| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0009188 |
| Description | Red blood cell distribution width (RDW or RDW-CV or RCDW and RDW-SD) is a measure of the range of variation of red blood cell (RBC) volume that is reported as part of a standard complete blood count. Usually red blood cells are a standard size of about 6-8 μm in diameter. Certain disorders, however, cause a significant variation in cell size. Higher RDW values indicate greater variation in size. Normal reference range of RDW-CV in human red blood cells is 11.5-14.5%.[1] If anemia is observed, RDW test results are often used together with mean corpuscular volume (MCV) results to determine the possible causes of the anemia. It is mainly used to differentiate an anemia of mixed causes from an anemia of a single cause. | Trait category |
Hematological measurement
|
| Synonyms |
7 synonyms
|
| 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) |
|---|---|---|---|---|---|---|
| PGS000188 (rdw) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Red cell distribution width | Red cell distribution width | 546 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000188/ScoringFiles/PGS000188.txt.gz |
| PGS001152 (GBE_INI30070) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 10,179 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001152/ScoringFiles/PGS001152.txt.gz |
| PGS001908 (portability-PLR_erythrocyte_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 32,431 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001908/ScoringFiles/PGS001908.txt.gz |
| PGS002122 (portability-ldpred2_erythrocyte_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 543,714 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002122/ScoringFiles/PGS002122.txt.gz |
| PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002346/ScoringFiles/PGS002346.txt.gz |
| PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 16,996 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002418/ScoringFiles/PGS002418.txt.gz |
| PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 36,619 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002467/ScoringFiles/PGS002467.txt.gz |
| PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 136,154 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002516/ScoringFiles/PGS002516.txt.gz |
| PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 7,740 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002565/ScoringFiles/PGS002565.txt.gz |
| PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 5,543 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002614/ScoringFiles/PGS002614.txt.gz |
| PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 340,172 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002663/ScoringFiles/PGS002663.txt.gz |
| PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 976,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002712/ScoringFiles/PGS002712.txt.gz |
| PGS003503 (cont-decay-erythrocyte_width) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003503/ScoringFiles/PGS003503.txt.gz |
| PGS003931 (INI30070) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 12,557 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003931/ScoringFiles/PGS003931.txt.gz |
| PGS004351 (X30070.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004351/ScoringFiles/PGS004351.txt.gz |
| PGS004825 (RDW_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red cell distribution width | Red cell distribution width | 1,082,665 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004825/ScoringFiles/PGS004825.txt.gz |
| PGS004826 (RDW_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red cell distribution width | Red cell distribution width | 5,175,389 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004826/ScoringFiles/PGS004826.txt.gz |
| PGS004827 (RDW_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red cell distribution width | Red cell distribution width | 4,698,860 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004827/ScoringFiles/PGS004827.txt.gz |
| PGS004828 (RDW_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red cell distribution width | Red cell distribution width | 5,175,389 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004828/ScoringFiles/PGS004828.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000559 | PGS000188 (rdw) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red cell distribution width | — | — | R²: 0.07409 | sex, age, 10 genetic PCs | — |
| PPM000542 | PGS000188 (rdw) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red cell distribution width | — | — | R²: 0.09519 | sex, age, 10 genetic PCs | — |
| PPM008482 | PGS001152 (GBE_INI30070) |
PSS006941| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.02633 [0.01865, 0.03401] Incremental R2 (full-covars): 0.00466 PGS R2 (no covariates): 0.00617 [0.00238, 0.00997] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008483 | PGS001152 (GBE_INI30070) |
PSS006942| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.06947 [0.04623, 0.09271] Incremental R2 (full-covars): 0.04028 PGS R2 (no covariates): 0.04714 [0.02754, 0.06675] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008484 | PGS001152 (GBE_INI30070) |
PSS006943| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.08241 [0.07587, 0.08895] Incremental R2 (full-covars): 0.07409 PGS R2 (no covariates): 0.0754 [0.06909, 0.0817] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008485 | PGS001152 (GBE_INI30070) |
PSS006944| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.06357 [0.05312, 0.07403] Incremental R2 (full-covars): 0.04077 PGS R2 (no covariates): 0.04137 [0.03274, 0.05] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008486 | PGS001152 (GBE_INI30070) |
PSS006945| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.0852 [0.08117, 0.08923] Incremental R2 (full-covars): 0.07926 PGS R2 (no covariates): 0.07945 [0.07553, 0.08337] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010147 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS009400| European Ancestry| 19,392 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.3342 [0.3217, 0.3467] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010148 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS009174| European Ancestry| 3,996 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.3297 [0.3017, 0.3571] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010149 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS008728| European Ancestry| 6,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2987 [0.2762, 0.3208] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010150 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS008502| Greater Middle Eastern Ancestry| 1,144 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2615 [0.2062, 0.3152] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010151 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS008280| South Asian Ancestry| 6,035 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2435 [0.2196, 0.2671] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010152 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS008057| East Asian Ancestry| 1,757 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2371 [0.1922, 0.281] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010154 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS008948| African Ancestry| 3,680 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.1241 [0.092, 0.1558] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010153 | PGS001908 (portability-PLR_erythrocyte_width) |
