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 Scoring File (FTP Link)
PGS000978
(GBE_INI1438)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
Portion size diet measurement 591
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001518/ScoringFiles/PGS001518.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
PPM005225 PGS001518
(GBE_INI100010)
PSS004766|
African Ancestry|
2,091 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Portion size : 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. medRxiv (2021)
|Pre
Reported Trait: Portion size : 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. medRxiv (2021)
|Pre
Reported Trait: Portion size : 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. medRxiv (2021)
|Pre
Reported Trait: Portion size : 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. medRxiv (2021)
|Pre
Reported Trait: Portion size : 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
PPM005240 PGS001389
(GBE_INI1319)
PSS004821|
African Ancestry|
5,684 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Dried fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Dried fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Dried fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Dried fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Dried fruit intake : 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
PPM007683 PGS000978
(GBE_INI1438)
PSS004841|
African Ancestry|
5,979 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Bread intake : 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
PPM008064 PGS001061
(GBE_INI1289)
PSS004812|
East Asian Ancestry|
1,578 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Cooked vegetable intake : 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
PPM007684 PGS000978
(GBE_INI1438)
PSS004842|
East Asian Ancestry|
1,557 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Bread intake : 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. medRxiv (2021)
|Pre
Reported Trait: Bread intake : 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
PPM008065 PGS001061
(GBE_INI1289)
PSS004813|
European Ancestry|
24,087 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Cooked vegetable intake Incremental R2 (full-covars): 0.00028
: 0.01788 [0.01462, 0.02114]
PGS R2 (no covariates): 0.00042 [-0.00009, 0.00093]
age, sex, UKB array type, Genotype PCs
PPM008068 PGS001062
(GBE_INI1309)
PSS004816|
African Ancestry|
6,032 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Fresh fruit intake : 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
PPM007727 PGS000991
(GBE_BIN_FC4006144)
PSS003948|
European Ancestry|
67,271 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Never eat sugar AUROC: 0.61373 [0.60865, 0.61881] : 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
PPM007686 PGS000978
(GBE_INI1438)
PSS004844|
South Asian Ancestry|
7,412 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Bread intake : 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. medRxiv (2021)
|Pre
Reported Trait: Bread intake : 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
PPM007723 PGS000991
(GBE_BIN_FC4006144)
PSS003944|
African Ancestry|
6,368 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Never eat sugar AUROC: 0.6377 [0.61811, 0.6573] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat sugar AUROC: 0.64533 [0.60258, 0.68809] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat sugar AUROC: 0.62033 [0.61189, 0.62878] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat sugar AUROC: 0.6355 [0.61763, 0.65337] : 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
PPM008106 PGS001069
(GBE_INI1528)
PSS004864|
South Asian Ancestry|
7,550 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Water intake : 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
PPM008066 PGS001061
(GBE_INI1289)
PSS004814|
South Asian Ancestry|
7,034 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Cooked vegetable intake : 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
PPM008069 PGS001062
(GBE_INI1309)
PSS004817|
East Asian Ancestry|
1,592 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Fresh fruit intake : 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
PPM007933 PGS001034
(GBE_QT_FC10001478)
PSS007506|
African Ancestry|
6,428 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Salt added to food : 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. medRxiv (2021)
|Pre
Reported Trait: Salt added to food : 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. medRxiv (2021)
|Pre
Reported Trait: Salt added to food : 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. medRxiv (2021)
|Pre
Reported Trait: Salt added to food : 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. medRxiv (2021)
|Pre
Reported Trait: Salt added to food : 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
PPM008107 PGS001069
(GBE_INI1528)
PSS004865|
European Ancestry|
62,737 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Water intake : 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
PPM008038 PGS001056
(GBE_QT_FC1001369)
PSS007556|
African Ancestry|
6,271 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Beef intake : 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. medRxiv (2021)
|Pre
Reported Trait: Beef intake : 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. medRxiv (2021)
|Pre
Reported Trait: Beef intake : 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. medRxiv (2021)
|Pre
Reported Trait: Beef intake : 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. medRxiv (2021)
|Pre
Reported Trait: Beef intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) AUROC: 0.53868 [0.51659, 0.56077] PGS R2 (no covariates): 0.00013
: 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) AUROC: 0.56685 [0.51503, 0.61867] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) AUROC: 0.58711 [0.57552, 0.5987] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) AUROC: 0.56331 [0.54576, 0.58087] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Biscuit cereal (e.g. Weetabix) AUROC: 0.55057 [0.54462, 0.55652] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) AUROC: 0.61741 [0.59849, 0.63633] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) AUROC: 0.64303 [0.60109, 0.68497] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) AUROC: 0.60408 [0.59345, 0.6147] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) AUROC: 0.59996 [0.58323, 0.61669] : 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. medRxiv (2021)
