Evidence map›Paper›PMID 37986797›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers.

Xingyi Guo, Jie Ping, Yaohua Yang, Xinwan Su, Xiao-Ou Shu, Wanqing Wen, Zhishan Chen, Yunjing Zhang, Ran Tao, Guochong Jia and 14 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors at 11 institutions in 6 countries.

Jie Ping
Yaohua Yang
Xinwan Su
Xiao-Ou Shu
Wanqing Wen
Zhishan Chen
Yunjing Zhang
Ran Tao
Guochong Jia
Jingni He
Qiuyin Cai
Qingrun Zhang
Graham G Giles
Rachel Pearlman
Gad Rennert
Pavel Vodicka
Amanda Phipps
Stephen B Gruber
Graham Casey
Ulrike Peters
Jirong Long
Weiqiang Lin
Wei Zheng
Vanderbilt University · USZhejiang University · CNUniversity of Calgary · CAUniversity of Virginia · USUniversity of Washington · USCancer Council Victoria · AUCarmel Medical Center · ILCharles University · CZThe Ohio State University · USUniversity of Southern California · USVanderbilt University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected

Identifiers

PMID37986797
PMCPMC10659493
OpenAlexW4388449625

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.