Evidence map›Paper›PMID 33277604›Full record

ArticleScientific reports2020

Clinical and molecular analysis in a cohort of Chinese children with Cornelia de Lange syndrome.

Qun Li, Guoying Chang, Lei Yin, Juan Li, Xiaodong Huang, Yongnian Shen, Guoqiang Li, Yufei Xu, Jian Wang, Xiumin Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  3. Co-Occurrence ofInternational journal of molecular sciences · 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

10 authors at 1 institution in 1 country.

Qun LiDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China.
Guoying ChangDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China.
Lei YinDepartment of Rare Disease Clinic, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Juan LiDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China.
Xiaodong HuangDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China.
Yongnian ShenDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China.
Guoqiang LiDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Yufei XuDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Jian WangDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. labwangjian@shsmu.edu.cn.
Xiumin WangDepartment of Endocrinology and Metabolism, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Shanghai, 200127, China. wangxiumin1019@126.com.
Shanghai Children's Medical Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cornelia de Lange Syndrome (CdLS) is a rare genetic disorder, which causes a range of physical, cognitive, and medical challenges. To retrospectively analyze the clinical characteristics and genetic variations of Chinese patients, and to provide experience for further diagnosis and treatment of CdLS in Chinese children, we identified 15 unrelated Chinese children who presented with unusual facial features, short stature, developmental delay, limb abnormalities, and a wide range of health conditions. In this study, targeted-next generation sequencing was used to screen for causal variants and the clinically relevant variants were subsequently verified using Sanger sequencing. DNA sequencing identified 15 genetic variations, including 11 NIPBL gene variants, two SMC1A gene variants, one RAD21 gene variant, and one HDAC8 variant. The phenotype of these patients was summarized and differences between this cohort and another four groups were compared. The clinical manifestations of the patients in this cohort were mostly consistent with other ethnicities, but several clinical features in our cohort had different frequencies compared with other groups. We identified 15 deleterious variants of which 11 were novel. Variants in the NIPBL gene were the most common cause in our cohort. Our study not only expands upon the spectrum of genetic variations in CdLS, but also broadens our understanding of the clinical features of CdLS.

Indexed as

Abnormalities, MultipleAsian PeopleCell Cycle ProteinsChildChild, PreschoolChromosomal Proteins, Non-HistoneCohort StudiesDe Lange SyndromeDNA-Binding ProteinsFemaleFrameshift MutationGenotypeHeterozygoteHigh-Throughput Nucleotide SequencingHistone DeacetylasesHomozygoteCell Cycle ProteinsChromosomal Proteins, Non-HistoneDNA-Binding ProteinsHDAC8 protein, humanHistone DeacetylasesNIPBL protein, humanRAD21 protein, humanRepressor ProteinsStructural Maintenance of Chromosome Protein 1

Identifiers

PMID33277604
PMCPMC7718889
OpenAlexW3110342539

What OpenQuestion holds

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LicenceCC BY
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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.