|Pre
Reported Trait: Cereal type: Other (e.g. Cornflakes, Frosties) AUROC: 0.58769 [0.58186, 0.59353] : 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. medRxiv (2021)
|Pre
Reported Trait: Cheese intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cheese intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cheese intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cheese intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cheese intake : 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
PPM008063 PGS001061
(GBE_INI1289)
PSS004811|
African Ancestry|
5,840 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Cooked vegetable intake : 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. medRxiv (2021)
|Pre
Reported Trait: Cooked vegetable intake : 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
PPM008070 PGS001062
(GBE_INI1309)
PSS004818|
European Ancestry|
24,138 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Fresh fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Fresh fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Fresh fruit intake : 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. medRxiv (2021)
|Pre
Reported Trait: Major dietary changes in the last 5 years becuase of illness AUROC: 0.62048 [0.60331, 0.63766] : 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. medRxiv (2021)
|Pre
Reported Trait: Major dietary changes in the last 5 years becuase of illness AUROC: 0.63276 [0.58471, 0.68082] : 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. medRxiv (2021)
|Pre
Reported Trait: Major dietary changes in the last 5 years becuase of illness AUROC: 0.58219 [0.57084, 0.59354] : 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. medRxiv (2021)
|Pre
Reported Trait: Major dietary changes in the last 5 years becuase of illness AUROC: 0.59898 [0.58379, 0.61417] : 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. medRxiv (2021)
|Pre
Reported Trait: Major dietary changes in the last 5 years becuase of illness AUROC: 0.57633 [0.56954, 0.58313] : 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. medRxiv (2021)
|Pre
Reported Trait: Milk type: Skimmed AUROC: 0.56598 [0.54374, 0.58822] : 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. medRxiv (2021)
|Pre
Reported Trait: Milk type: Skimmed AUROC: 0.58283 [0.5384, 0.62725] : 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. medRxiv (2021)
|Pre
Reported Trait: Milk type: Skimmed AUROC: 0.56928 [0.56021, 0.57836] : 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. medRxiv (2021)
|Pre
Reported Trait: Milk type: Skimmed AUROC: 0.56624 [0.54661, 0.58587] : 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. medRxiv (2021)
|Pre
Reported Trait: Milk type: Skimmed AUROC: 0.57752 [0.57233, 0.58271] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat wheat AUROC: 0.55785 [0.52697, 0.58872] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat wheat AUROC: 0.64888 [0.57732, 0.72044] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat wheat AUROC: 0.62411 [0.60564, 0.64259] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat wheat AUROC: 0.59764 [0.56396, 0.63132] : 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. medRxiv (2021)
|Pre
Reported Trait: Never eat wheat AUROC: 0.58236 [0.56955, 0.59518] : 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. medRxiv (2021)
|Pre
Reported Trait: Poultry intake : 0.02159 [0.0146, 0.02858]
Incremental R2 (full-covars): 0.00053
PGS R2 (no covariates): 0.00093 [-0.00055, 0.00241]
age, sex, UKB array type, Genotype PCs
PPM008089 PGS001066
(GBE_QT_FC1001359)
PSS007552|
East Asian Ancestry|
1,655 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Poultry intake : 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. medRxiv (2021)
|Pre
Reported Trait: Poultry intake : 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. medRxiv (2021)
|Pre
Reported Trait: Poultry intake : 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. medRxiv (2021)
|Pre
Reported Trait: Poultry intake : 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. medRxiv (2021)
|Pre
Reported Trait: Processed meat intake : 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. medRxiv (2021)
|Pre
Reported Trait: Processed meat intake : 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. medRxiv (2021)
|Pre
Reported Trait: Processed meat intake : 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. medRxiv (2021)
|Pre
Reported Trait: Processed meat intake : 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. medRxiv (2021)
|Pre
Reported Trait: Processed meat intake : 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. medRxiv (2021)
|Pre
Reported Trait: Variation in diet : 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. medRxiv (2021)
|Pre
Reported Trait: Variation in diet : 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. medRxiv (2021)
|Pre
Reported Trait: Variation in diet : 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. medRxiv (2021)
|Pre
Reported Trait: Variation in diet : 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. medRxiv (2021)
|Pre
Reported Trait: Variation in diet : 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
PPM008103 PGS001069
(GBE_INI1528)
PSS004861|
African Ancestry|
6,061 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Water intake : 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. medRxiv (2021)
|Pre
Reported Trait: Water intake : 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. medRxiv (2021)
|Pre
Reported Trait: Water intake : 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

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)
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
PSS007547 1,642 individuals East Asian UKB
PSS007548 24,852 individuals European non-white British ancestry 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)
PSS007549 7,555 individuals South Asian UKB
PSS007550 67,321 individuals European white British ancestry UKB Testing cohort (heldout set)