PGS Preprint: PGP000366

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.
Released in PGS Catalog: Dec. 6, 2022

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported

PGS Developed By This Publication

Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
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
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
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
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

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

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 : 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 : 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 : 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 : 0.1 sex, batch, age at initial assessment, PCs1-4

Evaluated Samples

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