1 Ocak 2022 Dergi makalesi Açık Erişim

Yildirim, Suleyman; Nalbantoglu, Ozkan Ufuk; Bayraktar, Abdulahad; Ercan, Fatma Betul; Gundogdu, Aycan; Velioglu, Halil Aziz; Gol, Mehmet Fatih; Soylu, Ayten Ekinci; Koc, Fatma; Gulpinar, Ezgi Aslan; Kadak, Kubra Sogukkanli; Arikan, Muzaffer; Mardinoglu, Adil; Kocak, Mehmet; Koseoglu, Emel; Hanoglu, Lutfu

DataCite XML

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  <identifier identifierType="DOI">10.48623/aperta.258199</identifier>
  <creators>
    <creator>
      <creatorName>Yildirim, Suleyman</creatorName>
      <givenName>Suleyman</givenName>
      <familyName>Yildirim</familyName>
    </creator>
    <creator>
      <creatorName>Nalbantoglu, Ozkan Ufuk</creatorName>
      <givenName>Ozkan Ufuk</givenName>
      <familyName>Nalbantoglu</familyName>
    </creator>
    <creator>
      <creatorName>Bayraktar, Abdulahad</creatorName>
      <givenName>Abdulahad</givenName>
      <familyName>Bayraktar</familyName>
      <affiliation>Kings Coll London, Fac Dent Oral &amp; Craniofacial Sci, Ctr Host Microbiome Interact, London, England</affiliation>
    </creator>
    <creator>
      <creatorName>Ercan, Fatma Betul</creatorName>
      <givenName>Fatma Betul</givenName>
      <familyName>Ercan</familyName>
      <affiliation>Istanbul Medipol Univ, Grad Program Neurosci, Int Sch Med, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Gundogdu, Aycan</creatorName>
      <givenName>Aycan</givenName>
      <familyName>Gundogdu</familyName>
    </creator>
    <creator>
      <creatorName>Velioglu, Halil Aziz</creatorName>
      <givenName>Halil Aziz</givenName>
      <familyName>Velioglu</familyName>
    </creator>
    <creator>
      <creatorName>Gol, Mehmet Fatih</creatorName>
      <givenName>Mehmet Fatih</givenName>
      <familyName>Gol</familyName>
      <affiliation>Erciyes Univ, Dept Microbiol &amp; Clin Microbiol, Sch Med, Kayseri, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Soylu, Ayten Ekinci</creatorName>
      <givenName>Ayten Ekinci</givenName>
      <familyName>Soylu</familyName>
      <affiliation>Erciyes Univ, Dept Microbiol &amp; Clin Microbiol, Sch Med, Kayseri, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Koc, Fatma</creatorName>
      <givenName>Fatma</givenName>
      <familyName>Koc</familyName>
      <affiliation>Istanbul Medipol Univ, Dept Med Microbiol, Int Sch Med, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Gulpinar, Ezgi Aslan</creatorName>
      <givenName>Ezgi Aslan</givenName>
      <familyName>Gulpinar</familyName>
      <affiliation>Erciyes Univ, Dept Microbiol &amp; Clin Microbiol, Sch Med, Kayseri, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Kadak, Kubra Sogukkanli</creatorName>
      <givenName>Kubra Sogukkanli</givenName>
      <familyName>Kadak</familyName>
      <affiliation>Istanbul Medipol Univ, Grad Program Neurosci, Int Sch Med, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Arikan, Muzaffer</creatorName>
      <givenName>Muzaffer</givenName>
      <familyName>Arikan</familyName>
      <affiliation>Istanbul Medipol Univ, Res Inst Hlth Sci &amp; Technol SABITA, Regenerat &amp; Restorat Med Res Ctr REMER, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Mardinoglu, Adil</creatorName>
      <givenName>Adil</givenName>
      <familyName>Mardinoglu</familyName>
    </creator>
    <creator>
      <creatorName>Kocak, Mehmet</creatorName>
      <givenName>Mehmet</givenName>
      <familyName>Kocak</familyName>
      <affiliation>Univ Tennessee Hlth Sci Ctr, Dept Prevent Med, Memphis, TN USA</affiliation>
    </creator>
    <creator>
      <creatorName>Koseoglu, Emel</creatorName>
      <givenName>Emel</givenName>
      <familyName>Koseoglu</familyName>
      <affiliation>Erciyes Univ, Dept Neurol, Sch Med, Kayseri, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Hanoglu, Lutfu</creatorName>
      <givenName>Lutfu</givenName>
      <familyName>Hanoglu</familyName>
      <affiliation>Istanbul Medipol Univ, Dept Neurol, Sch Med, Istanbul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Stratification Of The Gut Microbiota Composition Landscape Across The Alzheimer'S Disease Continuum In A Turkish Cohort</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/258199</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.48623/aperta.258198</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Alzheimer's disease (AD) is a heterogeneous disorder that spans a continuum with multiple phases, including preclinical, mild cognitive impairment, and dementia. Unlike for most other chronic diseases, human studies reporting on AD gut microbiota in the literature are very limited. With the scarcity of approved drugs for AD therapies, the rational and precise modulation of gut microbiota composition using diet and other tools is a promising approach to the management of AD. Such an approach could be personalized if an AD continuum can first be deconstructed into multiple strata based on specific microbiota features by using single or multiomics techniques. However, stratification of AD gut microbiota has not been systematically investigated before, leaving an important research gap for gut microbiota-based therapeutic approaches. Here, we analyze 16S rRNA amplicon sequencing of stool samples from 27 patients with mild cognitive impairment, 47 patients with AD, and 51 nondemented control subjects by using tools compatible with the compositional nature of microbiota. To stratify the AD gut microbiota community, we applied four machine learning techniques, including partitioning around the medoid clustering and fitting a probabilistic Dirichlet mixture model, the latent Dirichlet allocation model, and we performed topological data analysis for population-scale microbiome stratification based on the Mapper algorithm. These four distinct techniques all converge on Prevotella and Bacteroides stratification of the gut microbiota across the AD continuum, while some methods provided fine-scale resolution in stratifying the community landscape. Finally, we demonstrate that the signature taxa and neuropsychometric parameters together robustly classify the groups. Our results provide a framework for precision nutrition approaches aiming to modulate the AD gut microbiota.</description>
  </descriptions>
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