| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0006336 |
| Description | The blood pressure after the contraction of the heart while the chambers of the heart refill with blood. | Trait category |
Other measurement
|
| Synonyms |
2 synonyms
|
| Mapped terms |
3 mapped terms
|
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | Ancestry distribution | Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000302 (GRS962_DBP) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Diastolic blood pressure | diastolic blood pressure | 962 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000302/ScoringFiles/PGS000302.txt.gz |
| PGS000912 (ukb_dbp_prs) |
PGP000240 | Vaura F et al. Hypertension (2021) |
Diastolic blood pressure | diastolic blood pressure | 1,098,015 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000912/ScoringFiles/PGS000912.txt.gz |
| PGS001133 (GBE_INI4079) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Diastolic BP (AR) | diastolic blood pressure | 14,103 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001133/ScoringFiles/PGS001133.txt.gz |
| PGS001900 (portability-PLR_diastolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diastolic blood pressure, automated reading | diastolic blood pressure | 66,335 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001900/ScoringFiles/PGS001900.txt.gz |
| PGS002114 (portability-ldpred2_diastolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diastolic blood pressure, automated reading | diastolic blood pressure | 933,950 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002114/ScoringFiles/PGS002114.txt.gz |
| PGS002258 (GRS901_DBP) |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Diastolic blood pressure | diastolic blood pressure | 885 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002258/ScoringFiles/PGS002258.txt.gz |
|
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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000772 | PGS000302 (GRS962_DBP) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Diastolic blood pressure (mmHg) | — | — | R²: 0.0448 | Sex, age, age^2, BMI | — |
| PPM000802 | PGS000302 (GRS962_DBP) |
PSS000371| European Ancestry| 288 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Diastolic blood pressure (mmHg) | — | — | R²: 0.0088 | Sex, age, age^2, BMI | — |
| PPM002972 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | HR: 1.41 [1.4, 1.42] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.26 [2.17, 2.36] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002974 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Late onset incident hypertension (≥55 years) | HR: 1.26 [1.25, 1.28] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.6 [1.48, 1.73] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002976 | PGS000912 (ukb_dbp_prs) |
PSS001450| European Ancestry| 9,906 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | — | C-index: 0.803 | — | Age, sex, systolic blood pressure, diastolic blood pressure, body mass index, diabetes, current smoking | — |
| PPM002973 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Early onset incident hypertension (< 55 years) | HR: 1.58 [1.56, 1.6] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.78 [2.64, 2.93] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM008393 | PGS001133 (GBE_INI4079) |
PSS007261| African Ancestry| 6,409 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.00961 [0.00489, 0.01433] Incremental R2 (full-covars): 0.004 PGS R2 (no covariates): 0.00541 [0.00186, 0.00897] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008394 | PGS001133 (GBE_INI4079) |
PSS007262| East Asian Ancestry| 1,634 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.10887 [0.081, 0.13673] Incremental R2 (full-covars): 0.03804 PGS R2 (no covariates): 0.04085 [0.02248, 0.05923] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008395 | PGS001133 (GBE_INI4079) |
PSS007263| European Ancestry| 23,727 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.08484 [0.07822, 0.09146] Incremental R2 (full-covars): 0.04531 PGS R2 (no covariates): 0.04978 [0.04451, 0.05504] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008396 | PGS001133 (GBE_INI4079) |
PSS007264| South Asian Ancestry| 7,640 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.03516 [0.02715, 0.04317] Incremental R2 (full-covars): 0.02383 PGS R2 (no covariates): 0.02615 [0.01918, 0.03312] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008397 | PGS001133 (GBE_INI4079) |
PSS007265| European Ancestry| 63,825 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.07507 [0.07124, 0.07889] Incremental R2 (full-covars): 0.04511 PGS R2 (no covariates): 0.04581 [0.04273, 0.04889] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010083 | PGS001900 (portability-PLR_diastolic_BP) |
PSS009397| European Ancestry| 18,718 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2491 [0.2356, 0.2625] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010084 | PGS001900 (portability-PLR_diastolic_BP) |
PSS009171| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2605 [0.231, 0.2895] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010085 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008725| European Ancestry| 6,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2168 [0.1932, 0.2402] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010086 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008499| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1801 [0.1231, 0.2359] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010087 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008277| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1863 [0.162, 0.2105] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010088 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008054| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2437 [0.1985, 0.288] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010090 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008945| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0834 [0.0519, 0.1148] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010089 | PGS001900 (portability-PLR_diastolic_BP) |
PSS007841| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1048 [0.0652, 0.144] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011767 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS009397| European Ancestry| 18,718 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2531 [0.2397, 0.2665] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011768 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS009171| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2679 [0.2385, 0.2967] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011769 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008725| European Ancestry| 6,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2221 [0.1986, 0.2455] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011770 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008499| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1869 [0.1301, 0.2426] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011771 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008277| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1939 [0.1695, 0.2179] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011772 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008054| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2244 [0.1788, 0.2691] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011773 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS007841| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1014 [0.0618, 0.1407] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011774 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008945| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0818 [0.0502, 0.1131] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012847 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.06 [1.79, 2.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012848 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.64 [1.46, 1.81] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012849 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.42 [0.25, 0.58] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012850 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.27 [1.23, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012851 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.38 [1.85, 2.9] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012852 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.39 [1.09, 1.7] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012853 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.99 [0.65, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012854 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.26 [1.2, 1.33] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012855 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.58 [2.13, 3.03] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012856 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.49 [1.25, 1.74] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012857 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 1.09 [0.8, 1.39] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012858 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.3 [1.24, 1.36] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS009171 | — | — | 3,930 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS008277 | — | — | 6,098 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS007261 | — | — | 6,409 individuals | — | African unspecified | — | UKB | — |
| PSS007262 | — | — | 1,634 individuals | — | East Asian | — | UKB | — |
| PSS007263 | — | — | 23,727 individuals | — | European | non-white British ancestry | UKB | — |
| PSS007264 | — | — | 7,640 individuals | — | South Asian | — | UKB | — |
| PSS007265 | — | — | 63,825 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008945 | — | — | 3,850 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS000371 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 288 individuals, 69.2 % Male samples |
Mean = 15.83 years Sd = 0.6 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS008054 | — | — | 1,719 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS000376 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,354 individuals, 47.56 % Male samples |
Mean = 16.22 years Sd = 0.66 years |
European | — | TRAILS | — |
| PSS008725 | — | — | 6,338 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS007841 | — | — | 2,438 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009574 | — | — | 14,004 individuals | — | European | — | Airwave | — |
| PSS009575 | — | — | 6,970 individuals | — | African unspecified | — | UKB | — |
| PSS008499 | — | — | 1,151 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009576 | — | — | 8,827 individuals | — | South Asian | — | UKB | — |
| PSS009397 | — | — | 18,718 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS001446 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). Of the 55,917 cases, 27,361 had early-onset incident hypertension, whilst 28,556 had late-onset incident hypertension. Early-onset and late-onset hypertension were defined as age of onset <55 and ≥55 years, respectively. | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS001450 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). | — | [
|
— | European (Finnish) |
— | FINRISK | — |