AFGen genetic interaction GWAS

Publications

Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium.
Weng LC, et al.
Sci Rep. 2017 Sep 12;7(1):11303. doi: 10.1038/s41598-017-09396-7

Dataset phenotypes

  • AF-SNP age interaction
  • AF-over age 65
  • AF-age 65 and under
  • AF-SNP BMI interaction
  • AF-SNP hypertension interaction
  • AF-SNP sex interaction

Dataset subjects

Cases Controls Cohort Ancestry
448 438 Arrhythmia-Biobank-LMU (AFLMU, formerly known as AFNET) and the Cooperative Health Research in the Region of Augsburg (AFNET/KORA) European
399 5,278 Age, Gene/Environment Susceptibility Study (AGES) Reykjavik study European
799 8,254 Atherosclerosis Risk in Communities Study (ARIC) European
120 3,670 Vanderbilt University Medical Center BioVU Biorepository 660 European
238 4,528 Vanderbilt University Medical Center BioVU Biorepository o1 European
807 1,854 Cleveland Clinic Lone Atrial Fibrillation GeneBank Study (CCAF) European
763 2,422 Cardiovascular Health Study (CHS) European
559 7,867 Framingham Heart Study (FHS) European
361 2,598 Ludwigshafen Risk and Cardiovascular Health (LURIC) European
155 2,371 Multi-Ethnic Study of Atherosclerosis (MESA) European
366 911 Massachusetts General Hospital/MIGEN (MGH/MIGEN) European
113 3,407 Prevention of Renal and Vascular Endstage Disease (PREVEND) European
505 4,739 PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) European
900 10,739 Rotterdam Study (RS) European
107 1,816 Study of Health in Pomerania (SHIP) European
648 20,194 Women’s Genome Health Study (WGHS) European
Total: 7,288 cases | 81,086 controls  

Project

Atrial Fibrillation Consortium

The Atrial Fibrillation Consortium (AFGen) seeks to identify the genetic basis of atrial fibrillation using a wide variety of genetic analyses.

Experiment summary

AFGen GEI GWAS is a genome-wide association study for atrial fibrillation associations in about 88,000 individuals, over 7,000 with AF. The authors further performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index (see the Weng et al. publication cited above).

Dataset ID
GWAS_GEI