PGS Publication: PGP000724

Publication Information (EuropePMC)
Title Polygenic prediction of body mass index and obesity through the life course and across ancestries.
PubMed ID 40691366(Europe PMC)
doi 10.1038/s41591-025-03827-z
Publication Date July 21, 2025
Journal Nat Med
Author(s) Smit RAJ, Wade KH, Hui Q, Arias JD, Yin X, Christiansen MR, Yengo L, Preuss MH, Nakabuye M, Rocheleau G, Graham SE, Buchanan VL, Chittoor G, Graff M, Guindo-Martínez M, Lu Y, Marouli E, Sakaue S, Spracklen CN, Vedantam S, Wilson EP, Chen SH, Ferreira T, Ji Y, Karaderi T, Lüll K, Machado M, Malden DE, Medina-Gomez C, Moore A, Rüeger S, Akiyama M, Allison MA, Alvarez M, Andersen MK, Appadurai V, Arbeeva L, Bartell E, Bhaskar S, Bielak LF, Bis JC, Bollepalli S, Bork-Jensen J, Bradfield JP, Bradford Y, Brandl C, Braund PS, Brody JA, Broeckel U, Burgdorf KS, Cade BE, Cai Q, Camarda S, Campbell A, Cañadas-Garre M, Chai JF, Chesi A, Choi SH, Christofidou P, Couture C, Cuellar-Partida G, Danning R, Degenhardt F, Delgado GE, Delitala A, Demirkan A, Deng X, Dietl A, Dimitriou M, Dimitrov L, Dorajoo R, Eichelmann F, Eliasen AU, Engmann JE, Erdos MR, Fairhurst-Hunter Z, Farmaki AE, Faul JD, Fernandez-Lopez JC, Forer L, Frank M, Freitag-Wolf S, Fritsche LG, Fuchsberger C, Galesloot TE, Gao Y, Geller F, Giannakopoulou O, Giulianini F, Gjesing AP, Goel A, Gordon SD, Gorski M, Grove J, Guo X, Gustafsson S, Haessler J, Hansen TF, Havulinna AS, Haworth SJ, Heard-Costa N, Hemerich D, Highland HM, Hindy G, Ho YL, Hofer E, Holliday E, Horn K, Hornsby WE, Hottenga JJ, Huang H, Huang J, Huerta-Chagoya A, Huo S, Hwang MY, Hwu CM, Iha H, Ikeda DD, Isono M, Jackson AU, Jansen IE, Jiang Y, Johansson I, Jonsson A, Jørgensen T, Kalafati IP, Kanai M, Kanoni S, Kårhus LL, Kasturiratne A, Katsuya T, Kawaguchi T, Kember RL, Kentistou KA, Kim D, Kim HN, Kim YJ, Kleber ME, Knol MJ, Kurbasic A, Lauzon M, Le P, Lea R, Lee JY, Lee WJ, Leonard HL, Li H, Li SA, Li X, Li X, Liang J, Lin H, Lin K, Liu J, Liu X, Lo KS, Long J, Lores-Motta L, Luan J, Lyssenko V, Lyytikäinen LP, Mahajan A, Malik MZ, Mamakou V, Mangino M, Manichaikul A, Marten J, Mattheisen M, McDaid AF, Mei Q, Meiselbach H, Melendez TL, Milaneschi Y, Miller JE, Millwood IY, Mishra PP, Mitchell RE, Møllehave LT, Mononen N, Mucha S, Munz M, Mykkänen J, Nakatochi M, Nardone GG, Nelson CP, Nethander M, Nho CW, Nielsen AA, Nolte IM, Nongmaithem SS, Noordam R, Ntalla I, Nutile T, Pandit A, Pauper M, Petersen ERB, Petersen LV, Piluso F, Polašek O, Poveda A, Pyarajan S, Raffield LM, Rakugi H, Ramirez J, Rasheed A, Raven D, Rayner NW, Riveros C, Rohde R, Ruggiero D, Ruotsalainen SE, Ryan KA, Sabater-Lleal M, Santin A, Saxena R, Scholz M, Shen B, Shi J, Shin JH, Sidore C, Sidorenko J, Sim X, Slieker RC, Smith AV, Smith JA, Smyth LJ, Southam L, Steinthorsdottir V, Sun L, Takeuchi F, Taylor KD, Tayo BO, Tcheandjieu C, Terzikhan N, Tesolin P, Teumer A, Theusch E, Thompson DJ, Thorleifsson G, Timmers PRHJ, Trompet S, Turman C, Vaccargiu S, van der Laan SW, van der Most PJ, van Klinken JB, van Setten J, Verma SS, Verweij N, Veturi Y, Wang CA, Wang C, Wang JS, Wang L, Wang YX, Wang Z, Warren HR, Bin Wei W, Wen W, Wheeler WA, Wickremasinghe AR, Wielscher M, Winsvold BS, Wong A, Wuttke M, Xia R, Yamamoto K, Yang J, Yao J, Young H, Yousri NA, Yu L, Zeng L, Zhang W, Zhang X, Zhao JH, Zhao W, Zhou W, Zimmermann ME, Zoledziewska M, 't Hart LM, Adair LS, Adams HHH, Aguilar-Salinas CA, Al-Mulla F, Arnett DK, Asselbergs FW, Åsvold BO, Attia J, Banas B, Bandinelli S, Beilin LJ, Bennett DA, Bergler T, Bharadwaj D, Biino G, Boerwinkle E, Böger CA, Borja JB, Bouchard C, Bowden DW, Brandslund I, Brumpton B, Buring JE, Caulfield MJ, Chambers JC, Chandak GR, Chanock SJ, Chaturvedi N, Ida Chen YD, Chen Z, Cheng CY, Cho YS, Christensen K, Christophersen IE, Ciullo M, Cole JW, Collins FS, Concas