PSS007844| African Ancestry| 2,328 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.1157 [0.0753, 0.1558] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011832 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS009174| European Ancestry| 3,996 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.3227 [0.2946, 0.3503] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011831 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS009400| European Ancestry| 19,392 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.3341 [0.3215, 0.3465] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011833 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS008728| European Ancestry| 6,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2938 [0.2713, 0.3161] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011834 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS008502| Greater Middle Eastern Ancestry| 1,144 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2528 [0.1972, 0.3067] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011835 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS008280| South Asian Ancestry| 6,035 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2424 [0.2185, 0.266] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011836 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS008057| East Asian Ancestry| 1,757 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.2289 [0.1838, 0.273] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011837 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS007844| African Ancestry| 2,328 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.0986 [0.058, 0.1388] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011838 | PGS002122 (portability-ldpred2_erythrocyte_width) |
PSS008948| African Ancestry| 3,680 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | Partial Correlation (partial-r): 0.1434 [0.1115, 0.175] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM013111 | PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0257 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013160 | PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0933 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013209 | PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.1557 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013258 | PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0998 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013399 | PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013448 | PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0576 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013497 | PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0994 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013546 | PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0649 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013595 | PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013644 | PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0099 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013693 | PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0856 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013742 | PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0084 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013791 | PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013840 | PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013889 | PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0643 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013938 | PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0048 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013987 | PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.014 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014036 | PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0554 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014085 | PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0938 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014134 | PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0644 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014183 | PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0136 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014232 | PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0506 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014281 | PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0887 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014330 | PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0604 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014379 | PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0343 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RBC_DISTRIB_WIDTH.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014428 | PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1048 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RBC_DISTRIB_WIDTH.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014477 | PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1682 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RBC_DISTRIB_WIDTH.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014526 | PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1097 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RBC_DISTRIB_WIDTH.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014575 | PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PSS009827| African Ancestry| 5,990 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0314 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014624 | PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PSS009828| East Asian Ancestry| 888 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0864 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014673 | PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PSS009829| European Ancestry| 41,837 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.1461 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014722 | PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PSS009830| South Asian Ancestry| 7,623 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Distribution Width | — | — | Incremental R2 (full model vs. covariates alone): 0.0986 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM017431 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010864| European Ancestry| 19,389 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.11 | sex, age, deprivation index, PC1-16 | — |
| PPM017515 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010780| European Ancestry| 3,985 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
| PPM017599 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010612| European Ancestry| 6,263 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.09 | sex, age, deprivation index, PC1-16 | — |
