| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004339 |
| Description | The distance from the sole to the crown of the head with body standing on a flat surface and fully extended. | Trait category |
Body measurement
|
| Synonym | height |
| Mapped terms |
3 mapped terms
|
| 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) |
|---|---|---|---|---|---|---|
| PGS000297 (GRS3290_Height) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Height | body height | 3,290 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000297/ScoringFiles/PGS000297.txt.gz |
| PGS000758 (LASSO_Height) |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Adult standing height | body height | 33,938 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000758/ScoringFiles/PGS000758.txt.gz | |
| PGS001229 (GBE_INI50) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Standing height | body height | 51,209 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001229/ScoringFiles/PGS001229.txt.gz |
| PGS001405 (GBE_INI12144) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Height | body height | 3,166 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001405/ScoringFiles/PGS001405.txt.gz |
| PGS001929 (portability-PLR_height) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Standing height | body height | 156,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001929/ScoringFiles/PGS001929.txt.gz |
| PGS002146 (portability-ldpred2_height) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Standing height | body height | 922,538 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002146/ScoringFiles/PGS002146.txt.gz |
| PGS002332 (body_HEIGHTz.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002332/ScoringFiles/PGS002332.txt.gz |
| PGS002368 (body_HEIGHTz.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 920,927 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002368/ScoringFiles/PGS002368.txt.gz |
| PGS002404 (body_HEIGHTz.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 56,984 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002404/ScoringFiles/PGS002404.txt.gz |
| PGS002453 (body_HEIGHTz.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 103,911 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002453/ScoringFiles/PGS002453.txt.gz |
| PGS002502 (body_HEIGHTz.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 262,080 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002502/ScoringFiles/PGS002502.txt.gz |
| PGS002551 (body_HEIGHTz.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 27,070 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002551/ScoringFiles/PGS002551.txt.gz |
| PGS002600 (body_HEIGHTz.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 18,937 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002600/ScoringFiles/PGS002600.txt.gz |
| PGS002649 (body_HEIGHTz.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 478,839 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002649/ScoringFiles/PGS002649.txt.gz |
| PGS002698 (body_HEIGHTz.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Height | body height | 986,966 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002698/ScoringFiles/PGS002698.txt.gz |
| PGS002748 (PRS_251) |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Height | body height | 251 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002748/ScoringFiles/PGS002748.txt.gz |
| PGS002800 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_SAS) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 1,156,741 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002800/ScoringFiles/PGS002800.txt.gz |
| PGS002801 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_AFR) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 975,455 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002801/ScoringFiles/PGS002801.txt.gz |
| PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 1,103,042 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002802/ScoringFiles/PGS002802.txt.gz |
| PGS002803 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_EAS) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 990,792 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002803/ScoringFiles/PGS002803.txt.gz |
| PGS002804 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_EUR) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 1,099,005 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002804/ScoringFiles/PGS002804.txt.gz |
| PGS002805 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_HIS) |
PGP000382 | Yengo L et al. Nature (2022) |
Height | body height | 1,245,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002805/ScoringFiles/PGS002805.txt.gz |
| PGS002964 (ExPRSweb_Height_50-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,291,379 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002964/ScoringFiles/PGS002964.txt.gz | |
| PGS002965 (ExPRSweb_Height_50-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 34,284 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002965/ScoringFiles/PGS002965.txt.gz | |
| PGS002966 (ExPRSweb_Height_50-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 49,307 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002966/ScoringFiles/PGS002966.txt.gz | |
| PGS002967 (ExPRSweb_Height_50-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 10,297,259 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002967/ScoringFiles/PGS002967.txt.gz | |
| PGS002968 (ExPRSweb_Height_50-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002968/ScoringFiles/PGS002968.txt.gz | |
| PGS002969 (ExPRSweb_Height_50-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,296,068 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002969/ScoringFiles/PGS002969.txt.gz | |
| PGS002970 (ExPRSweb_Height_50-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 31,805 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002970/ScoringFiles/PGS002970.txt.gz | |
| PGS002971 (ExPRSweb_Height_50-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 44,500 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002971/ScoringFiles/PGS002971.txt.gz | |
| PGS002972 (ExPRSweb_Height_50-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 10,297,262 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002972/ScoringFiles/PGS002972.txt.gz | |
| PGS002973 (ExPRSweb_Height_50-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002973/ScoringFiles/PGS002973.txt.gz | |
| PGS002974 (ExPRSweb_Height_GIANT-Yang2012-height_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 66,842 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002974/ScoringFiles/PGS002974.txt.gz | |
| PGS002975 (ExPRSweb_Height_GIANT-Yang2012-height_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 22,154 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002975/ScoringFiles/PGS002975.txt.gz | |
| PGS002976 (ExPRSweb_Height_GIANT-Yang2012-height_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 22,443 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002976/ScoringFiles/PGS002976.txt.gz | |
| PGS002977 (ExPRSweb_Height_GIANT-Yang2012-height_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,851,736 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002977/ScoringFiles/PGS002977.txt.gz | |
| PGS002978 (ExPRSweb_Height_GIANT-Yang2012-height_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 996,356 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002978/ScoringFiles/PGS002978.txt.gz | |
| PGS002979 (ExPRSweb_Height_ieu-a-89_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 280,347 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002979/ScoringFiles/PGS002979.txt.gz | |
| PGS002980 (ExPRSweb_Height_ieu-a-89_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 2,469 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002980/ScoringFiles/PGS002980.txt.gz | |
| PGS002981 (ExPRSweb_Height_ieu-a-89_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 2,500 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002981/ScoringFiles/PGS002981.txt.gz | |
| PGS002982 (ExPRSweb_Height_ieu-a-89_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 912,901 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002982/ScoringFiles/PGS002982.txt.gz | |
| PGS002983 (ExPRSweb_Height_ieu-a-89_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 915,020 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002983/ScoringFiles/PGS002983.txt.gz | |
| PGS002984 (ExPRSweb_Height_GIANT-Yang2012-height_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 67,333 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002984/ScoringFiles/PGS002984.txt.gz | |
| PGS002985 (ExPRSweb_Height_GIANT-Yang2012-height_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 31,267 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002985/ScoringFiles/PGS002985.txt.gz | |
| PGS002986 (ExPRSweb_Height_GIANT-Yang2012-height_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 31,700 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002986/ScoringFiles/PGS002986.txt.gz | |
| PGS002987 (ExPRSweb_Height_GIANT-Yang2012-height_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 1,661,426 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002987/ScoringFiles/PGS002987.txt.gz | |
