Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies.
Identifieur interne : 000F12 ( PubMed/Corpus ); précédent : 000F11; suivant : 000F13Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies.
Auteurs : Mohammad Ali Moni ; Pietro LiSource :
- BMC bioinformatics [ 1471-2105 ] ; 2014.
English descriptors
- KwdEn :
- Chronic Disease, Comorbidity, HIV Infections (complications), HIV Infections (epidemiology), HIV Infections (immunology), HIV Infections (virology), HIV-1 (physiology), Humans, Protein Interaction Maps, Risk Factors, SARS Virus (physiology), Severe Acute Respiratory Syndrome (complications), Severe Acute Respiratory Syndrome (epidemiology), Severe Acute Respiratory Syndrome (immunology), Severe Acute Respiratory Syndrome (virology).
- MESH :
- complications : HIV Infections, Severe Acute Respiratory Syndrome.
- epidemiology : HIV Infections, Severe Acute Respiratory Syndrome.
- immunology : HIV Infections, Severe Acute Respiratory Syndrome.
- physiology : HIV-1, SARS Virus.
- virology : HIV Infections, Severe Acute Respiratory Syndrome.
- Chronic Disease, Comorbidity, Humans, Protein Interaction Maps, Risk Factors.
Abstract
Infections are often associated to comorbidity that increases the risk of medical conditions which can lead to further morbidity and mortality. SARS is a threat which is similar to MERS virus, but the comorbidity is the key aspect to underline their different impacts. One UK doctor says "I'd rather have HIV than diabetes" as life expectancy among diabetes patients is lower than that of HIV. However, HIV has a comorbidity impact on the diabetes.
DOI: 10.1186/1471-2105-15-333
PubMed: 25344230
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pubmed:25344230Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies.</title><author><name sortKey="Moni, Mohammad Ali" sort="Moni, Mohammad Ali" uniqKey="Moni M" first="Mohammad Ali" last="Moni">Mohammad Ali Moni</name><affiliation><nlm:affiliation>Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK. Mohammad.Moni@cl.cam.ac.uk.</nlm:affiliation></affiliation></author><author><name sortKey="Li, Pietro" sort="Li, Pietro" uniqKey="Li P" first="Pietro" last="Li">Pietro Li</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2014">2014</date><idno type="RBID">pubmed:25344230</idno><idno type="pmid">25344230</idno><idno type="doi">10.1186/1471-2105-15-333</idno><idno type="wicri:Area/PubMed/Corpus">000F12</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000F12</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies.</title><author><name sortKey="Moni, Mohammad Ali" sort="Moni, Mohammad Ali" uniqKey="Moni M" first="Mohammad Ali" last="Moni">Mohammad Ali Moni</name><affiliation><nlm:affiliation>Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK. Mohammad.Moni@cl.cam.ac.uk.</nlm:affiliation></affiliation></author><author><name sortKey="Li, Pietro" sort="Li, Pietro" uniqKey="Li P" first="Pietro" last="Li">Pietro Li</name></author></analytic><series><title level="j">BMC bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Chronic Disease</term><term>Comorbidity</term><term>HIV Infections (complications)</term><term>HIV Infections (epidemiology)</term><term>HIV Infections (immunology)</term><term>HIV Infections (virology)</term><term>HIV-1 (physiology)</term><term>Humans</term><term>Protein Interaction Maps</term><term>Risk Factors</term><term>SARS Virus (physiology)</term><term>Severe Acute Respiratory Syndrome (complications)</term><term>Severe Acute Respiratory Syndrome (epidemiology)</term><term>Severe Acute Respiratory Syndrome (immunology)</term><term>Severe Acute Respiratory Syndrome (virology)</term></keywords><keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>HIV Infections</term><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>HIV Infections</term><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" qualifier="immunology" xml:lang="en"><term>HIV Infections</term><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>HIV-1</term><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>HIV Infections</term><term>Severe Acute Respiratory Syndrome</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Chronic Disease</term><term>Comorbidity</term><term>Humans</term><term>Protein Interaction Maps</term><term>Risk Factors</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Infections are often associated to comorbidity that increases the risk of medical conditions which can lead to further morbidity and mortality. SARS is a threat which is similar to MERS virus, but the comorbidity is the key aspect to underline their different impacts. One UK doctor says "I'd rather have HIV than diabetes" as life expectancy among diabetes patients is lower than that of HIV. However, HIV has a comorbidity impact on the diabetes.