Trait: PR interval

Experimental Factor Ontology (EFO) Information
Identifier EFO_0004462
Description A PR interval is an electrocardiography measurement which measures from the beginning of the P wave to the beginning of the QRS complex in the heart's electrical cycle
Trait category
Cardiovascular measurement
Synonym PQ interval
Mapped terms 2 mapped terms
  • NCIt:C83502
  • https://biobank.ndph.ox.ac.uk/showcase/field.cgi?id=22330

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 Scoring File (FTP Link)
PGS000735
(PRS_PR)
PGP000144 |
Tadros R et al. Eur Heart J (2019)
PR interval PR interval 44
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000735/ScoringFiles/PGS000735.txt.gz
PGS000904
(PRS582_PR)
PGP000236 |
Ntalla I et al. Nat Commun (2020)
PR interval PR interval 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000904/ScoringFiles/PGS000904.txt.gz
PGS000905
(PRS743_PR)
PGP000236 |
Ntalla I et al. Nat Commun (2020)
PR interval PR interval 743
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000905/ScoringFiles/PGS000905.txt.gz
PGS001521
(GBE_INI22330)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
PQ interval PR interval 391
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001521/ScoringFiles/PGS001521.txt.gz
PGS001904
(portability-PLR_ECG_PQ_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PQ interval PR interval 826
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001904/ScoringFiles/PGS001904.txt.gz
PGS002118
(portability-ldpred2_ECG_PQ_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PQ interval PR interval 413,539
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002118/ScoringFiles/PGS002118.txt.gz
PGS003499
(cont-decay-ECG_PQ_interval)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
PQ interval PR interval 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003499/ScoringFiles/PGS003499.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
PPM001759 PGS000735
(PRS_PR)
PSS000905|
European Ancestry|
1,185 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Ajmaline-induced Type I Brugada syndrome electrocardiogram OR: 1.017 [1.013, 1.022]
PPM001754 PGS000735
(PRS_PR)
PSS000904|
European Ancestry|
1,257 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: PR slope β: 0.22 (0.08)
PPM001750 PGS000735
(PRS_PR)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Baseline PR in non SCN5A mutation carriers Correlation coefficent (r): 0.23
PPM001752 PGS000735
(PRS_PR)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: PR slope in non SCN5A mutation carriers β: 0.16 (0.08) Correlation coefficient (r): 0.09
PPM002666 PGS000904
(PRS582_PR)
PSS001175|
European Ancestry|
309,269 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrial fibrillation OR: 0.95
β: -0.047 (0.009)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002667 PGS000904
(PRS582_PR)
PSS001178|
European Ancestry|
290,252 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Distal conduction disease OR: 1.11
β: 0.103 (0.019)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002668 PGS000904
(PRS582_PR)
PSS001176|
European Ancestry|
309,041 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrioventricular preexcitation OR: 0.85
β: -0.168 (0.057)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002669 PGS000904
(PRS582_PR)
PSS001179|
European Ancestry|
309,241 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Implantable cardioverter defibrillator OR: 1.09
β: 0.086 (0.04)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002670 PGS000904
(PRS582_PR)
PSS001180|
European Ancestry|
309,246 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Mitral valve prolapse OR: 1.1
β: 0.093 (0.044)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002671 PGS000904
(PRS582_PR)
PSS001181|
European Ancestry|
305,471 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Non-ischemic cardiomyopathy OR: 0.95
β: -0.051 (0.024)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002672 PGS000904
(PRS582_PR)
PSS001182|
European Ancestry|
309,270 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Pacemaker OR: 1.06
β: 0.062 (0.016)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002673 PGS000904
(PRS582_PR)
PSS001183|
European Ancestry|
309,255 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Valve disease OR: 1.03
β: 0.03 (0.013)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002674 PGS000905
(PRS743_PR)
PSS001175|
European Ancestry|
309,269 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrial fibrillation OR: 0.94
β: -0.058 (0.009)
Baseline age, sex, genotyping array, trait-related principal components
PPM002675 PGS000905
(PRS743_PR)
PSS001178|
European Ancestry|
290,252 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Distal conduction disease β: 0.105 (0.019)
OR: 1.11
Baseline age, sex, genotyping array, trait-related principal components
PPM002676 PGS000905
(PRS743_PR)
PSS001176|
European Ancestry|
309,041 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrioventricular preexcitation OR: 0.83
β: -0.191 (0.057)
Baseline age, sex, genotyping array, trait-related principal components
