Trait: body mass index

Experimental Factor Ontology (EFO) Information
Identifier EFO_0004340
Description An indicator of body density as determined by the relationship of BODY WEIGHT to BODY HEIGHT. BMI=weight (kg)/height squared (m2). BMI correlates with body fat (ADIPOSE TISSUE). Their relationship varies with age and gender. For adults, BMI falls into these categories: below 18.5 (underweight); 18.5-24.9 (normal); 25.0-29.9 (overweight); 30.0 and above (obese). (National Center for Health Statistics, Centers for Disease Control and Prevention)
Trait category
Body measurement
Synonyms 2 synonyms
  • BMI
  • Quetelet's Index
Mapped terms 5 mapped terms
  • ICD9:V85-V85.99
  • MeSH:D015992
  • MedDRA:10005894
  • NCIt:C16358
  • SNOMEDCT:60621009
Child trait(s) overweight body mass index status

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 "body mass index" 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)
PGS000027
(GPS_BMI)
PGP000017 |
Khera AV et al. Cell (2019)
Body Mass Index body mass index 2,100,302
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000027/ScoringFiles/PGS000027.txt.gz - Check Terms/Licenses
PGS000034
(GRS_BMI)
PGP000021 |
Song M et al. Diabetes (2017)
Adult Body Mass Index body mass index 97
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000034/ScoringFiles/PGS000034.txt.gz
PGS000298
(GRS941_BMI)
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Body mass index body mass index 941
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000298/ScoringFiles/PGS000298.txt.gz
PGS000320
(PRS_BMI)
PGP000096 |
Chami N et al. PLoS Med (2020)
Body mass index body mass index 263,640
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000320/ScoringFiles/PGS000320.txt.gz
PGS000716
(PGS295_elbs)
PGP000132 |
Richardson TG et al. BMJ (2020)
Early life body size body mass index,
comparative body size at age 10, self-reported
295
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000716/ScoringFiles/PGS000716.txt.gz
PGS000717
(PGS557_albs)
PGP000132 |
Richardson TG et al. BMJ (2020)
Adult life body size body mass index 557
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000717/ScoringFiles/PGS000717.txt.gz
PGS000770
(PRS231)
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Body mass index body mass index 231
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000770/ScoringFiles/PGS000770.txt.gz
PGS000829
(BMI_PGS_M)
PGP000210 |
Zubair N et al. Sci Rep (2019)
Body mass index (male) body mass index,
male
290
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000829/ScoringFiles/PGS000829.txt.gz - Check Terms/Licenses
PGS000830
(BMI_PGS_F)
PGP000210 |
Zubair N et al. Sci Rep (2019)
Body mass index (female) body mass index,
female
372
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000830/ScoringFiles/PGS000830.txt.gz - Check Terms/Licenses
PGS000841
(BMI)
PGP000211 |
Aly DM et al. Nat Genet (2021)
Body mass index body mass index 122
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000841/ScoringFiles/PGS000841.txt.gz
PGS000910
(PRS_BMI)
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Body mass index body mass index 735,440
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000910/ScoringFiles/PGS000910.txt.gz
PGS000921
(PRS_BMI)
PGP000243 |
Borisevich D et al. PLoS One (2021)
Body mass index body mass index 1,947,711
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000921/ScoringFiles/PGS000921.txt.gz
PGS001228
(GBE_INI21001)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Body mass index body mass index 27,126
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001228/ScoringFiles/PGS001228.txt.gz
PGS001825
(portability-PLR_278)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Overweight, obesity and other hyperalimentation obesity,
overweight body mass index status,
overnutrition
13,009
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001825/ScoringFiles/PGS001825.txt.gz
PGS001943
(portability-PLR_log_BMI)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Body mass index (BMI) body mass index 110,153
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001943/ScoringFiles/PGS001943.txt.gz
PGS002033
(portability-ldpred2_278)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Overweight, obesity and other hyperalimentation obesity,
overweight body mass index status,
overnutrition
846,292
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002033/ScoringFiles/PGS002033.txt.gz
PGS002161
(portability-ldpred2_log_BMI)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Body mass index (BMI) body mass index 990,022
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002161/ScoringFiles/PGS002161.txt.gz
PGS002251
(PRS97_BMI)
PGP000278 |
Dashti HS et al. BMC Med (2022)
Body mass index body mass index 97
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002251/ScoringFiles/PGS002251.txt.gz
PGS002313
(body_BMIz.BOLT-LMM)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 1,109,311
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002313/ScoringFiles/PGS002313.txt.gz
PGS002360
(body_BMIz.BOLT-LMM-BBJ)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 920,920
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002360/ScoringFiles/PGS002360.txt.gz
PGS002385
(body_BMIz.P+T.0.0001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 15,518
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002385/ScoringFiles/PGS002385.txt.gz
PGS002434
(body_BMIz.P+T.0.001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 41,662
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002434/ScoringFiles/PGS002434.txt.gz
PGS002483
(body_BMIz.P+T.0.01)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 162,598
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002483/ScoringFiles/PGS002483.txt.gz
PGS002532
(body_BMIz.P+T.1e-06)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 4,284
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002532/ScoringFiles/PGS002532.txt.gz
PGS002581
(body_BMIz.P+T.5e-08)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 2,385
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002581/ScoringFiles/PGS002581.txt.gz
PGS002630
(body_BMIz.PolyFun-pred)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 620,484
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002630/ScoringFiles/PGS002630.txt.gz
PGS002679
(body_BMIz.SBayesR)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
BMI body mass index 987,879
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002679/ScoringFiles/PGS002679.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
PPM000054 PGS000027
(GPS_BMI)
PSS000037|
European Ancestry|
288,016 individuals
PGP000017 |
Khera AV et al. Cell (2019)
Reported Trait: Body mass index β: 1.41 : 0.08526 First 10 genetic PCs Beta is in units of kg/m^2
PPM001725 PGS000027
(GPS_BMI)
PSS000885|
European Ancestry|