| PPM017683 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010528| Greater Middle Eastern Ancestry| 1,114 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
| PPM017851 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010444| South Asian Ancestry| 5,983 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.06 | sex, age, deprivation index, PC1-16 | — |
| PPM017935 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010360| East Asian Ancestry| 1,744 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.06 | sex, age, deprivation index, PC1-16 | — |
| PPM018019 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010276| African Ancestry| 2,315 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.01 | sex, age, deprivation index, PC1-16 | — |
| PPM017767 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010192| European Ancestry| 2,258 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.09 | sex, age, deprivation index, PC1-16 | — |
| PPM018103 | PGS003503 (cont-decay-erythrocyte_width) |
PSS010696| African Ancestry| 3,651 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | partial-R2: 0.02 | sex, age, deprivation index, PC1-16 | — |
| PPM018974 | PGS003931 (INI30070) |
PSS011136| European Ancestry| 65,932 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | R²: 0.09215 [0.088, 0.0963] PGS R2 (no covariates): 0.07947 [0.07556, 0.08338] Incremental R2 (full-covars): 0.07934 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018975 | PGS003931 (INI30070) |
PSS011109| European Ancestry| 2,813 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | R²: 0.10616 [0.08496, 0.12736] PGS R2 (no covariates): 0.08744 [0.06781, 0.10708] Incremental R2 (full-covars): 0.08479 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018976 | PGS003931 (INI30070) |
PSS011113| South Asian Ancestry| 1,433 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | R²: 0.06648 [0.04207, 0.09088] PGS R2 (no covariates): 0.05249 [0.03048, 0.07451] Incremental R2 (full-covars): 0.05172 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018977 | PGS003931 (INI30070) |
PSS011155| African Ancestry| 1,157 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | R²: 0.0264 [0.00865, 0.04415] PGS R2 (no covariates): 0.01807 [0.00326, 0.03288] Incremental R2 (full-covars): 0.01826 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018978 | PGS003931 (INI30070) |
PSS011166| Multi-ancestry (excluding European)| 7,746 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | R²: 0.08776 [0.07593, 0.09959] PGS R2 (no covariates): 0.06743 [0.05683, 0.07804] Incremental R2 (full-covars): 0.06076 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM020466 | PGS004351 (X30070.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Red blood cell (erythrocyte) distribution width | — | — | PGS R2 (no covariates): 0.26452 | — | — |
| PPM021050 | PGS004825 (RDW_PRSmix_eur) |
PSS011504| European Ancestry| 5,060 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red cell distribution width | — | — | Incremental R2 (Full model versus model with only covariates): 0.076 [0.062, 0.09] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021051 | PGS004826 (RDW_PRSmix_sas) |
PSS011473| South Asian Ancestry| 6,847 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red cell distribution width | — | — | Incremental R2 (Full model versus model with only covariates): 0.04 [0.031, 0.049] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021052 | PGS004827 (RDW_PRSmixPlus_eur) |
PSS011504| European Ancestry| 5,060 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red cell distribution width | — | — | Incremental R2 (Full model versus model with only covariates): 0.093 [0.078, 0.108] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021053 | PGS004828 (RDW_PRSmixPlus_sas) |
PSS011473| South Asian Ancestry| 6,847 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red cell distribution width | — | — | Incremental R2 (Full model versus model with only covariates): 0.047 [0.037, 0.056] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS010528 | — | — | 1,114 individuals, 60.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
| PSS010276 | — | — | 2,315 individuals, 37.0 % Male samples |
Mean = 52.5 years Sd = 8.1 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
| PSS011155 | — | — | 1,157 individuals | — | African unspecified | — | UKB | — |
| PSS009174 | — | — | 3,996 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS008280 | — | — | 6,035 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011166 | — | — | 7,746 individuals | — | East Asian, Other admixed ancestry | East Asian, Other admixed ancestry | UKB | — |
| PSS011473 | — | — | 6,847 individuals | — | South Asian | — | G&H | — |
| PSS000290 | — | — | 2,314 individuals | — | European (French Canadian) |
— | CARTaGENE | — |
| PSS000291 | — | — | 39,260 individuals | — | European | — | INTERVAL | — |
| PSS010696 | — | — | 3,651 individuals, 47.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
| PSS010444 | — | — | 5,983 individuals, 55.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
| PSS008948 | — | — | 3,680 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS010192 | — | — | 2,258 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
| PSS008057 | — | — | 1,757 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS011504 | — | — | 5,060 individuals | — | European | — | AllofUs | — |
| PSS010864 | — | — | 19,389 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
| PSS008728 | — | — | 6,422 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS010612 | — | — | 6,263 individuals, 45.0 % Male samples |
Mean = 54.5 years Sd = 8.4 years |
European | Italian | UKB | — |
| PSS009827 | — | — | 5,990 individuals | — | African unspecified | — | UKB | — |
| PSS009828 | — | — | 888 individuals | — | East Asian | — | UKB | — |
| PSS009829 | — | — | 41,837 individuals | — | European | Non-British European | UKB | — |
| PSS009830 | — | — | 7,623 individuals | — | South Asian | — | UKB | — |
| PSS010360 | — | — | 1,744 individuals, 33.0 % Male samples |
Mean = 52.5 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS007844 | — | — | 2,328 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS006941 | — | — | 6,139 individuals | — | African unspecified | — | UKB | — |
| PSS006942 | — | — | 1,655 individuals | — | East Asian | — | UKB | — |
| PSS006943 | — | — | 24,175 individuals | — | European | non-white British ancestry | UKB | — |
| PSS006944 | — | — | 7,520 individuals | — | South Asian | — | UKB | — |
| PSS006945 | — | — | 65,638 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011109 | — | — | 2,813 individuals | — | European (non-white British ancestry) |
— | UKB | — |
| PSS011113 | — | — | 1,433 individuals | — | South Asian | — | UKB | — |
| PSS008502 | — | — | 1,144 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009400 | — | — | 19,392 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011136 | — | — | 65,932 individuals | — | European (white British ancestry) |
— | UKB | — |
| PSS010780 | — | — | 3,985 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |