Trait: diet measurement

Experimental Factor Ontology (EFO) Information
Identifier EFO_0008111
Description quantification of some aspect of diet, including diet patterns, balance of nutrient consumption and glycemic load
Trait category
Other 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 "diet 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
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS000978
(GBE_INI1438)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Bread intake carbohydrate intake measurement 3,483
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000978/ScoringFiles/PGS000978.txt.gz
PGS000991
(GBE_BIN_FC4006144)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Never eat sugar sugar consumption measurement 2,816
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000991/ScoringFiles/PGS000991.txt.gz
PGS001034
(GBE_QT_FC10001478)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Salt added to food diet measurement 6,651
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001034/ScoringFiles/PGS001034.txt.gz
PGS001056
(GBE_QT_FC1001369)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Beef intake diet measurement 991
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001056/ScoringFiles/PGS001056.txt.gz
PGS001057
(GBE_INI1458)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Cereal consumption diet measurement 4,882
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001057/ScoringFiles/PGS001057.txt.gz
PGS001058
(GBE_BIN_FC20001468)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Cereal consumption (biscuit cereal) diet measurement 146
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001058/ScoringFiles/PGS001058.txt.gz
PGS001059
(GBE_BIN_FC50001468)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Cereal consumption (other) diet measurement 1,286
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001059/ScoringFiles/PGS001059.txt.gz
PGS001060
(GBE_QT_FC1001408)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Cheese intake diet measurement 6,678
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001060/ScoringFiles/PGS001060.txt.gz
PGS001061
(GBE_INI1289)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Cooked vegetable consumption diet measurement 1,085
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001061/ScoringFiles/PGS001061.txt.gz
PGS001062
(GBE_INI1309)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Fresh fruit intake diet measurement 4,257
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001062/ScoringFiles/PGS001062.txt.gz
PGS001063
(GBE_BIN_FC10001538)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Major dietary changes in the last 5 years due to illness diet measurement 730
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001063/ScoringFiles/PGS001063.txt.gz
PGS001064
(GBE_BIN_FC30001418)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Milk consumption (skimmed) diet measurement 116
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001064/ScoringFiles/PGS001064.txt.gz
PGS001065
(GBE_BIN_FC3006144)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Never eat wheat diet measurement 5
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001065/ScoringFiles/PGS001065.txt.gz
PGS001066
(GBE_QT_FC1001359)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Poultry intake diet measurement 1,609
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001066/ScoringFiles/PGS001066.txt.gz
PGS001067
(GBE_QT_FC1001349)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Processed meat intake diet measurement 2,346
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001067/ScoringFiles/PGS001067.txt.gz
PGS001068
(GBE_INI1548)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Variation in diet diet measurement 1,353
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001068/ScoringFiles/PGS001068.txt.gz
PGS001069
(GBE_INI1528)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Water intake diet measurement 4,994
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001069/ScoringFiles/PGS001069.txt.gz
PGS001389
(GBE_INI1319)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Dried fruit intake diet measurement 989
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001389/ScoringFiles/PGS001389.txt.gz
PGS001518
(GBE_INI100010)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Portion size diet measurement 591
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001518/ScoringFiles/PGS001518.txt.gz
PGS004221
(PRS8_carbohydrate)
 PGP000521 |
Merino J et al. Mol Psychiatry (2023)
 Carbohydrate preference carbohydrate intake measurement 8
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004221/ScoringFiles/PGS004221.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
PPM007683 PGS000978
(GBE_INI1438)
 PSS004841|
African Ancestry|
5,979 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Bread intake — — R²: 0.08606 [0.07303, 0.09909]
Incremental R2 (full-covars): -0.00106
PGS R2 (no covariates): 0.00083 [-0.00057, 0.00223]		 age, sex, UKB array type, Genotype PCs —
PPM007684 PGS000978
(GBE_INI1438)
 PSS004842|
East Asian Ancestry|
1,557 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Bread intake — — R²: 0.04803 [0.02826, 0.0678]
Incremental R2 (full-covars): -0.00683
PGS R2 (no covariates): 1e-05 [-0.00021, 0.00022]		 age, sex, UKB array type, Genotype PCs —
PPM007685 PGS000978
(GBE_INI1438)
 PSS004843|
European Ancestry|
24,277 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Bread intake — — R²: 0.09076 [0.08395, 0.09756]
Incremental R2 (full-covars): 0.00266
PGS R2 (no covariates): 0.0026 [0.00134, 0.00386]		 age, sex, UKB array type, Genotype PCs —
PPM007686 PGS000978
(GBE_INI1438)
 PSS004844|
South Asian Ancestry|
7,412 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Bread intake — — R²: 0.05893 [0.04882, 0.06905]
Incremental R2 (full-covars): -0.00378
PGS R2 (no covariates): 0.00041 [-0.00049, 0.0013]		 age, sex, UKB array type, Genotype PCs —
PPM007687 PGS000978
(GBE_INI1438)
 PSS004845|
European Ancestry|
66,112 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Bread intake — — R²: 0.09655 [0.09231, 0.10079]
Incremental R2 (full-covars): 0.00312
PGS R2 (no covariates): 0.0033 [0.00243, 0.00416]		 age, sex, UKB array type, Genotype PCs —
PPM007727 PGS000991
(GBE_BIN_FC4006144)
 PSS003948|
European Ancestry|
67,271 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat sugar — AUROC: 0.61373 [0.60865, 0.61881] R²: 0.04147
Incremental AUROC (full-covars): 0.00834
PGS R2 (no covariates): 0.00519
PGS AUROC (no covariates): 0.54069 [0.5353, 0.54607]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007723 PGS000991
(GBE_BIN_FC4006144)
 PSS003944|
African Ancestry|
6,368 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat sugar — AUROC: 0.6377 [0.61811, 0.6573] R²: 0.05071
Incremental AUROC (full-covars): -4e-05
PGS R2 (no covariates): 0.00087
PGS AUROC (no covariates): 0.51667 [0.49625, 0.5371]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007724 PGS000991
(GBE_BIN_FC4006144)
 PSS003945|
East Asian Ancestry|
1,653 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat sugar — AUROC: 0.64533 [0.60258, 0.68809] R²: 0.05896
Incremental AUROC (full-covars): 0.0007
PGS R2 (no covariates): 0.0005
PGS AUROC (no covariates): 0.51881 [0.47535, 0.56226]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007725 PGS000991
(GBE_BIN_FC4006144)
 PSS003946|
European Ancestry|
24,800 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat sugar — AUROC: 0.62033 [0.61189, 0.62878] R²: 0.04489
Incremental AUROC (full-covars): 0.00242
PGS R2 (no covariates): 0.00208
PGS AUROC (no covariates): 0.5258 [0.51682, 0.53477]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007726 PGS000991
(GBE_BIN_FC4006144)
 PSS003947|
South Asian Ancestry|
7,539 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat sugar — AUROC: 0.6355 [0.61763, 0.65337] R²: 0.04896
Incremental AUROC (full-covars): 0.00252
PGS R2 (no covariates): 0.00172
PGS AUROC (no covariates): 0.52933 [0.51032, 0.54833]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007933 PGS001034
(GBE_QT_FC10001478)
 PSS007506|
African Ancestry|
6,428 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Salt added to food — — R²: 0.01628 [0.01018, 0.02238]
Incremental R2 (full-covars): -0.00168
PGS R2 (no covariates): 0.00089 [-0.00056, 0.00234]		 age, sex, UKB array type, Genotype PCs —
PPM007934 PGS001034
(GBE_QT_FC10001478)
 PSS007507|
East Asian Ancestry|
1,671 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Salt added to food — — R²: 0.04497 [0.02578, 0.06416]
Incremental R2 (full-covars): 0.00495
PGS R2 (no covariates): 0.00478 [-0.00174, 0.0113]		 age, sex, UKB array type, Genotype PCs —
PPM007935 PGS001034
(GBE_QT_FC10001478)
 PSS007508|
European Ancestry|
24,900 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Salt added to food — — R²: 0.02412 [0.02036, 0.02789]
Incremental R2 (full-covars): 0.01326
PGS R2 (no covariates): 0.01337 [0.01054, 0.01621]		 age, sex, UKB array type, Genotype PCs —
PPM007936 PGS001034
(GBE_QT_FC10001478)
 PSS007509|
South Asian Ancestry|
7,681 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Salt added to food — — R²: 0.01555 [0.01012, 0.02099]
Incremental R2 (full-covars): -0.00122
PGS R2 (no covariates): 0.00138 [-0.00026, 0.00302]		 age, sex, UKB array type, Genotype PCs —
PPM007937 PGS001034
(GBE_QT_FC10001478)
 PSS007510|
European Ancestry|
67,416 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Salt added to food — — R²: 0.02452 [0.02221, 0.02682]
Incremental R2 (full-covars): 0.01564
PGS R2 (no covariates): 0.01646 [0.01455, 0.01836]		 age, sex, UKB array type, Genotype PCs —
PPM008038 PGS001056
(GBE_QT_FC1001369)
 PSS007556|
African Ancestry|
6,271 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Beef intake — — R²: 0.09702 [0.08335, 0.11069]
Incremental R2 (full-covars): -0.00013
PGS R2 (no covariates): 0.00023 [-0.00051, 0.00097]		 age, sex, UKB array type, Genotype PCs —
PPM008039 PGS001056
(GBE_QT_FC1001369)
 PSS007557|
East Asian Ancestry|
1,641 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Beef intake — — R²: 0.05046 [0.03024, 0.07067]
Incremental R2 (full-covars): -0.00046
PGS R2 (no covariates): 0.00038 [-0.00147, 0.00224]		 age, sex, UKB array type, Genotype PCs —
PPM008040 PGS001056
(GBE_QT_FC1001369)
 PSS007558|
European Ancestry|
24,795 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Beef intake — — R²: 0.03152 [0.02725, 0.03579]
Incremental R2 (full-covars): 0.0011
PGS R2 (no covariates): 0.00146 [0.00051, 0.00241]		 age, sex, UKB array type, Genotype PCs —
PPM008041 PGS001056
(GBE_QT_FC1001369)
 PSS007559|
South Asian Ancestry|
7,508 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Beef intake — — R²: 0.0873 [0.07536, 0.09924]
Incremental R2 (full-covars): -0.0011
PGS R2 (no covariates): 0.00018 [-0.00042, 0.00078]		 age, sex, UKB array type, Genotype PCs —
PPM008042 PGS001056
(GBE_QT_FC1001369)
 PSS007560|
European Ancestry|
67,208 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Beef intake — — R²: 0.02397 [0.02169, 0.02626]
Incremental R2 (full-covars): 0.00158