19,588 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between male siblings OR: 2.21 [1.92, 2.54] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001726 PGS000027
(GPS_BMI)
PSS000886|
European Ancestry|
21,499 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within female siblings OR: 2.09 [1.74, 2.51] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001727 PGS000027
(GPS_BMI)
PSS000886|
European Ancestry|
21,499 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between female siblings OR: 2.13 [1.87, 2.43] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001728 PGS000027
(GPS_BMI)
PSS000887|
European Ancestry|
26,323 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within male siblings OR: 2.15 [1.91, 2.41] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001730 PGS000027
(GPS_BMI)
PSS000888|
European Ancestry|
29,527 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within female siblings OR: 1.87 [1.68, 2.09] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001731 PGS000027
(GPS_BMI)
PSS000888|
European Ancestry|
29,527 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between female siblings OR: 2.05 [1.89, 2.22] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001732 PGS000027
(GPS_BMI)
PSS000889|
European Ancestry|
21,187 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within male siblings OR: 2.0 [1.79, 2.23] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001733 PGS000027
(GPS_BMI)
PSS000889|
European Ancestry|
21,187 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between male siblings OR: 2.12 [1.96, 2.3] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001734 PGS000027
(GPS_BMI)
PSS000890|
European Ancestry|
25,096 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within female siblings OR: 2.0 [1.8, 2.21] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001735 PGS000027
(GPS_BMI)
PSS000890|
European Ancestry|
25,096 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between female siblings OR: 2.03 [1.88, 2.19] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001736 PGS000027
(GPS_BMI)
PSS000891|
European Ancestry|
14,487 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within male siblings OR: 1.9 [1.68, 2.14] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001769 PGS000027
(GPS_BMI)
PSS000911|
Greater Middle Eastern Ancestry|
13,989 individuals
PGP000147 |
Thareja G et al. Nat Commun (2021)
|Ext.
Reported Trait: Body mass index Pearson correlation coefficent (r): 0.22
PPM001737 PGS000027
(GPS_BMI)
PSS000891|
European Ancestry|
14,487 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between male siblings OR: 2.0 [1.83, 2.19] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001738 PGS000027
(GPS_BMI)
PSS000892|
European Ancestry|
17,740 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within female siblings OR: 1.72 [1.53, 1.93] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001739 PGS000027
(GPS_BMI)
PSS000892|
European Ancestry|
17,740 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between female siblings OR: 1.89 [1.74, 2.05] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001724 PGS000027
(GPS_BMI)
PSS000885|
European Ancestry|
19,588 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity within male siblings OR: 2.02 [1.66, 2.46] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM001729 PGS000027
(GPS_BMI)
PSS000887|
European Ancestry|
26,323 individuals
PGP000141 |
Brandkvist M et al. PLoS Med (2020)
|Ext.
Reported Trait: Obesity between male siblings OR: 2.15 [1.97, 2.34] Sex, time of measurement, age, PCs (1-20), genotyping batch 2.07 million of the 2.1 milliion common variants (excluding those with insufficient quality of genotyping or imputation (r^2 < 0.8) in the HUNT cohort) were included in the polygenic score previously developed by Khera et al (2019).
PPM000072 PGS000034
(GRS_BMI)
PSS000050|
European Ancestry|
5,640 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): 0.17 [0.03, 0.31]
PPM000071 PGS000034
(GRS_BMI)
PSS000048|
European Ancestry|
5,956 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): 0.54 [0.38, 0.71]
PPM000073 PGS000034
(GRS_BMI)
PSS000051|
European Ancestry|
2,942 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): -0.22 [-0.39, -0.05]
PPM000074 PGS000034
(GRS_BMI)
PSS000049|
European Ancestry|
6,705 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): 0.6 [0.42, 0.77]
PPM000075 PGS000034
(GRS_BMI)
PSS000052|
European Ancestry|
6,436 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): 0.07 [-0.04, 0.19]
PPM000076 PGS000034
(GRS_BMI)
PSS000045|
European Ancestry|
1,699 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): 0.23 [0.02, 0.44]
PPM000077 PGS000034
(GRS_BMI)
PSS000046|
European Ancestry|
1,634 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): -0.1 [-0.29, 0.09]
PPM000078 PGS000034
(GRS_BMI)
PSS000047|
European Ancestry|
2,020 individuals
PGP000021 |
Song M et al. Diabetes (2017)
Reported Trait: mean BMI difference β (per 10-allele increment): -0.01 [-0.16, 0.14]
PPM000791 PGS000298
(GRS941_BMI)
PSS000369|
European Ancestry|
334 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0671 Sex, age
PPM000792 PGS000298
(GRS941_BMI)
PSS000370|
European Ancestry|
329 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.057 Sex, age
PPM000793 PGS000298
(GRS941_BMI)
PSS000371|
European Ancestry|
288 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0886 Sex, age
PPM000794 PGS000298
(GRS941_BMI)
PSS000372|
European Ancestry|
265 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.092 Sex, age
PPM000795 PGS000298
(GRS941_BMI)
PSS000373|
European Ancestry|
245 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.1194 Sex, age
PPM000761 PGS000298
(GRS941_BMI)
PSS000374|
European Ancestry|
1,318 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0579 Sex, age
PPM000762 PGS000298
(GRS941_BMI)
PSS000375|
European Ancestry|
1,313 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0612 Sex, age
PPM000763 PGS000298
(GRS941_BMI)
PSS000376|
European Ancestry|
1,354 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0647 Sex, age
PPM000764 PGS000298
(GRS941_BMI)
PSS000377|
European Ancestry|
1,174 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0655 Sex, age
PPM000765 PGS000298
(GRS941_BMI)
PSS000378|
European Ancestry|
1,095 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Body mass index (kg/m2) : 0.0591 Sex, age
PPM000860 PGS000320
(PRS_BMI)
PSS000411|
European Ancestry|
104 individuals
PGP000096 |
Chami N et al. PLoS Med (2020)
Reported Trait: Body mass index (BMI; kg/m^2) in MC4R carriers Higher PRS in obese vs. normal weight MC4R mutation carriers (p-value): 1.70e-06 age, sex, 10 genetic PCs
PPM000859 PGS000320
(PRS_BMI)
PSS000412|
European Ancestry|
256,770 individuals
PGP000096 |
Chami N et al. PLoS Med (2020)
