Trait: reticulocyte measurement

Experimental Factor Ontology (EFO) Information
Identifier EFO_0010700
Description A quantification of some aspect of reticulocyte function, quantity, or composition.
Trait category
Hematological measurement
Child trait(s) 2 child traits

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
Note: This table shows all PGS for "reticulocyte measurement" and any child terms of this trait in the EFO hierarchy by default.
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. bioRxiv (2020)
|Pre
High light scatter reticulocyte count reticulocyte count 605
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000094/ScoringFiles/PGS000094.txt.gz
PGS000095
(hlr_p)
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
High light scatter reticulocyte percentage of red cells reticulocyte count 594
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000095/ScoringFiles/PGS000095.txt.gz
PGS000096
(irf)
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Immature fraction of reticulocytes reticulocyte count 390
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000096/ScoringFiles/PGS000096.txt.gz
PGS000111
(ret)
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reticulocyte count reticulocyte count 590
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000111/ScoringFiles/PGS000111.txt.gz
PGS000112
(ret_p)
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reticulocyte fraction of red cells reticulocyte count 572
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
PGS000180
(mrv)
PGP000078 |
Vuckovic D et al. Cell (2020)
Mean reticulocyte volume mean reticulocyte volume 629
-
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000180/ScoringFiles/PGS000180.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
PGS000987
(GBE_INI30260)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Mean reticulocyte volume mean reticulocyte volume 13,277
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000987/ScoringFiles/PGS000987.txt.gz
PGS000988
(GBE_INI30290)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
High light scatter reticulocyte percentage reticulocyte measurement 7,184
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000988/ScoringFiles/PGS000988.txt.gz
PGS000989
(GBE_INI30240)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reticulocyte % reticulocyte measurement 6,251
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000989/ScoringFiles/PGS000989.txt.gz
PGS001406
(GBE_INI30300)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
High light scatter reticulocyte count reticulocyte measurement 15,856
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001406/ScoringFiles/PGS001406.txt.gz
PGS001528
(GBE_INI30250)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reticulocyte count reticulocyte count 6,262
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001528/ScoringFiles/PGS001528.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. bioRxiv (2020)
|Pre
Reported Trait: High light scatter reticulocyte count Pearson correlation coefficent (r): 0.4294 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)
PPM000222 PGS000095
(hlr_p)
PSS000160|
European Ancestry|
80,088 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: High light scatter reticulocyte percentage of red cells Pearson correlation coefficent (r): 0.4385 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)
PPM000224 PGS000096
(irf)
PSS000161|
European Ancestry|
79,282 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Immature fraction of reticulocytes Pearson correlation coefficent (r): 0.3512 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)
PPM000254 PGS000111
(ret)
PSS000176|
European Ancestry|
79,344 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Reticulocyte count Pearson correlation coefficent (r): 0.4241 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)
PPM000256 PGS000112
(ret_p)
PSS000177|
European Ancestry|
79,362 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Reticulocyte fraction of red cells Pearson correlation coefficent (r): 0.4316 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. bioRxiv (2020)
|Pre
Reported Trait: High light scatter reticulocyte count Pearson correlation coefficent (r): 0.363 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)
PPM000223 PGS000095
(hlr_p)
PSS000134|
European Ancestry|
40,225 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: High light scatter reticulocyte percentage of red cells Pearson correlation coefficent (r): 0.3687 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)
PPM000225 PGS000096
(irf)
PSS000135|
European Ancestry|
40,227 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Immature fraction of reticulocytes Pearson correlation coefficent (r): 0.3367 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)
PPM000255 PGS000111
(ret)
PSS000150|
European Ancestry|
40,253 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Reticulocyte count Pearson correlation coefficent (r): 0.4069 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)
PPM000257 PGS000112
(ret_p)
PSS000151|
European Ancestry|
40,286 individuals
PGP000051 |
Xu Y et al. bioRxiv (2020)
|Pre
Reported Trait: Reticulocyte fraction of red cells Pearson correlation coefficent (r): 0.423 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)
PPM000544 PGS000190
(ret_p)
PSS000291|
European Ancestry|
39,260 individuals
PGP000078 |
Vuckovic D et al. Cell (2020)
Reported Trait: Reticulocyte fraction of red cells : 0.15022 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 : 0.14142 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 : 0.09164 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 : 0.12799 sex, age, 10 genetic PCs
PPM000525 PGS000169
(hlr)
PSS000291|
European Ancestry|
39,260 individuals
PGP000078 |
Vuckovic D et al. Cell (2020)
Reported Trait: High light scatter reticulocyte count : 0.11896 sex, age, 10 genetic PCs
PPM007061 PGS001528
(GBE_INI30250)
PSS007022|
East Asian Ancestry|
1,623 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte count : 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. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte count : 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. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte count : 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. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte count : 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. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte count : 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
PPM007070 PGS001406
(GBE_INI30300)
PSS007041|
African Ancestry|
5,974 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte count : 0.03376 [0.02514, 0.04239]
Incremental R2 (full-covars): 0.02097
PGS R2 (no covariates): 0.02166 [0.01466, 0.02866]
age, sex, UKB array type, Genotype PCs
PPM007071 PGS001406
(GBE_INI30300)
PSS007042|
East Asian Ancestry|
1,623 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte count : 0.08784 [0.06222, 0.11346]
Incremental R2 (full-covars): 0.06019
PGS R2 (no covariates): 0.06306 [0.04077, 0.08536]
age, sex, UKB array type, Genotype PCs
PPM007072 PGS001406
(GBE_INI30300)
PSS007043|
European Ancestry|
23,681 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte count : 0.116 [0.10853, 0.12348]
Incremental R2 (full-covars): 0.09413
PGS R2 (no covariates): 0.09553 [0.08859, 0.10247]
age, sex, UKB array type, Genotype PCs
PPM007073 PGS001406
(GBE_INI30300)
PSS007044|
South Asian Ancestry|
7,321 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte count : 0.09799 [0.08549, 0.1105]
Incremental R2 (full-covars): 0.07113
PGS R2 (no covariates): 0.07659 [0.06528, 0.08791]
age, sex, UKB array type, Genotype PCs
PPM007074 PGS001406
(GBE_INI30300)
PSS007045|
European Ancestry|
64,524 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte count : 0.12733 [0.12263, 0.13203]
Incremental R2 (full-covars): 0.11178
PGS R2 (no covariates): 0.1113 [0.10683, 0.11578]
age, sex, UKB array type, Genotype PCs
PPM007703 PGS000987
(GBE_INI30260)
PSS007026|
African Ancestry|
5,973 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Mean reticulocyte volume : 0.03718 [0.02815, 0.0462]
Incremental R2 (full-covars): 0.02777
PGS R2 (no covariates): 0.02867 [0.02068, 0.03667]
age, sex, UKB array type, Genotype PCs
PPM007704 PGS000987
(GBE_INI30260)
PSS007027|
East Asian Ancestry|
1,623 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Mean reticulocyte volume : 0.08812 [0.06247, 0.11377]
Incremental R2 (full-covars): 0.07173
PGS R2 (no covariates): 0.07447 [0.05053, 0.0984]
age, sex, UKB array type, Genotype PCs
PPM007705 PGS000987
(GBE_INI30260)
PSS007028|
European Ancestry|
23,687 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Mean reticulocyte volume : 0.1616 [0.15323, 0.16997]
Incremental R2 (full-covars): 0.14435
PGS R2 (no covariates): 0.1455 [0.1374, 0.15359]
age, sex, UKB array type, Genotype PCs
PPM007706 PGS000987
(GBE_INI30260)
PSS007029|
South Asian Ancestry|
7,323 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Mean reticulocyte volume : 0.13294 [0.11894, 0.14694]
Incremental R2 (full-covars): 0.09343
PGS R2 (no covariates): 0.09786 [0.08537, 0.11036]
age, sex, UKB array type, Genotype PCs
PPM007707 PGS000987
