Trait: erythrocyte count

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
  • RBC
  • erythrocyte number
  • red blood cell count
Mapped terms 3 mapped terms
  • MeSH:D004906
  • NCIt:C51946
  • SNOMEDCT:14089001

Associated Polygenic Score(s)

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

Performance Metrics

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

PGS Performance
Metric ID (PPM) 		Evaluated Score PGS Sample Set ID
(PSS) 		Performance Source Trait PGS Effect Sizes
(per SD change) 		Classification Metrics Other Metrics Covariates Included in the Model PGS Performance:
Other Relevant Information
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 —

Evaluated Samples

PGS Sample Set ID
(PSS) 		Phenotype Definitions and Methods Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
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 —
PSS009173 — — 4,001 individuals — European Poland (NE Europe) UKB —
PSS008279 — — 6,078 individuals — South Asian India (South Asia) UKB —
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 —
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 —
PSS007843 — — 2,342 individuals — African American or Afro-Caribbean Carribean 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 —
PSS010779 — — 3,990 individuals,
38.0 % Male samples
 Mean = 54.3 years
Sd = 7.5 years		 European Polish UKB —