PPM002677 PGS000905
(PRS743_PR)
PSS001177|
European Ancestry|
309,246 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Coronary artery disease OR: 0.99
β: -0.014 (0.007)
Baseline age, sex, genotyping array, trait-related principal components
PPM002678 PGS000905
(PRS743_PR)
PSS001182|
European Ancestry|
309,270 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Pacemaker OR: 1.06
β: 0.056 (0.016)
Baseline age, sex, genotyping array, trait-related principal components
PPM005300 PGS001521
(GBE_INI22330)
PSS004966|
African Ancestry|
120 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.14397 [0.12818, 0.15975]
Incremental R2 (full-covars): 0.00024
PGS R2 (no covariates): 0.01367 [0.00807, 0.01928]
age, sex, UKB array type, Genotype PCs
PPM005301 PGS001521
(GBE_INI22330)
PSS004967|
East Asian Ancestry|
68 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.2664 [0.23052, 0.30228]
Incremental R2 (full-covars): -0.00945
PGS R2 (no covariates): 0.00783 [-0.00049, 0.01615]
age, sex, UKB array type, Genotype PCs
PPM005302 PGS001521
(GBE_INI22330)
PSS004968|
European Ancestry|
834 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.10209 [0.09497, 0.10922]
Incremental R2 (full-covars): 0.04534
PGS R2 (no covariates): 0.05149 [0.04615, 0.05684]
age, sex, UKB array type, Genotype PCs
PPM005303 PGS001521
(GBE_INI22330)
PSS004969|
South Asian Ancestry|
193 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.13589 [0.12179, 0.15]
Incremental R2 (full-covars): -0.01928
PGS R2 (no covariates): 0.00031 [-0.00047, 0.00108]
age, sex, UKB array type, Genotype PCs
PPM005304 PGS001521
(GBE_INI22330)
PSS004970|
European Ancestry|
3,353 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.07982 [0.0759, 0.08375]
Incremental R2 (full-covars): 0.02363
PGS R2 (no covariates): 0.02488 [0.02256, 0.0272]
age, sex, UKB array type, Genotype PCs
PPM010115 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS009364|
European Ancestry|
992 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.173 [0.1113, 0.2333] sex, age, birth date, deprivation index, 16 PCs
PPM010116 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS009138|
European Ancestry|
181 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1945 [0.041, 0.3389] sex, age, birth date, deprivation index, 16 PCs
PPM010117 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008692|
European Ancestry|
217 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2467 [0.1108, 0.3736] sex, age, birth date, deprivation index, 16 PCs
PPM010118 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008466|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2876 [-0.7969, 0.9331] sex, age, birth date, deprivation index, 16 PCs
PPM010119 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008246|
South Asian Ancestry|
159 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.09 [-0.0776, 0.2527] sex, age, birth date, deprivation index, 16 PCs
PPM010120 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008024|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.0694 [-0.2047, 0.3335] sex, age, birth date, deprivation index, 16 PCs
PPM010121 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS007810|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.212 [-0.1676, 0.5368] sex, age, birth date, deprivation index, 16 PCs
PPM010122 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008914|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2774 [-0.0331, 0.539] sex, age, birth date, deprivation index, 16 PCs
PPM011801 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008692|
European Ancestry|
217 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2529 [0.1173, 0.3793] sex, age, birth date, deprivation index, 16 PCs
PPM011799 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS009364|
European Ancestry|
992 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1997 [0.1385, 0.2593] sex, age, birth date, deprivation index, 16 PCs
PPM011800 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS009138|
European Ancestry|
181 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2082 [0.0553, 0.3516] sex, age, birth date, deprivation index, 16 PCs
PPM011802 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008466|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1708 [-0.8377, 0.9152] sex, age, birth date, deprivation index, 16 PCs
PPM011803 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008246|
South Asian Ancestry|
159 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.116 [-0.0515, 0.2771] sex, age, birth date, deprivation index, 16 PCs
PPM011804 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008024|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1237 [-0.1517, 0.3812] sex, age, birth date, deprivation index, 16 PCs
PPM011805 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS007810|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1518 [-0.2274, 0.491] sex, age, birth date, deprivation index, 16 PCs
