Trait: platelet count

Experimental Factor Ontology (EFO) Information
Identifier EFO_0004309
Description The number of PLATELETS per unit volume in a sample of venous BLOOD.
Trait category
Hematological measurement
Synonym blood platelet number
Mapped terms 4 mapped terms
  • MeSH:D010976
  • MedDRA:10035525
  • NCIt:C51951
  • SNOMEDCT:61928009

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)
PGS000109
(plt)
PGP000051 |
Xu Y et al. Cell Genom (2022)
Platelet count platelet count 26,683
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000109/ScoringFiles/PGS000109.txt.gz
PGS000186
(plt)
PGP000078 |
Vuckovic D et al. Cell (2020)
Platelet count platelet count 739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000186/ScoringFiles/PGS000186.txt.gz
PGS001238
(GBE_INI30080)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Platelet count platelet count 24,893
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001238/ScoringFiles/PGS001238.txt.gz
PGS001973
(portability-PLR_log_platelet)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Platelet count platelet count 60,665
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001973/ScoringFiles/PGS001973.txt.gz
PGS002191
(portability-ldpred2_log_platelet)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Platelet count platelet count 663,591
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002191/ScoringFiles/PGS002191.txt.gz
PGS002343
(blood_PLATELET_COUNT.BOLT-LMM)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 1,109,311
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002343/ScoringFiles/PGS002343.txt.gz
PGS002373
(blood_PLATELET_COUNT.BOLT-LMM-BBJ)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 920,923
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002373/ScoringFiles/PGS002373.txt.gz
PGS002415
(blood_PLATELET_COUNT.P+T.0.0001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 27,345
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002415/ScoringFiles/PGS002415.txt.gz
PGS002464
(blood_PLATELET_COUNT.P+T.0.001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 54,318
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002464/ScoringFiles/PGS002464.txt.gz
PGS002513
(blood_PLATELET_COUNT.P+T.0.01)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 170,052
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002513/ScoringFiles/PGS002513.txt.gz
PGS002562
(blood_PLATELET_COUNT.P+T.1e-06)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 12,742
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002562/ScoringFiles/PGS002562.txt.gz
PGS002611
(blood_PLATELET_COUNT.P+T.5e-08)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 9,050
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002611/ScoringFiles/PGS002611.txt.gz
PGS002660
(blood_PLATELET_COUNT.PolyFun-pred)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 396,074
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002660/ScoringFiles/PGS002660.txt.gz
PGS002709
(blood_PLATELET_COUNT.SBayesR)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Platelet count platelet count 981,460
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002709/ScoringFiles/PGS002709.txt.gz
PGS003546
(cont-decay-log_platelet)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Platelet count platelet count 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003546/ScoringFiles/PGS003546.txt.gz
PGS003932
(INI30080)
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Platelet count platelet count 32,944
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003932/ScoringFiles/PGS003932.txt.gz
PGS004582
(PRSice_T1)
PGP000563 |
Yang Z et al. Blood (2023)
Platelet count during the first trimester platelet count 407,667
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004582/ScoringFiles/PGS004582.txt.gz
PGS004583
(PRSice_T2)
PGP000563 |
Yang Z et al. Blood (2023)
Platelet count during the second trimester platelet count 104,759
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004583/ScoringFiles/PGS004583.txt.gz
PGS004584
(PRSice_T3)
PGP000563 |
Yang Z et al. Blood (2023)
Platelet count during the third trimester platelet count 5,597
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004584/ScoringFiles/PGS004584.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
PPM000250 PGS000109
(plt)
PSS000174|
European Ancestry|
78,246 individuals
PGP000051 |
Xu Y et al. Cell Genom (2022)
Reported Trait: Platelet count Pearson correlation coefficent (r): 0.52039 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)
PPM000251 PGS000109
(plt)
PSS000148|
European Ancestry|
38,939 individuals
PGP000051 |
Xu Y et al. Cell Genom (2022)
Reported Trait: Platelet count Pearson correlation coefficent (r): 0.53746 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)
PPM001775 PGS000186
(plt)
PSS000911|
Greater Middle Eastern Ancestry|
13,989 individuals
PGP000147 |
Thareja G et al. Nat Commun (2021)
|Ext.