| PGS002988 (ExPRSweb_Height_GIANT-Yang2012-height_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 996,840 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002988/ScoringFiles/PGS002988.txt.gz | |
| PGS002989 (ExPRSweb_Height_ieu-a-89_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 282,132 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002989/ScoringFiles/PGS002989.txt.gz | |
| PGS002990 (ExPRSweb_Height_ieu-a-89_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 6,903 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002990/ScoringFiles/PGS002990.txt.gz | |
| PGS002991 (ExPRSweb_Height_ieu-a-89_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 7,080 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002991/ScoringFiles/PGS002991.txt.gz | |
| PGS002992 (ExPRSweb_Height_ieu-a-89_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 464,103 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002992/ScoringFiles/PGS002992.txt.gz | |
| PGS002993 (ExPRSweb_Height_ieu-a-89_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Height | body height | 915,553 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002993/ScoringFiles/PGS002993.txt.gz | |
| PGS003514 (cont-decay-height) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Standing height | body height | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003514/ScoringFiles/PGS003514.txt.gz |
| PGS003835 (height_EUR_CT) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 4,847 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003835/ScoringFiles/PGS003835.txt.gz | |
| PGS003836 (height_EUR_LDpred2) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 564,325 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003836/ScoringFiles/PGS003836.txt.gz | |
| PGS003837 (height_AFR_CT) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 49 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003837/ScoringFiles/PGS003837.txt.gz | |
| PGS003838 (height_AFR_LDpred2) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 752,195 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003838/ScoringFiles/PGS003838.txt.gz | |
| PGS003839 (height_AFR_weighted_LDpred2) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 817,204 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003839/ScoringFiles/PGS003839.txt.gz | |
| PGS003840 (height_AFR_PRSCSx) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 300,880 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003840/ScoringFiles/PGS003840.txt.gz | |
| PGS003841 (height_AFR_CTSLEB) |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Height | body height | 741,637 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003841/ScoringFiles/PGS003841.txt.gz | |
| PGS003888 (Height_PRScsx_ARB_AMRweights) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Height | body height | 1,067,771 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003888/ScoringFiles/PGS003888.txt.gz |
| PGS003889 (Height_PRScsx_ARB_ARBweights) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Height | body height | 882,001 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003889/ScoringFiles/PGS003889.txt.gz |
| PGS003890 (Height_PRScsx_ARB_EASweights) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Height | body height | 941,406 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003890/ScoringFiles/PGS003890.txt.gz |
| PGS003891 (Height_PRScsx_ARB_EURweights) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Height | body height | 921,738 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003891/ScoringFiles/PGS003891.txt.gz |
| PGS003895 (INI50) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Standing height | body height | 62,419 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003895/ScoringFiles/PGS003895.txt.gz |
| PGS003995 (dbslmm.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 1,119,867 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003995/ScoringFiles/PGS003995.txt.gz |
| PGS004011 (lassosum.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 315,596 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004011/ScoringFiles/PGS004011.txt.gz |
| PGS004036 (ldpred2.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 929,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004036/ScoringFiles/PGS004036.txt.gz |
| PGS004065 (megaprs.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 980,499 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004065/ScoringFiles/PGS004065.txt.gz |
| PGS004095 (prscs.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 1,088,125 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004095/ScoringFiles/PGS004095.txt.gz |
| PGS004119 (pt_clump.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 2,632 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004119/ScoringFiles/PGS004119.txt.gz |
| PGS004149 (sbayesr.auto.GCST90018959.Height) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Height | body height | 962,278 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004149/ScoringFiles/PGS004149.txt.gz |
| PGS004211 (height_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Standing height | body height | 21,950 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004211/ScoringFiles/PGS004211.txt.gz |
| PGS004212 (height_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Standing height | body height | 27,779 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004212/ScoringFiles/PGS004212.txt.gz |
| PGS004213 (height_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Standing height | body height | 21,984 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004213/ScoringFiles/PGS004213.txt.gz |
| PGS004214 (height_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Standing height | body height | 23,686 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004214/ScoringFiles/PGS004214.txt.gz |
| PGS004215 (height_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Standing height | body height | 22,938 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004215/ScoringFiles/PGS004215.txt.gz |
| PGS004407 (X50.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Standing height | body height | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004407/ScoringFiles/PGS004407.txt.gz |
| PGS004682 (height_AFR_lassosum2) |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Height | body height | 906 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004682/ScoringFiles/PGS004682.txt.gz | |
| PGS004683 (height_AFR_ldpred2) |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Height | body height | 774,968 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004683/ScoringFiles/PGS004683.txt.gz | |
| PGS004684 (height_AFR_PROSPER) |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Height | body height | 859,897 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004684/ScoringFiles/PGS004684.txt.gz | |
| PGS004685 (height_AFR_weighted_lassosum2) |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Height | body height | 279,186 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004685/ScoringFiles/PGS004685.txt.gz | |
| PGS004686 (height_AFR_weighted_ldpred2) |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Height | body height | 872,587 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004686/ScoringFiles/PGS004686.txt.gz | |
| PGS004779 (height_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Height | body height | 1,357,287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004779/ScoringFiles/PGS004779.txt.gz |
| PGS004780 (height_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Height | body height | 5,967,476 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004780/ScoringFiles/PGS004780.txt.gz |
| PGS004781 (height_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Height | body height | 3,220,389 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004781/ScoringFiles/PGS004781.txt.gz |
| PGS004782 (height_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Height | body height | 1,612,712 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004782/ScoringFiles/PGS004782.txt.gz |
| PGS004995 (mean_Height_INT_ldpred_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004995/ScoringFiles/PGS004995.txt.gz |
| PGS004996 (mean_Height_INT_ldpred_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004996/ScoringFiles/PGS004996.txt.gz |
| PGS004997 (mean_Height_INT_ldpred_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004997/ScoringFiles/PGS004997.txt.gz |
| PGS004998 (mean_Height_INT_ldpred_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004998/ScoringFiles/PGS004998.txt.gz |
| PGS004999 (mean_Height_INT_ldpred_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004999/ScoringFiles/PGS004999.txt.gz |
| PGS005000 (mean_Height_INT_ldpred_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005000/ScoringFiles/PGS005000.txt.gz |
| PGS005001 (mean_Height_INT_prscs_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005001/ScoringFiles/PGS005001.txt.gz |
| PGS005002 (mean_Height_INT_prscs_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005002/ScoringFiles/PGS005002.txt.gz |
| PGS005003 (mean_Height_INT_prscs_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005003/ScoringFiles/PGS005003.txt.gz |