Reported Trait: Body mass index (BMI; kg/m^2) in MC4R non-carriers Higher PRS in obese vs. normal weight MC4R non-carriers (p-value): 2.00e-16 age, sex, 10 genetic PCs
PPM000858 PGS000320
(PRS_BMI)
PSS000413|
European Ancestry|
451,508 individuals
PGP000096 |
Chami N et al. PLoS Med (2020)
Reported Trait: Body mass index (BMI; kg/m^2) β: 1.29 : 0.0676 age, sex, 10 genetic PCs
PPM001708 PGS000716
(PGS295_elbs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.569 [0.564, 0.574] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001709 PGS000716
(PGS295_elbs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.656 [0.626, 0.686] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001710 PGS000716
(PGS295_elbs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.623 [0.589, 0.657] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001711 PGS000716
(PGS295_elbs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.601 [0.589, 0.612] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001712 PGS000716
(PGS295_elbs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.591 [0.582, 0.6] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001713 PGS000716
(PGS295_elbs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.568 [0.563, 0.573] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001707 PGS000716
(PGS295_elbs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.618 [0.594, 0.641] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001687 PGS000716
(PGS295_elbs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.619 [0.596, 0.643] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001688 PGS000716
(PGS295_elbs)
PSS000881|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 24-29.9 AUROC: 0.602 [0.585, 0.618] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001689 PGS000716
(PGS295_elbs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.569 [0.564, 0.574] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001690 PGS000716
(PGS295_elbs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.658 [0.628, 0.687] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001691 PGS000716
(PGS295_elbs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.624 [0.589, 0.658] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001692 PGS000716
(PGS295_elbs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.602 [0.59, 0.613] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001693 PGS000716
(PGS295_elbs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.591 [0.582, 0.6] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001633 PGS000716
(PGS295_elbs)
PSS000849|
European Ancestry|
5,898 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Childhood body mass index AUROC: 0.64
PPM001635 PGS000716
(PGS295_elbs)
PSS000847|
European Ancestry|
3,997 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adolescent body mass index AUROC: 0.63
PPM001637 PGS000716
(PGS295_elbs)
PSS000848|
European Ancestry|
2,199 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adult body mass index AUROC: 0.57
PPM001705 PGS000716
(PGS295_elbs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.739 [0.667, 0.811] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001706 PGS000716
(PGS295_elbs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.66 [0.566, 0.754] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001685 PGS000716
(PGS295_elbs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.735 [0.663, 0.806] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001686 PGS000716
(PGS295_elbs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.672 [0.577, 0.766] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001694 PGS000716
(PGS295_elbs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.568 [0.563, 0.573] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001714 PGS000717
(PGS557_albs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.664 [0.574, 0.753] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001715 PGS000717
(PGS557_albs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.691 [0.589, 0.793] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001716 PGS000717
(PGS557_albs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.624 [0.601, 0.646] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001717 PGS000717
(PGS557_albs)
PSS000881|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 24-29.9 AUROC: 0.623 [0.607, 0.639] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001719 PGS000717
(PGS557_albs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.587 [0.556, 0.618] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001720 PGS000717
(PGS557_albs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.615 [0.58, 0.649] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001722 PGS000717
(PGS557_albs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.598 [0.589, 0.607] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001723 PGS000717
(PGS557_albs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.582 [0.578, 0.587] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001718 PGS000717
(PGS557_albs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.597 [0.591, 0.602] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001695 PGS000717
(PGS557_albs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.66 [0.57, 0.75] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001696 PGS000717
(PGS557_albs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.661 [0.551, 0.77] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001699 PGS000717
(PGS557_albs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.6 [0.595, 0.605] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001634 PGS000717
(PGS557_albs)
PSS000849|
European Ancestry|
5,898 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Childhood body mass index AUROC: 0.61
PPM001636 PGS000717
(PGS557_albs)
PSS000847|
European Ancestry|
3,997 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adolescent body mass index AUROC: 0.63
PPM001638 PGS000717
(PGS557_albs)
PSS000848|
European Ancestry|
2,199 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adult body mass index AUROC: 0.6
PPM001702 PGS000717
(PGS557_albs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.595 [0.583, 0.607] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001703 PGS000717
(PGS557_albs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.602 [0.593, 0.611] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001704 PGS000717
(PGS557_albs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.585 [0.58, 0.589] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001721 PGS000717
(PGS557_albs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.592 [0.58, 0.604] Due to a lack of information in the HUNT dataset, only 509 of the 557 common variants used to build the adult score by Richardson et al were included.
