Trait: reticulocyte count

Experimental Factor Ontology (EFO) Information
Identifier EFO_0007986
Description The number of reticulocytes per unit volume of blood. Reticulocytes are immature red blood cells and typically compose aoubt 1% of red blood cells in the human body.
Trait category
Hematological measurement
Mapped term MedDRA:10038787

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
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS000094
(hlr)
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 High light scatter reticulocyte count reticulocyte count 25,493
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000094/ScoringFiles/PGS000094.txt.gz
PGS000095
(hlr_p)
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 High light scatter reticulocyte percentage of red cells reticulocyte count 21,957
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000095/ScoringFiles/PGS000095.txt.gz
PGS000096
(irf)
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Immature fraction of reticulocytes reticulocyte count 17,850
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000096/ScoringFiles/PGS000096.txt.gz
PGS000111
(ret)
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reticulocyte count reticulocyte count 26,077
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000111/ScoringFiles/PGS000111.txt.gz
PGS000112
(ret_p)
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reticulocyte fraction of red cells reticulocyte count 25,939
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000112/ScoringFiles/PGS000112.txt.gz
PGS000169
(hlr)
 PGP000078 |
Vuckovic D et al. Cell (2020)
 High light scatter reticulocyte count reticulocyte count 570
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000169/ScoringFiles/PGS000169.txt.gz
PGS000170
(hlr_p)
 PGP000078 |
Vuckovic D et al. Cell (2020)
 High light scatter reticulocyte percentage of red cells reticulocyte count 566
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000170/ScoringFiles/PGS000170.txt.gz
PGS000171
(irf)
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Immature fraction of reticulocytes reticulocyte count 372
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000171/ScoringFiles/PGS000171.txt.gz
PGS000189
(ret)
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reticulocyte count reticulocyte count 555
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000189/ScoringFiles/PGS000189.txt.gz
PGS000190
(ret_p)
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reticulocyte fraction of red cells reticulocyte count 537
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000190/ScoringFiles/PGS000190.txt.gz
PGS001528
(GBE_INI30250)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reticulocyte count reticulocyte count 6,262
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001528/ScoringFiles/PGS001528.txt.gz
PGS001976
(portability-PLR_log_reticulocyte)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reticulocyte count reticulocyte count 75,033
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001976/ScoringFiles/PGS001976.txt.gz
PGS002194
(portability-ldpred2_log_reticulocyte)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reticulocyte count reticulocyte count 773,305
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002194/ScoringFiles/PGS002194.txt.gz
PGS002333
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 1,109,311
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002333/ScoringFiles/PGS002333.txt.gz
PGS002405
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 16,031
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002405/ScoringFiles/PGS002405.txt.gz
PGS002454
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 37,335
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002454/ScoringFiles/PGS002454.txt.gz
PGS002503
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 143,701
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002503/ScoringFiles/PGS002503.txt.gz
PGS002552
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 6,655
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002552/ScoringFiles/PGS002552.txt.gz
PGS002601
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 4,569
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002601/ScoringFiles/PGS002601.txt.gz
PGS002650
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 406,785
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002650/ScoringFiles/PGS002650.txt.gz
PGS002699
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR)
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 High light scatter reticulocyte count reticulocyte count 983,680
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002699/ScoringFiles/PGS002699.txt.gz
PGS003551
(cont-decay-log_reticulocyte)