| PGS005004 (mean_Height_INT_prscs_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005004/ScoringFiles/PGS005004.txt.gz |
| PGS005005 (mean_Height_INT_prscs_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005005/ScoringFiles/PGS005005.txt.gz |
| PGS005006 (mean_Height_INT_prscs_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005006/ScoringFiles/PGS005006.txt.gz |
| PGS005007 (mean_Height_INT_prscsx_METAweight) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Height | body height | 1,277,825 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005007/ScoringFiles/PGS005007.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000757 | PGS000297 (GRS3290_Height) |
PSS000375| European Ancestry| 1,313 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1172 | Sex, age | — |
| PPM000758 | PGS000297 (GRS3290_Height) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1368 | Sex, age | — |
| PPM000759 | PGS000297 (GRS3290_Height) |
PSS000377| European Ancestry| 1,174 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1273 | Sex, age | — |
| PPM000760 | PGS000297 (GRS3290_Height) |
PSS000378| European Ancestry| 1,095 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1382 | Sex, age | — |
| PPM000756 | PGS000297 (GRS3290_Height) |
PSS000374| European Ancestry| 1,318 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1192 | Sex, age | — |
| PPM000786 | PGS000297 (GRS3290_Height) |
PSS000369| European Ancestry| 334 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.087 | Sex, age | — |
| PPM000787 | PGS000297 (GRS3290_Height) |
PSS000370| European Ancestry| 329 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.0755 | Sex, age | — |
| PPM000788 | PGS000297 (GRS3290_Height) |
PSS000371| European Ancestry| 288 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.0887 | Sex, age | — |
| PPM000789 | PGS000297 (GRS3290_Height) |
PSS000372| European Ancestry| 265 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.0986 | Sex, age | — |
| PPM000790 | PGS000297 (GRS3290_Height) |
PSS000373| European Ancestry| 245 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Height (cm) | — | — | R²: 0.1158 | Sex, age | — |
| PPM001768 | PGS000297 (GRS3290_Height) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Height | — | — | Pearson correlation coefficent (r): 0.15 | — | — |
| PPM001931 | PGS000758 (LASSO_Height) |
PSS000967| European Ancestry| 941 individuals |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Reported Trait: Short stature in adulthood | — | AUROC: 0.843 [0.796, 0.89] | Area under the precision-recall curve (AUPRC): 0.284 [0.102, 0.5] | Sex | 33,783 SNPs were utilised from the 33,938 SNP score. |
| PPM001932 | PGS000758 (LASSO_Height) |
PSS000967| European Ancestry| 941 individuals |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Reported Trait: Short stature in adulthood (females) | OR: 0.62 [0.5, 0.75] | AUROC: 0.861 [0.814, 0.907] | Area under the precision-recall curve (AUPRC): 0.373 [0.087, 0.651] | — | 33,783 SNPs were utilised from the 33,938 SNP score. |
| PPM001930 | PGS000758 (LASSO_Height) |
PSS000967| European Ancestry| 941 individuals |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Reported Trait: Standing height in adulthood | — | — | R²: 0.71 [0.679, 0.741] | Sex | 33,783 SNPs were utilised from the 33,938 SNP score. |
| PPM001933 | PGS000758 (LASSO_Height) |
PSS000967| European Ancestry| 941 individuals |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Reported Trait: Short stature in adulthood (males) | OR: 0.7 [0.57, 0.83] | AUROC: 0.82 [0.731, 0.909] | Area under the precision-recall curve (AUPRC): 0.181 [0.044, 0.518] | — | 33,783 SNPs were utilised from the 33,938 SNP score. |
| PPM001929 | PGS000758 (LASSO_Height) |
PSS000969| European Ancestry| 81,902 individuals |
PGP000163 | Lu T et al. J Clin Endocrinol Metab (2021) |
Reported Trait: Standing height in adulthood | — | — | R²: 0.711 [0.708, 0.714] | Age, sex, recruitment center, genotyping array, PCs(1-20) | — |
| PPM008659 | PGS001229 (GBE_INI50) |
PSS007396| African Ancestry| 6,407 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Standing height | — | — | R²: 0.50012 [0.48294, 0.5173] Incremental R2 (full-covars): 0.02391 PGS R2 (no covariates): 0.03665 [0.02769, 0.04561] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008660 | PGS001229 (GBE_INI50) |
PSS007397| East Asian Ancestry| 1,697 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Standing height | — | — | R²: 0.60758 [0.5786, 0.63657] Incremental R2 (full-covars): 0.06552 PGS R2 (no covariates): 0.09127 [0.06525, 0.11728] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008661 | PGS001229 (GBE_INI50) |
PSS007398| European Ancestry| 24,826 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Standing height | — | — | R²: 0.7018 [0.69559, 0.708] Incremental R2 (full-covars): 0.16478 PGS R2 (no covariates): 0.1861 [0.17738, 0.19482] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008662 | PGS001229 (GBE_INI50) |
PSS007399| South Asian Ancestry| 7,650 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Standing height | — | — | R²: 0.66523 [0.65314, 0.67732] Incremental R2 (full-covars): 0.08156 PGS R2 (no covariates): 0.08889 [0.07686, 0.10092] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008663 | PGS001229 (GBE_INI50) |
PSS007400| European Ancestry| 67,298 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Standing height | — | — | R²: 0.71726 [0.71364, 0.72087] Incremental R2 (full-covars): 0.17893 PGS R2 (no covariates): 0.17757 [0.17234, 0.1828] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005231 | PGS001405 (GBE_INI12144) |
PSS004802| East Asian Ancestry| 133 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Height | — | — | R²: 0.509 [0.47581, 0.5422] Incremental R2 (full-covars): 0.00258 PGS R2 (no covariates): 0.00401 [-0.00197, 0.00998] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005230 | PGS001405 (GBE_INI12144) |
PSS004801| African Ancestry| 253 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Height | — | — | R²: 0.58747 [0.5721, 0.60284] Incremental R2 (full-covars): 0.01915 PGS R2 (no covariates): 0.00938 [0.00471, 0.01404] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005232 | PGS001405 (GBE_INI12144) |
PSS004803| European Ancestry| 2,131 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Height | — | — | R²: 0.59354 [0.58576, 0.60132] Incremental R2 (full-covars): 0.04611 PGS R2 (no covariates): 0.05219 [0.04681, 0.05757] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005233 | PGS001405 (GBE_INI12144) |
PSS004804| South Asian Ancestry| 414 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Height | — | — | R²: 0.56418 [0.54969, 0.57868] Incremental R2 (full-covars): 0.03739 PGS R2 (no covariates): 0.02079 [0.01454, 0.02704] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005234 | PGS001405 (GBE_INI12144) |
PSS004805| European Ancestry| 6,641 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Height | — | — | R²: 0.59871 [0.59403, 0.6034] Incremental R2 (full-covars): 0.05016 PGS R2 (no covariates): 0.05141 [0.04816, 0.05466] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010307 | PGS001929 (portability-PLR_height) |
PSS009416| European Ancestry| 19,953 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.6344 [0.626, 0.6426] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010308 | PGS001929 (portability-PLR_height) |
PSS009190| European Ancestry| 4,126 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.6098 [0.5902, 0.6286] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010310 | PGS001929 (portability-PLR_height) |
PSS008518| Greater Middle Eastern Ancestry| 1,180 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.5167 [0.4732, 0.5576] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010311 | PGS001929 (portability-PLR_height) |
PSS008296| South Asian Ancestry| 6,152 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.4923 [0.4731, 0.511] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010312 | PGS001929 (portability-PLR_height) |
PSS008073| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.4504 [0.4125, 0.4866] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010313 | PGS001929 (portability-PLR_height) |
PSS007860| African Ancestry| 2,450 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.3454 [0.3099, 0.3799] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010314 | PGS001929 (portability-PLR_height) |
PSS008964| African Ancestry| 3,863 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.2731 [0.2436, 0.3021] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010309 | PGS001929 (portability-PLR_height) |
PSS008744| European Ancestry| 6,633 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.5938 [0.578, 0.6092] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012015 | PGS002146 (portability-ldpred2_height) |
PSS009416| European Ancestry| 19,953 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.6133 [0.6046, 0.6219] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012016 | PGS002146 (portability-ldpred2_height) |
PSS009190| European Ancestry| 4,126 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.5922 [0.5719, 0.6117] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012017 | PGS002146 (portability-ldpred2_height) |
