| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004305 |
| Description | The number of red blood cells per unit volume in a sample of venous blood. | Trait category |
Hematological measurement
|
| Synonyms |
3 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) |
|---|---|---|---|---|---|---|
| PGS000110 (rbc) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Red blood cell count | erythrocyte count | 23,242 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000110/ScoringFiles/PGS000110.txt.gz | |
| PGS000187 (rbc) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Red blood cell count | erythrocyte count | 678 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000187/ScoringFiles/PGS000187.txt.gz |
| PGS001240 (GBE_INI30010) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Red blood cell count | erythrocyte count | 20,480 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001240/ScoringFiles/PGS001240.txt.gz |
| PGS001909 (portability-PLR_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 81,887 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001909/ScoringFiles/PGS001909.txt.gz |
| PGS002123 (portability-ldpred2_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 788,123 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002123/ScoringFiles/PGS002123.txt.gz |
| PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002345/ScoringFiles/PGS002345.txt.gz |
| PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 920,935 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002374/ScoringFiles/PGS002374.txt.gz |
| PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 18,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002417/ScoringFiles/PGS002417.txt.gz |
| PGS002466 (blood_RED_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 41,471 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002466/ScoringFiles/PGS002466.txt.gz |
| PGS002515 (blood_RED_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 150,047 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002515/ScoringFiles/PGS002515.txt.gz |
| PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 7,590 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002564/ScoringFiles/PGS002564.txt.gz |
| PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 5,156 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002613/ScoringFiles/PGS002613.txt.gz |
| PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 473,515 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002662/ScoringFiles/PGS002662.txt.gz |
| PGS002711 (blood_RED_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red blood cell count | erythrocyte count | 982,902 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002711/ScoringFiles/PGS002711.txt.gz |
| PGS003478 (LDPred2_RBC) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Red blood cell count | erythrocyte count | 860,281 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003478/ScoringFiles/PGS003478.txt.gz |
| PGS003502 (cont-decay-erythrocyte) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Red blood cell (erythrocyte) count | erythrocyte count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003502/ScoringFiles/PGS003502.txt.gz |
| PGS003925 (INI30010) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Red blood cell (erythrocyte) count | erythrocyte count | 27,293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003925/ScoringFiles/PGS003925.txt.gz |
| PGS004346 (X30010.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Red blood cell (erythrocyte) count | erythrocyte count | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004346/ScoringFiles/PGS004346.txt.gz |
| PGS004821 (RBC_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red blood cell count | erythrocyte count | 1,160,061 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004821/ScoringFiles/PGS004821.txt.gz |
| PGS004822 (RBC_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red blood cell count | erythrocyte count | 1,874,761 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004822/ScoringFiles/PGS004822.txt.gz |
| PGS004823 (RBC_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red blood cell count | erythrocyte count | 4,047,636 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004823/ScoringFiles/PGS004823.txt.gz |
| PGS004824 (RBC_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Red blood cell count | erythrocyte count | 1,542,933 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004824/ScoringFiles/PGS004824.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000252 | PGS000110 (rbc) |
PSS000175| European Ancestry| 81,614 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.45067 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | UKB Testing Set - these samples were held out from Score Development (regression training) but overlap with the samples used for variant selection (GWAS) |
| PPM000253 | PGS000110 (rbc) |
PSS000149| European Ancestry| 40,262 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.42574 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | — |
| PPM000558 | PGS000187 (rbc) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.06798 | sex, age, 10 genetic PCs | — |
| PPM000541 | PGS000187 (rbc) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.11765 | sex, age, 10 genetic PCs | — |
| PPM001771 | PGS000187 (rbc) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.22 | — | — |
| PPM008709 | PGS001240 (GBE_INI30010) |
PSS006896| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.26906 [0.25063, 0.28749] Incremental R2 (full-covars): 0.01652 PGS R2 (no covariates): 0.01819 [0.01175, 0.02463] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008710 | PGS001240 (GBE_INI30010) |
PSS006897| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.32546 [0.289, 0.36193] Incremental R2 (full-covars): 0.04519 PGS R2 (no covariates): 0.05665 [0.03538, 0.07793] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008711 | PGS001240 (GBE_INI30010) |
PSS006898| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37954 [0.37005, 0.38904] Incremental R2 (full-covars): 0.10462 PGS R2 (no covariates): 0.11155 [0.10418, 0.11892] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008712 | PGS001240 (GBE_INI30010) |
PSS006899| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.33598 [0.31894, 0.35302] Incremental R2 (full-covars): 0.05745 PGS R2 (no covariates): 0.05295 [0.0433, 0.0626] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008713 | PGS001240 (GBE_INI30010) |
PSS006900| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37344 [0.36766, 0.37922] Incremental R2 (full-covars): 0.11681 PGS R2 (no covariates): 0.11784 [0.11327, 0.12241] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010155 | PGS001909 (portability-PLR_erythrocyte) |
PSS009399| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3987 [0.3868, 0.4105] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010156 | PGS001909 (portability-PLR_erythrocyte) |
PSS009173| European Ancestry| 4,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.404 [0.3776, 0.4296] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010157 | PGS001909 (portability-PLR_erythrocyte) |
PSS008727| European Ancestry| 6,437 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3387 [0.3169, 0.3602] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010158 | PGS001909 (portability-PLR_erythrocyte) |