PPM001697 PGS000717
(PGS557_albs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.629 [0.606, 0.652] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001698 PGS000717
(PGS557_albs)
PSS000881|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 24-29.9 AUROC: 0.627 [0.611, 0.643] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001700 PGS000717
(PGS557_albs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.591 [0.559, 0.623] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001701 PGS000717
(PGS557_albs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.618 [0.583, 0.653] Due to a lack of information in the HUNT dataset, only 546 of the 557 common variants used to build the adult score by Richardson et al were included. Additionally, 28 of the 546 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001987 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity Odds Ratio (OR_Trend): 1.19 [1.06, 1.33] Age, sex, random effect (family relatedness)
PPM001988 PGS000770
(PRS231)
PSS000991|
European Ancestry|
141 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity Odds Ratio (OR_Trend): 1.12 [1.01, 1.25] Age, sex, random effect (family relatedness)
PPM001989 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence AUROC: 0.661 Bootstrapping (n=1000)
PPM001990 PGS000770
(PRS231)
PSS000991|
European Ancestry|
141 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence AUROC: 0.619 Bootstrapping (n=1000)
PPM001991 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence AUROC: 0.127 [0.04, 0.22] Age, sex, bootstrapping (n=1000)
PPM001992 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence Odds Ratio (OR, top 20% vs bottom 20%): 4.77 [1.54, 16.99] Age, sex, random effect (family relatedness)
PPM001993 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence Odds Ratio (OR, middle 40-60% vs bottom 20%): 3.46 [1.11, 12.31] Age, sex, random effect (family relatedness)
PPM001994 PGS000770
(PRS231)
PSS000991|
European Ancestry|
141 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Obesity prevalence Odds Ratio (OR, middle 60-80% vs bottom 20%): 3.79 [1.07, 15.86] Age, sex, random effect (family relatedness)
PPM001995 PGS000770
(PRS231)
PSS000992|
European Ancestry|
177 individuals
PGP000177 |
de Toro-Martín J et al. Front Genet (2019)
Reported Trait: Body mass index β: 0.33 : 0.032 Sex, age
PPM002236 PGS000829
(BMI_PGS_M)
PSS001083|
Multi-ancestry (including European)|
2,531 individuals
PGP000210 |
Zubair N et al. Sci Rep (2019)
Reported Trait: Body mass index (male) : 0.017 Age at baseline, sex, enrollment channel, PCs(1-7), observation season, observation vendor
PPM002235 PGS000830
(BMI_PGS_F)
PSS001083|
Multi-ancestry (including European)|
2,531 individuals
PGP000210 |
Zubair N et al. Sci Rep (2019)
Reported Trait: Body mass index (female) : 0.027 Age at baseline, sex, enrollment channel, PCs(1-7), observation season, observation vendor
PPM002288 PGS000841
(BMI)
PSS001086|
European Ancestry|
3,194 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Autoimmune Diabetes OR: 1.14 [1.03, 1.26] PC1-10
PPM002289 PGS000841
(BMI)
PSS001087|
European Ancestry|
3,930 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Deficient Diabetes OR: 1.15 [1.07, 1.23] PC1-10
PPM002290 PGS000841
(BMI)
PSS001088|
European Ancestry|
3,869 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Resistant Diabetes OR: 1.23 [1.14, 1.32] PC1-10
PPM002291 PGS000841
(BMI)
PSS001085|
European Ancestry|
4,116 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Obesity-related Diabetes OR: 1.29 [1.21, 1.38] PC1-10
PPM002292 PGS000841
(BMI)
PSS001084|
European Ancestry|
5,597 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Age-Related Diabetes OR: 1.05 [0.99, 1.1] PC1-10
PPM002930 PGS000910
(PRS_BMI)
PSS001433|
European Ancestry|
5,719 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Sertraline takers OR: 1.27 [1.19, 1.35] Variance explained (Nagelkerke's R2*100): 1.57 sex, age at study enrollment, genetic PCs 1-20
PPM002931 PGS000910
(PRS_BMI)
PSS001429|
European Ancestry|
4,365 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Escitalopram takers OR: 1.22 [1.14, 1.31] Variance explained (Nagelkerke's R2*100): 1.17 sex, age at study enrollment, genetic PCs 1-20
PPM002932 PGS000910
(PRS_BMI)
PSS001434|
European Ancestry|
3,967 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Venlafaxine takers OR: 1.23 [1.14, 1.32] Variance explained (Nagelkerke's R2*100): 1.28 sex, age at study enrollment, genetic PCs 1-20
PPM002933 PGS000910
(PRS_BMI)
PSS001425|
European Ancestry|
1,657 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Amitriptyline takers OR: 1.27 [1.13, 1.42] Variance explained (Nagelkerke's R2*100): 1.74 sex, age at study enrollment, genetic PCs 1-20
PPM002935 PGS000910
(PRS_BMI)
PSS001427|
European Ancestry|
2,524 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Desvenlafaxine takers OR: 1.24 [1.13, 1.36] Variance explained (Nagelkerke's R2*100): 1.36 sex, age at study enrollment, genetic PCs 1-20
PPM002936 PGS000910
(PRS_BMI)
PSS001426|
European Ancestry|
2,585 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Citalopram takers OR: 1.39 [1.26, 1.53] Variance explained (Nagelkerke's R2*100): 2.83 sex, age at study enrollment, genetic PCs 1-20
PPM002937 PGS000910
(PRS_BMI)
PSS001430|
European Ancestry|
3,670 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Fluoxetine takers OR: 1.3 [1.2, 1.4] Variance explained (Nagelkerke's R2*100): 1.87 sex, age at study enrollment, genetic PCs 1-20
PPM002938 PGS000910
(PRS_BMI)
PSS001428|
European Ancestry|
1,995 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Duloxetine takers OR: 1.21 [1.1, 1.34] Variance explained (Nagelkerke's R2*100): 1.26 sex, age at study enrollment, genetic PCs 1-20
PPM002934 PGS000910
(PRS_BMI)
PSS001431|
European Ancestry|
1,987 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Mirtazapine takers OR: 1.21 [1.1, 1.33] Variance explained (Nagelkerke's R2*100): 1.23 sex, age at study enrollment, genetic PCs 1-20
PPM002939 PGS000910
(PRS_BMI)
PSS001432|
European Ancestry|
1,580 individuals
PGP000238 |
Campos AI et al. medRxiv (2021)
|Pre
Reported Trait: Weight gain in Paroxetine takers OR: 1.19 [1.06, 1.33] Variance explained (Nagelkerke's R2*100): 0.84 sex, age at study enrollment, genetic PCs 1-20
PPM002993 PGS000921
(PRS_BMI)
PSS001456|
European Ancestry|
5,179 individuals
PGP000243 |
Borisevich D et al. PLoS One (2021)
Reported Trait: Body mass index β: 1.7 kg/m2 : 0.162
R2 (linear regression BMI ~ 1 + PRS): 0.131
age, sex
PPM008654 PGS001228
(GBE_INI21001)
PSS004911|
African Ancestry|
6,398 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: BMI : 0.06264 [0.05124, 0.07404]
Incremental R2 (full-covars): 0.01685
PGS R2 (no covariates): 0.02029 [0.0135, 0.02707]