PSS008744| European Ancestry| 6,633 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.5752 [0.5589, 0.5911] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012018 | PGS002146 (portability-ldpred2_height) |
PSS008518| Greater Middle Eastern Ancestry| 1,180 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.4948 [0.4501, 0.5371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012019 | PGS002146 (portability-ldpred2_height) |
PSS008296| South Asian Ancestry| 6,152 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.4752 [0.4556, 0.4943] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012020 | PGS002146 (portability-ldpred2_height) |
PSS008073| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.4297 [0.3911, 0.4668] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012021 | PGS002146 (portability-ldpred2_height) |
PSS007860| African Ancestry| 2,450 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.3207 [0.2846, 0.356] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012022 | PGS002146 (portability-ldpred2_height) |
PSS008964| African Ancestry| 3,863 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Standing height | — | — | Partial Correlation (partial-r): 0.2554 [0.2256, 0.2847] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM013097 | PGS002332 (body_HEIGHTz.BOLT-LMM) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0862 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013195 | PGS002332 (body_HEIGHTz.BOLT-LMM) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.3593 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013244 | PGS002332 (body_HEIGHTz.BOLT-LMM) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.2245 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013146 | PGS002332 (body_HEIGHTz.BOLT-LMM) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1592 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013280 | PGS002368 (body_HEIGHTz.BOLT-LMM-BBJ) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0088 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013303 | PGS002368 (body_HEIGHTz.BOLT-LMM-BBJ) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1462 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013326 | PGS002368 (body_HEIGHTz.BOLT-LMM-BBJ) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0353 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013349 | PGS002368 (body_HEIGHTz.BOLT-LMM-BBJ) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0429 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013385 | PGS002404 (body_HEIGHTz.P+T.0.0001) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.012 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013434 | PGS002404 (body_HEIGHTz.P+T.0.0001) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0968 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013532 | PGS002404 (body_HEIGHTz.P+T.0.0001) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1346 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013483 | PGS002404 (body_HEIGHTz.P+T.0.0001) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.2341 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013581 | PGS002453 (body_HEIGHTz.P+T.0.001) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0049 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013630 | PGS002453 (body_HEIGHTz.P+T.0.001) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0953 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013728 | PGS002453 (body_HEIGHTz.P+T.0.001) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1336 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013679 | PGS002453 (body_HEIGHTz.P+T.0.001) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.2461 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013777 | PGS002502 (body_HEIGHTz.P+T.0.01) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013826 | PGS002502 (body_HEIGHTz.P+T.0.01) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0353 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013875 | PGS002502 (body_HEIGHTz.P+T.0.01) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.2204 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013924 | PGS002502 (body_HEIGHTz.P+T.0.01) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0697 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013973 | PGS002551 (body_HEIGHTz.P+T.1e-06) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0455 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014022 | PGS002551 (body_HEIGHTz.P+T.1e-06) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.099 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014071 | PGS002551 (body_HEIGHTz.P+T.1e-06) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.207 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014120 | PGS002551 (body_HEIGHTz.P+T.1e-06) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1235 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014169 | PGS002600 (body_HEIGHTz.P+T.5e-08) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0447 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014218 | PGS002600 (body_HEIGHTz.P+T.5e-08) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0997 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014267 | PGS002600 (body_HEIGHTz.P+T.5e-08) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1921 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014316 | PGS002600 (body_HEIGHTz.P+T.5e-08) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1136 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014463 | PGS002649 (body_HEIGHTz.PolyFun-pred) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.3823 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See body_HEIGHTz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014365 | PGS002649 (body_HEIGHTz.PolyFun-pred) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1149 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See body_HEIGHTz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014414 | PGS002649 (body_HEIGHTz.PolyFun-pred) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1634 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See body_HEIGHTz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014512 | PGS002649 (body_HEIGHTz.PolyFun-pred) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.2378 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See body_HEIGHTz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014561 | PGS002698 (body_HEIGHTz.SBayesR) |
PSS009771| African Ancestry| 6,410 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.0852 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014610 | PGS002698 (body_HEIGHTz.SBayesR) |
PSS009772| East Asian Ancestry| 916 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.1499 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014659 | PGS002698 (body_HEIGHTz.SBayesR) |
PSS009773| European Ancestry| 43,376 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.3449 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014708 | PGS002698 (body_HEIGHTz.SBayesR) |
PSS009774| South Asian Ancestry| 7,921 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Height | — | — | Incremental R2 (full model vs. covariates alone): 0.212 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014929 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Height (male) | β: 0.257 | — | — | — | — |
| PPM014930 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Height (female) | β: 0.274 | — | — | — | — |
| PPM014931 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Body weight | β: 1.218 [1.141, 1.296] | — | — | — | — |
| PPM014932 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Waist circumference | β: 0.446 [0.375, 0.517] | — | — | — | — |
| PPM014933 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Hip circumference | β: 0.601 [0.549, 0.652] | — | — | — | — |
| PPM014934 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Body mass index | β: -0.084 [-0.111, -0.056] | — | — | — | — |
| PPM014935 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Waist‐hip ratio | β: -0.001 [-0.001, 0.0] | — | — | — | — |
| PPM014936 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Body fat | β: -0.14 [-0.186, -0.095] | — | — | — | — |
| PPM014937 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Total cholesterol | β: -0.587 [-0.853, -0.321] | — | — | — | — |
| PPM014938 | PGS002748 (PRS_251) |
PSS009934| East Asian Ancestry| 28,909 individuals |
PGP000361 | Chiou JS et al. BMC Med (2022) |
Reported Trait: Low‐density lipoprotein cholesterol | β: -0.629 [-0.867, -0.391] | — | — | — | — |
| PPM015528 | PGS002800 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_SAS) |
PSS009976| South Asian Ancestry| 9,257 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.033 | age, sex and 10 genetic principal components | — |
| PPM015534 | PGS002801 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_AFR) |
PSS009977| African Ancestry| 6,911 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.085 | age, sex and 10 genetic principal components | — |
| PPM015536 | PGS002801 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_AFR) |
PSS009978| African Ancestry| 8,238 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.085 | age, sex and 10 genetic principal components | — |