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">25344230</PMID><DateCompleted><Year>2015</Year><Month>04</Month><Day>28</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2105</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><PubDate><Year>2014</Year><Month>Oct</Month><Day>24</Day></PubDate></JournalIssue><Title>BMC bioinformatics</Title><ISOAbbreviation>BMC Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies.</ArticleTitle><Pagination><MedlinePgn>333</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1471-2105-15-333</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Infections are often associated to comorbidity that increases the risk of medical conditions which can lead to further morbidity and mortality. SARS is a threat which is similar to MERS virus, but the comorbidity is the key aspect to underline their different impacts. One UK doctor says "I'd rather have HIV than diabetes" as life expectancy among diabetes patients is lower than that of HIV. However, HIV has a comorbidity impact on the diabetes.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">We present a quantitative framework to compare and explore comorbidity between diseases. By using neighbourhood based benchmark and topological methods, we have built comorbidity relationships network based on the OMIM and our identified significant genes. Then based on the gene expression, PPI and signalling pathways data, we investigate the comorbidity association of these 2 infective pathologies with other 7 diseases (heart failure, kidney disorder, breast cancer, neurodegenerative disorders, bone diseases, Type 1 and Type 2 diabetes). Phenotypic association is measured by calculating both the Relative Risk as the quantified measures of comorbidity tendency of two disease pairs and the ϕ-correlation to measure the robustness of the comorbidity associations. The differential gene expression profiling strongly suggests that the response of SARS affected patients seems to be mainly an innate inflammatory response and statistically dysregulates a large number of genes, pathways and PPIs subnetworks in different pathologies such as chronic heart failure (21 genes), breast cancer (16 genes) and bone diseases (11 genes). HIV-1 induces comorbidities relationship with many other diseases, particularly strong correlation with the neurological, cancer, metabolic and immunological diseases. Similar comorbidities risk is observed from the clinical information. Moreover, SARS and HIV infections dysregulate 4 genes (ANXA3, GNS, HIST1H1C, RASA3) and 3 genes (HBA1, TFRC, GHITM) respectively that affect the ageing process. It is notable that HIV and SARS similarly dysregulated 11 genes and 3 pathways. Only 4 significantly dysregulated genes are common between SARS-CoV and MERS-CoV, including NFKBIA that is a key regulator of immune responsiveness implicated in susceptibility to infectious and inflammatory diseases.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Our method presents a ripe opportunity to use data-driven approaches for advancing our current knowledge on disease mechanism and predicting disease comorbidities in a quantitative way.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moni</LastName><ForeName>Mohammad Ali</ForeName><Initials>MA</Initials><AffiliationInfo><Affiliation>Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK. Mohammad.Moni@cl.cam.ac.uk.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liò</LastName><ForeName>Pietro</ForeName><Initials>P</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>10</Month><Day>24</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Bioinformatics</MedlineTA><NlmUniqueID>100965194</NlmUniqueID><ISSNLinking>1471-2105</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002908" MajorTopicYN="N">Chronic Disease</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015897" MajorTopicYN="N">Comorbidity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015658" MajorTopicYN="N">HIV Infections</DescriptorName><QualifierName UI="Q000150" MajorTopicYN="Y">complications</QualifierName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015497" MajorTopicYN="N">HIV-1</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060066" MajorTopicYN="N">Protein Interaction Maps</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D045473" MajorTopicYN="N">SARS Virus</DescriptorName><QualifierName UI="Q000502" 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