MaghrebDataLibMedV1, Main, Exploration, bibRecord, 000391

A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study.

Identifieur interne : 000391 ( Main/Exploration ); précédent : 000390; suivant : 000392

A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study.

Auteurs : Cherif Ben Hamda [Tunisie] ; Raphael Sangeda [Tanzanie] ; Liberata Mwita [Tanzanie] ; Ayton Meintjes [Afrique du Sud] ; Siana Nkya [Tanzanie] ; Sumir Panji [Afrique du Sud] ; Nicola Mulder [Afrique du Sud] ; Lamia Guizani-Tabbane [Tunisie] ; Alia Benkahla [Tunisie] ; Julie Makani [Tunisie] ; Kais Ghedira [Tunisie]

Source :

PloS one [ 1932-6203 ] ; 2018.

RBID : pubmed:29979707

Descripteurs français

English descriptors

KwdEn :
- Alleles (MeSH), Anemia, Sickle Cell (genetics), Computational Biology (methods), Data Mining (MeSH), Databases, Genetic (MeSH), Gene Expression Profiling (MeSH), Gene Ontology (MeSH), Gene Regulatory Networks (MeSH), Genome-Wide Association Study (MeSH), Genotype (MeSH), Humans (MeSH), Polymorphism, Single Nucleotide (MeSH), Transcriptome (MeSH).
MESH :
- genetics : Anemia, Sickle Cell.
- methods : Computational Biology.
- Alleles, Data Mining, Databases, Genetic, Gene Expression Profiling, Gene Ontology, Gene Regulatory Networks, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Transcriptome.

Abstract

A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.

DOI: 10.1371/journal.pone.0199461
PubMed: 29979707
PubMed Central: PMC6034806

Affiliations:

