PGS Publication: PGP000202

Publication Information (EuropePMC)
Title Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study.
PubMed ID 34082474(Europe PMC)
doi 10.1002/gepi.22389
Publication Date June 3, 2021
Journal Genet Epidemiol
Author(s) Bauer A, Zierer A, Gieger C, Büyüközkan M, Müller-Nurasyid M, Grallert H, Meisinger C, Strauch K, Prokisch H, Roden M, Peters A, Krumsiek J, Herder C, Koenig W, Thorand B, Huth C.
Released in PGS Catalog: July 29, 2021

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:
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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 Scoring File (FTP Link)
PGS000818
(GRS_Metabo)
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
Coronary heart disease coronary artery disease 138
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000818/ScoringFiles/PGS000818.txt.gz

External PGS Evaluated By This Publication

Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000013
(GPS_CAD)
PGP000006 |
Khera AV et al. Nat Genet (2018)
Coronary artery disease coronary artery disease 6,630,150
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000013/ScoringFiles/PGS000013.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
PPM002180 PGS000818
(GRS_Metabo)
PSS001064|
European Ancestry|
1,939 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
Reported Trait: Incident coronary heart disease HR: 1.2341 [1.1137, 1.3676]
PPM002181 PGS000818
(GRS_Metabo)
PSS001064|
European Ancestry|
1,939 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
Reported Trait: Incident coronary heart disease HR: 1.2126 [1.0766, 1.3659] Age, sex, survey
PPM002182 PGS000013
(GPS_CAD)
PSS001063|
European Ancestry|
2,909 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
|Ext.
Reported Trait: Incident coronary heart disease C-index: 0.573 [0.5254, 0.6212] Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3
PPM002178 PGS000818
(GRS_Metabo)
PSS001063|
European Ancestry|
2,909 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
Reported Trait: Incident coronary heart disease C-index: 0.7571 [0.7234, 0.7908] Age, sex, survey
PPM002179 PGS000818
(GRS_Metabo)
PSS001063|
European Ancestry|
2,909 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
Reported Trait: Incident coronary heart disease C-index: 0.792 [0.7622, 0.8219] Age, sex, survey, Framingham risk score (diabetes status, current and former smoking status, systolic blood pressure, antihypertensive medication, HDL cholesterol, total cholesterol)
PPM002183 PGS000013
(GPS_CAD)
PSS001063|
European Ancestry|
2,909 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
|Ext.
Reported Trait: Incident coronary heart disease C-index: 0.7752 [0.7443, 0.8029] Age, sex, survey Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3
PPM002184 PGS000013
(GPS_CAD)
PSS001063|
European Ancestry|
2,909 individuals
PGP000202 |
Bauer A et al. Genet Epidemiol (2021)
|Ext.
Reported Trait: Incident coronary heart disease C-index: 0.8012 [0.7775, 0.8353] Age, sex, survey, Framingham risk score (diabetes status, current and former smoking status, systolic blood pressure, antihypertensive medication, HDL cholesterol, total cholesterol) Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3

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
PSS001064 Cases were individuals with incident coronary heart disesase (CHD). The outcome CHD was a combined endpoint of nonfatal myocardial infarction as well as coronary death and sudden death (International Classification of Disease 9th Revision: 410–414 and 798). Until December 2000, the diagnosis of a major, nonfatal myocardial infarction and coronary death was based on the MONICA algorithm in which a diagnosis of a major CHD event was based on symptoms, cardiac enzymes (creatine kinase, aspartate aminotransferase, and lactate dehydrogenase), serial changes from 12‐lead electrocardiograms (ECGs) evaluated by Minnesota coding, necropsy results and history of CHD in fatal cases. Since January 1, 2001, the diagnosis of myocardial infarction was based on the European Society of Cardiology and American College of Cardiology criteria. Incident events were identified through follow‐up questionnaires or through the MONICA/KORA myocardial infarction registry, which monitors the occurrence of all in‐ and out of‐hospital fatal and nonfatal myocardial infarctions among the 25–74‐year‐old inhabitants of the study region. Initially identified self‐reported incident cases and the self‐reported date of diagnosis not covered by the MONICA/KORA myocardial infarction registry, were validated by hospital records or by contacting the patient's treating physician. Deaths from myocardial in- farction were validated by death certificates, autopsy reports, chart reviews, or information from the last treating physician. Median = 14.0 years
Iqr = [10.3, 14.0] years
[
  • 451 cases
  • , 1,488 controls
]
,
53.06 % Male samples
European KORA
PSS001063 Cases were individuals with incident coronary heart disesase (CHD). The outcome CHD was a combined endpoint of nonfatal myocardial infarction as well as coronary death and sudden death (International Classification of Disease 9th Revision: 410–414 and 798). Until December 2000, the diagnosis of a major, nonfatal myocardial infarction and coronary death was based on the MONICA algorithm in which a diagnosis of a major CHD event was based on symptoms, cardiac enzymes (creatine kinase, aspartate aminotransferase, and lactate dehydrogenase), serial changes from 12‐lead electrocardiograms (ECGs) evaluated by Minnesota coding, necropsy results and history of CHD in fatal cases. Since January 1, 2001, the diagnosis of myocardial infarction was based on the European Society of Cardiology and American College of Cardiology criteria. Incident events were identified through follow‐up questionnaires or through the MONICA/KORA myocardial infarction registry, which monitors the occurrence of all in‐ and out of‐hospital fatal and nonfatal myocardial infarctions among the 25–74‐year‐old inhabitants of the study region. Initially identified self‐reported incident cases and the self‐reported date of diagnosis not covered by the MONICA/KORA myocardial infarction registry, were validated by hospital records or by contacting the patient's treating physician. Deaths from myocardial in- farction were validated by death certificates, autopsy reports, chart reviews, or information from the last treating physician. Median = 14.0 years
Iqr = [14.0, 14.0] years
[
  • 160 cases
  • , 2,749 controls
]
,
48.1 % Male samples
European KORA S4