age, sex, UKB array type, Genotype PCs
PPM008655 PGS001228
(GBE_INI21001)
PSS004912|
East Asian Ancestry|
1,696 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: BMI : 0.16636 [0.13414, 0.19858]
Incremental R2 (full-covars): 0.03119
PGS R2 (no covariates): 0.06222 [0.04005, 0.08439]
age, sex, UKB array type, Genotype PCs
PPM008656 PGS001228
(GBE_INI21001)
PSS004913|
European Ancestry|
24,795 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: BMI : 0.13175 [0.12392, 0.13958]
Incremental R2 (full-covars): 0.09741
PGS R2 (no covariates): 0.10338 [0.09622, 0.11054]
age, sex, UKB array type, Genotype PCs
PPM008657 PGS001228
(GBE_INI21001)
PSS004914|
South Asian Ancestry|
7,639 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: BMI : 0.0872 [0.07527, 0.09914]
Incremental R2 (full-covars): 0.06488
PGS R2 (no covariates): 0.0648 [0.05426, 0.07534]
age, sex, UKB array type, Genotype PCs
PPM008658 PGS001228
(GBE_INI21001)
PSS004915|
European Ancestry|
67,235 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: BMI : 0.12084 [0.11623, 0.12545]
Incremental R2 (full-covars): 0.10799
PGS R2 (no covariates): 0.11052 [0.10606, 0.11499]
age, sex, UKB array type, Genotype PCs
PPM009497 PGS001825
(portability-PLR_278)
PSS009295|
European Ancestry|
20,000 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0547 [0.0409, 0.0686] sex, age, birth date, deprivation index, 16 PCs
PPM009499 PGS001825
(portability-PLR_278)
PSS008623|
European Ancestry|
6,660 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0516 [0.0276, 0.0756] sex, age, birth date, deprivation index, 16 PCs
PPM009500 PGS001825
(portability-PLR_278)
PSS008398|
Greater Middle Eastern Ancestry|
1,200 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0493 [-0.0078, 0.106] sex, age, birth date, deprivation index, 16 PCs
PPM009501 PGS001825
(portability-PLR_278)
PSS008177|
South Asian Ancestry|
6,331 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0334 [0.0087, 0.058] sex, age, birth date, deprivation index, 16 PCs
PPM009502 PGS001825
(portability-PLR_278)
PSS007963|
East Asian Ancestry|
1,810 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): -0.0049 [-0.0513, 0.0414] sex, age, birth date, deprivation index, 16 PCs
PPM009503 PGS001825
(portability-PLR_278)
PSS007744|
African Ancestry|
2,484 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0323 [-0.0072, 0.0717] sex, age, birth date, deprivation index, 16 PCs
PPM009504 PGS001825
(portability-PLR_278)
PSS008848|
African Ancestry|
3,924 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0208 [-0.0105, 0.0522] sex, age, birth date, deprivation index, 16 PCs
PPM009498 PGS001825
(portability-PLR_278)
PSS009069|
European Ancestry|
4,136 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0453 [0.0148, 0.0758] sex, age, birth date, deprivation index, 16 PCs
PPM010419 PGS001943
(portability-PLR_log_BMI)
PSS009429|
European Ancestry|
19,937 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3698 [0.3577, 0.3817] sex, age, birth date, deprivation index, 16 PCs
PPM010420 PGS001943
(portability-PLR_log_BMI)
PSS009203|
European Ancestry|
4,124 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3628 [0.336, 0.3891] sex, age, birth date, deprivation index, 16 PCs
PPM010421 PGS001943
(portability-PLR_log_BMI)
PSS008757|
European Ancestry|
6,622 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3557 [0.3345, 0.3766] sex, age, birth date, deprivation index, 16 PCs
PPM010422 PGS001943
(portability-PLR_log_BMI)
PSS008531|
Greater Middle Eastern Ancestry|
1,178 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3001 [0.2468, 0.3517] sex, age, birth date, deprivation index, 16 PCs
PPM010423 PGS001943
(portability-PLR_log_BMI)
PSS008309|
South Asian Ancestry|
6,145 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3048 [0.2819, 0.3274] sex, age, birth date, deprivation index, 16 PCs
PPM010424 PGS001943
(portability-PLR_log_BMI)
PSS008086|
East Asian Ancestry|
1,799 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.2501 [0.206, 0.2931] sex, age, birth date, deprivation index, 16 PCs
PPM010425 PGS001943
(portability-PLR_log_BMI)
PSS007873|
African Ancestry|
2,444 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.1973 [0.1587, 0.2352] sex, age, birth date, deprivation index, 16 PCs
PPM010426 PGS001943
(portability-PLR_log_BMI)
PSS008977|
African Ancestry|
3,859 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.1571 [0.1261, 0.1878] sex, age, birth date, deprivation index, 16 PCs
PPM011135 PGS002033
(portability-ldpred2_278)
PSS009295|
European Ancestry|
20,000 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0789 [0.0651, 0.0927] sex, age, birth date, deprivation index, 16 PCs
PPM011137 PGS002033
(portability-ldpred2_278)
PSS008623|
European Ancestry|
6,660 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0824 [0.0585, 0.1062] sex, age, birth date, deprivation index, 16 PCs
PPM011138 PGS002033
(portability-ldpred2_278)
PSS008398|
Greater Middle Eastern Ancestry|
1,200 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0801 [0.0232, 0.1366] sex, age, birth date, deprivation index, 16 PCs
PPM011139 PGS002033
(portability-ldpred2_278)
PSS008177|
South Asian Ancestry|
6,331 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0502 [0.0255, 0.0747] sex, age, birth date, deprivation index, 16 PCs
PPM011140 PGS002033
(portability-ldpred2_278)
PSS007963|
East Asian Ancestry|
1,810 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0109 [-0.0354, 0.0572] sex, age, birth date, deprivation index, 16 PCs
PPM011141 PGS002033
(portability-ldpred2_278)
PSS007744|
African Ancestry|
2,484 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0265 [-0.013, 0.0659] sex, age, birth date, deprivation index, 16 PCs
PPM011142 PGS002033
(portability-ldpred2_278)
PSS008848|
African Ancestry|
3,924 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0516 [0.0203, 0.0829] sex, age, birth date, deprivation index, 16 PCs
PPM011136 PGS002033
(portability-ldpred2_278)
PSS009069|
European Ancestry|
4,136 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Overweight, obesity and other hyperalimentation Partial Correlation (partial-r): 0.0523 [0.0218, 0.0827] sex, age, birth date, deprivation index, 16 PCs
PPM012135 PGS002161
(portability-ldpred2_log_BMI)
PSS009429|
European Ancestry|
19,937 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3664 [0.3544, 0.3784] sex, age, birth date, deprivation index, 16 PCs
PPM012136 PGS002161
(portability-ldpred2_log_BMI)
PSS009203|
European Ancestry|
4,124 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3698 [0.3431, 0.3959] sex, age, birth date, deprivation index, 16 PCs
PPM012137 PGS002161
(portability-ldpred2_log_BMI)
PSS008757|
European Ancestry|
6,622 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.3595 [0.3384, 0.3804] sex, age, birth date, deprivation index, 16 PCs
PPM012138 PGS002161
(portability-ldpred2_log_BMI)
PSS008531|
Greater Middle Eastern Ancestry|
1,178 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.2932 [0.2396, 0.345] sex, age, birth date, deprivation index, 16 PCs
PPM012139 PGS002161
(portability-ldpred2_log_BMI)
PSS008309|
South Asian Ancestry|
6,145 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.308 [0.2851, 0.3305] sex, age, birth date, deprivation index, 16 PCs
PPM012141 PGS002161
(portability-ldpred2_log_BMI)
PSS007873|
African Ancestry|
2,444 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.2104 [0.1721, 0.2482] sex, age, birth date, deprivation index, 16 PCs
PPM012142 PGS002161
(portability-ldpred2_log_BMI)
PSS008977|
African Ancestry|
3,859 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.1573 [0.1263, 0.188] sex, age, birth date, deprivation index, 16 PCs
PPM012140 PGS002161
(portability-ldpred2_log_BMI)
PSS008086|
East Asian Ancestry|
1,799 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Body mass index (BMI) Partial Correlation (partial-r): 0.2694 [0.2257, 0.3119] sex, age, birth date, deprivation index, 16 PCs
PPM012804 PGS002251
(PRS97_BMI)
PSS009565|
European Ancestry|
33,511 individuals
PGP000278 |
Dashti HS et al. BMC Med (2022)
Reported Trait: Body mass index β: 0.83 [0.76, 0.9] age, sex, genotyping array, and 5 PCs of ancestry beta unit kg/m2
PPM013078 PGS002313
(body_BMIz.BOLT-LMM)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.032 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013127 PGS002313
(body_BMIz.BOLT-LMM)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.06 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013176 PGS002313
(body_BMIz.BOLT-LMM)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.1326 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013225 PGS002313
(body_BMIz.BOLT-LMM)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.082 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013272 PGS002360
(body_BMIz.BOLT-LMM-BBJ)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0005 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013295 PGS002360
(body_BMIz.BOLT-LMM-BBJ)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0397 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013318 PGS002360
(body_BMIz.BOLT-LMM-BBJ)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0056 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013341 PGS002360
(body_BMIz.BOLT-LMM-BBJ)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0109 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013366 PGS002385
(body_BMIz.P+T.0.0001)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0003 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013415 PGS002385
(body_BMIz.P+T.0.0001)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0285 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013464 PGS002385
(body_BMIz.P+T.0.0001)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0584 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013513 PGS002385
(body_BMIz.P+T.0.0001)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0341 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013611 PGS002434
(body_BMIz.P+T.0.001)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0236 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013660 PGS002434
(body_BMIz.P+T.0.001)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0592 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013709 PGS002434
(body_BMIz.P+T.0.001)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0215 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013562 PGS002434
(body_BMIz.P+T.0.001)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0004 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013758 PGS002483
(body_BMIz.P+T.0.01)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0001 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013807 PGS002483
(body_BMIz.P+T.0.01)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.003 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013856 PGS002483
(body_BMIz.P+T.0.01)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0466 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013905 PGS002483
(body_BMIz.P+T.0.01)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0111 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM013954 PGS002532
(body_BMIz.P+T.1e-06)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0092 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014003 PGS002532
(body_BMIz.P+T.1e-06)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0149 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014052 PGS002532
(body_BMIz.P+T.1e-06)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0401 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014101 PGS002532
(body_BMIz.P+T.1e-06)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0269 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014199 PGS002581
(body_BMIz.P+T.5e-08)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0084 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014150 PGS002581
(body_BMIz.P+T.5e-08)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0077 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014248 PGS002581
(body_BMIz.P+T.5e-08)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0323 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014297 PGS002581
(body_BMIz.P+T.5e-08)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0229 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014346 PGS002630
(body_BMIz.PolyFun-pred)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0345 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs See body_BMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014395 PGS002630
(body_BMIz.PolyFun-pred)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0624 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs See body_BMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014444 PGS002630
(body_BMIz.PolyFun-pred)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1307 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs See body_BMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014493 PGS002630
(body_BMIz.PolyFun-pred)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0832 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs See body_BMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014591 PGS002679
(body_BMIz.SBayesR)
PSS009696|
East Asian Ancestry|
916 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0587 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014542 PGS002679
(body_BMIz.SBayesR)
PSS009695|
African Ancestry|
6,399 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0317 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014640 PGS002679
(body_BMIz.SBayesR)
PSS009697|
European Ancestry|
43,328 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.1271 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs
PPM014689 PGS002679
(body_BMIz.SBayesR)
PSS009698|
South Asian Ancestry|
7,911 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: BMI Incremental R2 (full model vs. covariates alone): 0.0823 age, sex, age‚age*sex, assessment center, genotyping array, 10 PCs

Evaluated Samples

PGS Sample Set ID
(PSS)
Phenotype Definitions and Methods Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
PSS000991 Cases were individuals defined as obese (BMI ≥ 30kg/m2)
[
  • 39 cases
  • , 102 controls
]
,
48.23 % Male samples
European
(French-Canadian)
FAS
PSS000992 Cases were individuals defined as obese (BMI ≥ 30kg/m2)
[
  • 50 cases
  • , 127 controls
]
,
43.5 % Male samples
European
(French-Canadian)
QFS
PSS008177 6,331 individuals South Asian India (South Asia) UKB
PSS000411 59 MC4R mutations that had previously been reported to play a role in obesity were included in our analyses (Table S2) All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2).
[
  • 76 cases
  • , 28 controls
]
European UKB
PSS000412 59 MC4R mutations that had previously been reported to play a role in obesity were included in our analyses (Table S2) All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2).
[
  • 109,216 cases
  • , 147,554 controls
]
European UKB
PSS000413 All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2). 206,612 individuals,
100.0 % Male samples
Mean = 57.0 years
Sd = 8.1 years
European UKB
PSS000413 All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2). 244,896 individuals,
0.0 % Male samples
Mean = 57.0 years
Sd = 7.9 years
European UKB
PSS009203 4,124 individuals European Poland (NE Europe) UKB
PSS008757 6,622 individuals European Italy (South Europe) UKB
PSS007744 2,484 individuals African American or Afro-Caribbean Carribean UKB
PSS000037 288,016 individuals,
45.0 % Male samples
European UKB
PSS009295 20,000 individuals European UK (+ Ireland) UKB
PSS000045 BMI difference between ages 21 and 45 1,699 individuals,
100.0 % Male samples
European HPFS
PSS000046 BMI difference between ages 45 and 65 1,634 individuals,
100.0 % Male samples
European HPFS
PSS000047 BMI difference between ages 65 and 80 2,020 individuals,
100.0 % Male samples
European HPFS
PSS000048 BMI difference between ages 18 and 45 5,956 individuals,
0.0 % Male samples
European NHS
PSS000049 BMI difference between age 18 and Menopause 6,705 individuals,
0.0 % Male samples
European NHS
PSS000050 BMI difference between ages 45 and 65 5,640 individuals,
0.0 % Male samples
European NHS
PSS000051 BMI difference between ages 65 and 80 2,942 individuals,
0.0 % Male samples
European NHS
PSS000052 BMI difference between Menopause and age 65 6,436 individuals,
0.0 % Male samples
European NHS
PSS000847 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 3,997 individuals Mean = 17.8 years European ALSPAC ALSPAC offspring
PSS000848 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 2,199 individuals,
0.0 % Male samples
Mean = 50.8 years European ALSPAC ALSPAC mothers
PSS000849 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 5,898 individuals Mean = 9.9 years European ALSPAC ALSPAC offspring
PSS008309 6,145 individuals South Asian India (South Asia) UKB
PSS008848 3,924 individuals African unspecified Nigeria (West Africa) UKB
PSS000875 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 37 cases
  • , 3,087 controls
]
European HUNT
PSS000876 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 344 cases
  • , 2,780 controls
]
European HUNT
PSS000877 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 30 cases
  • , 2,866 controls
]
European HUNT
PSS000878 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 274 cases
  • , 2,622 controls
]
European HUNT
PSS004911 6,398 individuals African unspecified UKB
PSS004912 1,696 individuals East Asian UKB
PSS004913 24,795 individuals European non-white British ancestry UKB
PSS004914 7,639 individuals South Asian UKB
PSS004915 67,235 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS000879 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 542 cases
  • , 11,637 controls
]
European HUNT
PSS000880 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 2,898 cases
  • , 9,281 controls
]
European HUNT
PSS000881 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 1,240 cases
  • , 15,899 controls
]
European HUNT
PSS000882 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 5,775 cases
  • , 11,364 controls
]
European HUNT
PSS000883 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 15,112 cases
  • , 47,429 controls
]
European HUNT
PSS000884 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 43,408 cases
  • , 19,133 controls
]
European HUNT
PSS000885 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 19,588 cases
]
,
100.0 % Male samples
Mean = 42.4 years
Sd = 12.6 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000886 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 21,499 cases
]
,
0.0 % Male samples
Mean = 42.6 years
Sd = 12.8 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000892 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 17,740 cases
]
,
0.0 % Male samples
Mean = 58.9 years
Sd = 11.9 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000887 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 26,336 cases
]
,
100.0 % Male samples
Mean = 47.6 years
Sd = 16.1 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000888 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 29,545 cases
]
,
0.0 % Male samples
Mean = 47.1 years
Sd = 16.5 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000889 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 21,192 cases
]
,
100.0 % Male samples
Mean = 52.3 years
Sd = 14.5 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000890 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 25,108 cases
]
,
0.0 % Male samples
Mean = 51.2 years
Sd = 15.0 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS000891 Body mass index (BMI) measurements were standardized with weight measured to the nearest half kilogram with the participants wearing light clothes and no shoes, and height was measured to the nearest centimeter. BMI was calculated using the formula weight in kilograms per meter squared. As defined by the World Health Organization (WHO), the authors rrefer to overweight as having BMI greater than or equal to 25 and obesity as having BMI greater than or equal to 30. Severe obesity was defined as having BMI greater than or equal to 35.
