| Publication Information (EuropePMC) | |
| Title | Implicating genes, pleiotropy and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis |
| doi | 10.1101/2021.12.15.21267852 |
| Publication Date | Dec. 16, 2021 |
| Journal | medRxiv Preprint |
| Author(s) | Kanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJ, Wu KH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao J, Matsuda F, Jang H, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu C, Hung Y, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Vazquez-Moreno M, Feitosa MF, Wojczynski MK, Wang Z, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Tsao NL, Verma A, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Frank M, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Bayyana S, Stringham HM, Irvin MR, Oldmeadow C, Kim H, Ryu S, Timmers PR, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Chen S, Liu F, Yang J, Kentistou KA, Banas B, Nardone GG, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki A, Hofer E, Lin M, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, van der Laan SW, Chitrala KN, Weiss S, Bentley AR, Doumatey AP, Adeyemo AA, Lee JY, Petersen ER, Nielsen AA, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin S, Wang J, Couture C, Lyytikäinen L, Nikus K, Cuellar-Partida G, Vestergaard H, Hidalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Liang J, Tang H, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Zhengmin. |
| 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) |
|---|---|---|---|---|---|---|
| PGS002784 (GLGC_2021_ALL_logTG_PRS_weights_PT) |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Triglycerides | triglyceride measurement | 30,071 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002784/ScoringFiles/PGS002784.txt.gz |
| PGS002782 (GLGC_2021_ALL_nonHDL_PRS_weights_PRS-CS) |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
nonHDL Cholesterol | non-high density lipoprotein cholesterol measurement | 1,239,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002782/ScoringFiles/PGS002782.txt.gz |
| PGS002781 (GLGC_2021_ALL_HDL_PRS_weights_PRS-CS) |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 1,239,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002781/ScoringFiles/PGS002781.txt.gz |
| PGS002783 (GLGC_2021_ALL_TC_PRS_weights_PT) |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Total cholesterol | total cholesterol measurement | 10,699 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002783/ScoringFiles/PGS002783.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM016161 | PGS002781 (GLGC_2021_ALL_HDL_PRS_weights_PRS-CS) |
PSS010052| Multi-ancestry (including European)| 461,918 individuals |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Reported Trait: Baseline HDL cholesterol | — | — | R²: 0.13 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM016162 | PGS002782 (GLGC_2021_ALL_nonHDL_PRS_weights_PRS-CS) |
PSS010052| Multi-ancestry (including European)| 461,918 individuals |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Reported Trait: Baseline nonHDL cholesterol | — | — | R²: 0.14 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM016163 | PGS002783 (GLGC_2021_ALL_TC_PRS_weights_PT) |
PSS010052| Multi-ancestry (including European)| 461,918 individuals |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Reported Trait: Baseline Total cholesterol | — | — | R²: 0.14 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM016164 | PGS002784 (GLGC_2021_ALL_logTG_PRS_weights_PT) |
PSS010052| Multi-ancestry (including European)| 461,918 individuals |
PGP000366 | Kanoni S et al. medRxiv (2021) |Pre |
Reported Trait: Baseline Triglycerides | — | — | R²: 0.1 | sex, batch, age at initial assessment, PCs1-4 | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS010052 | — | — | 461,918 individuals | — | European, African unspecified, East Asian, South Asian | — | UKB | — |