| PPM015523 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009974| European Ancestry| 14,587 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.401 | age, sex and 10 genetic principal components | — |
| PPM015525 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009973| European Ancestry| 14,058 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.399 | age, sex and 10 genetic principal components | — |
| PPM015527 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009976| South Asian Ancestry| 9,257 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.214 | age, sex and 10 genetic principal components | — |
| PPM015529 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009972| East Asian Ancestry| 2,246 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.202 | age, sex and 10 genetic principal components | — |
| PPM015531 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009975| Hispanic or Latin American Ancestry| 5,798 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.201 | age, sex and 10 genetic principal components | — |
| PPM015533 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009977| African Ancestry| 6,911 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.123 | age, sex and 10 genetic principal components | — |
| PPM015535 | PGS002802 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_ALL) |
PSS009978| African Ancestry| 8,238 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.094 | age, sex and 10 genetic principal components | — |
| PPM015530 | PGS002803 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_EAS) |
PSS009972| East Asian Ancestry| 2,246 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.157 | age, sex and 10 genetic principal components | — |
| PPM015524 | PGS002804 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_EUR) |
PSS009974| European Ancestry| 14,587 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.401 | age, sex and 10 genetic principal components | — |
| PPM015526 | PGS002804 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_EUR) |
PSS009973| European Ancestry| 14,058 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.4 | age, sex and 10 genetic principal components | — |
| PPM015532 | PGS002805 (GIANT_HEIGHT_YENGO_2022_PGS_WEIGHTS_HIS) |
PSS009975| Hispanic or Latin American Ancestry| 5,798 individuals |
PGP000382 | Yengo L et al. Nature (2022) |
Reported Trait: Height | — | — | R²: 0.131 | age, sex and 10 genetic principal components | — |
| PPM015843 | PGS002964 (ExPRSweb_Height_50-irnt_LASSOSUM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.64 (0.0391) | — | R²: 0.134 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015846 | PGS002965 (ExPRSweb_Height_50-irnt_PT_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.52 (0.0396) | — | R²: 0.125 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015844 | PGS002966 (ExPRSweb_Height_50-irnt_PLINK_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.51 (0.0398) | — | R²: 0.125 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015842 | PGS002967 (ExPRSweb_Height_50-irnt_DBSLMM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.4 (0.0426) | — | R²: 0.0613 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015845 | PGS002968 (ExPRSweb_Height_50-irnt_PRSCS_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.69 (0.0387) | — | R²: 0.138 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015848 | PGS002969 (ExPRSweb_Height_50-raw_LASSOSUM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.65 (0.0391) | — | R²: 0.135 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015851 | PGS002970 (ExPRSweb_Height_50-raw_PT_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.53 (0.0396) | — | R²: 0.126 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015849 | PGS002971 (ExPRSweb_Height_50-raw_PLINK_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.51 (0.0396) | — | R²: 0.125 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015847 | PGS002972 (ExPRSweb_Height_50-raw_DBSLMM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.41 (0.0425) | — | R²: 0.0619 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015850 | PGS002973 (ExPRSweb_Height_50-raw_PRSCS_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.7 (0.0386) | — | R²: 0.139 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015854 | PGS002974 (ExPRSweb_Height_GIANT-Yang2012-height_LASSOSUM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.0721 (0.0462) | — | R²: 6e-05 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015860 | PGS002975 (ExPRSweb_Height_GIANT-Yang2012-height_PT_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.162 (0.0533) | — | R²: 0.00014 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015856 | PGS002976 (ExPRSweb_Height_GIANT-Yang2012-height_PLINK_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.176 (0.0535) | — | R²: 0.00012 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015852 | PGS002977 (ExPRSweb_Height_GIANT-Yang2012-height_DBSLMM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.0806 (0.0446) | — | R²: 3e-05 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015858 | PGS002978 (ExPRSweb_Height_GIANT-Yang2012-height_PRSCS_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.105 (0.0468) | — | R²: 3e-05 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015864 | PGS002979 (ExPRSweb_Height_ieu-a-89_LASSOSUM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.79 (0.0488) | — | R²: 0.0563 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015870 | PGS002980 (ExPRSweb_Height_ieu-a-89_PT_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.21 (0.0455) | — | R²: 0.0834 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015866 | PGS002981 (ExPRSweb_Height_ieu-a-89_PLINK_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.12 (0.0449) | — | R²: 0.0819 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015862 | PGS002982 (ExPRSweb_Height_ieu-a-89_DBSLMM_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.992 (0.0493) | — | R²: 0.012 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015868 | PGS002983 (ExPRSweb_Height_ieu-a-89_PRSCS_MGI_20211120) |
PSS010007| European Ancestry| 23,349 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.32 (0.0521) | — | R²: 0.0599 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015855 | PGS002984 (ExPRSweb_Height_GIANT-Yang2012-height_LASSOSUM_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.78 (0.0126) | — | R²: 0.0888 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015861 | PGS002985 (ExPRSweb_Height_GIANT-Yang2012-height_PT_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.0594 (0.014) | — | R²: 8e-05 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015857 | PGS002986 (ExPRSweb_Height_GIANT-Yang2012-height_PLINK_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.06 (0.014) | — | R²: 8e-05 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015853 | PGS002987 (ExPRSweb_Height_GIANT-Yang2012-height_DBSLMM_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.525 (0.014) | — | R²: 0.00307 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015859 | PGS002988 (ExPRSweb_Height_GIANT-Yang2012-height_PRSCS_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.03 (0.0123) | — | R²: 0.106 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015865 | PGS002989 (ExPRSweb_Height_ieu-a-89_LASSOSUM_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.78 (0.0126) | — | R²: 0.0888 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015871 | PGS002990 (ExPRSweb_Height_ieu-a-89_PT_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.92 (0.0124) | — | R²: 0.0975 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015867 | PGS002991 (ExPRSweb_Height_ieu-a-89_PLINK_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 2.91 (0.0124) | — | R²: 0.0974 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015863 | PGS002992 (ExPRSweb_Height_ieu-a-89_DBSLMM_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 0.525 (0.014) | — | R²: 0.00307 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015869 | PGS002993 (ExPRSweb_Height_ieu-a-89_PRSCS_UKB_20211120) |
PSS010029| European Ancestry| 203,681 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Height | β: 3.03 (0.0123) | — | R²: 0.106 | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM017442 | PGS003514 (cont-decay-height) |
PSS010876| European Ancestry| 19,949 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.38 | sex, age, deprivation index, PC1-16 | — |
| PPM017526 | PGS003514 (cont-decay-height) |
PSS010792| European Ancestry| 4,115 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.34 | sex, age, deprivation index, PC1-16 | — |
| PPM017610 | PGS003514 (cont-decay-height) |
PSS010624| European Ancestry| 6,470 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.33 | sex, age, deprivation index, PC1-16 | — |
| PPM017694 | PGS003514 (cont-decay-height) |
PSS010540| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.25 | sex, age, deprivation index, PC1-16 | — |
| PPM017778 | PGS003514 (cont-decay-height) |
PSS010204| European Ancestry| 2,346 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.33 | sex, age, deprivation index, PC1-16 | — |
