Strategies Beyond Genome-Wide Association Studies for Atherosclerosis is a research paper published in Arteriosclerosis, Thrombosis, and Vascular Biology (2012). On theSindex it has a DataRank of 2.3. It has been cited 44 times, with 43 citing works in its 1-hop citation network.
Atherosclerotic diseases, including coronary artery disease (CAD) and myocardial infarction (MI), are the leading causes of death in the world. The genetic basis of CAD and MI, which are caused by multiple interacting endogenous and exogenous factors, has gained considerable interest in the last years as genome-wide association studies (GWASs) have identified many new susceptibility loci for CAD and MI, and the underlying genes provide new insights into the genetic architecture of these diseases. Here we summarize the recent findings from GWASs of atherosclerosis and discuss their functional and biological implications. We also discuss the different post-GWAS strategies that are currently used for refining the location of causal variants, understanding their role, and shedding light on molecular mechanisms explaining their association to CAD. We finally discuss potential clinical translations of GWAS findings for individual risk prediction, advanced clinical strategies, and personalized treatments.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.571
From this paper's citation signal
Citation Network Contribution
1.7
From 37 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 25% comes from its base citations and 75% from the citation network (37 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
Click a node to highlight its connections. Use scroll to zoom. Drag to pan.