, Cucca F, de Silva HJ, Dedoussis G, Elmståhl S, Evans MK, Ferrannini E, Ferrucci L, Florez JC, Franks PW, Frayling TM, Froguel P, Gigante B, Goodarzi MO, Gordon-Larsen P, Grallert H, Grarup N, Grimsgaard S, Groop L, Gudnason V, Guo X, Hamsten A, Hansen T, Hayward C, Heckbert SR, Horta BL, Huang W, Ingelsson E, James PS, Jarvelin MR, Jonas JB, Jukema JW, Kaleebu P, Kaplan R, Kardia SLR, Kato N, Keinanen-Kiukaanniemi SM, Kim BJ, Kivimaki M, Koistinen HA, Kooner JS, Körner A, Kovacs P, Kuh D, Kumari M, Kutalik Z, Laakso M, Lakka TA, Launer LJ, Leander K, Li H, Lin X, Lind L, Lindgren C, Liu S, Loos RJF, Magnusson PKE, Mahajan A, Metspalu A, Mook-Kanamori DO, Mori TA, Munroe PB, Njølstad I, O'Connell JR, Oldehinkel AJ, Ong KK, Padmanabhan S, Palmer CNA, Palmer ND, Pedersen O, Pennell CE, Porteous DJ, Pramstaller PP, Province MA, Psaty BM, Qi L, Raffel LJ, Rauramaa R, Redline S, Ridker PM, Rosendaal FR, Saaristo TE, Sandhu M, Saramies J, Schneiderman N, Schwarz P, Scott LJ, Selvin E, Sever P, Shu XO, Slagboom PE, Small KS, Smith BH, Snieder H, Sofer T, Sørensen TIA, Spector TD, Stanton A, Steves CJ, Stumvoll M, Sun L, Tabara Y, Tai ES, Timpson NJ, Tönjes A, Tuomilehto J, Tusie T, Uusitupa M, van der Harst P, van Duijn C, Vitart V, Vollenweider P, Vrijkotte TGM, Wagenknecht LE, Walker M, Wang YX, Wareham NJ, Watanabe RM, Watkins H, Wei WB, Wickremasinghe AR, Willemsen G, Wilson JF, Wong TY, Wu JY, Xiang AH, Yanek LR, Yengo L, Yokota M, Zeggini E, Zheng W, Zonderman AB, Rotter JI, Gloyn AL, McCarthy MI, Dupuis J, Meigs JB, Scott RA, Prokopenko I, Leong A, Liu CT, Parker SCJ, Mohlke KL, Langenberg C, Wheeler E, Morris AP, Barroso I, Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC). |
Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
---|---|---|---|---|---|---|
PGS001350 (MAGICTA_EUR_PGS_FG) |
PGP000246 | Chen J et al. Nat Genet (2021) |
Fasting glucose | fasting blood glucose measurement | 1,023,373 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001350/ScoringFiles/PGS001350.txt.gz | |
PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PGP000246 | Chen J et al. Nat Genet (2021) |
Glycated haemoglobin levels (HbA1c) | HbA1c measurement | 1,018,836 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001352/ScoringFiles/PGS001352.txt.gz | |
PGS001351 (MAGICTA_EUR_PGS_FI) |
PGP000246 | Chen J et al. Nat Genet (2021) |
Fasting insulin | fasting blood insulin measurement | 1,025,098 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001351/ScoringFiles/PGS001351.txt.gz |
PGS Performance Metric ID (PPM) |
Evaluated Score |
PGS Sample Set ID (PSS) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
Classification Metrics | Other Metrics | Covariates Included in the Model |
PGS Performance: Other Relevant Information |
---|---|---|---|---|---|---|---|---|---|
PPM005137 | PGS001350 (MAGICTA_EUR_PGS_FG) |
PSS003587| European Ancestry| 45,038 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting glucose | — | — | R²: 0.229 | — | — |
PPM005138 | PGS001351 (MAGICTA_EUR_PGS_FI) |
PSS003590| European Ancestry| 29,123 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting insulin | — | — | R²: 0.095 | — | — |
PPM005139 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003594| European Ancestry| 61,820 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.178 | — | — |
PPM005140 | PGS001350 (MAGICTA_EUR_PGS_FG) |
PSS003585| African Ancestry| 16,579 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting glucose | — | — | R²: 0.032 | — | — |
PPM005141 | PGS001351 (MAGICTA_EUR_PGS_FI) |
PSS003588| African Ancestry| 8,101 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting insulin | — | — | R²: 0.028 | — | — |
PPM005142 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003591| African Ancestry| 6,647 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.012 | — | — |
PPM005143 | PGS001350 (MAGICTA_EUR_PGS_FG) |
PSS003586| East Asian Ancestry| 31,669 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting glucose | — | — | R²: 0.027 | — | — |
PPM005144 | PGS001351 (MAGICTA_EUR_PGS_FI) |
PSS003589| East Asian Ancestry| 26,691 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Fasting insulin | — | — | R²: 0.014 | — | — |
PPM005145 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003593| East Asian Ancestry| 31,236 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.026 | — | — |
PPM005146 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003592| African Ancestry| 4,441 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.006 | — | — |
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
---|---|---|---|---|---|---|---|---|
PSS003594 | — | — | 61,820 individuals | — | European | — | EPIC, InterAct, LifeLines, METSIM, WGHS | — |
PSS003585 | — | — | 16,579 individuals | — | African American or Afro-Caribbean | — | 10 cohorts
|
— |
PSS003586 | — | — | 31,669 individuals | — | East Asian (Japanese, Chinese, Malay, Filipino, Han Chinese) |
— | 13 cohorts
|
— |
PSS003587 | — | — | 45,038 individuals | — | European | — | ARIC, LifeLines, METSIM, TwinGene | Additional cases and controls were obtained from Fenland-OMICS. |
PSS003588 | — | — | 8,101 individuals | — | African American or Afro-Caribbean | — | 9 cohorts
|
— |
PSS003589 | — | — | 26,691 individuals | — | East Asian (Japanese, Filipino, Chinese, Han Chinese) |
— | 10 cohorts
|
— |
PSS003590 | — | — | 29,123 individuals | — | European | — | ARIC, METSIM, NTR, PROCARDIS | — |
PSS003591 | — | — | 6,647 individuals | — | African American or Afro-Caribbean | — | ARIC, BioMe, HANDLS, JHS, MESA | — |
PSS003592 | — | — | 4,441 individuals | — | Sub-Saharan African (Ugandan) |
— | NR | — |
PSS003593 | — | — | 31,236 individuals | — | East Asian (Japanese, Chinese, Malay, Han Chinese) |
— | 15 cohorts
|
— |