| PPM017862 | PGS003514 (cont-decay-height) |
PSS010456| South Asian Ancestry| 6,100 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.23 | sex, age, deprivation index, PC1-16 | — |
| PPM017946 | PGS003514 (cont-decay-height) |
PSS010372| East Asian Ancestry| 1,789 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.18 | sex, age, deprivation index, PC1-16 | — |
| PPM018030 | PGS003514 (cont-decay-height) |
PSS010288| African Ancestry| 2,437 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
| PPM018114 | PGS003514 (cont-decay-height) |
PSS010708| African Ancestry| 3,834 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Standing height | — | — | partial-R2: 0.06 | sex, age, deprivation index, PC1-16 | — |
| PPM018642 | PGS003835 (height_EUR_CT) |
PSS011042| European Ancestry| 9,969 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.09039 | — | — |
| PPM018643 | PGS003836 (height_EUR_LDpred2) |
PSS011042| European Ancestry| 9,969 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.16006 | — | — |
| PPM018644 | PGS003837 (height_AFR_CT) |
PSS011041| African Ancestry| 4,527 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.00285 | — | — |
| PPM018645 | PGS003838 (height_AFR_LDpred2) |
PSS011041| African Ancestry| 4,527 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.00695 | — | — |
| PPM018646 | PGS003839 (height_AFR_weighted_LDpred2) |
PSS011041| African Ancestry| 4,527 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.03319 | — | — |
| PPM018647 | PGS003840 (height_AFR_PRSCSx) |
PSS011041| African Ancestry| 4,527 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.04139 | — | — |
| PPM018648 | PGS003841 (height_AFR_CTSLEB) |
PSS011041| African Ancestry| 4,527 individuals |
PGP000489 | Zhang H et al. Nat Genet (2023) |
Reported Trait: Height | — | — | R²: 0.03775 | — | — |
| PPM018780 | PGS003888 (Height_PRScsx_ARB_AMRweights) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Height | β: 0.026 (0.0013) | — | R²: 0.5202 | age, sex, array version, and the first 10 principal components of ancestry | The reported performance was derived from a linearly combined score of 4 normalized ancestry-specific scores using the following coefficients: Score = (0.0043399119*zscoreAMR) + (0.0003544699*zscoreARB) + (0.0034973575*zscoreEAS) + (0.0218689041*zscoreEUR). |
| PPM018781 | PGS003889 (Height_PRScsx_ARB_ARBweights) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Height | β: 0.026 (0.0013) | — | R²: 0.5202 | age, sex, array version, and the first 10 principal components of ancestry | The reported performance was derived from a linearly combined score of 4 normalized ancestry-specific scores using the following coefficients: Score = (0.0043399119*zscoreAMR) + (0.0003544699*zscoreARB) + (0.0034973575*zscoreEAS) + (0.0218689041*zscoreEUR). |
| PPM018782 | PGS003890 (Height_PRScsx_ARB_EASweights) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Height | β: 0.026 (0.0013) | — | R²: 0.5202 | age, sex, array version, and the first 10 principal components of ancestry | The reported performance was derived from a linearly combined score of 4 normalized ancestry-specific scores using the following coefficients: Score = (0.0043399119*zscoreAMR) + (0.0003544699*zscoreARB) + (0.0034973575*zscoreEAS) + (0.0218689041*zscoreEUR). |
| PPM018783 | PGS003891 (Height_PRScsx_ARB_EURweights) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Height | β: 0.026 (0.0013) | — | R²: 0.5202 | age, sex, array version, and the first 10 principal components of ancestry | The reported performance was derived from a linearly combined score of 4 normalized ancestry-specific scores using the following coefficients: Score = (0.0043399119*zscoreAMR) + (0.0003544699*zscoreARB) + (0.0034973575*zscoreEAS) + (0.0218689041*zscoreEUR). |
| PPM018794 | PGS003895 (INI50) |
PSS011146| European Ancestry| 67,603 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Standing height | — | — | R²: 0.71901 [0.71542, 0.7226] PGS R2 (no covariates): 0.1804 [0.17516, 0.18565] Incremental R2 (full-covars): 0.17961 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018795 | PGS003895 (INI50) |
PSS011103| European Ancestry| 2,885 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Standing height | — | — | R²: 0.72848 [0.71161, 0.74534] PGS R2 (no covariates): 0.21016 [0.18381, 0.23651] Incremental R2 (full-covars): 0.18808 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018796 | PGS003895 (INI50) |
PSS011114| South Asian Ancestry| 1,448 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Standing height | — | — | R²: 0.66918 [0.64174, 0.69663] PGS R2 (no covariates): 0.08326 [0.05643, 0.11009] Incremental R2 (full-covars): 0.08875 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018797 | PGS003895 (INI50) |
PSS011159| African Ancestry| 1,191 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Standing height | — | — | R²: 0.50307 [0.46351, 0.54262] PGS R2 (no covariates): 0.02787 [0.00966, 0.04609] Incremental R2 (full-covars): 0.01372 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018798 | PGS003895 (INI50) |
PSS011173| Multi-ancestry (excluding European)| 7,968 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Standing height | — | — | R²: 0.69915 [0.68814, 0.71017] PGS R2 (no covariates): 0.151 [0.13655, 0.16545] Incremental R2 (full-covars): 0.14737 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM020065 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.35385 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020066 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.32614 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020067 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26677 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020068 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.33511 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020069 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.27048 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020090 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.31544 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020091 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.29137 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020092 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.25831 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020093 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.31267 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020094 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.24786 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020075 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.36472 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020076 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.33197 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020077 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.28234 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020078 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.34509 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020079 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.28559 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020080 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.33881 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020081 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.30485 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020082 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26196 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020083 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.31748 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020084 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26382 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020085 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.35864 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020086 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.33536 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020087 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26465 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020088 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.34613 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020089 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26176 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020061 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.26981 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020062 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.25362 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020063 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.27669 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020064 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.24036 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020060 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.29998 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020070 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.35918 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020071 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.32289 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020072 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.28496 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020073 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.33073 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020074 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Height | β: 0.28263 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020144 | PGS004211 (height_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Standing height | — | — | R²: 0.71113 | year of birth, sex | — |