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reticulocyte count reticulocyte count 979,739
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003551/ScoringFiles/PGS003551.txt.gz
PGS003947
(INI30250)
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reticulocyte count reticulocyte count 9,558
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003947/ScoringFiles/PGS003947.txt.gz
PGS003952
(INI30300)
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 High light scatter reticulocyte count reticulocyte count 19,565
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003952/ScoringFiles/PGS003952.txt.gz
PGS004364
(X30250.score)
 PGP000561 |
Jung H et al. Commun Biol (2024)
 Reticulocyte count reticulocyte count 1,059,939
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004364/ScoringFiles/PGS004364.txt.gz
PGS004369
(X30300.score)
 PGP000561 |
Jung H et al. Commun Biol (2024)
 High light scatter reticulocyte count reticulocyte count 1,059,939
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004369/ScoringFiles/PGS004369.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
PPM000220 PGS000094
(hlr)
 PSS000159|
European Ancestry|
80,067 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: High light scatter reticulocyte count — — Pearson correlation coefficent (r): 0.4559 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)
PPM000221 PGS000094
(hlr)
 PSS000133|
European Ancestry|
40,244 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: High light scatter reticulocyte count — — Pearson correlation coefficent (r): 0.40097 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) —
PPM000222 PGS000095
(hlr_p)
 PSS000160|
European Ancestry|
80,088 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: High light scatter reticulocyte percentage of red cells — — Pearson correlation coefficent (r): 0.46291 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)
PPM000223 PGS000095
(hlr_p)
 PSS000134|
European Ancestry|
40,225 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: High light scatter reticulocyte percentage of red cells — — Pearson correlation coefficent (r): 0.40544 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) —
PPM000224 PGS000096
(irf)
 PSS000161|
European Ancestry|
79,282 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Immature fraction of reticulocytes — — Pearson correlation coefficent (r): 0.35972 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)
PPM000225 PGS000096
(irf)
 PSS000135|
European Ancestry|
40,227 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Immature fraction of reticulocytes — — Pearson correlation coefficent (r): 0.36441 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) —
PPM000254 PGS000111
(ret)
 PSS000176|
European Ancestry|
79,344 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Reticulocyte count — — Pearson correlation coefficent (r): 0.45071 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)
PPM000255 PGS000111
(ret)
 PSS000150|
European Ancestry|
40,253 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Reticulocyte count — — Pearson correlation coefficent (r): 0.44742 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) —
PPM000256 PGS000112
(ret_p)
 PSS000177|
European Ancestry|
79,362 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Reticulocyte fraction of red cells — — Pearson correlation coefficent (r): 0.45239 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)
PPM000257 PGS000112
(ret_p)
 PSS000151|
European Ancestry|
40,286 individuals
 PGP000051 |
Xu Y et al. Cell Genom (2022)
 Reported Trait: Reticulocyte fraction of red cells — — Pearson correlation coefficent (r): 0.45318 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) —
PPM000525 PGS000169
(hlr)
 PSS000291|
European Ancestry|
39,260 individuals
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.11896 sex, age, 10 genetic PCs —
PPM000526 PGS000170
(hlr_p)
 PSS000291|
European Ancestry|
39,260 individuals
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reported Trait: High light scatter reticulocyte percentage of red cells — — R²: 0.12799 sex, age, 10 genetic PCs —
PPM000527 PGS000171
(irf)
 PSS000291|
European Ancestry|
39,260 individuals
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reported Trait: Immature fraction of reticulocytes — — R²: 0.09164 sex, age, 10 genetic PCs —
PPM000543 PGS000189
(ret)
 PSS000291|
European Ancestry|
39,260 individuals
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reported Trait: Reticulocyte count — — R²: 0.14142 sex, age, 10 genetic PCs —
PPM000544 PGS000190
(ret_p)
 PSS000291|
European Ancestry|
39,260 individuals
 PGP000078 |
Vuckovic D et al. Cell (2020)
 Reported Trait: Reticulocyte fraction of red cells — — R²: 0.15022 sex, age, 10 genetic PCs —
PPM007061 PGS001528
(GBE_INI30250)
 PSS007022|
East Asian Ancestry|
