Evidence map›Paper›PMID 36789417›Full record

ArticlebioRxiv : the preprint server for biology2023

Systematic assessment of the contribution of structural variants to inherited retinal diseases.

Shu Wen, Meng Wang, Xinye Qian, Yumei Li, Keqing Wang, Jongsu Choi, Mark E Pennesi, Paul Yang, Molly Marra, Robert K Koenekoop and 8 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 7 institutions in 4 countries.

Shu Wen
Meng Wang
Xinye Qian
Yumei Li
Keqing Wang
Jongsu Choi
Mark E Pennesi
Paul Yang
Molly Marra
Robert K Koenekoop
Irma Lopez
Anna Matynia
Michael Gorin
Ruifang Sui
Fengxia Yao
Kerry Goetz
Fernanda Belga Ottoni Porto
Rui Chen
Baylor College of Medicine · USOregon Health & Science University · USChinese Academy of Medical Sciences & Peking Union Medical College · CNMcGill University Health Centre · CAUniversity of California, Los Angeles · USGrupo Santa Casa de Belo Horizonte · BRNational Institutes of Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite increasing success in determining genetic diagnosis for patients with inherited retinal diseases (IRDs), mutations in about 30% of the IRD cases remain unclear or unsettled after targeted gene panel or whole exome sequencing. In this study, we aimed to investigate the contributions of structural variants (SVs) to settling the molecular diagnosis of IRD with whole-genome sequencing (WGS). A cohort of 755 IRD patients whose pathogenic mutations remain undefined was subjected to WGS. Four SV calling algorithms including include MANTA, DELLY, LUMPY, and CNVnator were used to detect SVs throughout the genome. All SVs identified by any one of these four algorithms were included for further analysis. AnnotSV was used to annotate these SVs. SVs that overlap with known IRD-associated genes were examined with sequencing coverage, junction reads, and discordant read pairs. PCR followed by Sanger sequencing was used to further confirm the SVs and identify the breakpoints. Segregation of the candidate pathogenic alleles with the disease was performed when possible. In total, sixteen candidate pathogenic SVs were identified in sixteen families, including deletions and inversions, representing 2.1% of patients with previously unsolved IRDs. Autosomal dominant, autosomal recessive, and X-linked inheritance of disease-causing SVs were observed in 12 different genes. Among these, SVs in

Identifiers

PMID36789417
PMCPMC9928032
OpenAlexW4313458604

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.