PGS R2 (no covariates): 0.00171 [0.00109, 0.00234]		 age, sex, UKB array type, Genotype PCs —
PPM008043 PGS001057
(GBE_INI1458)
 PSS004846|
African Ancestry|
5,708 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal intake — — R²: 0.00609 [0.00232, 0.00986]
Incremental R2 (full-covars): -0.00296
PGS R2 (no covariates): 4e-05 [-0.00026, 0.00033]		 age, sex, UKB array type, Genotype PCs —
PPM008044 PGS001057
(GBE_INI1458)
 PSS004847|
East Asian Ancestry|
1,426 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal intake — — R²: 0.03238 [0.01588, 0.04888]
Incremental R2 (full-covars): 0.00542
PGS R2 (no covariates): 0.00483 [-0.00173, 0.01138]		 age, sex, UKB array type, Genotype PCs —
PPM008045 PGS001057
(GBE_INI1458)
 PSS004848|
European Ancestry|
23,372 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal intake — — R²: 0.03202 [0.02771, 0.03632]
Incremental R2 (full-covars): 0.0053
PGS R2 (no covariates): 0.00607 [0.00415, 0.00799]		 age, sex, UKB array type, Genotype PCs —
PPM008046 PGS001057
(GBE_INI1458)
 PSS004849|
South Asian Ancestry|
7,023 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal intake — — R²: 0.01676 [0.01112, 0.02239]
Incremental R2 (full-covars): 0.00168
PGS R2 (no covariates): 0.0026 [0.00035, 0.00485]		 age, sex, UKB array type, Genotype PCs —
PPM008047 PGS001057
(GBE_INI1458)
 PSS004850|
European Ancestry|
64,778 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal intake — — R²: 0.0216 [0.01943, 0.02377]
Incremental R2 (full-covars): 0.00622
PGS R2 (no covariates): 0.0067 [0.00547, 0.00792]		 age, sex, UKB array type, Genotype PCs —
PPM008048 PGS001058
(GBE_BIN_FC20001468)
 PSS003810|
African Ancestry|
4,766 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) — AUROC: 0.53868 [0.51659, 0.56077] PGS R2 (no covariates): 0.00013
R²: 0.00503
Incremental AUROC (full-covars): 0.00148
PGS AUROC (no covariates): 0.50487 [0.48225, 0.52748]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008049 PGS001058
(GBE_BIN_FC20001468)
 PSS003811|
East Asian Ancestry|
988 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) — AUROC: 0.56685 [0.51503, 0.61867] R²: 0.02055
Incremental AUROC (full-covars): 0.00316
PGS R2 (no covariates): 0.00024
PGS AUROC (no covariates): 0.50224 [0.44501, 0.55946]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008050 PGS001058
(GBE_BIN_FC20001468)
 PSS003812|
European Ancestry|
18,951 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) — AUROC: 0.58711 [0.57552, 0.5987] R²: 0.01991
Incremental AUROC (full-covars): 0.00031
PGS R2 (no covariates): 4e-05
PGS AUROC (no covariates): 0.50281 [0.49093, 0.51469]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008051 PGS001058
(GBE_BIN_FC20001468)
 PSS003813|
South Asian Ancestry|
5,759 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) — AUROC: 0.56331 [0.54576, 0.58087] R²: 0.01354
Incremental AUROC (full-covars): -0.00093
PGS R2 (no covariates): 2e-05
PGS AUROC (no covariates): 0.49754 [0.47927, 0.5158]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008052 PGS001058
(GBE_BIN_FC20001468)
 PSS003814|
European Ancestry|
56,841 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) — AUROC: 0.55057 [0.54462, 0.55652] R²: 0.00808
Incremental AUROC (full-covars): 0.00209
PGS R2 (no covariates): 0.00069
PGS AUROC (no covariates): 0.51496 [0.50892, 0.521]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008053 PGS001059
(GBE_BIN_FC50001468)
 PSS003959|
African Ancestry|
4,766 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) — AUROC: 0.61741 [0.59849, 0.63633] R²: 0.04438
Incremental AUROC (full-covars): -0.00159
PGS R2 (no covariates): 0.0
PGS AUROC (no covariates): 0.49817 [0.47857, 0.51776]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008054 PGS001059
(GBE_BIN_FC50001468)
 PSS003960|
East Asian Ancestry|
988 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) — AUROC: 0.64303 [0.60109, 0.68497] R²: 0.07487
Incremental AUROC (full-covars): -0.00286
PGS R2 (no covariates): 0.00017
PGS AUROC (no covariates): 0.5106 [0.46867, 0.55253]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008055 PGS001059
(GBE_BIN_FC50001468)
 PSS003961|
European Ancestry|
18,951 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) — AUROC: 0.60408 [0.59345, 0.6147] R²: 0.03191
Incremental AUROC (full-covars): 0.00341
PGS R2 (no covariates): 0.00282
PGS AUROC (no covariates): 0.53042 [0.51944, 0.54141]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008056 PGS001059
(GBE_BIN_FC50001468)
 PSS003962|
South Asian Ancestry|
5,759 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) — AUROC: 0.59996 [0.58323, 0.61669] R²: 0.03365
Incremental AUROC (full-covars): 0.00229
PGS R2 (no covariates): 0.0016
PGS AUROC (no covariates): 0.52513 [0.50821, 0.54206]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008057 PGS001059
(GBE_BIN_FC50001468)
 PSS003963|
European Ancestry|
56,841 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) — AUROC: 0.58769 [0.58186, 0.59353] R²: 0.02328
Incremental AUROC (full-covars): 0.00502
PGS R2 (no covariates): 0.00268
PGS AUROC (no covariates): 0.52828 [0.52234, 0.53422]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008058 PGS001060
(GBE_QT_FC1001408)
 PSS007561|
African Ancestry|
5,882 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cheese intake — — R²: 0.04412 [0.03436, 0.05388]
Incremental R2 (full-covars): -0.00685
PGS R2 (no covariates): 0.0 [-0.00005, 0.00006]		 age, sex, UKB array type, Genotype PCs —
PPM008059 PGS001060
(GBE_QT_FC1001408)
 PSS007562|
East Asian Ancestry|
1,552 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cheese intake — — R²: 0.01193 [0.0017, 0.02215]