1,623 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Reticulocyte count — — R²: 0.07592 [0.05179, 0.10005]
Incremental R2 (full-covars): 0.04581
PGS R2 (no covariates): 0.04535 [0.02608, 0.06461]		 age, sex, UKB array type, Genotype PCs —
PPM007062 PGS001528
(GBE_INI30250)
 PSS007023|
European Ancestry|
23,688 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Reticulocyte count — — R²: 0.04398 [0.039, 0.04896]
Incremental R2 (full-covars): 0.0298
PGS R2 (no covariates): 0.03007 [0.02589, 0.03425]		 age, sex, UKB array type, Genotype PCs —
PPM007063 PGS001528
(GBE_INI30250)
 PSS007024|
South Asian Ancestry|
7,323 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Reticulocyte count — — R²: 0.05148 [0.04195, 0.06101]
Incremental R2 (full-covars): 0.03077
PGS R2 (no covariates): 0.03212 [0.02444, 0.0398]		 age, sex, UKB array type, Genotype PCs —
PPM007060 PGS001528
(GBE_INI30250)
 PSS007021|
African Ancestry|
5,974 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Reticulocyte count — — R²: 0.03089 [0.02261, 0.03917]
Incremental R2 (full-covars): 0.01205
PGS R2 (no covariates): 0.01388 [0.00823, 0.01953]		 age, sex, UKB array type, Genotype PCs —
PPM007064 PGS001528
(GBE_INI30250)
 PSS007025|
European Ancestry|
64,570 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Reticulocyte count — — R²: 0.0518 [0.04854, 0.05506]
Incremental R2 (full-covars): 0.03968
PGS R2 (no covariates): 0.03966 [0.03677, 0.04254]		 age, sex, UKB array type, Genotype PCs —
PPM010683 PGS001976
(portability-PLR_log_reticulocyte)
 PSS009465|
European Ancestry|
19,117 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3967 [0.3847, 0.4086] sex, age, birth date, deprivation index, 16 PCs —
PPM010684 PGS001976
(portability-PLR_log_reticulocyte)
 PSS009239|
European Ancestry|
3,923 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3757 [0.3485, 0.4024] sex, age, birth date, deprivation index, 16 PCs —
PPM010685 PGS001976
(portability-PLR_log_reticulocyte)
 PSS008793|
European Ancestry|
6,297 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3753 [0.3538, 0.3963] sex, age, birth date, deprivation index, 16 PCs —
PPM010686 PGS001976
(portability-PLR_log_reticulocyte)
 PSS008567|
Greater Middle Eastern Ancestry|
1,127 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3116 [0.2574, 0.3638] sex, age, birth date, deprivation index, 16 PCs —
PPM010688 PGS001976
(portability-PLR_log_reticulocyte)
 PSS008122|
East Asian Ancestry|
1,722 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.2708 [0.2261, 0.3142] sex, age, birth date, deprivation index, 16 PCs —
PPM010690 PGS001976
(portability-PLR_log_reticulocyte)
 PSS009013|
African Ancestry|
3,602 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.1736 [0.1416, 0.2052] sex, age, birth date, deprivation index, 16 PCs —
PPM010687 PGS001976
(portability-PLR_log_reticulocyte)
 PSS008345|
South Asian Ancestry|
5,935 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.2981 [0.2747, 0.3211] sex, age, birth date, deprivation index, 16 PCs —
PPM010689 PGS001976
(portability-PLR_log_reticulocyte)
 PSS007909|
African Ancestry|
2,294 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.1931 [0.1532, 0.2323] sex, age, birth date, deprivation index, 16 PCs —
PPM012399 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS009465|
European Ancestry|
19,117 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.391 [0.3789, 0.403] sex, age, birth date, deprivation index, 16 PCs —
PPM012400 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS009239|
European Ancestry|
3,923 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3672 [0.3398, 0.3941] sex, age, birth date, deprivation index, 16 PCs —
PPM012401 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS008793|
European Ancestry|
6,297 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3718 [0.3503, 0.393] sex, age, birth date, deprivation index, 16 PCs —
PPM012402 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS008567|
Greater Middle Eastern Ancestry|
1,127 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.3104 [0.2562, 0.3627] sex, age, birth date, deprivation index, 16 PCs —
PPM012403 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS008345|
South Asian Ancestry|
5,935 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.2814 [0.2577, 0.3047] sex, age, birth date, deprivation index, 16 PCs —
PPM012404 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS008122|
East Asian Ancestry|
1,722 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.2574 [0.2125, 0.3013] sex, age, birth date, deprivation index, 16 PCs —
PPM012405 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS007909|
African Ancestry|
2,294 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.21 [0.1704, 0.249] sex, age, birth date, deprivation index, 16 PCs —
PPM012406 PGS002194