PPM011806 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008914|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1868 [-0.1282, 0.4676] sex, age, birth date, deprivation index, 16 PCs
PPM017427 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010860|
European Ancestry|
995 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017511 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010776|
European Ancestry|
180 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM017595 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010608|
European Ancestry|
213 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017679 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010524|
Greater Middle Eastern Ancestry|
25 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.32 sex, age, deprivation index, PC1-16
PPM017763 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010188|
European Ancestry|
103 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017847 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010440|
South Asian Ancestry|
159 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017931 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010356|
East Asian Ancestry|
73 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM018015 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010272|
African Ancestry|
49 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM018099 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010692|
African Ancestry|
61 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.01 sex, age, deprivation index, PC1-16

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
PSS010272 49 individuals,
31.0 % Male samples
Mean = 48.8 years
Sd = 6.4 years
African American or Afro-Caribbean Caribbean UKB
PSS008914 61 individuals African unspecified Nigeria (West Africa) UKB
PSS000904 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.12 1,257 individuals European Amsterdam
PSS000905 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.15 1,185 individuals European Amsterdam
PSS000906 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.13 1,193 individuals European Amsterdam
PSS008024 73 individuals East Asian China (East Asia) UKB
PSS010692 61 individuals,
64.0 % Male samples
Mean = 49.5 years
Sd = 6.5 years
African unspecified Nigerian UKB
PSS004966 120 individuals African unspecified UKB
PSS004967 68 individuals East Asian UKB
PSS004968 834 individuals European non-white British ancestry UKB
PSS004969 193 individuals South Asian UKB
PSS004970 3,353 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS010188 103 individuals,
55.0 % Male samples
Mean = 56.0 years
Sd = 6.1 years
European Ashkenazi UKB
PSS008692 217 individuals European Italy (South Europe) UKB
PSS010440 159 individuals,
65.0 % Male samples
Mean = 51.1 years
Sd = 8.2 years
South Asian Indian UKB
PSS007810 49 individuals African American or Afro-Caribbean Carribean UKB
PSS008466 25 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS010860 995 individuals,
51.0 % Male samples
Mean = 55.4 years
Sd = 7.5 years
European white British UKB
PSS009364 992 individuals European UK (+ Ireland) UKB
PSS010608 213 individuals,
48.0 % Male samples
Mean = 53.8 years
Sd = 7.4 years
European Italian UKB
PSS010356 73 individuals,
34.0 % Male samples
Mean = 50.3 years
Sd = 7.1 years
East Asian Chinese UKB
PSS001175 Cases were individuals with atrial fibrillation. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 14,812 cases
  • , 294,457 controls
]
European UKB
PSS001176 Cases were individuals with atrioventricular preexcitation. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 307 cases
  • , 308,734 controls
]
European UKB
PSS001177 Cases were individuals with congential artery disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 27,072 cases
  • , 282,174 controls
]
European UKB
PSS001178 Cases were individuals with distal conduction disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 2,789 cases
  • , 287,463 controls
]
European UKB
PSS001179 Cases were individuals with implantable cardioverter defibrillators. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 633 cases
  • , 308,608 controls
]
European UKB
PSS001180 Cases were individuals with mitral valve prolapse. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 529 cases
  • , 308,717 controls
]
European UKB
PSS001181 Cases were individuals with non-ischemic cardiomyopathy. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 1,703 cases
  • , 303,768 controls
]
European UKB
PSS001182 Cases were individuals with a pacemaker. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 3,975 cases
  • , 305,295 controls
]
European UKB
PSS001183 Cases were individuals with valve disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 6,244 cases
  • , 303,011 controls
]
European UKB
PSS009138 181 individuals European Poland (NE Europe) UKB
PSS008246 159 individuals South Asian India (South Asia) UKB
PSS010776 180 individuals,
41.0 % Male samples
Mean = 53.2 years
Sd = 6.5 years
European Polish UKB
PSS010524 25 individuals,
64.0 % Male samples
Mean = 52.6 years
Sd = 6.8 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB