Trait: mineral metabolism disease

Trait Information
Identifier MONDO_0000226
Trait categories
Metabolic disorder
Other disease
Synonyms 2 synonyms
  • disease of mineral metabolism
  • disorder of mineral metabolism
Child trait(s) iron metabolism disease

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 "mineral metabolism disease" 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
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS001023
(GBE_HC703)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Disorders of mineral metabolism (time-to-event) mineral metabolism disease 2
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001023/ScoringFiles/PGS001023.txt.gz
PGS001823
(portability-PLR_275.1)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Disorders of iron metabolism iron metabolism disease 654
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001823/ScoringFiles/PGS001823.txt.gz
PGS002031
(portability-ldpred2_275.1)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Disorders of iron metabolism iron metabolism disease 6,713
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002031/ScoringFiles/PGS002031.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
PPM007878 PGS001023
(GBE_HC703)
 PSS004605|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.70572 [0.64003, 0.77141] R²: 0.04772
Incremental AUROC (full-covars): -0.00243
PGS R2 (no covariates): 0.00257
PGS AUROC (no covariates): 0.49279 [0.49133, 0.49424]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007879 PGS001023
(GBE_HC703)
 PSS004606|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.72332 [0.56417, 0.88247] Incremental AUROC (full-covars): 0.0
R²: 0.06686
PGS R2 (no covariates): 0.00038
PGS AUROC (no covariates): 0.49882 [0.49767, 0.49998]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007880 PGS001023
(GBE_HC703)
 PSS004607|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.70459 [0.66766, 0.74152] R²: 0.07164
Incremental AUROC (full-covars): 0.05404
PGS R2 (no covariates): 0.07064
PGS AUROC (no covariates): 0.63902 [0.6046, 0.67344]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007881 PGS001023
(GBE_HC703)
 PSS004608|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.60481 [0.54255, 0.66706] R²: 0.01967
Incremental AUROC (full-covars): -0.00045
PGS R2 (no covariates): 0.00194
PGS AUROC (no covariates): 0.50905 [0.4878, 0.5303]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007882 PGS001023
(GBE_HC703)
 PSS004609|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.65351 [0.63175, 0.67527] R²: 0.03407
Incremental AUROC (full-covars): 0.05096
PGS R2 (no covariates): 0.02793
PGS AUROC (no covariates): 0.57843 [0.55918, 0.59767]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009484 PGS001823
(portability-PLR_275.1)
 PSS009293|
European Ancestry|
19,883 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.1307 [0.117, 0.1444] sex, age, birth date, deprivation index, 16 PCs —
PPM009485 PGS001823
(portability-PLR_275.1)
 PSS009067|
European Ancestry|
4,105 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.109 [0.0786, 0.1392] sex, age, birth date, deprivation index, 16 PCs —
PPM009486 PGS001823
(portability-PLR_275.1)
 PSS008621|
European Ancestry|
6,637 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.0178 [-0.0063, 0.0419] sex, age, birth date, deprivation index, 16 PCs —
PPM009487 PGS001823
(portability-PLR_275.1)
 PSS008175|
South Asian Ancestry|
6,298 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.0003 [-0.0244, 0.025] sex, age, birth date, deprivation index, 16 PCs —
PPM009489 PGS001823
(portability-PLR_275.1)
 PSS008846|
African Ancestry|
3,903 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.0193 [-0.0121, 0.0507] sex, age, birth date, deprivation index, 16 PCs —
PPM009488 PGS001823
(portability-PLR_275.1)
 PSS007962|
East Asian Ancestry|
1,809 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.0117 [-0.0346, 0.058] sex, age, birth date, deprivation index, 16 PCs —
PPM011122 PGS002031
(portability-ldpred2_275.1)
 PSS009293|
European Ancestry|
19,883 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.1355 [0.1219, 0.1492] sex, age, birth date, deprivation index, 16 PCs —
PPM011123 PGS002031
(portability-ldpred2_275.1)
 PSS009067|
European Ancestry|
4,105 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.1073 [0.0769, 0.1375] sex, age, birth date, deprivation index, 16 PCs —
PPM011124 PGS002031
(portability-ldpred2_275.1)
 PSS008621|
European Ancestry|
6,637 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): 0.0173 [-0.0068, 0.0414] sex, age, birth date, deprivation index, 16 PCs —
PPM011125 PGS002031
(portability-ldpred2_275.1)
 PSS008175|
South Asian Ancestry|
6,298 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): -0.0027 [-0.0274, 0.0221] sex, age, birth date, deprivation index, 16 PCs —
PPM011127 PGS002031
(portability-ldpred2_275.1)
 PSS008846|
African Ancestry|
3,903 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): -0.0075 [-0.039, 0.0239] sex, age, birth date, deprivation index, 16 PCs —
PPM011126 PGS002031
(portability-ldpred2_275.1)
 PSS007962|
East Asian Ancestry|
1,809 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Disorders of iron metabolism — — Partial Correlation (partial-r): -0.008 [-0.0543, 0.0384] sex, age, birth date, deprivation index, 16 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
PSS004605 — —
[
  • 49 cases
  • , 6,448 controls
]
 — African unspecified — UKB —
PSS004606 — —
[
  • 8 cases
  • , 1,696 controls
]
 — East Asian — UKB —
PSS004607 — —
[
  • 225 cases
  • , 24,680 controls
]
 — European non-white British ancestry UKB —
PSS004608 — —
[
  • 65 cases
  • , 7,766 controls
]
 — South Asian — UKB —
PSS004609 — —
[
  • 613 cases
  • , 66,812 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS009067 — — 4,105 individuals — European Poland (NE Europe) UKB —
PSS009293 — — 19,883 individuals — European UK (+ Ireland) UKB —
PSS008621 — — 6,637 individuals — European Italy (South Europe) UKB —
PSS008175 — — 6,298 individuals — South Asian India (South Asia) UKB —
PSS008846 — — 3,903 individuals — African unspecified Nigeria (West Africa) UKB —
PSS007962 — — 1,809 individuals — East Asian China (East Asia) UKB —