ArticleHerz2014
[Genetic analyses as basis for a personalized medicine in patients with coronary artery disease].
Article in Herz, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Current Developments of Clinical Sequencing and the Clinical Utility of Polygenic Risk Scores in Inflammatory Diseases.Frontiers in immunology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Knowledge about the etiology of coronary artery disease (CAD) entered new dimensions using genome-wide association studies. The current situation is that 46 chromosomal loci have been identified to be associated with CAD with genome-wide significance, i.e. p<5×10(-8), in Western Europeans. As the individual DNA sequence remains unchanged after fertilization, the risk variants cannot occur due to confounders, such as secondary disease processes. Thus, it can be proposed that these variants are directly affecting a primary and thereby causal pathophysiological process in CAD. Interestingly, only 20% of the effects mediated by the identified loci can be explained by the influence of traditional risk factors. This implies that yet unknown mechanisms and, as a consequence, new therapeutic targets play an important role in the pathophysiology of CAD. However, the high allele frequency of risk loci was also surprising. In the diploid chromosome set Western European individuals carry on average 30-50 risk variants at the 46 loci. Considering this, every individual in the population carries a larger or smaller genetic predisposition for CAD. On the other hand it is remarkable that many risk allele carriers seem to be able to compensate the genetic risk: even in old age not everyone suffers from CAD. This indicates yet unknown gene-gene and gene-environment interactions and limits the current possibilities in individual risk prediction.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.