Incremental R2 (full-covars): -0.00537
PGS R2 (no covariates): 2e-05 [-0.00041, 0.00045]		 age, sex, UKB array type, Genotype PCs —
PPM008060 PGS001060
(GBE_QT_FC1001408)
 PSS007563|
European Ancestry|
24,143 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cheese intake — — R²: 0.05514 [0.04963, 0.06065]
Incremental R2 (full-covars): 0.00809
PGS R2 (no covariates): 0.01422 [0.0113, 0.01714]		 age, sex, UKB array type, Genotype PCs —
PPM008061 PGS001060
(GBE_QT_FC1001408)
 PSS007564|
South Asian Ancestry|
7,212 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cheese intake — — R²: 0.02111 [0.01481, 0.0274]
Incremental R2 (full-covars): -0.00079
PGS R2 (no covariates): 0.00163 [-0.00015, 0.00342]		 age, sex, UKB array type, Genotype PCs —
PPM008062 PGS001060
(GBE_QT_FC1001408)
 PSS007565|
European Ancestry|
65,948 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cheese intake — — R²: 0.02335 [0.0211, 0.0256]
Incremental R2 (full-covars): 0.00727
PGS R2 (no covariates): 0.00852 [0.00714, 0.00991]		 age, sex, UKB array type, Genotype PCs —
PPM008064 PGS001061
(GBE_INI1289)
 PSS004812|
East Asian Ancestry|
1,578 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cooked vegetable intake — — R²: 0.0129 [0.00227, 0.02352]
Incremental R2 (full-covars): -0.00036
PGS R2 (no covariates): 0.00013 [-0.00096, 0.00123]		 age, sex, UKB array type, Genotype PCs —
PPM008065 PGS001061
(GBE_INI1289)
 PSS004813|
European Ancestry|
24,087 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cooked vegetable intake — — Incremental R2 (full-covars): 0.00028
R²: 0.01788 [0.01462, 0.02114]
PGS R2 (no covariates): 0.00042 [-0.00009, 0.00093]		 age, sex, UKB array type, Genotype PCs —
PPM008066 PGS001061
(GBE_INI1289)
 PSS004814|
South Asian Ancestry|
7,034 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cooked vegetable intake — — R²: 0.02023 [0.01406, 0.0264]
Incremental R2 (full-covars): -0.00028
PGS R2 (no covariates): 0.0 [-0.00004, 0.00004]		 age, sex, UKB array type, Genotype PCs —
PPM008063 PGS001061
(GBE_INI1289)
 PSS004811|
African Ancestry|
5,840 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cooked vegetable intake — — R²: 0.01567 [0.00968, 0.02166]
Incremental R2 (full-covars): 0.00017
PGS R2 (no covariates): 0.00022 [-0.0005, 0.00094]		 age, sex, UKB array type, Genotype PCs —
PPM008067 PGS001061
(GBE_INI1289)
 PSS004815|
European Ancestry|
65,598 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Cooked vegetable intake — — R²: 0.01065 [0.00911, 0.01219]
Incremental R2 (full-covars): 0.0009
PGS R2 (no covariates): 0.00097 [0.0005, 0.00145]		 age, sex, UKB array type, Genotype PCs —
PPM008068 PGS001062
(GBE_INI1309)
 PSS004816|
African Ancestry|
6,032 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Fresh fruit intake — — R²: 0.02533 [0.01779, 0.03287]
Incremental R2 (full-covars): 0.00021
PGS R2 (no covariates): 0.00107 [-0.00052, 0.00265]		 age, sex, UKB array type, Genotype PCs —
PPM008069 PGS001062
(GBE_INI1309)
 PSS004817|
East Asian Ancestry|
1,592 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Fresh fruit intake — — R²: 0.01082 [0.00107, 0.02056]
Incremental R2 (full-covars): -0.00286
PGS R2 (no covariates): 4e-05 [-0.00054, 0.00062]		 age, sex, UKB array type, Genotype PCs —
PPM008070 PGS001062
(GBE_INI1309)
 PSS004818|
European Ancestry|
24,138 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Fresh fruit intake — — R²: 0.03809 [0.03342, 0.04275]
Incremental R2 (full-covars): 0.00379
PGS R2 (no covariates): 0.00464 [0.00295, 0.00632]		 age, sex, UKB array type, Genotype PCs —
PPM008071 PGS001062
(GBE_INI1309)
 PSS004819|
South Asian Ancestry|
7,340 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Fresh fruit intake — — R²: 0.01209 [0.00728, 0.0169]
Incremental R2 (full-covars): 0.00017
PGS R2 (no covariates): 0.00092 [-0.00042, 0.00226]		 age, sex, UKB array type, Genotype PCs —
PPM008072 PGS001062
(GBE_INI1309)
 PSS004820|
European Ancestry|
65,281 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Fresh fruit intake — — R²: 0.02519 [0.02286, 0.02753]
Incremental R2 (full-covars): 0.00617
PGS R2 (no covariates): 0.00619 [0.00501, 0.00737]		 age, sex, UKB array type, Genotype PCs —
PPM008073 PGS001063
(GBE_BIN_FC10001538)
 PSS003696|
African Ancestry|
6,357 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Major dietary changes in the last 5 years becuase of illness — AUROC: 0.62048 [0.60331, 0.63766] R²: 0.04237
Incremental AUROC (full-covars): 0.0032
PGS R2 (no covariates): 0.00132
PGS AUROC (no covariates): 0.52027 [0.50231, 0.53822]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008074 PGS001063
(GBE_BIN_FC10001538)
 PSS003697|
East Asian Ancestry|
1,645 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Major dietary changes in the last 5 years becuase of illness — AUROC: 0.63276 [0.58471, 0.68082] R²: 0.0543
Incremental AUROC (full-covars): 0.00877
PGS R2 (no covariates): 0.001
PGS AUROC (no covariates): 0.51406 [0.46553, 0.56259]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008075 PGS001063
(GBE_BIN_FC10001538)
 PSS003698|
European Ancestry|
24,842 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Major dietary changes in the last 5 years becuase of illness — AUROC: 0.58219 [0.57084, 0.59354] R²: 0.01696
Incremental AUROC (full-covars): 0.00638
PGS R2 (no covariates): 0.00241
PGS AUROC (no covariates): 0.53194 [0.52043, 0.54345]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008076 PGS001063
(GBE_BIN_FC10001538)
 PSS003699|
South Asian Ancestry|
