Evidence map›Paper›PMID 33023636›Full record

ArticleMolecular autism2020

Functional relationships between recessive inherited genes and genes with de novo variants in autism spectrum disorder.

Lin Wang, Yi Zhang, Kuokuo Li, Zheng Wang, Xiaomeng Wang, Bin Li, Guihu Zhao, Zhenghuan Fang, Zhengbao Ling, Tengfei Luo and 7 more

Open access · goldAbstract read
In one paragraph

Article in Molecular autism, 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
0.6field-weighted citation impact, top 36% 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, 12 citations in OpenAlex.

  1. Article
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  6. Cross-Disorder Analysis of De Novo Mutations in Neuropsychiatric Disorders.Journal of autism and developmental disorders · 2022
    Article
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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

17 authors at 2 institutions in 1 country.

Lin WangCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Yi ZhangNational Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Kuokuo LiCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Zheng WangNational Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xiaomeng WangCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Bin LiNational Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Guihu ZhaoNational Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Zhenghuan FangCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Zhengbao LingCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Tengfei LuoCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Lu XiaCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Yanping LiReproductive Medicine Center, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Hui GuoCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Zhengmao HuCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Jinchen LiNational Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China. lijinchen@csu.edu.cn.
Zhongsheng SunInstitute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China. sunzs@biols.ac.cn.
Kun XiaCenter for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China. xiakun@sklmg.edu.cn.ORCID 0000-0001-8090-6002
Central South University · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBoth de novo variants and recessive inherited variants were associated with autism spectrum disorder (ASD). This study aimed to use exome data to prioritize recessive inherited genes (RIGs) with biallelically inherited variants in autosomes or X-linked inherited variants in males and investigate the functional relationships between RIGs and genes with de novo variants (DNGs).

methodsWe used a bioinformatics pipeline to analyze whole-exome sequencing data from 1799 ASD quads (containing one proband, one unaffected sibling, and their parents) from the Simons Simplex Collection and prioritize candidate RIGs with rare biallelically inherited variants in autosomes or X-linked inherited variants in males. The relationships between RIGs and DNGs were characterized based on different genetic perspectives, including genetic variants, functional networks, and brain expression patterns.

resultsAmong the biallelically or hemizygous constrained genes that were expressed in the brain, ASD probands carried significantly more biallelically inherited protein-truncating variants (PTVs) in autosomes (p = 0.038) and X-linked inherited PTVs in males (p = 0.026) than those in unaffected siblings. We prioritized eight autosomal, and 13 X-linked candidate RIGs, including 11 genes already associated with neurodevelopmental disorders. In total, we detected biallelically inherited variants or X-linked inherited variants of these 21 candidate RIGs in 26 (1.4%) of 1799 probands. We then integrated previously reported known or candidate genes in ASD, ultimately obtaining 70 RIGs and 87 DNGs for analysis. We found that RIGs were less likely to carry multiple recessive inherited variants than DNGs were to carry multiple de novo variants. Additionally, RIGs and DNGs were significantly co-expressed and interacted with each other, forming a network enriched in known functional ASD clusters, although RIGs were less likely to be enriched in these functional clusters compared with DNGs. Furthermore, although RIGs and DNGs presented comparable expression patterns in the human brain, RIGs were less likely to be associated with prenatal brain regions, the middle cortical layers, and excitatory neurons than DNGs. LIMITATIONS: The RIGs analyzed in this study require functional validation, and the results should be replicated in more patients with ASD.

conclusionsASD RIGs were functionally associated with DNGs; however, they exhibited higher heterogeneity than DNGs.

Indexed as

Genes, RecessiveGenetic Predisposition to DiseaseAllelesAutism Spectrum DisorderBrainGene Expression RegulationGene Regulatory NetworksGenes, X-LinkedGenetic HeterogeneityHumansInheritance PatternsMutationSiblingsAutism spectrum disorderDe novo variantExpression patternFunctional networkRecessive inherited variant

Identifiers

PMID33023636
PMCPMC7541261
OpenAlexW3092000535

What OpenQuestion holds

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LicenceCC BY
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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.