Evidence map›Paper›PMID 32241273›Full record

ArticleBMC medical genomics2020

An integrative, genomic, transcriptomic and network-assisted study to identify genes associated with human cleft lip with or without cleft palate.

Fangfang Yan, Yulin Dai, Junichi Iwata, Zhongming Zhao, Peilin Jia

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Damaging Mutations inThe Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2024
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  5. Review
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  15. ExcessiveFrontiers in cell and developmental biology · 2021
    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

5 authors at 1 institution in 1 country.

Fangfang YanCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX, 77030, USA.
Yulin DaiCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX, 77030, USA.
Junichi IwataDepartment of Diagnostic and Biomedical Sciences, School of Dentistry, The University of Texas Health Science Center at Houston, Houston, TX, 77054, USA.
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.
Peilin JiaCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 600, Houston, TX, 77030, USA. peilin.jia@uth.tmc.edu.
The University of Texas Health Science Center at Houston · US

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
Identification of microRNAs associated with cleft lipR03DE026509 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI IWATA, JUNICHI · 2017 to 2018
$462k
Transcriptional and Post-transcriptional Co-regulation in Lip DevelopmentR03DE027393 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI IWATA, JUNICHI, ZHAO, ZHONGMING · 2018 to 2019
$308k
Deep learning methods to predict the function of genetic variants in orofacial cleftsR03DE027711 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHAO, ZHONGMING · 2018 to 2019
$308k
Mining Genomic Data in FaceBase for Cleft GenesR03DE028103 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHAO, ZHONGMING · 2018 to 2019
$308k
NIDCR NIH HHS R03 DE026509NIDCR NIH HHS R03 DE027393NIDCR NIH HHS R03 DE027711NIDCR NIH HHS R03 DE028103NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

backgroundCleft lip with or without cleft palate (CL/P) is one of the most common congenital human birth defects. A combination of genetic and epidemiology studies has contributed to a better knowledge of CL/P-associated candidate genes and environmental risk factors. However, the etiology of CL/P remains not fully understood. In this study, to identify new CL/P-associated genes, we conducted an integrative analysis using our in-house network tools, dmGWAS [dense module search for Genome-Wide Association Studies (GWAS)] and EW_dmGWAS (Edge-Weighted dmGWAS), in a combination with GWAS data, the human protein-protein interaction (PPI) network, and differential gene expression profiles.

resultsA total of 87 genes were consistently detected in both European and Asian ancestries in dmGWAS. There were 31.0% (27/87) showed nominal significance with CL/P (gene-based p < 0.05), with three genes showing strong association signals, including KIAA1598, GPR183, and ZMYND11 (p < 1 × 10

conclusionsThe genes identified through superimposing GWAS signals and differential gene expression profiles onto human PPI network, as well as their functional features, helped our understanding of the etiology of CL/P. Our multi-omics integrative analyses revealed nine novel candidate genes involved in CL/P.

Indexed as

Polymorphism, Single NucleotideTranscriptomeAsian PeopleCase-Control StudiesCleft LipCleft PalateGene Regulatory NetworksGenetic MarkersGenome-Wide Association StudyGenomicsHumansProtein Interaction MapsWhite PeopleGenetic MarkersCleft lipCleft palateDense module searchGenome-wide association studies (GWAS)Network

Identifiers

PMID32241273
PMCPMC7118807
OpenAlexW3014113792

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.