Reported Trait: Platelet count Pearson correlation coefficent (r): 0.35
PPM000557 PGS000186
(plt)
PSS000290|
European Ancestry|
2,314 individuals
PGP000078 |
Vuckovic D et al. Cell (2020)
Reported Trait: Platelet count : 0.16049 sex, age, 10 genetic PCs
PPM000540 PGS000186
(plt)
PSS000291|
European Ancestry|
39,260 individuals
PGP000078 |
Vuckovic D et al. Cell (2020)
Reported Trait: Platelet count : 0.19195 sex, age, 10 genetic PCs
PPM008699 PGS001238
(GBE_INI30080)
PSS006946|
African Ancestry|
6,139 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Platelet count : 0.13129 [0.11599, 0.14659]
Incremental R2 (full-covars): 0.04423
PGS R2 (no covariates): 0.04881 [0.03859, 0.05902]
age, sex, UKB array type, Genotype PCs
PPM008700 PGS001238
(GBE_INI30080)
PSS006947|
East Asian Ancestry|
1,655 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Platelet count : 0.14398 [0.1132, 0.17476]
Incremental R2 (full-covars): 0.09414
PGS R2 (no covariates): 0.09846 [0.07165, 0.12527]
age, sex, UKB array type, Genotype PCs
PPM008701 PGS001238
(GBE_INI30080)
PSS006948|
European Ancestry|
24,175 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Platelet count : 0.26403 [0.25464, 0.27343]
Incremental R2 (full-covars): 0.21574
PGS R2 (no covariates): 0.21973 [0.21064, 0.22881]
age, sex, UKB array type, Genotype PCs
PPM008702 PGS001238
(GBE_INI30080)
PSS006949|
South Asian Ancestry|
7,520 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Platelet count : 0.24088 [0.22438, 0.25738]
Incremental R2 (full-covars): 0.15169
PGS R2 (no covariates): 0.153 [0.13833, 0.16767]
age, sex, UKB array type, Genotype PCs
PPM008703 PGS001238
(GBE_INI30080)
PSS006950|
European Ancestry|
65,637 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Platelet count : 0.26678 [0.26106, 0.2725]
Incremental R2 (full-covars): 0.20845
PGS R2 (no covariates): 0.20987 [0.20441, 0.21533]
age, sex, UKB array type, Genotype PCs
PPM010665 PGS001973
(portability-PLR_log_platelet)
PSS007903|
African Ancestry|
2,343 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.2414 [0.2028, 0.2794] sex, age, birth date, deprivation index, 16 PCs
PPM010659 PGS001973
(portability-PLR_log_platelet)
PSS009459|
European Ancestry|
19,422 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4839 [0.473, 0.4946] sex, age, birth date, deprivation index, 16 PCs
PPM010660 PGS001973
(portability-PLR_log_platelet)
PSS009233|
European Ancestry|
4,002 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4742 [0.4498, 0.498] sex, age, birth date, deprivation index, 16 PCs
PPM010661 PGS001973
(portability-PLR_log_platelet)
PSS008787|
European Ancestry|
6,436 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4739 [0.4547, 0.4927] sex, age, birth date, deprivation index, 16 PCs
PPM010662 PGS001973
(portability-PLR_log_platelet)
PSS008561|
Greater Middle Eastern Ancestry|
1,153 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4562 [0.4088, 0.5011] sex, age, birth date, deprivation index, 16 PCs
PPM010663 PGS001973
(portability-PLR_log_platelet)
PSS008339|
South Asian Ancestry|
6,076 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4242 [0.4034, 0.4447] sex, age, birth date, deprivation index, 16 PCs
PPM010664 PGS001973
(portability-PLR_log_platelet)
PSS008116|
East Asian Ancestry|
1,762 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.3503 [0.3084, 0.3908] sex, age, birth date, deprivation index, 16 PCs
PPM010666 PGS001973
(portability-PLR_log_platelet)
PSS009007|
African Ancestry|
3,711 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.2443 [0.2137, 0.2744] sex, age, birth date, deprivation index, 16 PCs
PPM012375 PGS002191
(portability-ldpred2_log_platelet)
PSS009459|
European Ancestry|
19,422 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4757 [0.4648, 0.4866] sex, age, birth date, deprivation index, 16 PCs
PPM012376 PGS002191
(portability-ldpred2_log_platelet)
PSS009233|
European Ancestry|
4,002 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.469 [0.4444, 0.4929] sex, age, birth date, deprivation index, 16 PCs
PPM012377 PGS002191
(portability-ldpred2_log_platelet)
PSS008787|
European Ancestry|
6,436 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.468 [0.4487, 0.4869] sex, age, birth date, deprivation index, 16 PCs
PPM012378 PGS002191
(portability-ldpred2_log_platelet)
PSS008561|
Greater Middle Eastern Ancestry|
1,153 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4476 [0.3998, 0.493] sex, age, birth date, deprivation index, 16 PCs
PPM012379 PGS002191
(portability-ldpred2_log_platelet)
PSS008339|
South Asian Ancestry|
6,076 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.4155 [0.3944, 0.4361] sex, age, birth date, deprivation index, 16 PCs
PPM012380 PGS002191
(portability-ldpred2_log_platelet)
PSS008116|
East Asian Ancestry|