| PPM020145 | PGS004212 (height_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Standing height | — | — | R²: 0.71242 | year of birth, sex | — |
| PPM020146 | PGS004213 (height_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Standing height | — | — | R²: 0.71113 | year of birth, sex | — |
| PPM020147 | PGS004214 (height_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Standing height | — | — | R²: 0.71242 | year of birth, sex | — |
| PPM020148 | PGS004215 (height_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Standing height | — | — | R²: 0.71242 | year of birth, sex | — |
| PPM020522 | PGS004407 (X50.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Standing height | — | — | PGS R2 (no covariates): 0.32082 | — | — |
| PPM020867 | PGS004682 (height_AFR_lassosum2) |
PSS011422| African Ancestry| 4,527 individuals |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Reported Trait: Height | — | — | adjusted R2: 0.0079 | — | — |
| PPM020868 | PGS004683 (height_AFR_ldpred2) |
PSS011422| African Ancestry| 4,527 individuals |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Reported Trait: Height | — | — | adjusted R2: 0.0119 | — | — |
| PPM020869 | PGS004684 (height_AFR_PROSPER) |
PSS011422| African Ancestry| 4,527 individuals |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Reported Trait: Height | — | — | adjusted R2: 0.0479 | — | — |
| PPM020870 | PGS004685 (height_AFR_weighted_lassosum2) |
PSS011422| African Ancestry| 4,527 individuals |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Reported Trait: Height | — | — | adjusted R2: 0.0295 | — | — |
| PPM020871 | PGS004686 (height_AFR_weighted_ldpred2) |
PSS011422| African Ancestry| 4,527 individuals |
PGP000595 | Zhang J et al. Nat Commun (2024) |
Reported Trait: Height | — | — | adjusted R2: 0.0297 | — | — |
| PPM021004 | PGS004779 (height_PRSmix_eur) |
PSS011497| European Ancestry| 9,045 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Height | — | — | Incremental R2 (Full model versus model with only covariates): 0.201 [0.186, 0.216] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021005 | PGS004780 (height_PRSmix_sas) |
PSS011498| South Asian Ancestry| 6,835 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Height | — | — | Incremental R2 (Full model versus model with only covariates): 0.088 [0.075, 0.101] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021006 | PGS004781 (height_PRSmixPlus_eur) |
PSS011497| European Ancestry| 9,045 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Height | — | — | Incremental R2 (Full model versus model with only covariates): 0.201 [0.187, 0.216] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021007 | PGS004782 (height_PRSmixPlus_sas) |
PSS011498| South Asian Ancestry| 6,835 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Height | — | — | Incremental R2 (Full model versus model with only covariates): 0.089 [0.076, 0.102] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM022133 | PGS004995 (mean_Height_INT_ldpred_AFRss_afrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.184 [0.18, 0.19] | — | R²: 0.064 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022139 | PGS004995 (mean_Height_INT_ldpred_AFRss_afrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.219 [0.21, 0.23] | — | R²: 0.081 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022145 | PGS004995 (mean_Height_INT_ldpred_AFRss_afrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.181 [0.17, 0.19] | — | R²: 0.064 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022135 | PGS004996 (mean_Height_INT_ldpred_EURss_eurld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.309 [0.3, 0.32] | — | R²: 0.18 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022141 | PGS004996 (mean_Height_INT_ldpred_EURss_eurld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.174 [0.16, 0.18] | — | R²: 0.051 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022147 | PGS004996 (mean_Height_INT_ldpred_EURss_eurld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.253 [0.24, 0.26] | — | R²: 0.125 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022134 | PGS004997 (mean_Height_INT_ldpred_HISss_amrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.221 [0.21, 0.23] | — | R²: 0.092 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022140 | PGS004997 (mean_Height_INT_ldpred_HISss_amrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.166 [0.16, 0.18] | — | R²: 0.047 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022146 | PGS004997 (mean_Height_INT_ldpred_HISss_amrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.25 [0.24, 0.26] | — | R²: 0.121 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022130 | PGS004998 (mean_Height_INT_ldpred_METAss_afrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.32 [0.31, 0.33] | — | R²: 0.193 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022136 | PGS004998 (mean_Height_INT_ldpred_METAss_afrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.252 [0.24, 0.26] | — | R²: 0.107 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022142 | PGS004998 (mean_Height_INT_ldpred_METAss_afrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.291 [0.28, 0.3] | — | R²: 0.164 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022131 | PGS004999 (mean_Height_INT_ldpred_METAss_amrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.337 [0.33, 0.34] | — | R²: 0.214 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022137 | PGS004999 (mean_Height_INT_ldpred_METAss_amrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.274 [0.26, 0.28] | — | R²: 0.127 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022143 | PGS004999 (mean_Height_INT_ldpred_METAss_amrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.306 [0.3, 0.32] | — | R²: 0.183 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022132 | PGS005000 (mean_Height_INT_ldpred_METAss_eurld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.328 [0.32, 0.33] | — | R²: 0.202 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022138 | PGS005000 (mean_Height_INT_ldpred_METAss_eurld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.216 [0.21, 0.23] | — | R²: 0.079 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022144 | PGS005000 (mean_Height_INT_ldpred_METAss_eurld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.253 [0.24, 0.26] | — | R²: 0.125 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022038 | PGS005001 (mean_Height_INT_prscs_AFRss_afrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.179 [0.17, 0.19] | — | R²: 0.06 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022045 | PGS005001 (mean_Height_INT_prscs_AFRss_afrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.166 [0.15, 0.18] | — | R²: 0.046 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022052 | PGS005001 (mean_Height_INT_prscs_AFRss_afrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.144 [0.13, 0.16] | — | R²: 0.04 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022040 | PGS005002 (mean_Height_INT_prscs_EURss_eurld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.374 [0.37, 0.38] | — | R²: 0.263 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022047 | PGS005002 (mean_Height_INT_prscs_EURss_eurld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.22 [0.21, 0.23] | — | R²: 0.082 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022054 | PGS005002 (mean_Height_INT_prscs_EURss_eurld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.311 [0.3, 0.32] | — | R²: 0.188 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022039 | PGS005003 (mean_Height_INT_prscs_HISss_amrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.234 [0.23, 0.24] | — | R²: 0.103 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022046 | PGS005003 (mean_Height_INT_prscs_HISss_amrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.163 [0.15, 0.17] | — | R²: 0.045 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022053 | PGS005003 (mean_Height_INT_prscs_HISss_amrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.234 [0.22, 0.25] | — | R²: 0.107 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022035 | PGS005004 (mean_Height_INT_prscs_METAss_afrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.288 [0.28, 0.29] | — | R²: 0.156 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022042 | PGS005004 (mean_Height_INT_prscs_METAss_afrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.221 [0.21, 0.23] | — | R²: 0.083 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022049 | PGS005004 (mean_Height_INT_prscs_METAss_afrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.263 [0.25, 0.27] | — | R²: 0.135 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022036 | PGS005005 (mean_Height_INT_prscs_METAss_amrld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.296 [0.29, 0.3] | — | R²: 0.165 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022043 | PGS005005 (mean_Height_INT_prscs_METAss_amrld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.23 [0.22, 0.24] | — | R²: 0.09 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022050 | PGS005005 (mean_Height_INT_prscs_METAss_amrld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.254 [0.24, 0.27] | — | R²: 0.126 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022037 | PGS005006 (mean_Height_INT_prscs_METAss_eurld) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.291 [0.28, 0.3] | — | R²: 0.159 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022044 | PGS005006 (mean_Height_INT_prscs_METAss_eurld) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.174 [0.16, 0.18] | — | R²: 0.051 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022051 | PGS005006 (mean_Height_INT_prscs_METAss_eurld) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.199 [0.19, 0.21] | — | R²: 0.077 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022034 | PGS005007 (mean_Height_INT_prscsx_METAweight) |