(GBE_INI30260)
PSS007030|
European Ancestry|
64,570 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Mean reticulocyte volume : 0.15675 [0.15171, 0.16179]
Incremental R2 (full-covars): 0.14554
PGS R2 (no covariates): 0.14631 [0.14138, 0.15124]
age, sex, UKB array type, Genotype PCs
PPM007708 PGS000988
(GBE_INI30290)
PSS007036|
African Ancestry|
5,974 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte % : 0.02767 [0.0198, 0.03553]
Incremental R2 (full-covars): 0.01965
PGS R2 (no covariates): 0.01997 [0.01324, 0.0267]
age, sex, UKB array type, Genotype PCs
PPM007709 PGS000988
(GBE_INI30290)
PSS007037|
East Asian Ancestry|
1,623 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte % : 0.05671 [0.03542, 0.07799]
Incremental R2 (full-covars): 0.04573
PGS R2 (no covariates): 0.04876 [0.02885, 0.06866]
age, sex, UKB array type, Genotype PCs
PPM007710 PGS000988
(GBE_INI30290)
PSS007038|
European Ancestry|
23,681 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte % : 0.08594 [0.07929, 0.0926]
Incremental R2 (full-covars): 0.07798
PGS R2 (no covariates): 0.07863 [0.07222, 0.08505]
age, sex, UKB array type, Genotype PCs
PPM007711 PGS000988
(GBE_INI30290)
PSS007039|
South Asian Ancestry|
7,321 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte % : 0.07357 [0.06245, 0.0847]
Incremental R2 (full-covars): 0.06049
PGS R2 (no covariates): 0.06609 [0.05546, 0.07672]
age, sex, UKB array type, Genotype PCs
PPM007712 PGS000988
(GBE_INI30290)
PSS007040|
European Ancestry|
64,524 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: High light scatter reticulocyte % : 0.01671 [0.0148, 0.01863]
Incremental R2 (full-covars): 0.01605
PGS R2 (no covariates): 0.016 [0.01412, 0.01788]
age, sex, UKB array type, Genotype PCs
PPM007713 PGS000989
(GBE_INI30240)
PSS007016|
African Ancestry|
5,974 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte % : 0.01993 [0.01321, 0.02666]
Incremental R2 (full-covars): 0.01309
PGS R2 (no covariates): 0.01384 [0.0082, 0.01948]
age, sex, UKB array type, Genotype PCs
PPM007714 PGS000989
(GBE_INI30240)
PSS007017|
East Asian Ancestry|
1,623 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte % : 0.05032 [0.03013, 0.0705]
Incremental R2 (full-covars): 0.03871
PGS R2 (no covariates): 0.03842 [0.02056, 0.05628]
age, sex, UKB array type, Genotype PCs
PPM007715 PGS000989
(GBE_INI30240)
PSS007018|
European Ancestry|
23,688 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte % : 0.0318 [0.02751, 0.03609]
Incremental R2 (full-covars): 0.02883
PGS R2 (no covariates): 0.02905 [0.02494, 0.03316]
age, sex, UKB array type, Genotype PCs
PPM007716 PGS000989
(GBE_INI30240)
PSS007019|
South Asian Ancestry|
7,323 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte % : 0.03312 [0.02533, 0.04091]
Incremental R2 (full-covars): 0.02678
PGS R2 (no covariates): 0.02784 [0.02066, 0.03502]
age, sex, UKB array type, Genotype PCs
PPM007717 PGS000989
(GBE_INI30240)
PSS007020|
European Ancestry|
64,569 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Reticulocyte % : 0.02928 [0.02677, 0.03179]
Incremental R2 (full-covars): 0.02823
PGS R2 (no covariates): 0.02826 [0.0258, 0.03073]
age, sex, UKB array type, Genotype 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
PSS000291 39,260 individuals European INTERVAL
PSS007016 5,974 individuals African unspecified UKB
PSS007017 1,623 individuals East Asian UKB
PSS007018 23,688 individuals European non-white British ancestry UKB
PSS007019 7,323 individuals South Asian UKB
PSS007020 64,569 individuals European white British ancestry UKB Testing cohort (heldout set)
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)
PSS007026 5,973 individuals African unspecified UKB
PSS007027 1,623 individuals East Asian UKB
PSS007028 23,687 individuals European non-white British ancestry UKB
PSS007029 7,323 individuals South Asian UKB
PSS007030 64,570 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS007036 5,974 individuals African unspecified 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
PSS007037 1,623 individuals East Asian UKB
PSS007041 5,974 individuals African unspecified UKB
PSS007042 1,623 individuals East Asian UKB
PSS007043 23,681 individuals European non-white British ancestry UKB
PSS007044 7,321 individuals South Asian UKB
PSS007045 64,524 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS007038 23,681 individuals European non-white British ancestry UKB
PSS007039 7,321 individuals South Asian UKB
PSS007040 64,524 individuals European white British ancestry UKB Testing cohort (heldout set)
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
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