1,762 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.3472 [0.3052, 0.3878] sex, age, birth date, deprivation index, 16 PCs
PPM012381 PGS002191
(portability-ldpred2_log_platelet)
PSS007903|
African Ancestry|
2,343 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.2554 [0.217, 0.293] sex, age, birth date, deprivation index, 16 PCs
PPM012382 PGS002191
(portability-ldpred2_log_platelet)
PSS009007|
African Ancestry|
3,711 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Platelet count Partial Correlation (partial-r): 0.2355 [0.2048, 0.2658] sex, age, birth date, deprivation index, 16 PCs
PPM013108 PGS002343
(blood_PLATELET_COUNT.BOLT-LMM)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0682 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013157 PGS002343
(blood_PLATELET_COUNT.BOLT-LMM)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0998 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013206 PGS002343
(blood_PLATELET_COUNT.BOLT-LMM)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.2489 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013255 PGS002343
(blood_PLATELET_COUNT.BOLT-LMM)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1747 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013285 PGS002373
(blood_PLATELET_COUNT.BOLT-LMM-BBJ)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0054 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013308 PGS002373
(blood_PLATELET_COUNT.BOLT-LMM-BBJ)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.091 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013331 PGS002373
(blood_PLATELET_COUNT.BOLT-LMM-BBJ)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0111 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013354 PGS002373
(blood_PLATELET_COUNT.BOLT-LMM-BBJ)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0186 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013396 PGS002415
(blood_PLATELET_COUNT.P+T.0.0001)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.001 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013494 PGS002415
(blood_PLATELET_COUNT.P+T.0.0001)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1524 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013543 PGS002415
(blood_PLATELET_COUNT.P+T.0.0001)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0979 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013445 PGS002415
(blood_PLATELET_COUNT.P+T.0.0001)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0672 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013592 PGS002464
(blood_PLATELET_COUNT.P+T.0.001)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0009 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013641 PGS002464
(blood_PLATELET_COUNT.P+T.0.001)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0596 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013690 PGS002464
(blood_PLATELET_COUNT.P+T.0.001)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1455 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013739 PGS002464
(blood_PLATELET_COUNT.P+T.0.001)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0778 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013788 PGS002513
(blood_PLATELET_COUNT.P+T.0.01)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0006 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013886 PGS002513
(blood_PLATELET_COUNT.P+T.0.01)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1163 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013935 PGS002513
(blood_PLATELET_COUNT.P+T.0.01)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0301 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013837 PGS002513
(blood_PLATELET_COUNT.P+T.0.01)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0374 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013984 PGS002562
(blood_PLATELET_COUNT.P+T.1e-06)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.035 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014033 PGS002562
(blood_PLATELET_COUNT.P+T.1e-06)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0664 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014131 PGS002562
(blood_PLATELET_COUNT.P+T.1e-06)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1092 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014082 PGS002562
(blood_PLATELET_COUNT.P+T.1e-06)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1496 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014180 PGS002611
(blood_PLATELET_COUNT.P+T.5e-08)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0343 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014229 PGS002611
(blood_PLATELET_COUNT.P+T.5e-08)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0598 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014278 PGS002611
(blood_PLATELET_COUNT.P+T.5e-08)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1408 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014327 PGS002611
(blood_PLATELET_COUNT.P+T.5e-08)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1049 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014376 PGS002660
(blood_PLATELET_COUNT.PolyFun-pred)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1041 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014425 PGS002660
(blood_PLATELET_COUNT.PolyFun-pred)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1227 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014474 PGS002660
(blood_PLATELET_COUNT.PolyFun-pred)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.2716 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014523 PGS002660
(blood_PLATELET_COUNT.PolyFun-pred)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.2014 age, sex, age*sex, assessment center, genotyping array, 10 PCs See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014572 PGS002709
(blood_PLATELET_COUNT.SBayesR)
PSS009815|
African Ancestry|
6,143 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0667 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014621 PGS002709
(blood_PLATELET_COUNT.SBayesR)
PSS009816|
East Asian Ancestry|
895 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.0811 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014670 PGS002709
(blood_PLATELET_COUNT.SBayesR)
PSS009817|
European Ancestry|
42,007 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.24 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014719 PGS002709
(blood_PLATELET_COUNT.SBayesR)
PSS009818|
South Asian Ancestry|
7,730 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Platelet count Incremental R2 (full model vs. covariates alone): 0.1748 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM017474 PGS003546
(cont-decay-log_platelet)
PSS010911|
European Ancestry|
19,418 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.23 sex, age, deprivation index, PC1-16
PPM017558 PGS003546
(cont-decay-log_platelet)
PSS010827|
European Ancestry|
3,991 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.22 sex, age, deprivation index, PC1-16
PPM017642 PGS003546
(cont-decay-log_platelet)
PSS010659|
European Ancestry|
6,277 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.21 sex, age, deprivation index, PC1-16
PPM017726 PGS003546
(cont-decay-log_platelet)
PSS010575|
Greater Middle Eastern Ancestry|
1,123 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.22 sex, age, deprivation index, PC1-16
PPM017810 PGS003546
(cont-decay-log_platelet)
PSS010239|
European Ancestry|
2,263 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.17 sex, age, deprivation index, PC1-16
PPM017894 PGS003546
(cont-decay-log_platelet)
PSS010491|
South Asian Ancestry|
6,024 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.17 sex, age, deprivation index, PC1-16
PPM017978 PGS003546
(cont-decay-log_platelet)
PSS010407|
East Asian Ancestry|
1,750 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.11 sex, age, deprivation index, PC1-16
PPM018062 PGS003546
(cont-decay-log_platelet)
PSS010323|
African Ancestry|
2,330 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.06 sex, age, deprivation index, PC1-16
PPM018146 PGS003546
(cont-decay-log_platelet)
PSS010743|
African Ancestry|
3,682 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Platelet count partial-R2: 0.06 sex, age, deprivation index, PC1-16
PPM018979 PGS003932
(INI30080)
PSS011145|
European Ancestry|
65,931 individuals
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Reported Trait: Platelet count : 0.26848 [0.26277, 0.27419]
PGS R2 (no covariates): 0.20939 [0.20394, 0.21484]
Incremental R2 (full-covars): 0.20822
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18)
PPM018980 PGS003932
(INI30080)
PSS011109|
European Ancestry|
2,813 individuals
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Reported Trait: Platelet count : 0.26562 [0.23807, 0.29316]
PGS R2 (no covariates): 0.22463 [0.19789, 0.25138]
Incremental R2 (full-covars): 0.22027
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18)
PPM018981 PGS003932
(INI30080)
PSS011113|
South Asian Ancestry|
1,433 individuals
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Reported Trait: Platelet count : 0.23486 [0.19726, 0.27247]
PGS R2 (no covariates): 0.15582 [0.12203, 0.18962]
Incremental R2 (full-covars): 0.15006
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18)
PPM018982 PGS003932
(INI30080)
PSS011155|
African Ancestry|
1,157 individuals
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Reported Trait: Platelet count : 0.13941 [0.10335, 0.17547]
PGS R2 (no covariates): 0.06653 [0.03951, 0.09355]
Incremental R2 (full-covars): 0.0492
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18)