PSS011823| European Ancestry| 45,413 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.378 [0.37, 0.38] | — | R²: 0.269 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022041 | PGS005007 (mean_Height_INT_prscsx_METAweight) |
PSS011803| African Ancestry| 19,353 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.267 [0.26, 0.28] | — | R²: 0.121 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022048 | PGS005007 (mean_Height_INT_prscsx_METAweight) |
PSS011813| Hispanic or Latin American Ancestry| 13,065 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Height | β: 0.316 [0.3, 0.33] | — | R²: 0.194 | score previously adjusted for age, sex, 20 PCs | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS008518 | — | — | 1,180 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009416 | — | — | 19,953 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS004801 | — | — | 253 individuals | — | African unspecified | — | UKB | — |
| PSS004802 | — | — | 133 individuals | — | East Asian | — | UKB | — |
| PSS004803 | — | — | 2,131 individuals | — | European | non-white British ancestry | UKB | — |
| PSS004804 | — | — | 414 individuals | — | South Asian | — | UKB | — |
| PSS004805 | — | — | 6,641 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS010792 | — | — | 4,115 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS011146 | — | — | 67,603 individuals | — | European (white British ancestry) |
— | UKB | — |
| PSS010540 | — | — | 1,151 individuals, 60.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
| PSS011287 | — | — | 9,108 individuals | — | South Asian | — | UKB | — |
| PSS010288 | — | — | 2,437 individuals, 36.0 % Male samples |
Mean = 52.5 years Sd = 8.1 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
| PSS011159 | — | — | 1,191 individuals | — | African unspecified | — | UKB | — |
| PSS009771 | — | — | 6,410 individuals | — | African unspecified | — | UKB | — |
| PSS009772 | — | — | 916 individuals | — | East Asian | — | UKB | — |
| PSS009773 | — | — | 43,376 individuals | — | European | Non-British European | UKB | — |
| PSS009190 | — | — | 4,126 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009774 | — | — | 7,921 individuals | — | South Asian | — | UKB | — |
| PSS008296 | — | — | 6,152 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011042 | — | — | 9,969 individuals, 47.0 % Male samples |
Mean = 56.86 years Sd = 8.05 years |
European | — | UKB | — |
| PSS011041 | — | — | 4,527 individuals, 42.0 % Male samples |
Mean = 51.82 years Sd = 8.06 years |
African American or Afro-Caribbean (African American) |
— | UKB | — |
| PSS011173 | — | — | 7,968 individuals | — | East Asian, Other admixed ancestry | East Asian, Other admixed ancestry | UKB | — |
| PSS007396 | — | — | 6,407 individuals | — | African unspecified | — | UKB | — |
| PSS007397 | — | — | 1,697 individuals | — | East Asian | — | UKB | — |
| PSS007398 | — | — | 24,826 individuals | — | European | non-white British ancestry | UKB | — |
| PSS007399 | — | — | 7,650 individuals | — | South Asian | — | UKB | — |
| PSS007400 | — | — | 67,298 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS000369 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 334 individuals, 69.2 % Male samples |
Mean = 11.1 years Sd = 0.48 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000370 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 329 individuals, 69.2 % Male samples |
Mean = 12.81 years Sd = 0.59 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000371 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 288 individuals, 69.2 % Male samples |
Mean = 15.83 years Sd = 0.6 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000372 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 265 individuals, 69.2 % Male samples |
Mean = 19.2 years Sd = 0.66 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000373 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 245 individuals, 69.2 % Male samples |
Mean = 22.04 years Sd = 0.69 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000374 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,318 individuals, 47.6 % Male samples |
Mean = 11.1 years | European | — | TRAILS | — |
| PSS000375 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,313 individuals, 47.6 % Male samples |
Mean = 13.5 years | European | — | TRAILS | — |
| PSS000376 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,354 individuals, 47.56 % Male samples |
Mean = 16.22 years Sd = 0.66 years |
European | — | TRAILS | — |
| PSS000377 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,174 individuals, 47.6 % Male samples |
Mean = 19.2 years | European | — | TRAILS | — |
| PSS000378 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,095 individuals, 47.6 % Male samples |
Mean = 22.4 years | European | — | TRAILS | — |
| PSS000911 | — | — | 13,989 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
| PSS009934 | — | — | 28,909 individuals, 38.0 % Male samples |
— | East Asian (Han Chinese) |
— | TWB | — |
| PSS010007 | body height (cm); Quantitative | — | 23,349 individuals | — | European | — | MGI | — |
| PSS010456 | — | — | 6,100 individuals, 53.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
| PSS010708 | — | — | 3,834 individuals, 46.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
| PSS011497 | — | — | 9,045 individuals | — | European | — | AllofUs | — |
| PSS000967 | — | — | [ ,
42.5 % Male samples |
— | European | — | ALSPAC | — |
| PSS010204 | — | — | 2,346 individuals, 45.0 % Male samples |
Mean = 58.1 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
| PSS000969 | — | — | 81,902 individuals, 45.9 % Male samples |
— | European | — | UKB | This dataset is independent of UKB source/training and model selection datasets |
| PSS008964 | — | — | 3,863 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS009972 | — | — | 2,246 individuals | — | East Asian | — | UKB | — |
| PSS009973 | — | — | 14,058 individuals | — | European | — | NR | LLB |
| PSS009974 | — | — | 14,587 individuals | — | European | — | UKB | — |
| PSS009975 | — | — | 5,798 individuals | — | Hispanic or Latin American | — | PAGE | — |
| PSS008073 | — | — | 1,801 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS009976 | — | — | 9,257 individuals | — | South Asian | — | UKB | — |
| PSS009977 | — | — | 6,911 individuals | — | African unspecified | — | PAGE | — |
| PSS009978 | — | — | 8,238 individuals | — | African unspecified | — | UKB | — |
| PSS011219 | — | — | 190,013 individuals | — | European | — | EB | — |
| PSS010029 | Field ID: 50; Quantitative | — | 203,681 individuals | — | European | — | UKB | — |
| PSS011230 | — | — | 267,343 individuals | — | European | — | FinnGen | — |
| PSS011498 | — | — | 6,835 individuals | — | South Asian | — | G&H | — |
| PSS011103 | — | — | 2,885 individuals | — | European (non-white British ancestry) |
— | UKB | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS010876 | — | — | 19,949 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
| PSS010624 | — | — | 6,470 individuals, 45.0 % Male samples |
Mean = 54.5 years Sd = 8.4 years |
European | Italian | UKB | — |
| PSS008744 | — | — | 6,633 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS011243 | — | — | 34,089 individuals | — | South Asian | — | G&H | — |
| PSS010372 | — | — | 1,789 individuals, 33.0 % Male samples |
Mean = 52.4 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
| PSS011114 | — | — | 1,448 individuals | — | South Asian | — | UKB | — |
| PSS011803 | — | — | 19,353 individuals | — | African American or Afro-Caribbean | — | AllofUs | — |
| PSS007860 | — | — | 2,450 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011259 | — | — | 66,700 individuals | — | European | — | HUNT | — |
| PSS011813 | — | — | 13,065 individuals | — | Hispanic or Latin American | — | AllofUs | — |
| PSS011296 | 22,667 sibling pairs | — | 45,334 individuals | — | European | — | UKB | — |
| PSS011422 | — | — | 4,527 individuals, 42.0 % Male samples |
Mean = 51.82 years Sd = 8.06 years |
African American or Afro-Caribbean | — | UKB | — |
| PSS011823 | — | — | 45,413 individuals | — | European | — | AllofUs | — |