[
  • 14,487 cases
]
,
100.0 % Male samples
Mean = 60.2 years
Sd = 11.5 years
European HUNT number o cases = number of observations (more than 1 pp)
PSS007873 2,444 individuals African American or Afro-Caribbean Carribean UKB
PSS008398 1,200 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS009429 19,937 individuals European UK (+ Ireland) UKB
PSS000911 13,989 individuals Greater Middle Eastern (Middle Eastern, North African or Persian)
(Qatari)
QBB
PSS008977 3,859 individuals African unspecified Nigeria (West Africa) UKB
PSS009695 6,399 individuals African unspecified UKB
PSS009696 916 individuals East Asian UKB
PSS009697 43,328 individuals European Non-British European UKB
PSS009698 7,911 individuals South Asian UKB
PSS007963 1,810 individuals East Asian China (East Asia) UKB
PSS001425
[
  • 140 cases
  • , 1,517 controls
]
European AGDS
PSS001426
[
  • 367 cases
  • , 2,218 controls
]
European AGDS
PSS001427
[
  • 489 cases
  • , 2,035 controls
]
European AGDS
PSS001428
[
  • 382 cases
  • , 1,613 controls
]
European AGDS
PSS001429
[
  • 712 cases
  • , 3,653 controls
]
European AGDS
PSS001430
[
  • 583 cases
  • , 3,087 controls
]
European AGDS
PSS001431
[
  • 186 cases
  • , 1,801 controls
]
European AGDS
PSS001432
[
  • 236 cases
  • , 1,344 controls
]
European AGDS
PSS001433
[
  • 1,020 cases
  • , 4,699 controls
]
European AGDS
PSS001434
[
  • 794 cases
  • , 3,173 controls
]
European AGDS
PSS008531 1,178 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS001456 5,179 individuals European
(Danish)
Inter99 Independent subset of Inter99, doesn't overlap with score development samples
PSS001083 Of the 2,531 participants, 1,809 had longitudinal observations for total cholesterol (mg/dL), high density lipoprotein cholesterol (mg/dL) and trigycerides (mg/dL), 1,801 had longitudinal observations for low density lipoprotein cholesterol (mg/dL), 1,325 had longitudinal observations for waist circumference (inches), 2,355 had longitudinal observations for body mass index (kg/m^2) and 1,572 had longitudinal observations for homocysteine (μmol/L). 2,531 individuals,
40.0 % Male samples
Mean = 48.0 years
Sd = 12.0 years
European, Asian unspecified, Hispanic or Latin American, African unspecified, NR European = 1,999, Asian unspecified = 228, Hispanic or Latin American = 101, African unspecified = 51, Not reported = 152 NR Participants were obtained from the Scientific Wellness Program.
PSS009069 4,136 individuals European Poland (NE Europe) UKB
PSS000369 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 334 individuals,
69.2 % Male samples
Mean = 11.1 years
Sd = 0.48 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000370 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 329 individuals,
69.2 % Male samples
Mean = 12.81 years
Sd = 0.59 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000371 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 288 individuals,
69.2 % Male samples
Mean = 15.83 years
Sd = 0.6 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000372 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 265 individuals,
69.2 % Male samples
Mean = 19.2 years
Sd = 0.66 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000373 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 245 individuals,
69.2 % Male samples
Mean = 22.04 years
Sd = 0.69 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000374 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,318 individuals,
47.6 % Male samples
Mean = 11.1 years European TRAILS
PSS000375 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,313 individuals,
47.6 % Male samples
Mean = 13.5 years European TRAILS
PSS000376 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,354 individuals,
47.56 % Male samples
Mean = 16.22 years
Sd = 0.66 years
European TRAILS
PSS000377 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,174 individuals,
47.6 % Male samples
Mean = 19.2 years European TRAILS
PSS000378 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,095 individuals,
47.6 % Male samples
Mean = 22.4 years European TRAILS
PSS001084 Moderate Age-Related Diabetes (MARD) vs. controls
[
  • 2,853 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001085 Moderate Obesity-related Diabetes (MOD) vs. controls
[
  • 1,372 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001086 Severe Autoimmune Diabetes (SAID) vs. controls
[
  • 450 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001087 Severe Insulin-Deficient Diabetes (SIDD) vs. controls
[
  • 1,186 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001088 Severe Insulin-Resistant Diabetes (SIRD) vs. controls
[
  • 1,125 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS009565 Clinically measured BMI 33,511 individuals,
46.9 % Male samples
Mean = 60.2 years
Sd = 16.9 years
European MGBB
PSS008086 1,799 individuals East Asian China (East Asia) UKB
PSS008623 6,660 individuals European Italy (South Europe) UKB