PSS008501| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3306 [0.2777, 0.3815] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010159 | PGS001909 (portability-PLR_erythrocyte) |
PSS008279| South Asian Ancestry| 6,078 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2916 [0.2684, 0.3145] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010160 | PGS001909 (portability-PLR_erythrocyte) |
PSS008056| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2689 [0.2247, 0.3119] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010161 | PGS001909 (portability-PLR_erythrocyte) |
PSS007843| African Ancestry| 2,342 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1886 [0.149, 0.2275] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010162 | PGS001909 (portability-PLR_erythrocyte) |
PSS008947| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1298 [0.098, 0.1614] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011839 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS009399| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.39 [0.3781, 0.4019] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011840 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS009173| European Ancestry| 4,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.398 [0.3716, 0.4239] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011841 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008727| European Ancestry| 6,437 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3326 [0.3107, 0.3542] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011842 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008501| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3308 [0.2779, 0.3816] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011843 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008279| South Asian Ancestry| 6,078 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2888 [0.2656, 0.3117] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011844 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008056| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.271 [0.2269, 0.314] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011845 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS007843| African Ancestry| 2,342 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1984 [0.159, 0.2371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011846 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008947| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1336 [0.1018, 0.1651] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM013208 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1566 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013257 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0917 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013110 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0248 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013159 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0807 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013286 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013309 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0611 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013332 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0146 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013355 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0119 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013398 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0031 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013447 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0331 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013545 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.037 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013496 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0916 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013594 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013643 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0089 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013741 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.027 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013692 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0939 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013790 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013839 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0033 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013937 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.018 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013888 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0705 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014035 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0602 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014084 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0762 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013986 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0079 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014133 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0496 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014182 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0114 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014231 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0594 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014280 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0684 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014329 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0445 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014427 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0976 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014476 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1679 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014525 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1044 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014378 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0299 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014574 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.027 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014672 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1523 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014623 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0804 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014721 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0944 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM017288 | PGS003478 (LDPred2_RBC) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Respiratory event index | β: -0.001 (0.01) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017311 | PGS003478 (LDPred2_RBC) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Obstructive sleep apnea | β: 0.008 (0.024) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017598 | PGS003502 (cont-decay-erythrocyte) |
PSS010611| European Ancestry| 6,278 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.12 | sex, age, deprivation index, PC1-16 | — |
| PPM017682 | PGS003502 (cont-decay-erythrocyte) |
PSS010527| Greater Middle Eastern Ancestry| 1,123 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
| PPM017766 | PGS003502 (cont-decay-erythrocyte) |
PSS010191| European Ancestry| 2,264 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.15 | sex, age, deprivation index, PC1-16 | — |
