PGS Catalog - reticulocyte count [EFO:0007986] (Polygenic Trait)

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)

Polygenic Score ID & Name	PGS Publication ID (PGP)	Reported Trait	Mapped Trait(s) (Ontology)	Number of Variants	Ancestry distribution	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

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	—

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
PSS008793	—	—	6,297 individuals	—	European	Italy (South Europe)	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	—
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	—
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	—
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	—