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<term>Computational Biology (methods)</term>
<term>Data Mining (MeSH)</term>
<term>Databases, Genetic (MeSH)</term>
<term>Gene Expression Profiling (MeSH)</term>
<term>Gene Ontology (MeSH)</term>
<term>Gene Regulatory Networks (MeSH)</term>
<term>Genome-Wide Association Study (MeSH)</term>
<term>Genotype (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Polymorphism, Single Nucleotide (MeSH)</term>
<term>Transcriptome (MeSH)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Allèles (MeSH)</term>
<term>Analyse de profil d'expression de gènes (MeSH)</term>
<term>Bases de données génétiques (MeSH)</term>
<term>Biologie informatique (méthodes)</term>
<term>Drépanocytose (génétique)</term>
<term>Fouille de données (MeSH)</term>
<term>Gene Ontology (MeSH)</term>
<term>Génotype (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Polymorphisme de nucléotide simple (MeSH)</term>
<term>Réseaux de régulation génique (MeSH)</term>
<term>Transcriptome (MeSH)</term>
<term>Étude d'association pangénomique (MeSH)</term>
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<term>Data Mining</term>
<term>Databases, Genetic</term>
<term>Gene Expression Profiling</term>
<term>Gene Ontology</term>
<term>Gene Regulatory Networks</term>
<term>Genome-Wide Association Study</term>
<term>Genotype</term>
<term>Humans</term>
<term>Polymorphism, Single Nucleotide</term>
<term>Transcriptome</term>
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<term>Fouille de données</term>
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<term>Génotype</term>
<term>Humains</term>
<term>Polymorphisme de nucléotide simple</term>
<term>Réseaux de régulation génique</term>
<term>Transcriptome</term>
<term>Étude d'association pangénomique</term>
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<front><div type="abstract" xml:lang="en">A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.</div>
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<ISOAbbreviation>PLoS One</ISOAbbreviation>
</Journal>
<ArticleTitle>A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study.</ArticleTitle>
<Pagination><MedlinePgn>e0199461</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0199461</ELocationID>
<Abstract><AbstractText>A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ben Hamda</LastName>
<ForeName>Cherif</ForeName>
<Initials>C</Initials>
<Identifier Source="ORCID">0000-0003-0985-4881</Identifier>
<AffiliationInfo><Affiliation>Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institute Pasteur of Tunis, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>University of Tunis El Manar, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Faculty of Science of Bizerte, Jarzouna, University of Carthage, Tunisia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Sangeda</LastName>
<ForeName>Raphael</ForeName>
<Initials>R</Initials>
<AffiliationInfo><Affiliation>Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Mwita</LastName>
<ForeName>Liberata</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Meintjes</LastName>
<ForeName>Ayton</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>University of Cape Town, Cape Town, South Africa.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Nkya</LastName>
<ForeName>Siana</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Panji</LastName>
<ForeName>Sumir</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>University of Cape Town, Cape Town, South Africa.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Mulder</LastName>
<ForeName>Nicola</ForeName>
<Initials>N</Initials>
<AffiliationInfo><Affiliation>University of Cape Town, Cape Town, South Africa.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Guizani-Tabbane</LastName>
<ForeName>Lamia</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>University of Tunis El Manar, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Laboratory of Medical Parasitology, Biotechnology and Biomolecules, Institute Pasteur of Tunis, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Benkahla</LastName>
<ForeName>Alia</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institute Pasteur of Tunis, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>University of Tunis El Manar, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Makani</LastName>
<ForeName>Julie</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Faculty of Science of Bizerte, Jarzouna, University of Carthage, Tunisia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ghedira</LastName>
<ForeName>Kais</ForeName>
<Initials>K</Initials>
<AffiliationInfo><Affiliation>Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institute Pasteur of Tunis, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>University of Tunis El Manar, Tunis, Tunisia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><CollectiveName>H3ABioNet Consortium</CollectiveName>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><Agency>Wellcome Trust</Agency>
<Country>United Kingdom</Country>
</Grant>
<Grant><GrantID>U24 HG006941</GrantID>
<Acronym>HG</Acronym>
<Agency>NHGRI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>U41 HG006941</GrantID>
<Acronym>HG</Acronym>
<Agency>NHGRI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D017418">Meta-Analysis</PublicationType>
<PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2018</Year>
<Month>07</Month>
<Day>06</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>PLoS One</MedlineTA>
<NlmUniqueID>101285081</NlmUniqueID>
<ISSNLinking>1932-6203</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000483" MajorTopicYN="N">Alleles</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000755" MajorTopicYN="N">Anemia, Sickle Cell</DescriptorName>
<QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D019295" MajorTopicYN="N">Computational Biology</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D057225" MajorTopicYN="N">Data Mining</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D030541" MajorTopicYN="N">Databases, Genetic</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D020869" MajorTopicYN="Y">Gene Expression Profiling</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D063990" MajorTopicYN="N">Gene Ontology</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D053263" MajorTopicYN="N">Gene Regulatory Networks</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D055106" MajorTopicYN="Y">Genome-Wide Association Study</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005838" MajorTopicYN="N">Genotype</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D020641" MajorTopicYN="N">Polymorphism, Single Nucleotide</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D059467" MajorTopicYN="Y">Transcriptome</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<CoiStatement>The authors declare that they have no competing interests.</CoiStatement>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2018</Year>
<Month>01</Month>
<Day>03</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2018</Year>
<Month>06</Month>
<Day>07</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2018</Year>
<Month>7</Month>
<Day>7</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="pubmed"><Year>2018</Year>
<Month>7</Month>
<Day>7</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2019</Year>
<Month>1</Month>
<Day>1</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
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<PublicationStatus>epublish</PublicationStatus>
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<affiliations><list><country><li>Afrique du Sud</li>
<li>Tanzanie</li>
<li>Tunisie</li>
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<region><li>Gouvernorat de Tunis</li>
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</settlement>
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<name sortKey="Ben Hamda, Cherif" sort="Ben Hamda, Cherif" uniqKey="Ben Hamda C" first="Cherif" last="Ben Hamda">Cherif Ben Hamda</name>
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<name sortKey="Benkahla, Alia" sort="Benkahla, Alia" uniqKey="Benkahla A" first="Alia" last="Benkahla">Alia Benkahla</name>
<name sortKey="Benkahla, Alia" sort="Benkahla, Alia" uniqKey="Benkahla A" first="Alia" last="Benkahla">Alia Benkahla</name>
<name sortKey="Ghedira, Kais" sort="Ghedira, Kais" uniqKey="Ghedira K" first="Kais" last="Ghedira">Kais Ghedira</name>
<name sortKey="Ghedira, Kais" sort="Ghedira, Kais" uniqKey="Ghedira K" first="Kais" last="Ghedira">Kais Ghedira</name>
<name sortKey="Guizani Tabbane, Lamia" sort="Guizani Tabbane, Lamia" uniqKey="Guizani Tabbane L" first="Lamia" last="Guizani-Tabbane">Lamia Guizani-Tabbane</name>
<name sortKey="Guizani Tabbane, Lamia" sort="Guizani Tabbane, Lamia" uniqKey="Guizani Tabbane L" first="Lamia" last="Guizani-Tabbane">Lamia Guizani-Tabbane</name>
<name sortKey="Makani, Julie" sort="Makani, Julie" uniqKey="Makani J" first="Julie" last="Makani">Julie Makani</name>
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<country name="Tanzanie"><noRegion><name sortKey="Sangeda, Raphael" sort="Sangeda, Raphael" uniqKey="Sangeda R" first="Raphael" last="Sangeda">Raphael Sangeda</name>
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<name sortKey="Mwita, Liberata" sort="Mwita, Liberata" uniqKey="Mwita L" first="Liberata" last="Mwita">Liberata Mwita</name>
<name sortKey="Nkya, Siana" sort="Nkya, Siana" uniqKey="Nkya S" first="Siana" last="Nkya">Siana Nkya</name>
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<country name="Afrique du Sud"><noRegion><name sortKey="Meintjes, Ayton" sort="Meintjes, Ayton" uniqKey="Meintjes A" first="Ayton" last="Meintjes">Ayton Meintjes</name>
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<name sortKey="Mulder, Nicola" sort="Mulder, Nicola" uniqKey="Mulder N" first="Nicola" last="Mulder">Nicola Mulder</name>
<name sortKey="Panji, Sumir" sort="Panji, Sumir" uniqKey="Panji S" first="Sumir" last="Panji">Sumir Panji</name>
</country>
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A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study.

A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study.

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