| Publication Information (EuropePMC) | |
| Title | Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program. |
| PubMed ID | 32981348(Europe PMC) |
| doi | 10.1161/circulationaha.120.047544 |
| Publication Date | Sept. 28, 2020 |
| Journal | Circulation |
| Author(s) | Klarin D, Verma SS, Judy R, Dikilitas O, Wolford BN, Paranjpe I, Levin MG, Pan C, Tcheandjieu C, Spin JM, Lynch J, Assimes TL, Åldstedt Nyrønning L, Mattsson E, Edwards TL, Denny J, Larson E, Lee MTM, Carrell D, Zhang Y, Jarvik GP, Gharavi AG, Harley J, Mentch F, Pacheco JA, Hakonarson H, Skogholt AH, Thomas L, Gabrielsen ME, Hveem K, Nielsen JB, Zhou W, Fritsche L, Huang J, Natarajan P, Sun YV, DuVall SL, Rader DJ, Cho K, Chang KM, Wilson PWF, O'Donnell CJ, Kathiresan S, Scali ST, Berceli SA, Willer C, Jones GT, Bown MJ, Nadkarni G, Kullo IJ, Ritchie M, Damrauer SM, Tsao PS, Veterans Affairs Million Veteran Program†. |
| 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) |
|---|---|---|---|---|---|---|
| PGS000753 (PRS29_AAA) |
PGP000159 | Klarin D et al. Circulation (2020) |
Abdominal aortic aneurysm | Abdominal Aortic Aneurysm | 29 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000753/ScoringFiles/PGS000753.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM001912 | PGS000753 (PRS29_AAA) |
PSS000958| European Ancestry| 46,564 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.37 [1.3, 1.44] | — | — | Age, sex, PCs (1-5) | — |
| PPM001913 | PGS000753 (PRS29_AAA) |
PSS000956| African Ancestry| 47,098 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.15 [1.07, 1.24] | — | — | Age, sex, PCs (1-5) | — |
| PPM001915 | PGS000753 (PRS29_AAA) |
PSS000959| European Ancestry| 10,231 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.31 [1.18, 1.46] | — | — | Age, sex, PCs (1-5) | — |
| PPM001917 | PGS000753 (PRS29_AAA) |
PSS000956| African Ancestry| 47,098 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.13 [1.04, 1.22] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
| PPM001918 | PGS000753 (PRS29_AAA) |
PSS000957| European Ancestry| 9,525 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.58 [1.25, 1.98] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
| PPM001914 | PGS000753 (PRS29_AAA) |
PSS000957| European Ancestry| 9,525 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 2.46 [1.46, 4.14] | — | — | Age, sex, PCs (1-5) | — |
| PPM001916 | PGS000753 (PRS29_AAA) |
PSS000958| European Ancestry| 46,564 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.34 [1.27, 1.41] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS000958 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. Controls were defined as possessing no occurrences of the aforementioned ICD codes, as well as no occurrences of the ICD-9 codes 440 through 448 or ICD-10 codes I71 through I75, I77 through I79, or K55. | — | [ ,
92.1 % Male samples |
Mean = 63.8 years Sd = 13.7 years |
European | — | MVP | Sample is independent to the MVP sample used to identify SNPs and determine their weights |
| PSS000959 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. | — | [ ,
65.4 % Male samples |
Mean = 71.0 years Sd = 13.7 years |
European | — | PMB | — |
| PSS000956 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. Controls were defined as possessing no occurrences of the aforementioned ICD codes, as well as no occurrences of the ICD-9 codes 440 through 448 or ICD-10 codes I71 through I75, I77 through I79, or K55. | — | [ ,
86.0 % Male samples |
Mean = 56.3 years Sd = 11.8 years |
African unspecified | — | MVP | — |
| PSS000957 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. | — | [ ,
48.1 % Male samples |
Mean = 58.3 years Sd = 19.5 years |
European | — | BioMe | — |