| PPM017934 | PGS003502 (cont-decay-erythrocyte) |
PSS010359| East Asian Ancestry| 1,750 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.08 | sex, age, deprivation index, PC1-16 | — |
| PPM018018 | PGS003502 (cont-decay-erythrocyte) |
PSS010275| African Ancestry| 2,329 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
| PPM018102 | PGS003502 (cont-decay-erythrocyte) |
PSS010695| African Ancestry| 3,682 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.02 | sex, age, deprivation index, PC1-16 | — |
| PPM017430 | PGS003502 (cont-decay-erythrocyte) |
PSS010863| European Ancestry| 19,416 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.16 | sex, age, deprivation index, PC1-16 | — |
| PPM017514 | PGS003502 (cont-decay-erythrocyte) |
PSS010779| European Ancestry| 3,990 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.16 | sex, age, deprivation index, PC1-16 | — |
| PPM017850 | PGS003502 (cont-decay-erythrocyte) |
PSS010443| South Asian Ancestry| 6,026 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Red blood cell (erythrocyte) count | — | — | partial-R2: 0.08 | sex, age, deprivation index, PC1-16 | — |
| PPM018944 | PGS003925 (INI30010) |
PSS011136| European Ancestry| 65,932 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | R²: 0.38181 [0.37606, 0.38756] PGS R2 (no covariates): 0.1179 [0.11333, 0.12246] Incremental R2 (full-covars): 0.1164 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018945 | PGS003925 (INI30010) |
PSS011109| European Ancestry| 2,813 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | R²: 0.38936 [0.36163, 0.41709] PGS R2 (no covariates): 0.09281 [0.0727, 0.11293] Incremental R2 (full-covars): 0.09305 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018946 | PGS003925 (INI30010) |
PSS011113| South Asian Ancestry| 1,433 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | R²: 0.35286 [0.31388, 0.39185] PGS R2 (no covariates): 0.07492 [0.04924, 0.1006] Incremental R2 (full-covars): 0.0761 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018947 | PGS003925 (INI30010) |
PSS011155| African Ancestry| 1,157 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | R²: 0.29476 [0.25179, 0.33773] PGS R2 (no covariates): 0.04144 [0.01954, 0.06333] Incremental R2 (full-covars): 0.03544 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM018948 | PGS003925 (INI30010) |
PSS011166| Multi-ancestry (excluding European)| 7,746 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | R²: 0.38816 [0.37147, 0.40486] PGS R2 (no covariates): 0.10146 [0.08893, 0.114] Incremental R2 (full-covars): 0.07754 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
| PPM020461 | PGS004346 (X30010.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | PGS R2 (no covariates): 0.24747 | — | — |
| PPM021046 | PGS004821 (RBC_PRSmix_eur) |
PSS011503| European Ancestry| 5,163 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red blood count | — | — | Incremental R2 (Full model versus model with only covariates): 0.08 [0.066, 0.094] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021047 | PGS004822 (RBC_PRSmix_sas) |
PSS011472| South Asian Ancestry| 7,055 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red blood count | — | — | Incremental R2 (Full model versus model with only covariates): 0.039 [0.031, 0.048] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021048 | PGS004823 (RBC_PRSmixPlus_eur) |
PSS011503| European Ancestry| 5,163 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red blood count | — | — | Incremental R2 (Full model versus model with only covariates): 0.083 [0.068, 0.097] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021049 | PGS004824 (RBC_PRSmixPlus_sas) |
PSS011472| South Asian Ancestry| 7,055 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Red blood count | — | — | Incremental R2 (Full model versus model with only covariates): 0.041 [0.031, 0.05] | 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 |
|---|---|---|---|---|---|---|---|---|
| PSS010527 | — | — | 1,123 individuals, 59.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
| PSS010275 | — | — | 2,329 individuals, 36.0 % Male samples |
Mean = 52.4 years Sd = 8.0 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
| PSS011155 | — | — | 1,157 individuals | — | African unspecified | — | UKB | — |
| PSS009173 | — | — | 4,001 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS008279 | — | — | 6,078 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011166 | — | — | 7,746 individuals | — | East Asian, Other admixed ancestry | East Asian, Other admixed ancestry | UKB | — |
| PSS011472 | — | — | 7,055 individuals | — | South Asian | — | G&H | — |
| PSS000290 | — | — | 2,314 individuals | — | European (French Canadian) |
— | CARTaGENE | — |
| PSS000291 | — | — | 39,260 individuals | — | European | — | INTERVAL | — |
| PSS010695 | — | — | 3,682 individuals, 47.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
| PSS010443 | — | — | 6,026 individuals, 55.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
| PSS008947 | — | — | 3,711 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS000911 | — | — | 13,989 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
| PSS010191 | — | — | 2,264 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
| PSS006896 | — | — | 6,139 individuals | — | African unspecified | — | UKB | — |
| PSS006897 | — | — | 1,655 individuals | — | East Asian | — | UKB | — |
| PSS006898 | — | — | 24,175 individuals | — | European | non-white British ancestry | UKB | — |
| PSS006899 | — | — | 7,520 individuals | — | South Asian | — | UKB | — |
| PSS006900 | — | — | 65,638 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008056 | — | — | 1,762 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS010185 | — | — | 1,115 individuals, 41.1 % Male samples |
Mean = 46.18 years | Hispanic or Latin American | — | HCHS, SOL | — |
| PSS011503 | — | — | 5,163 individuals | — | European | — | AllofUs | — |
| PSS000149 | — | — | 40,262 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
| PSS010863 | — | — | 19,416 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
| PSS008727 | — | — | 6,437 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS009823 | — | — | 6,120 individuals | — | African unspecified | — | UKB | — |
| PSS009825 | — | — | 42,065 individuals | — | European | Non-British European | UKB | — |
| PSS009826 | — | — | 7,707 individuals | — | South Asian | — | UKB | — |
| PSS009824 | — | — | 885 individuals | — | East Asian | — | UKB | — |
| PSS010611 | — | — | 6,278 individuals, 45.0 % Male samples |
Mean = 54.5 years Sd = 8.4 years |
European | Italian | UKB | — |
| PSS010359 | — | — | 1,750 individuals, 33.0 % Male samples |
Mean = 52.5 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS007843 | — | — | 2,342 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011109 | — | — | 2,813 individuals | — | European (non-white British ancestry) |
— | UKB | — |
| PSS011113 | — | — | 1,433 individuals | — | South Asian | — | UKB | — |
| PSS000175 | — | — | 81,614 individuals, 45.0 % Male samples |
Mean = 57.26 years Range = [39.99, 70.99] years |
European | — | UKB | — |
| PSS008501 | — | — | 1,153 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009399 | — | — | 19,422 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011136 | — | — | 65,932 individuals | — | European (white British ancestry) |
— | UKB | — |
| PSS010779 | — | — | 3,990 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |