Evidence map›Paper›PMID 38245557›Full record

ArticleNPJ genomic medicine2024

Whole genome sequencing enables new genetic diagnosis for inherited retinal diseases by identifying pathogenic variants.

Xubing Liu, Fangyuan Hu, Daowei Zhang, Zhe Li, Jianquan He, Shenghai Zhang, Zhenguo Wang, Yingke Zhao, Jiawen Wu, Chen Liu and 3 more

Open access · goldAbstract read
In one paragraph

Article in NPJ genomic medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
6.5field-weighted citation impact, top 2% of its field
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

26 citing papers in PubMed, 28 citations in OpenAlex.

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  16. Genetics and diagnostics of inherited retinal diseases in the era of whole genome sequencing.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 1 country.

Xubing Liu *CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Fangyuan Hu *Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Daowei ZhangEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Zhe LiCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Jianquan HeComputer Center, Eye & ENT Hospital, Fudan University, Shanghai, China.
Shenghai ZhangEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Zhenguo WangCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Yingke ZhaoEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Jiawen WuEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Chen LiuCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Chenchen LiEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.
Xin LiCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. lixin@sinh.ac.cn.
Jihong WuEye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China. jihongwu@fudan.edu.cn.ORCID http://orcid.org/0000-0003-3892-5757
Chinese Academy of Medical Sciences & Peking Union Medical College · CNShanghai Institute of Nutrition and Health · CNEye & ENT Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inherited retinal diseases (IRDs) are a group of common primary retinal degenerative disorders. Conventional genetic testing strategies, such as panel-based sequencing and whole exome sequencing (WES), can only elucidate the genetic etiology in approximately 60% of IRD patients. Studies have suggested that unsolved IRD cases could be attributed to previously undetected structural variants (SVs) and intronic variants in IRD-related genes. The aim of our study was to obtain a definitive genetic diagnosis by employing whole genome sequencing (WGS) in IRD cases where the causative genes were inconclusive following an initial screening by panel sequencing. A total of 271 unresolved IRD patients and their available family members (n = 646) were screened using WGS to identify pathogenic SVs and intronic variants in 792 known ocular disease genes. Overall, 13% (34/271) of IRD patients received a confirmed genetic diagnosis, among which 7% were exclusively attributed to SVs, 4% to a combination of single nucleotide variants (SNVs) and SVs while another 2% were linked to intronic variants. 22 SVs, 3 deep-intronic variants, and 2 non-canonical splice-site variants across 14 IRD genes were identified in the entire cohort. Notably, all of these detected SVs and intronic variants were novel pathogenic variants. Among those, 74% (20/27) of variants were found in genes causally linked to Retinitis Pigmentosa (RP), with the gene EYS being the most frequently affected by SVs. The identification of SVs and intronic variants through WGS enhances the genetic diagnostic yield of IRDs and broadens the mutational spectrum of known IRD-associated genes.

Identifiers

PMID38245557
PMCPMC10799956
OpenAlexW4391052949

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Registered trials

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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.