ArticleHuman genomics2018
Abundance of clinical variants in exons included in multiple transcripts.
Article in Human genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- X-CAP improves pathogenicity prediction of stopgain variants.Genome medicine · 2022Article
- The Human Gene Mutation Database (HGMDHuman genetics · 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
1 author.
Funding
Abstract
Previous studies showed that the magnitude of selection pressure in constitutive exons is higher than that in alternatively spliced exons. The intensity of selection was also shown to be depended on the inclusion level of exons: the number of transcripts that include an exon. Here, we examined how the difference in selection pressure influences the patterns of clinical variants in human exons. Our analysis revealed a positive relationship between exon inclusion level and the abundance of pathogenic variants. The proportion of pathogenic variants in the exons that are included in > 10 transcripts was 6.8 times higher than those in the exons included in only one transcript. This suggests that the mutations occurring in the exons included in multiple transcripts are more deleterious than those present in the exons included in one transcript. The findings of this study highlight that the exon inclusion level could be used to predict the mutations associated with diseases.
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.