7,568 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Major dietary changes in the last 5 years becuase of illness — AUROC: 0.59898 [0.58379, 0.61417] R²: 0.02965
Incremental AUROC (full-covars): 0.00116
PGS R2 (no covariates): 0.00081
PGS AUROC (no covariates): 0.5156 [0.49978, 0.53141]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008077 PGS001063
(GBE_BIN_FC10001538)
 PSS003700|
European Ancestry|
67,297 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Major dietary changes in the last 5 years becuase of illness — AUROC: 0.57633 [0.56954, 0.58313] R²: 0.01433
Incremental AUROC (full-covars): 0.00677
PGS R2 (no covariates): 0.00246
PGS AUROC (no covariates): 0.53277 [0.52584, 0.5397]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008078 PGS001064
(GBE_BIN_FC30001418)
 PSS003869|
African Ancestry|
6,403 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Milk type: Skimmed — AUROC: 0.56598 [0.54374, 0.58822] R²: 0.01233
Incremental AUROC (full-covars): -0.00074
PGS R2 (no covariates): 1e-05
PGS AUROC (no covariates): 0.49637 [0.47444, 0.51829]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008079 PGS001064
(GBE_BIN_FC30001418)
 PSS003870|
East Asian Ancestry|
1,665 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Milk type: Skimmed — AUROC: 0.58283 [0.5384, 0.62725] R²: 0.0164
Incremental AUROC (full-covars): -0.00089
PGS R2 (no covariates): 0.00033
PGS AUROC (no covariates): 0.48955 [0.44321, 0.53588]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008080 PGS001064
(GBE_BIN_FC30001418)
 PSS003871|
European Ancestry|
24,862 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Milk type: Skimmed — AUROC: 0.56928 [0.56021, 0.57836] R²: 0.01433
Incremental AUROC (full-covars): 0.0004
PGS R2 (no covariates): 0.00014
PGS AUROC (no covariates): 0.50724 [0.49799, 0.51648]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008081 PGS001064
(GBE_BIN_FC30001418)
 PSS003872|
South Asian Ancestry|
7,664 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Milk type: Skimmed — AUROC: 0.56624 [0.54661, 0.58587] R²: 0.01224
Incremental AUROC (full-covars): 2e-05
PGS R2 (no covariates): 0.00032
PGS AUROC (no covariates): 0.51585 [0.49596, 0.53574]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008082 PGS001064
(GBE_BIN_FC30001418)
 PSS003873|
European Ancestry|
67,386 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Milk type: Skimmed — AUROC: 0.57752 [0.57233, 0.58271] R²: 0.01907
Incremental AUROC (full-covars): 0.00126
PGS R2 (no covariates): 0.00095
PGS AUROC (no covariates): 0.51868 [0.51338, 0.52397]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008083 PGS001065
(GBE_BIN_FC3006144)
 PSS003909|
African Ancestry|
6,368 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat wheat — AUROC: 0.55785 [0.52697, 0.58872] R²: 0.0067
Incremental AUROC (full-covars): -0.00998
PGS R2 (no covariates): 1e-05
PGS AUROC (no covariates): 0.49224 [0.4594, 0.52508]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008084 PGS001065
(GBE_BIN_FC3006144)
 PSS003910|
East Asian Ancestry|
1,653 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat wheat — AUROC: 0.64888 [0.57732, 0.72044] R²: 0.04019
Incremental AUROC (full-covars): 0.00386
PGS R2 (no covariates): 0.00453
PGS AUROC (no covariates): 0.56299 [0.49269, 0.63329]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008085 PGS001065
(GBE_BIN_FC3006144)
 PSS003911|
European Ancestry|
24,800 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat wheat — AUROC: 0.62411 [0.60564, 0.64259] R²: 0.02456
Incremental AUROC (full-covars): 0.02182
PGS R2 (no covariates): 0.01049
PGS AUROC (no covariates): 0.56561 [0.54517, 0.58606]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008086 PGS001065
(GBE_BIN_FC3006144)
 PSS003912|
South Asian Ancestry|
7,539 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat wheat — AUROC: 0.59764 [0.56396, 0.63132] R²: 0.01641
Incremental AUROC (full-covars): 0.00593
PGS R2 (no covariates): 0.00163
PGS AUROC (no covariates): 0.53668 [0.50324, 0.57012]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008087 PGS001065
(GBE_BIN_FC3006144)
 PSS003913|
European Ancestry|
67,271 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Never eat wheat — AUROC: 0.58236 [0.56955, 0.59518] R²: 0.0117
Incremental AUROC (full-covars): 0.01856
PGS R2 (no covariates): 0.00607
PGS AUROC (no covariates): 0.55077 [0.53718, 0.56437]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008088 PGS001066
(GBE_QT_FC1001359)
 PSS007551|
African Ancestry|
6,377 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Poultry intake — — PGS R2 (no covariates): 0.00093 [-0.00055, 0.00241]
R²: 0.02159 [0.0146, 0.02858]
Incremental R2 (full-covars): 0.00053		 age, sex, UKB array type, Genotype PCs —
PPM008089 PGS001066
(GBE_QT_FC1001359)
 PSS007552|
East Asian Ancestry|
1,655 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Poultry intake — — R²: 0.0497 [0.02962, 0.06977]
Incremental R2 (full-covars): -0.00108
PGS R2 (no covariates): 0.00013 [-0.00097, 0.00123]		 age, sex, UKB array type, Genotype PCs —
PPM008090 PGS001066
(GBE_QT_FC1001359)
 PSS007553|
European Ancestry|
24,847 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Poultry intake — — R²: 0.00958 [0.00717, 0.01199]
Incremental R2 (full-covars): 0.0005
PGS R2 (no covariates): 0.00079 [0.00009, 0.00149]		 age, sex, UKB array type, Genotype PCs —
PPM008091 PGS001066
(GBE_QT_FC1001359)
 PSS007554|
South Asian Ancestry|
7,623 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Poultry intake — — R²: 0.15633 [0.14156, 0.1711]
Incremental R2 (full-covars): -0.00044
PGS R2 (no covariates): 0.00074 [-0.00046, 0.00195]		 age, sex, UKB array type, Genotype PCs —
PPM008092 PGS001066
(GBE_QT_FC1001359)
 PSS007555|
European Ancestry|
67,313 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Poultry intake — — R²: 0.00656 [0.00535, 0.00778]
Incremental R2 (full-covars): 0.0012
PGS R2 (no covariates): 0.00124 [0.00071, 0.00177]		 age, sex, UKB array type, Genotype PCs —
PPM008093 PGS001067
(GBE_QT_FC1001349)
 PSS007546|
African Ancestry|
6,311 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Processed meat intake — — R²: 0.05609 [0.04522, 0.06695]
Incremental R2 (full-covars): 0.00153
PGS R2 (no covariates): 0.00178 [-0.00027, 0.00382]		 age, sex, UKB array type, Genotype PCs —
PPM008094 PGS001067
(GBE_QT_FC1001349)
 PSS007547|
East Asian Ancestry|
1,642 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Processed meat intake — — R²: 0.07224 [0.04861, 0.09588]
Incremental R2 (full-covars): -0.0026
PGS R2 (no covariates): 4e-05 [-0.00058, 0.00066]		 age, sex, UKB array type, Genotype PCs —
PPM008095 PGS001067
(GBE_QT_FC1001349)
 PSS007548|
European Ancestry|
24,852 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Processed meat intake — — R²: 0.10754 [0.10027, 0.11481]
Incremental R2 (full-covars): 0.00194
PGS R2 (no covariates): 0.003 [0.00165, 0.00436]		 age, sex, UKB array type, Genotype PCs —
PPM008096 PGS001067
(GBE_QT_FC1001349)
 PSS007549|
South Asian Ancestry|
7,555 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Processed meat intake — — R²: 0.10977 [0.09671, 0.12282]
Incremental R2 (full-covars): -0.00173
PGS R2 (no covariates): 1e-05 [-0.00014, 0.00017]		 age, sex, UKB array type, Genotype PCs —
PPM008097 PGS001067
(GBE_QT_FC1001349)
 PSS007550|
European Ancestry|
67,321 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Processed meat intake — — R²: 0.08633 [0.08228, 0.09039]
Incremental R2 (full-covars): 0.00281
PGS R2 (no covariates): 0.00275 [0.00196, 0.00354]		 age, sex, UKB array type, Genotype PCs —
PPM008098 PGS001068
(GBE_INI1548)
 PSS004866|
African Ancestry|
6,271 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Variation in diet — — R²: 0.01563 [0.00965, 0.02161]
Incremental R2 (full-covars): 1e-05
PGS R2 (no covariates): 0.00026 [-0.00053, 0.00105]		 age, sex, UKB array type, Genotype PCs —
PPM008099 PGS001068
(GBE_INI1548)
 PSS004867|
East Asian Ancestry|
1,585 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Variation in diet — — R²: 0.04021 [0.02197, 0.05845]
Incremental R2 (full-covars): 0.00116
PGS R2 (no covariates): 0.00216 [-0.00223, 0.00655]		 age, sex, UKB array type, Genotype PCs —
PPM008100 PGS001068
(GBE_INI1548)
 PSS004868|
European Ancestry|
24,750 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Variation in diet — — R²: 0.00852 [0.00625, 0.01079]
Incremental R2 (full-covars): 0.00183
PGS R2 (no covariates): 0.00183 [0.00077, 0.00289]		 age, sex, UKB array type, Genotype PCs —
PPM008101 PGS001068
(GBE_INI1548)
 PSS004869|
South Asian Ancestry|
7,343 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Variation in diet — — R²: 0.01371 [0.00859, 0.01882]
Incremental R2 (full-covars): 0.00049
PGS R2 (no covariates): 0.00066 [-0.00048, 0.00181]		 age, sex, UKB array type, Genotype PCs —
PPM008102 PGS001068
(GBE_INI1548)
 PSS004870|
European Ancestry|
67,259 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Variation in diet — — R²: 0.0081 [0.00675, 0.00944]
Incremental R2 (full-covars): 0.00212
PGS R2 (no covariates): 0.00213 [0.00144, 0.00283]		 age, sex, UKB array type, Genotype PCs —
PPM008106 PGS001069
(GBE_INI1528)
 PSS004864|
South Asian Ancestry|
7,550 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Water intake — — R²: 0.01463 [0.00935, 0.01991]
Incremental R2 (full-covars): 0.0043
PGS R2 (no covariates): 0.00415 [0.00131, 0.00699]		 age, sex, UKB array type, Genotype PCs —
PPM008107 PGS001069
(GBE_INI1528)
 PSS004865|
European Ancestry|
62,737 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Water intake — — R²: 0.038 [0.03517, 0.04084]
Incremental R2 (full-covars): 0.0082
PGS R2 (no covariates): 0.0083 [0.00694, 0.00966]		 age, sex, UKB array type, Genotype PCs —
PPM008103 PGS001069
(GBE_INI1528)
 PSS004861|
African Ancestry|
6,061 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Water intake — — R²: 0.02463 [0.01719, 0.03207]
Incremental R2 (full-covars): 0.00076
PGS R2 (no covariates): 0.00216 [-0.00009, 0.00442]		 age, sex, UKB array type, Genotype PCs —
PPM008104 PGS001069
(GBE_INI1528)
 PSS004862|
East Asian Ancestry|
1,590 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Water intake — — R²: 0.03011 [0.01416, 0.04605]
Incremental R2 (full-covars): 0.0
PGS R2 (no covariates): 0.00076 [-0.00185, 0.00338]		 age, sex, UKB array type, Genotype PCs —
PPM008105 PGS001069
(GBE_INI1528)
 PSS004863|
European Ancestry|
23,579 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Water intake — — R²: 0.05496 [0.04946, 0.06046]
Incremental R2 (full-covars): 0.00553
PGS R2 (no covariates): 0.00756 [0.00542, 0.00971]		 age, sex, UKB array type, Genotype PCs —
PPM005240 PGS001389
(GBE_INI1319)
 PSS004821|
African Ancestry|
5,684 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Dried fruit intake — — R²: 0.00681 [0.00283, 0.0108]
Incremental R2 (full-covars): -0.00044
PGS R2 (no covariates): 1e-05 [-0.00017, 0.0002]		 age, sex, UKB array type, Genotype PCs —
PPM005241 PGS001389
(GBE_INI1319)
 PSS004822|
East Asian Ancestry|
1,402 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Dried fruit intake — — R²: 0.02296 [0.00893, 0.03699]
Incremental R2 (full-covars): 0.00042
PGS R2 (no covariates): 0.00045 [-0.00156, 0.00245]		 age, sex, UKB array type, Genotype PCs —
PPM005242 PGS001389
(GBE_INI1319)
 PSS004823|
European Ancestry|
22,608 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Dried fruit intake — — R²: 0.0347 [0.03024, 0.03917]
Incremental R2 (full-covars): 0.00018
PGS R2 (no covariates): 0.00038 [-0.00011, 0.00086]		 age, sex, UKB array type, Genotype PCs —
PPM005243 PGS001389
(GBE_INI1319)
 PSS004824|
South Asian Ancestry|
6,844 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Dried fruit intake — — R²: 0.01593 [0.01043, 0.02143]
Incremental R2 (full-covars): -1e-05
PGS R2 (no covariates): 4e-05 [-0.00024, 0.00032]		 age, sex, UKB array type, Genotype PCs —
PPM005244 PGS001389
(GBE_INI1319)
 PSS004825|
European Ancestry|
62,203 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Dried fruit intake — — R²: 0.0166 [0.01469, 0.01852]
Incremental R2 (full-covars): 0.00087
PGS R2 (no covariates): 0.00107 [0.00058, 0.00157]		 age, sex, UKB array type, Genotype PCs —
PPM005225 PGS001518
(GBE_INI100010)
 PSS004766|
African Ancestry|
2,091 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Portion size — — R²: 0.02984 [0.02169, 0.03798]
Incremental R2 (full-covars): 0.00275
PGS R2 (no covariates): 0.00229 [-0.00003, 0.00461]		 age, sex, UKB array type, Genotype PCs —
PPM005226 PGS001518
(GBE_INI100010)
 PSS004767|
East Asian Ancestry|
613 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Portion size — — R²: 0.08303 [0.05799, 0.10806]
Incremental R2 (full-covars): 0.00287
PGS R2 (no covariates): 0.00511 [-0.00163, 0.01184]		 age, sex, UKB array type, Genotype PCs —
PPM005227 PGS001518
(GBE_INI100010)
 PSS004768|
European Ancestry|
11,475 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Portion size — — R²: 0.05028 [0.04499, 0.05557]
Incremental R2 (full-covars): 0.00227
PGS R2 (no covariates): 0.00184 [0.00078, 0.0029]		 age, sex, UKB array type, Genotype PCs —
PPM005228 PGS001518
(GBE_INI100010)
 PSS004769|
South Asian Ancestry|
2,331 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Portion size — — R²: 0.02167 [0.01529, 0.02805]
Incremental R2 (full-covars): -0.00034
PGS R2 (no covariates): 0.00013 [-0.00038, 0.00064]		 age, sex, UKB array type, Genotype PCs —
PPM005229 PGS001518
(GBE_INI100010)
 PSS004770|
European Ancestry|
29,044 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Portion size — — R²: 0.05298 [0.04969, 0.05627]
Incremental R2 (full-covars): 0.00155
PGS R2 (no covariates): 0.00164 [0.00103, 0.00226]		 age, sex, UKB array type, Genotype PCs —
PPM020156 PGS004221
(PRS8_carbohydrate)
 PSS011297|
European Ancestry|
397 individuals
 PGP000521 |
Merino J et al. Mol Psychiatry (2023)
 Reported Trait: Number of 'green' beverages purchased per month β: 1.1 [0.3, 1.9] — — age, sex, education level (high school/some college, college degree, graduate degree), job type (administrative/service, craft/technicians, management/professionals, MDs/PhDs), BMI (18.5-24.9 kg/m2, 25.0-29.9 kg/m2, and ≥30 kg/m2), current smoking status (yes, no), and physical activity (categorized into low, intermediate, and high physical activity level) —
PPM020154 PGS004221
(PRS8_carbohydrate)
 PSS011297|
European Ancestry|
397 individuals
 PGP000521 |
Merino J et al. Mol Psychiatry (2023)
 Reported Trait: Total workplace purchases per month β: 2.3 [0.2, 4.3] — — age, sex, education level (high school/some college, college degree, graduate degree), job type (administrative/service, craft/technicians, management/professionals, MDs/PhDs), BMI (18.5-24.9 kg/m2, 25.0-29.9 kg/m2, and ≥30 kg/m2), current smoking status (yes, no), and physical activity (categorized into low, intermediate, and high physical activity level) —
PPM020155 PGS004221
(PRS8_carbohydrate)
 PSS011297|
European Ancestry|
397 individuals
 PGP000521 |
Merino J et al. Mol Psychiatry (2023)
 Reported Trait: Number of 'green' items purchased per month β: 1.9 [0.5, 3.3] — — age, sex, education level (high school/some college, college degree, graduate degree), job type (administrative/service, craft/technicians, management/professionals, MDs/PhDs), BMI (18.5-24.9 kg/m2, 25.0-29.9 kg/m2, and ≥30 kg/m2), current smoking status (yes, no), and physical activity (categorized into low, intermediate, and high physical activity level) —

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
PSS003696 — —
[
  • 1,242 cases
  • , 5,115 controls
]
 — African unspecified — UKB —
PSS003697 — —
[
  • 150 cases
  • , 1,495 controls
]
 — East Asian — UKB —
PSS003698 — —
[
  • 2,719 cases
  • , 22,123 controls
]
 — European non-white British ancestry UKB —
PSS003699 — —
[
  • 1,617 cases
  • , 5,951 controls
]
 — South Asian — UKB —
PSS003700 — —
[
  • 7,422 cases
  • , 59,875 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS004766 — — 2,091 individuals — African unspecified — UKB —
PSS004767 — — 613 individuals — East Asian — UKB —
PSS004768 — — 11,475 individuals — European non-white British ancestry UKB —
PSS004769 — — 2,331 individuals — South Asian — UKB —
PSS004770 — — 29,044 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004811 — — 5,840 individuals — African unspecified — UKB —
PSS004812 — — 1,578 individuals — East Asian — UKB —
PSS004813 — — 24,087 individuals — European non-white British ancestry UKB —
PSS004814 — — 7,034 individuals — South Asian — UKB —
PSS004815 — — 65,598 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004816 — — 6,032 individuals — African unspecified — UKB —
PSS004817 — — 1,592 individuals — East Asian — UKB —
PSS004818 — — 24,138 individuals — European non-white British ancestry UKB —
PSS004819 — — 7,340 individuals — South Asian — UKB —
PSS004820 — — 65,281 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004821 — — 5,684 individuals — African unspecified — UKB —
PSS004822 — — 1,402 individuals — East Asian — UKB —
PSS004823 — — 22,608 individuals — European non-white British ancestry UKB —
PSS004824 — — 6,844 individuals — South Asian — UKB —
PSS004825 — — 62,203 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS003810 — —
[
  • 785 cases
  • , 3,981 controls
]
 — African unspecified — UKB —
PSS003811 — —
[
  • 115 cases
  • , 873 controls
]
 — East Asian — UKB —
PSS003812 — —
[
  • 2,595 cases
  • , 16,356 controls
]
 — European non-white British ancestry UKB —
PSS003813 — —
[
  • 1,252 cases
  • , 4,507 controls
]
 — South Asian — UKB —
PSS003814 — —
[
  • 10,762 cases
  • , 46,079 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS011297 — — 397 individuals,
19.1 % Male samples
 — European — ChooseWell 365 —
PSS004841 — — 5,979 individuals — African unspecified — UKB —
PSS004842 — — 1,557 individuals — East Asian — UKB —
PSS004843 — — 24,277 individuals — European non-white British ancestry UKB —
PSS004844 — — 7,412 individuals — South Asian — UKB —
PSS004845 — — 66,112 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004846 — — 5,708 individuals — African unspecified — UKB —
PSS004847 — — 1,426 individuals — East Asian — UKB —
PSS004848 — — 23,372 individuals — European non-white British ancestry UKB —
PSS004849 — — 7,023 individuals — South Asian — UKB —
PSS004850 — — 64,778 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004861 — — 6,061 individuals — African unspecified — UKB —
PSS004862 — — 1,590 individuals — East Asian — UKB —
PSS004863 — — 23,579 individuals — European non-white British ancestry UKB —
PSS004864 — — 7,550 individuals — South Asian — UKB —
PSS004865 — — 62,737 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS004866 — — 6,271 individuals — African unspecified — UKB —
PSS004867 — — 1,585 individuals — East Asian — UKB —
PSS004868 — — 24,750 individuals — European non-white British ancestry UKB —
PSS004869 — — 7,343 individuals — South Asian — UKB —
PSS004870 — — 67,259 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS003869 — —
[
  • 746 cases
  • , 5,657 controls
]
 — African unspecified — UKB —
PSS003870 — —
[
  • 173 cases
  • , 1,492 controls
]
 — East Asian — UKB —
PSS003871 — —
[
  • 4,620 cases
  • , 20,242 controls
]
 — European non-white British ancestry UKB —
PSS003872 — —
[
  • 950 cases
  • , 6,714 controls
]
 — South Asian — UKB —
PSS003873 — —
[
  • 14,461 cases
  • , 52,925 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS003909 — —
[
  • 327 cases
  • , 6,041 controls
]
 — African unspecified — UKB —
PSS003910 — —
[
  • 55 cases
  • , 1,598 controls
]
 — East Asian — UKB —
PSS003911 — —
[
  • 865 cases
  • , 23,935 controls
]
 — European non-white British ancestry UKB —
PSS003912 — —
[
  • 287 cases
  • , 7,252 controls
]
 — South Asian — UKB —
PSS003913 — —
[
  • 1,955 cases
  • , 65,316 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS007506 — — 6,428 individuals — African unspecified — UKB —
PSS007507 — — 1,671 individuals — East Asian — UKB —
PSS007508 — — 24,900 individuals — European non-white British ancestry UKB —
PSS007509 — — 7,681 individuals — South Asian — UKB —
PSS007510 — — 67,416 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS003944 — —
[
  • 916 cases
  • , 5,452 controls
]
 — African unspecified — UKB —
PSS003945 — —
[
  • 190 cases
  • , 1,463 controls
]
 — East Asian — UKB —
PSS003946 — —
[
  • 4,945 cases
  • , 19,855 controls
]
 — European non-white British ancestry UKB —
PSS003947 — —
[
  • 1,046 cases
  • , 6,493 controls
]
 — South Asian — UKB —
PSS003948 — —
[
  • 13,687 cases
  • , 53,584 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS003959 — —
[
  • 1,053 cases
  • , 3,713 controls
]
 — African unspecified — UKB —
PSS003960 — —
[
  • 218 cases
  • , 770 controls
]
 — East Asian — UKB —
PSS003961 — —
[
  • 3,166 cases
  • , 15,785 controls
]
 — European non-white British ancestry UKB —
PSS003962 — —
[
  • 1,476 cases
  • , 4,283 controls
]
 — South Asian — UKB —
PSS003963 — —
[
  • 11,307 cases
  • , 45,534 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS007546 — — 6,311 individuals — African unspecified — UKB —
PSS007548 — — 24,852 individuals — European non-white British ancestry UKB —
PSS007549 — — 7,555 individuals — South Asian — UKB —
PSS007551 — — 6,377 individuals — African unspecified — UKB —
PSS007552 — — 1,655 individuals — East Asian — UKB —
PSS007553 — — 24,847 individuals — European non-white British ancestry UKB —
PSS007554 — — 7,623 individuals — South Asian — UKB —
PSS007555 — — 67,313 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS007556 — — 6,271 individuals — African unspecified — UKB —
PSS007557 — — 1,641 individuals — East Asian — UKB —
PSS007558 — — 24,795 individuals — European non-white British ancestry UKB —
PSS007559 — — 7,508 individuals — South Asian — UKB —
PSS007560 — — 67,208 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS007561 — — 5,882 individuals — African unspecified — UKB —
PSS007562 — — 1,552 individuals — East Asian — UKB —
PSS007563 — — 24,143 individuals — European non-white British ancestry UKB —
PSS007564 — — 7,212 individuals — South Asian — UKB —
PSS007565 — — 65,948 individuals — European white British ancestry UKB Testing cohort (heldout set)
PSS007547 — — 1,642 individuals — East Asian — UKB —
PSS007550 — — 67,321 individuals — European white British ancestry UKB Testing cohort (heldout set)