Trait: jaw disease

Experimental Factor Ontology (EFO) Information
Identifier EFO_0009468
Description A disease affecting the jaw region, i.e. the part of the head that corresponds to the jaw skeleton, containing soft tissue, skeleton and teeth.
Trait category
Other trait

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
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)
PGS019315
(TPMI_526_Lassosum2)
PGP000835 |
Chen HH et al. Nature (2025)
Diseases of the jaws jaw disease 477,467
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019315/ScoringFiles/PGS019315.txt.gz
PGS019316
(TPMI_526_LDpred2)
PGP000835 |
Chen HH et al. Nature (2025)
Diseases of the jaws jaw disease 939,803
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019316/ScoringFiles/PGS019316.txt.gz
PGS019317
(TPMI_526_MegaPRS)
PGP000835 |
Chen HH et al. Nature (2025)
Diseases of the jaws jaw disease 25,953
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019317/ScoringFiles/PGS019317.txt.gz
PGS019318
(TPMI_526_PRS-CS)
PGP000835 |
Chen HH et al. Nature (2025)
Diseases of the jaws jaw disease 983,750
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019318/ScoringFiles/PGS019318.txt.gz
PGS019319
(TPMI_526_SBayesR)
PGP000835 |
Chen HH et al. Nature (2025)
Diseases of the jaws jaw disease 1,003,540
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019319/ScoringFiles/PGS019319.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
PPM037497 PGS019315
(TPMI_526_Lassosum2)
PSS013223|
East Asian Ancestry|
16,830 individuals
PGP000835 |
Chen HH et al. Nature (2025)
Reported Trait: Diseases of the jaws AUROC: 0.64385 : 0.01103 sex, age, array, PCs 1-10
PPM037498 PGS019316
(TPMI_526_LDpred2)
PSS013222|
East Asian Ancestry|
16,830 individuals
PGP000835 |
Chen HH et al. Nature (2025)
Reported Trait: Diseases of the jaws AUROC: 0.64917 : 0.01152 sex, age, array, PCs 1-10
PPM037499 PGS019317
(TPMI_526_MegaPRS)
PSS013224|
East Asian Ancestry|
16,830 individuals
PGP000835 |
Chen HH et al. Nature (2025)
Reported Trait: Diseases of the jaws AUROC: 0.6412 : 0.01096 sex, age, array, PCs 1-10
PPM037500 PGS019318
(TPMI_526_PRS-CS)
PSS013225|
East Asian Ancestry|
16,830 individuals
PGP000835 |
Chen HH et al. Nature (2025)
Reported Trait: Diseases of the jaws AUROC: 0.64493 : 0.01115 sex, age, array, PCs 1-10
PPM037501 PGS019319
(TPMI_526_SBayesR)
PSS013226|
East Asian Ancestry|
16,830 individuals
PGP000835 |
Chen HH et al. Nature (2025)
Reported Trait: Diseases of the jaws AUROC: 0.64695 : 0.01142 sex, age, array, PCs 1-10

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
PSS013222 524.0, 524.1, 524.51, 524.6, 526, 784.92,K09.0, K09.1, M26.0, M26.1, M26.51, M26.6, M27.0, M27.1, M27.2, M27.3, M27.4, M27.5, M27.8, M27.9, R68.84
[
  • 208 cases
  • , 16,622 controls
]
,
45.47 % Male samples
East Asian
(Han Chinese)
TPMI
PSS013223 524.0, 524.1, 524.51, 524.6, 526, 784.92,K09.0, K09.1, M26.0, M26.1, M26.51, M26.6, M27.0, M27.1, M27.2, M27.3, M27.4, M27.5, M27.8, M27.9, R68.84
[
  • 208 cases
  • , 16,622 controls
]
,
45.47 % Male samples
East Asian
(Han Chinese)
TPMI
PSS013224 524.0, 524.1, 524.51, 524.6, 526, 784.92,K09.0, K09.1, M26.0, M26.1, M26.51, M26.6, M27.0, M27.1, M27.2, M27.3, M27.4, M27.5, M27.8, M27.9, R68.84
[
  • 208 cases
  • , 16,622 controls
]
,
45.47 % Male samples
East Asian
(Han Chinese)
TPMI
PSS013225 524.0, 524.1, 524.51, 524.6, 526, 784.92,K09.0, K09.1, M26.0, M26.1, M26.51, M26.6, M27.0, M27.1, M27.2, M27.3, M27.4, M27.5, M27.8, M27.9, R68.84
[
  • 208 cases
  • , 16,622 controls
]
,
45.47 % Male samples
East Asian
(Han Chinese)
TPMI
PSS013226 524.0, 524.1, 524.51, 524.6, 526, 784.92,K09.0, K09.1, M26.0, M26.1, M26.51, M26.6, M27.0, M27.1, M27.2, M27.3, M27.4, M27.5, M27.8, M27.9, R68.84
[
  • 208 cases
  • , 16,622 controls
]
,
45.47 % Male samples
East Asian
(Han Chinese)
TPMI