(portability-ldpred2_log_reticulocyte)
 PSS009013|
African Ancestry|
3,602 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Reticulocyte count — — Partial Correlation (partial-r): 0.1782 [0.1463, 0.2097] sex, age, birth date, deprivation index, 16 PCs —
PPM013147 PGS002333
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0931 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013196 PGS002333
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.1501 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013098 PGS002333
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0378 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013245 PGS002333
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0872 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013435 PGS002405
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.055 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013484 PGS002405
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0785 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013533 PGS002405
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.05 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013386 PGS002405
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0037 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013582 PGS002454
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0011 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013631 PGS002454
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0141 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013680 PGS002454
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0817 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013729 PGS002454
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0228 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013778 PGS002503
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0055 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013876 PGS002503
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0492 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013925 PGS002503
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0066 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013827 PGS002503
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0057 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM013974 PGS002552
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0149 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014072 PGS002552
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0653 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014121 PGS002552
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0442 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014023 PGS002552
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0649 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014219 PGS002601
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0643 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014268 PGS002601
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0598 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014170 PGS002601
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0141 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014317 PGS002601
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0413 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014513 PGS002650
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1032 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014366 PGS002650
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0563 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014415 PGS002650
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1068 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014464 PGS002650
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1606 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014562 PGS002699
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR)
 PSS009775|
African Ancestry|
5,976 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0423 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014611 PGS002699
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR)
 PSS009776|
East Asian Ancestry|
881 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0835 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014660 PGS002699
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR)
 PSS009777|
European Ancestry|
41,231 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.1452 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM014709 PGS002699
(blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR)
 PSS009778|
South Asian Ancestry|
7,560 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: High Light Scatter Reticulocyte Count — — Incremental R2 (full model vs. covariates alone): 0.0888 age, sex, age*sex, assessment center, genotyping array, 10 PCs —
PPM017479 PGS003551
(cont-decay-log_reticulocyte)
 PSS010917|
European Ancestry|
19,111 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.15 sex, age, deprivation index, PC1-16 —
PPM017563 PGS003551
(cont-decay-log_reticulocyte)
 PSS010833|
European Ancestry|
3,912 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.14 sex, age, deprivation index, PC1-16 —
PPM017647 PGS003551
(cont-decay-log_reticulocyte)
 PSS010665|
European Ancestry|
6,143 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.14 sex, age, deprivation index, PC1-16 —
PPM017731 PGS003551
(cont-decay-log_reticulocyte)
 PSS010581|
Greater Middle Eastern Ancestry|
1,097 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.09 sex, age, deprivation index, PC1-16 —
PPM017815 PGS003551
(cont-decay-log_reticulocyte)
 PSS010245|
European Ancestry|
2,221 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.13 sex, age, deprivation index, PC1-16 —
PPM017899 PGS003551
(cont-decay-log_reticulocyte)
 PSS010497|
South Asian Ancestry|
5,886 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.08 sex, age, deprivation index, PC1-16 —
PPM017983 PGS003551
(cont-decay-log_reticulocyte)
 PSS010413|
East Asian Ancestry|
1,711 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.07 sex, age, deprivation index, PC1-16 —
PPM018067 PGS003551
(cont-decay-log_reticulocyte)
 PSS010329|
African Ancestry|
2,282 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.04 sex, age, deprivation index, PC1-16 —
PPM018151 PGS003551
(cont-decay-log_reticulocyte)
 PSS010749|
African Ancestry|
3,574 individuals
 PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre		 Reported Trait: Reticulocyte count — — partial-R2: 0.03 sex, age, deprivation index, PC1-16 —
PPM019054 PGS003947
(INI30250)
 PSS011140|
European Ancestry|
64,861 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: Reticulocyte count — — R²: 0.0537 [0.0504, 0.057]
PGS R2 (no covariates): 0.04073 [0.03782, 0.04365]
Incremental R2 (full-covars): 0.04072		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019056 PGS003947
(INI30250)
 PSS011111|
South Asian Ancestry|
1,393 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: Reticulocyte count — — R²: 0.09735 [0.06879, 0.12592]
PGS R2 (no covariates): 0.07127 [0.04612, 0.09641]
Incremental R2 (full-covars): 0.06906		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019057 PGS003947
(INI30250)
 PSS011153|
African Ancestry|
1,125 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: Reticulocyte count — — R²: 0.02713 [0.00914, 0.04511]
PGS R2 (no covariates): 0.01461 [0.00124, 0.02797]
Incremental R2 (full-covars): 0.01527		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019058 PGS003947
(INI30250)
 PSS011169|
Multi-ancestry (excluding European)|
7,578 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: Reticulocyte count — — R²: 0.05468 [0.045, 0.06436]
PGS R2 (no covariates): 0.03553 [0.02757, 0.04349]
Incremental R2 (full-covars): 0.03303		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019055 PGS003947
(INI30250)
 PSS011099|
European Ancestry|
2,770 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: Reticulocyte count — — R²: 0.10144 [0.08061, 0.12226]
PGS R2 (no covariates): 0.07084 [0.05284, 0.08884]
Incremental R2 (full-covars): 0.07225		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019079 PGS003952
(INI30300)
 PSS011143|
European Ancestry|
64,816 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.13075 [0.12601, 0.13548]
PGS R2 (no covariates): 0.11335 [0.10885, 0.11784]
Incremental R2 (full-covars): 0.11327		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019080 PGS003952
(INI30300)
 PSS011100|
European Ancestry|
2,768 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.14122 [0.11773, 0.16471]
PGS R2 (no covariates): 0.12176 [0.09946, 0.14407]
Incremental R2 (full-covars): 0.12235		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019081 PGS003952
(INI30300)
 PSS011111|
South Asian Ancestry|
1,393 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.11255 [0.08236, 0.14275]
PGS R2 (no covariates): 0.0909 [0.0631, 0.1187]
Incremental R2 (full-covars): 0.08654		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019082 PGS003952
(INI30300)
 PSS011153|
African Ancestry|
1,125 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.04777 [0.02441, 0.07112]
PGS R2 (no covariates): 0.04026 [0.01865, 0.06188]
Incremental R2 (full-covars): 0.04027		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM019083 PGS003952
(INI30300)
 PSS011170|
Multi-ancestry (excluding European)|
7,574 individuals
 PGP000502 |
Tanigawa Y et al. AJHG (2023)
 Reported Trait: High light scatter reticulocyte count — — R²: 0.12479 [0.11125, 0.13833]
PGS R2 (no covariates): 0.09343 [0.0813, 0.10557]
Incremental R2 (full-covars): 0.08525		 age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) —
PPM020479 PGS004364
(X30250.score)
 PSS011364|
European Ancestry|
56,192 individuals
 PGP000561 |
Jung H et al. Commun Biol (2024)
 Reported Trait: Reticulocyte count — — PGS R2 (no covariates): 0.26266 — —
PPM020484 PGS004369
(X30300.score)
 PSS011364|
European Ancestry|
56,192 individuals
 PGP000561 |
Jung H et al. Commun Biol (2024)
 Reported Trait: High light scatter reticulocyte count — — PGS R2 (no covariates): 0.27177 — —

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
PSS011140 — — 64,861 individuals — European
(white British ancestry)		 — UKB —
PSS011143 — — 64,816 individuals — European
(white British ancestry)		 — UKB —
PSS010917 — — 19,111 individuals,
46.0 % Male samples
 Mean = 56.9 years
Sd = 7.9 years		 European white British UKB —
PSS010665 — — 6,143 individuals,
45.0 % Male samples
 Mean = 54.4 years
Sd = 8.4 years		 European Italian UKB —
PSS011153 — — 1,125 individuals — African unspecified — UKB —
PSS010413 — — 1,711 individuals,
33.0 % Male samples
 Mean = 52.4 years
Sd = 7.8 years		 East Asian Chinese UKB —
PSS008793 — — 6,297 individuals — European Italy (South Europe) UKB —
PSS011169 — — 7,578 individuals — East Asian, Other admixed ancestry East Asian, Other admixed ancestry UKB —
PSS011170 — — 7,574 individuals — East Asian, Other admixed ancestry East Asian, Other admixed ancestry UKB —
PSS007909 — — 2,294 individuals — African American or Afro-Caribbean Carribean UKB —
PSS009775 — — 5,976 individuals — African unspecified — UKB —
PSS009776 — — 881 individuals — East Asian — UKB —
PSS009777 — — 41,231 individuals — European Non-British European UKB —
PSS009778 — — 7,560 individuals — South Asian — UKB —
PSS000291 — — 39,260 individuals — European — INTERVAL —
PSS007021 — — 5,974 individuals — African unspecified — UKB —
PSS007022 — — 1,623 individuals — East Asian — UKB —
PSS007023 — — 23,688 individuals — European non-white British ancestry UKB —
PSS007024 — — 7,323 individuals — South Asian — UKB —
PSS007025 — — 64,570 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS009465 — — 19,117 individuals — European UK (+ Ireland) UKB —
PSS008567 — — 1,127 individuals — Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB —
PSS010833 — — 3,912 individuals,
38.0 % Male samples
 Mean = 54.3 years
Sd = 7.5 years		 European Polish UKB —
PSS010581 — — 1,097 individuals,
59.0 % Male samples
 Mean = 52.0 years
Sd = 8.0 years		 Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB —
PSS010329 — — 2,282 individuals,
37.0 % Male samples
 Mean = 52.4 years
Sd = 8.0 years		 African American or Afro-Caribbean Caribbean UKB —
PSS000133 — — 40,244 individuals,
49.0 % Male samples
 Mean = 43.84 years
Range = [18.0, 76.4] years		 European — INTERVAL —
PSS000134 — — 40,225 individuals,
49.0 % Male samples
 Mean = 43.84 years
Range = [18.0, 76.4] years		 European — INTERVAL —
PSS000135 — — 40,227 individuals,
49.0 % Male samples
 Mean = 43.85 years
Range = [18.0, 76.4] years		 European — INTERVAL —
PSS000150 — — 40,253 individuals,
49.0 % Male samples
 Mean = 43.84 years
Range = [18.0, 76.4] years		 European — INTERVAL —
PSS000151 — — 40,286 individuals,
49.0 % Male samples
 Mean = 43.84 years
Range = [18.0, 76.4] years		 European — INTERVAL —
PSS009239 — — 3,923 individuals — European Poland (NE Europe) UKB —
PSS008345 — — 5,935 individuals — South Asian India (South Asia) UKB —
PSS011099 — — 2,770 individuals — European
(non-white British ancestry)		 — UKB —
PSS011100 — — 2,768 individuals — European
(non-white British ancestry)		 — UKB —
PSS000159 — — 80,067 individuals,
46.0 % Male samples
 Mean = 57.2 years
Range = [39.91, 70.52] years		 European — UKB —
PSS000160 — — 80,088 individuals,
46.0 % Male samples
 Mean = 57.19 years
Range = [39.66, 72.91] years		 European — UKB —
PSS000161 — — 79,282 individuals,
46.0 % Male samples
 Mean = 57.28 years
Range = [39.91, 70.99] years		 European — UKB —
PSS011364 — — 56,192 individuals — European — UKB —
PSS010749 — — 3,574 individuals,
47.0 % Male samples
 Mean = 51.9 years
Sd = 8.1 years		 African unspecified Nigerian UKB —
PSS010497 — — 5,886 individuals,
55.0 % Male samples
 Mean = 53.3 years
Sd = 8.4 years		 South Asian Indian UKB —
PSS011111 — — 1,393 individuals — South Asian — UKB —
PSS010245 — — 2,221 individuals,
45.0 % Male samples
 Mean = 58.0 years
Sd = 7.1 years		 European Ashkenazi UKB —
PSS000176 — — 79,344 individuals,
46.0 % Male samples
 Mean = 57.29 years
Range = [39.66, 72.91] years		 European — UKB —
PSS000177 — — 79,362 individuals,
46.0 % Male samples
 Mean = 57.22 years
Range = [39.66, 72.91] years		 European — UKB —
PSS009013 — — 3,602 individuals — African unspecified Nigeria (West Africa) UKB —
PSS008122 — — 1,722 individuals — East Asian China (East Asia) UKB —