Genetic Predisposition to Atrial Fibrillation

To estimate the genetic predisposition of AF, we constructed a polygenic risk score for each participant, which was derived from the current optimal genetic risk variant list from the meta-analyses excluding the UK Biobank participants (n=165 SNPs, Additional file 1: Text S3, and Table S1) [15 (link)]. Briefly, most of the genome-wide significant risk variants for AF fall in genes that cause serious heart defects in humans (e.g., PITX2, TBX5) or near genes important for striated muscle function and integrity (e.g., CFL2, MYH7), which are crucial for the function of cardiac ion channels and calcium signaling. According to the number of risk alleles, we used imputed data to calculate the PRS through multiplying by the regression coefficient obtained from the previous study [23 (link)]: PRS = (β₁ × SNP₁ + β₂ × SNP₂ + … + β₁₆₅ × SNP₁₆₅). Furthermore, we classified each participant into three categories: low (lowest quartile), intermediate (mid two quartiles), and high (highest quartile) genetic AF risk groups.

Free full text: Click here

Zhang J., Chen G., Wang C., Wang X., Qian Z.(., Cai M., Vaughn M.G., Bingheim E., Li H., Gao Y., Lip G.Y, & Lin H. (2023). Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants. BMC Medicine, 21, 88.

Publication 2023

Alleles Cardiac Genes Genetic predisposition Genetic variant Genome Heart defects Humans Ion channels Risk Risk groups Snps Striated muscle

Corresponding Organization :

Other organizations : Sun Yat-sen University, Zhengzhou University, Saint Louis University, Shenzhen University Health Science Center, Jinan University, Liverpool Heart and Chest Hospital, Liverpool John Moores University, University of Liverpool

Top 5 similar protocols

Variable analysis

independent variables

Genetic risk variants for atrial fibrillation (AF)

dependent variables

Genetic predisposition to AF
Polygenic risk score for each participant

control variables

Participants from the UK Biobank (excluded from the meta-analysis used to derive the genetic risk variant list)

Annotations

Based on most similar protocols

Etiam vel ipsum. Morbi facilisis vestibulum nisl. Praesent cursus laoreet felis. Integer adipiscing pretium orci. Nulla facilisi. Quisque posuere bibendum purus. Nulla quam mauris, cursus eget, convallis ac, molestie non, enim. Aliquam congue. Quisque sagittis nonummy sapien. Proin molestie sem vitae urna. Maecenas lorem.

As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!