MP, Cooper RS, Cruz M, Cucca F, Cutler MJ, Damrauer SM, Dantoft TM, de Borst GJ, de Geus EJC, de Groot LCPGM, De Jager PL, de Kleijn DPV, de Silva HJ, Dedoussis GV, den Hollander AI, Du S, Easton DF, Eckardt KU, Elders PJM, Eliassen AH, Ellinor PT, Elmståhl S, Erdmann J, Evans MK, Fatkin D, Feenstra B, Feitosa MF, Ferrucci L, Florez JC, Ford I, Fornage M, Franke A, Franks PW, Freedman BI, Gieger C, Girotto G, Golightly YM, Gonzalez-Villalpando C, Gordon-Larsen P, Grallert H, Grant SFA, Grarup N, Griffiths L, Gudnason V, Haiman C, Hakonarson H, Hansen T, Hartman CA, Hattersley AT, Hayward C, Heid IM, Heng CK, Hengstenberg C, Herzig KH, Hewitt AW, Hishigaki H, Hougaard DM, Hoyng CB, Huang PL, Huang W, Huang WY, Huffman JE, Hunt SC, Hutri N, Hveem K, Hyppönen E, Iacono WG, Ichihara S, Ikram MA, Isasi CR, Jarvelin MR, Jin ZB, Jöckel KH, Jonas JB, Joshi PK, Jousilahti P, Jukema JW, Kähönen M, Kamatani Y, Kang KD, Kaprio J, Kardia SLR, Karpe F, Kato N, Kavousi M, Kee F, Kessler T, Khera AV, Khor CC, Kiemeney LALM, Kim BJ, Kim EK, Kim HL, Kirchhof P, Kivimaki M, Koh WP, Koistinen HA, Kokkinos A, Kooner JS, Kooperberg C, Kovacs P, Kraaijeveld A, Kraft P, Krauss RM, Kumari M, Kutalik Z, Laakso M, Lange LA, Langenberg C, Launer LJ, Lee H, Lee NR, Lehtimäki T, Lemaitre RN, Li H, Li L, Lieb W, Lin X, Lind L, Linneberg A, Liu CT, Liu J, Loeffler M, London B, Lu F, Lubitz SA, Mackey DA, Magnusson PKE, Manson JE, Marcus GM, Marques Vidal P, Martin NG, März W, Matsuda F, McCarthy MI, McGarrah RW, McGue M, McKnight AJ, Medland SE, Mellström D, Metspalu A, Mitchell BD, Mitchell P, Mook-Kanamori DO, Mori TA, Morris AD, Mucci LA, Munroe PB, Nalls MA, Nazarian S, Nelson AE, Neville MJ, Newton-Cheh C, Nielsen CS, Niinikoski H, Nikus K, Nöthen MM, Ogunniyi A, Ohlsson C, Oldehinkel AJ, Orozco L, Pahkala K, Pajukanta P, Palmer CNA, Parra EJ, Pattaro C, Pedersen O, Pennell CE, Penninx BWJH, Perusse L, Peters A, Peyser PA, Porteous DJ, Posthuma D, Power C, Pramstaller PP, Province MA, Psaty BM, Qi Q, Qu J, Rader DJ, Raitakari OT, Rallidis LS, Rao DC, Redline S, Reilly DF, Reiner AP, Rhee SY, Ridker PM, Rienstra M, Ripatti S, Ritchie MD, Rivadeneira F, Roden DM, Rosendaal FR, Rotter JI, Rudan I, Rutters F, Ryu S, Sabanayagam C, Salako B, Saleheen D, Salomaa V, Samani NJ, Sanghera DK, Sattar N, Schmidt B, Schmidt H, Schmidt R, Schulze MB, Schunkert H, Scott LJ, Scott RJ, Sever P, Sheu WHH, Shoemaker MB, Shu XO, Simonsick EM, Sims M, Singleton AB, Sinner MF, Smith JG, Snieder H, Spector TD, Spedicati B, Stampfer MJ, Stark KJ, Strachan DP, Tabara Y, Tai ES, Tang H, Tardif JC, Thanaraj TA, Tönjes A, Tuomi T, Tuomilehto J, Tusié-Luna MT, van Dam RM, van der Harst P, Van der Velde N, van Duijn CM, van Schoor NM, Vitart V, Vohl MC, Völker U, Vollenweider P, Völzke H, Vrieze S, Wacher-Rodarte NH, Walker M, Wander GS, Wareham NJ, Watanabe RM, Watkins H, Weir DR, Werge TM, Widen E, Willemsen G, Willett WC, Wilson JF, Wilson PWF, Wong TY, Woo JT, Wright AF, Xu H, Yajnik CS, Yang J, Yokota M, Yuan JM, Zeggini E, Zemel BS, Zheng W, Zhu X, Zillikens MC, Zonderman AB, Zwart JA, 23andMe Research Team, DiscovEHR (DiscovEHR and MyCode Community Health Initiative), eMERGE (Electronic Medical Records and Genomics Network), GPC-UGR, PRACTICAL Consortium, Understanding Society Scientific Group, VA Million Veteran Program, Abecasis GR, Assimes TL, Auton A, Boehnke M, Chasman DI, Esko T, Stefansson K, Lettre G, Lindgren CM, Ng MCY, O'Donnell CJ, Thorsteinsdottir U, Visscher PM, Walters RG, Winkler TW, Wood AR, Deloukas P, Frayling TM, Justice AE, Kilpeläinen TO, Locke AE, Mohlke KL, North KE, Okada Y, Willer CJ, Young KL, Fatumo S, McCaffery JM, Timpson NJ, Hirschhorn JN, Sun YV, Berndt SI, Loos RJF.
Released in PGS Catalog: July 24, 2025

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

PGS Developed By This Publication

Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS005200
(G23_BMI_2025_PRSCSx_LC_AFR)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,223,921
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005200/ScoringFiles/PGS005200.txt.gz - Check Terms/Licenses
PGS005199
(G23_BMI_2025_PRSCSx_META)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,296,245
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005199/ScoringFiles/PGS005199.txt.gz - Check Terms/Licenses
PGS005202
(G23_BMI_2025_PRSCSx_LC_EAS)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,022,487
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005202/ScoringFiles/PGS005202.txt.gz - Check Terms/Licenses
PGS005203
(G23_BMI_2025_PRSCSx_LC_EUR)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,091,375
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005203/ScoringFiles/PGS005203.txt.gz - Check Terms/Licenses
PGS005204
(G23_BMI_2025_PRSCSx_LC_SAS)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,129,666
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005204/ScoringFiles/PGS005204.txt.gz - Check Terms/Licenses
PGS005201
(G23_BMI_2025_PRSCSx_LC_AMR)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,020,295
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005201/ScoringFiles/PGS005201.txt.gz - Check Terms/Licenses
PGS005198
(GIANT_BMI_2025_PRSCS)
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Body mass index (BMI) body mass index 1,217,710
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005198/ScoringFiles/PGS005198.txt.gz - Check Terms/Licenses

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
PPM022558 PGS005198
(GIANT_BMI_2025_PRSCS)
 PSS012014|
Additional Asian Ancestries|
1,299 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: Obesity class I, or higher (BMI ≥27.5 kg/m2) [Asian specific] OR: 5.73 [2.28, 14.57] — — age, sex, 4 PCs OR [95%CI] is for top 3% of score, adjusting for the covariates
PPM022560 PGS005199
(G23_BMI_2025_PRSCSx_META)
 PSS012017|
Hispanic or Latin American Ancestry|
16,192 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.42 [0.39, 0.44] — R²: 10.8 [9.5, 12.1] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022561 PGS005199
(G23_BMI_2025_PRSCSx_META)
 PSS012019|
European Ancestry|
139,656 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.37 [0.36, 0.37] — R²: 13.2 [12.7, 13.6] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022562 PGS005199
(G23_BMI_2025_PRSCSx_META)
 PSS012018|
Additional Asian Ancestries|
12,603 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.34 [0.31, 0.38] — R²: 8.8 [7.2, 10.5] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022563 PGS005200
(G23_BMI_2025_PRSCSx_LC_AFR)
 PSS012016|
African Ancestry|
37,402 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.3 [0.27, 0.32] — R²: 5.1 [4.5, 5.7] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022564 PGS005201
(G23_BMI_2025_PRSCSx_LC_AMR)
 PSS012017|
Hispanic or Latin American Ancestry|
16,192 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.46 [0.43, 0.49] — R²: 9.9 [8.7, 11.2] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022565 PGS005202
(G23_BMI_2025_PRSCSx_LC_EAS)
 PSS012018|
Additional Asian Ancestries|
12,603 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.36 [0.33, 0.39] — R²: 10.1 [8.6, 11.9] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022566 PGS005203
(G23_BMI_2025_PRSCSx_LC_EUR)
 PSS012019|
European Ancestry|
139,656 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.37 [0.36, 0.37] — R²: 12.9 [12.4, 13.4] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022567 PGS005204
(G23_BMI_2025_PRSCSx_LC_SAS)
 PSS012018|
Additional Asian Ancestries|
12,603 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.34 [0.31, 0.38] — R²: 9.0 [7.4, 10.8] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.
PPM022556 PGS005198
(GIANT_BMI_2025_PRSCS)
 PSS012013|
Hispanic or Latin American Ancestry|
4,710 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: Obesity class I, or higher (BMI ≥30 kg/m2) OR: 2.33 [1.64, 3.31] — — age, sex, 4 PCs OR [95%CI] is for top 3% of score, adjusting for the covariates
PPM022555 PGS005198
(GIANT_BMI_2025_PRSCS)
 PSS012012|
African Ancestry|
3,215 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: Obesity class I, or higher (BMI ≥30 kg/m2) OR: 2.54 [1.55, 3.98] — — age, sex, 4 PCs OR [95%CI] is for top 3% of score, adjusting for the covariates
PPM022557 PGS005198
(GIANT_BMI_2025_PRSCS)
 PSS012015|
European Ancestry|
6,134 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: Obesity class I, or higher (BMI ≥30 kg/m2) OR: 4.08 [3.02, 5.52] — — age, sex, 4 PCs OR [95%CI] is for top 3% of score, adjusting for the covariates
PPM022559 PGS005199
(G23_BMI_2025_PRSCSx_META)
 PSS012016|
African Ancestry|
37,402 individuals
 PGP000724 |
Smit RAJ et al. Nat Med (2025)
 Reported Trait: body mass index (BMI) β: 0.29 [0.27, 0.31] — R²: 5.0 [4.5, 5.7] age, sex, 10 PCs The beta [95%CI] reflects the per-PGS-SD linear regression coefficient with BMI (inverse-normalized by sex), adjusting for the covariates. R2 [95%CI] reflects the adjusted R2, incremental to base model including the covariates.

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
PSS012012 — —
[
  • 1,396 cases
  • , 1,819 controls
]
 — African American or Afro-Caribbean — BioMe —
PSS012013 — —
[
  • 1,821 cases
  • , 2,889 controls
]
 — Hispanic or Latin American — BioMe —
PSS012014 — —
[
  • 282 cases
  • , 1,017 controls
]
 — Asian unspecified — BioMe —
PSS012015 — —
[
  • 1,226 cases
  • , 4,908 controls
]
 — European — BioMe —
PSS012016 — — 18,701 individuals,
84.85 % Male samples
 Mean = 57.0 years
Sd = 12.8 years		 African American or Afro-Caribbean
(non-Hispanic Black)		 — MVP —
PSS012016 — — 18,701 individuals,
84.85 % Male samples
 Mean = 57.0 years
Sd = 12.8 years		 African American or Afro-Caribbean
(non-Hispanic Black)		 — MVP —
PSS012017 — — 8,096 individuals,
89.43 % Male samples
 Mean = 53.0 years
Sd = 16.6 years		 Hispanic or Latin American — MVP —
PSS012017 — — 8,096 individuals,
89.43 % Male samples
 Mean = 53.0 years
Sd = 16.6 years		 Hispanic or Latin American — MVP —
PSS012018 — — 4,201 individuals,
92.6 % Male samples
 Mean = 52.1 years
Sd = 16.9 years		 Asian unspecified — MVP —
PSS012018 — — 4,201 individuals,
92.6 % Male samples
 Mean = 52.1 years
Sd = 16.9 years		 Asian unspecified — MVP —
PSS012018 — — 4,201 individuals,
92.6 % Male samples
 Mean = 52.1 years
Sd = 16.9 years		 Asian unspecified — MVP —
PSS012019 — — 69,828 individuals,
92.25 % Male samples
 Mean = 63.0 years
Sd = 14.2 years		 European — MVP —
PSS012019 — — 69,828 individuals,
92.25 % Male samples
 Mean = 63.0 years
Sd = 14.2 years		 European — MVP —