PPM018983 PGS003932
(INI30080)
PSS011166|
Multi-ancestry (excluding European)|
7,746 individuals
PGP000502 |
Tanigawa Y et al. AJHG (2023)
Reported Trait: Platelet count : 0.24864 [0.23223, 0.26504]
PGS R2 (no covariates): 0.19334 [0.17781, 0.20888]
Incremental R2 (full-covars): 0.18573
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18)
PPM020697 PGS004582
(PRSice_T1)
PSS011369|
East Asian Ancestry|
818 individuals
PGP000563 |
Yang Z et al. Blood (2023)
Reported Trait: Gestational Thrombocytopenia AUROC: 0.617 : 0.02
PPM020698 PGS004583
(PRSice_T2)
PSS011370|
East Asian Ancestry|
878 individuals
PGP000563 |
Yang Z et al. Blood (2023)
Reported Trait: Gestational Thrombocytopenia AUROC: 0.637 : 0.035
PPM020699 PGS004584
(PRSice_T3)
PSS011371|
East Asian Ancestry|
615 individuals
PGP000563 |
Yang Z et al. Blood (2023)
Reported Trait: Gestational Thrombocytopenia AUROC: 0.637 : 0.057

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
PSS010911 19,418 individuals,
46.0 % Male samples
Mean = 56.9 years
Sd = 7.9 years
European white British UKB
PSS010659 6,277 individuals,
45.0 % Male samples
Mean = 54.5 years
Sd = 8.4 years
European Italian UKB
PSS011145 65,931 individuals European
(white British ancestry)
UKB
PSS010407 1,750 individuals,
33.0 % Male samples
Mean = 52.5 years
Sd = 7.8 years
East Asian Chinese UKB
PSS008787 6,436 individuals European Italy (South Europe) UKB
PSS011155 1,157 individuals African unspecified UKB
PSS011166 7,746 individuals East Asian, Other admixed ancestry East Asian, Other admixed ancestry UKB
PSS007903 2,343 individuals African American or Afro-Caribbean Carribean UKB
PSS000290 2,314 individuals European
(French Canadian)
CARTaGENE
PSS000291 39,260 individuals European INTERVAL
PSS008561 1,153 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS010827 3,991 individuals,
38.0 % Male samples
Mean = 54.3 years
Sd = 7.5 years
European Polish UKB
PSS009459 19,422 individuals European UK (+ Ireland) UKB
PSS000911 13,989 individuals Greater Middle Eastern (Middle Eastern, North African or Persian)
(Qatari)
QBB
PSS010575 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
PSS010323 2,330 individuals,
37.0 % Male samples
Mean = 52.4 years
Sd = 8.0 years
African American or Afro-Caribbean Caribbean UKB
PSS009815 6,143 individuals African unspecified UKB
PSS009816 895 individuals East Asian UKB
PSS009233 4,002 individuals European Poland (NE Europe) UKB
PSS009817 42,007 individuals European Non-British European UKB
PSS008339 6,076 individuals South Asian India (South Asia) UKB
PSS000148 38,939 individuals,
49.0 % Male samples
Mean = 43.75 years
Range = [18.0, 76.4] years
European INTERVAL
PSS009818 7,730 individuals South Asian UKB
PSS010743 3,682 individuals,
47.0 % Male samples
Mean = 51.9 years
Sd = 8.1 years
African unspecified Nigerian UKB
PSS010491 6,024 individuals,
55.0 % Male samples
Mean = 53.3 years
Sd = 8.4 years
South Asian Indian UKB
PSS010239 2,263 individuals,
45.0 % Male samples
Mean = 58.0 years
Sd = 7.1 years
European Ashkenazi UKB
PSS011109 2,813 individuals European
(non-white British ancestry)
UKB
PSS011113 1,433 individuals South Asian UKB
PSS006946 6,139 individuals African unspecified UKB
PSS006947 1,655 individuals East Asian UKB
PSS006948 24,175 individuals European non-white British ancestry UKB
PSS006949 7,520 individuals South Asian UKB
PSS000174 78,246 individuals,
46.0 % Male samples
Mean = 57.23 years
Range = [39.98, 70.43] years
European UKB
PSS006950 65,637 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS009007 3,711 individuals African unspecified Nigeria (West Africa) UKB
PSS011369 Pregnancy with at least one platelet count measurements in each trimester during pregnancy. If multiple platelet count measurements were available, the earilest platelet count measurements within each trimester was chosen. 818 individuals,
0.0 % Male samples
East Asian
(Chinese)
NIPT PLUS 5,733 Chinese pregnant women underwent non-invasive prenatal PLUS testing.
PSS011370 Pregnancy with at least one platelet count measurements in each trimester during pregnancy. If multiple platelet count measurements were available, the earilest platelet count measurements within each trimester was chosen. 878 individuals,
0.0 % Male samples
East Asian
(Chinese)
NIPT PLUS 5,733 Chinese pregnant women underwent non-invasive prenatal PLUS testing.
PSS011371 Pregnancy with at least one platelet count measurements in each trimester during pregnancy. If multiple platelet count measurements were available, the earilest platelet count measurements within each trimester was chosen. 615 individuals,
0.0 % Male samples
East Asian
(Chinese)
NIPT PLUS 5,733 Chinese pregnant women underwent non-invasive prenatal PLUS testing.
PSS008116 1,762 individuals East Asian China (East Asia) UKB