Trait: salivary gland disorder

Trait Information
Identifier MONDO_0001142
Description A disease involving the saliva-secreting gland.
Trait category
Other trait
Synonyms 8 synonyms
  • disease of saliva-secreting gland
  • disease or disorder of saliva-secreting gland
  • disorder of saliva-secreting gland
  • non-neoplastic salivary gland disease
  • saliva-secreting gland disease
  • saliva-secreting gland disease or disorder
  • salivary gland disease
  • salivary gland disorder
Child trait(s) Sjogren syndrome

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 PGS for child terms of "salivary gland disorder" in the EFO hierarchy.
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)
PGS001308
(GBE_HC321)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Sjogren's syndrome/sicca syndrome Sjogren syndrome 7
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001308/ScoringFiles/PGS001308.txt.gz
PGS019645
(TPMI_709.2_Lassosum2)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 1,224
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019645/ScoringFiles/PGS019645.txt.gz
PGS019646
(TPMI_709.2_LDpred2)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 939,810
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019646/ScoringFiles/PGS019646.txt.gz
PGS019647
(TPMI_709.2_MegaPRS)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 49,185
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019647/ScoringFiles/PGS019647.txt.gz
PGS019648
(TPMI_709.2_PRS-CS)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 983,765
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019648/ScoringFiles/PGS019648.txt.gz
PGS019649
(TPMI_709.2_PRSmix+)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 1,071,405
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019649/ScoringFiles/PGS019649.txt.gz
PGS019650
(TPMI_709.2_SBayesR)
 PGP000835 |
Chen HH et al. Nature (2025)
 Sicca syndrome Sjogren syndrome 202,225
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019650/ScoringFiles/PGS019650.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
PPM009034 PGS001308
(GBE_HC321)
 PSS004437|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Sjogren's syndrome/sicca syndrome — AUROC: 0.79846 [0.71474, 0.88218] R²: 0.07345
Incremental AUROC (full-covars): 0.0079
PGS R2 (no covariates): 0.01471
PGS AUROC (no covariates): 0.59027 [0.45551, 0.72504]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009035 PGS001308
(GBE_HC321)
 PSS004438|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Sjogren's syndrome/sicca syndrome — AUROC: 0.75824 [0.55089, 0.96558] R²: 0.05686
Incremental AUROC (full-covars): 0.00691
PGS R2 (no covariates): 0.0091
PGS AUROC (no covariates): 0.69794 [0.63241, 0.76347]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009036 PGS001308
(GBE_HC321)
 PSS004439|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Sjogren's syndrome/sicca syndrome — AUROC: 0.77174 [0.71988, 0.82361] R²: 0.07435
Incremental AUROC (full-covars): 0.01461
PGS R2 (no covariates): 0.01453
PGS AUROC (no covariates): 0.65693 [0.58901, 0.72485]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009037 PGS001308
(GBE_HC321)
 PSS004440|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Sjogren's syndrome/sicca syndrome — AUROC: 0.8014 [0.74455, 0.85826] R²: 0.08893
Incremental AUROC (full-covars): 0.00953
PGS R2 (no covariates): 0.03189
PGS AUROC (no covariates): 0.61034 [0.48809, 0.73259]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009038 PGS001308
(GBE_HC321)
 PSS004441|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Sjogren's syndrome/sicca syndrome — AUROC: 0.73313 [0.69647, 0.76978] R²: 0.04771
Incremental AUROC (full-covars): 0.01551
PGS R2 (no covariates): 0.01074
PGS AUROC (no covariates): 0.60303 [0.55292, 0.65315]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM037827 PGS019645
(TPMI_709.2_Lassosum2)
 PSS013542|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.77927 R²: 0.24978 sex, age, array, PCs 1-10 —
PPM037828 PGS019646
(TPMI_709.2_LDpred2)
 PSS013541|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.78396 R²: 0.25747 sex, age, array, PCs 1-10 —
PPM037829 PGS019647
(TPMI_709.2_MegaPRS)
 PSS013543|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.77815 R²: 0.24514 sex, age, array, PCs 1-10 —
PPM037830 PGS019648
(TPMI_709.2_PRS-CS)
 PSS013544|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.78347 R²: 0.25531 sex, age, array, PCs 1-10 —
PPM037831 PGS019649
(TPMI_709.2_PRSmix+)
 PSS013545|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.78759 R²: 0.26384 sex, age, array, PCs 1-10 —
PPM037832 PGS019650
(TPMI_709.2_SBayesR)
 PSS013546|
East Asian Ancestry|
18,012 individuals
 PGP000835 |
Chen HH et al. Nature (2025)
 Reported Trait: Sicca syndrome — AUROC: 0.77877 R²: 0.2473 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
PSS013541 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS013542 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS013543 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS013544 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS013545 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS013546 710.2,M35.0 —
[
  • 1,032 cases
  • , 16,980 controls
]
,
46.5 % Male samples
 — East Asian
(Han Chinese)		 — TPMI —
PSS004437 — —
[
  • 17 cases
  • , 6,480 controls
]
 — African unspecified — UKB —
PSS004438 — —
[
  • 4 cases
  • , 1,700 controls
]
 — East Asian — UKB —
PSS004439 — —
[
  • 58 cases
  • , 24,847 controls
]
 — European non-white British ancestry UKB —
PSS004440 — —
[
  • 29 cases
  • , 7,802 controls
]
 — South Asian — UKB —
PSS004441 — —
[
  • 135 cases
  • , 67,290 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)