<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>62422</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>10</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>9</volume>
    <type>article</type>
    <publisherName>Nature Publ. Group</publisherName>
    <publisherPlace>London</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Metaproteogenomic analysis of saliva samples from Parkinson's disease patients with cognitive impairment</title>
    <abstract language="eng">Cognitive impairment (CI) is very common in patients with Parkinson’s Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.</abstract>
    <parentTitle language="eng">npj Biofilms and Microbiomes</parentTitle>
    <identifier type="issn">2055-5008</identifier>
    <identifier type="doi">10.1038/s41522-023-00452-x</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-624228</identifier>
    <enrichment key="opus_doi_flag">true</enrichment>
    <enrichment key="opus_import_data">{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T23:31:56Z","timestamp":1725147116974},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T00:00:00Z","timestamp":1700265600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T00:00:00Z","timestamp":1700265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000614","name":"Federation of European Microbiological Societies","doi-asserted-by":"publisher","award":["FEMS-GO-2020-197"],"id":[{"id":"10.13039\/501100000614","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Biofilms Microbiomes"],"abstract":"&lt;jats:title&gt;Abstract&lt;\/jats:title&gt;&lt;jats:p&gt;Cognitive impairment (CI) is very common in patients with Parkinson\u2019s Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.&lt;\/jats:p&gt;","DOI":"10.1038\/s41522-023-00452-x","type":"journal-article","created":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T20:02:04Z","timestamp":1700337724000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Metaproteogenomic analysis of saliva samples from Parkinson\u2019s disease patients with cognitive impairment"],"prefix":"10.1038","volume":"9","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-5162-2000","authenticated-orcid":false,"given":"Muzaffer","family":"Ar\u0131kan","sequence":"first","affiliation":[]},{"given":"Tu\u011f\u00e7e Kahraman","family":"Demir","sequence":"additional","affiliation":[]},{"given":"Zeynep","family":"Y\u0131ld\u0131z","sequence":"additional","affiliation":[]},{"given":"\u00d6zkan Ufuk","family":"Nalbanto\u011flu","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-1173-1701","authenticated-orcid":false,"given":"Nur Damla","family":"Korkmaz","sequence":"additional","affiliation":[]},{"given":"Nesrin H.","family":"Y\u0131lmaz","sequence":"additional","affiliation":[]},{"given":"Aysu","family":"\u015een","sequence":"additional","affiliation":[]},{"given":"Mutlu","family":"\u00d6zcan","sequence":"additional","affiliation":[]},{"given":"Thilo","family":"Muth","sequence":"additional","affiliation":[]},{"given":"L\u00fctf\u00fc","family":"Hano\u011flu","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-2752-1223","authenticated-orcid":false,"given":"S\u00fcleyman","family":"Y\u0131ld\u0131r\u0131m","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,18]]},"reference":[{"key":"452_CR1","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1016\/S0140-6736(15)60692-4","volume":"386","author":"T Vos","year":"2015","unstructured":"Vos, T. et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990\u20132013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386, 743\u2013800 (2015).","journal-title":"Lancet"},{"key":"452_CR2","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1212\/01.wnl.0000247740.47667.03","volume":"68","author":"ER Dorsey","year":"2007","unstructured":"Dorsey, E. R. et al. Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology 68, 384\u2013386 (2007).","journal-title":"Neurology"},{"key":"452_CR3","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1016\/S0140-6736(14)61393-3","volume":"386","author":"LV Kalia","year":"2015","unstructured":"Kalia, L. V. &amp; Lang, A. E. Parkinson\u2019s disease. Lancet 386, 896\u2013912 (2015).","journal-title":"Lancet"},{"key":"452_CR4","unstructured":"O\u2019Callaghan, C. &amp; Lewis, S. J. G. Cognition in Parkinson\u2019s disease. in International Review of Neurobiology, 1st edn Vol. 133 (Elsevier Inc., 2017)."},{"key":"452_CR5","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1038\/s41572-021-00280-3","volume":"7","author":"D Aarsland","year":"2021","unstructured":"Aarsland, D. et al. Parkinson disease-associated cognitive impairment. Nat. Rev. Dis. Prim. 7, 47 (2021).","journal-title":"Nat. Rev. Dis. Prim."},{"key":"452_CR6","doi-asserted-by":"crossref","unstructured":"Aro, K., Wei, F., Wong, D. T. &amp; Tu, M. Saliva liquid biopsy for point-of-care applications. Front. Public Health. 5, 77 (2017).","DOI":"10.3389\/fpubh.2017.00077"},{"key":"452_CR7","doi-asserted-by":"publisher","first-page":"14","DOI":"10.5603\/PJNNS.a2020.0011","volume":"54","author":"M Figura","year":"2020","unstructured":"Figura, M. &amp; Friedman, A. In search of Parkinson\u2019s disease biomarkers - is the answer in our mouths? A systematic review of the literature on salivary biomarkers of Parkinson\u2019s disease. Neurol. Neurochir. Pol. 54, 14\u201320 (2020).","journal-title":"Neurol. Neurochir. Pol."},{"key":"452_CR8","doi-asserted-by":"publisher","first-page":"e0151156","DOI":"10.1371\/journal.pone.0151156","volume":"11","author":"G Vivacqua","year":"2016","unstructured":"Vivacqua, G. et al. Abnormal salivary total and oligomeric alpha-synuclein in Parkinson\u2019s disease. PLoS One 11, e0151156 (2016).","journal-title":"PLoS One"},{"key":"452_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/srep28143","volume":"6","author":"W Kang","year":"2016","unstructured":"Kang, W. et al. Salivary total \u03b1-synuclein, oligomeric \u03b1-synuclein and SNCA variants in Parkinson\u2019s disease patients. Sci. Rep. 6, 28143 (2016).","journal-title":"Sci. Rep."},{"key":"452_CR10","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.parkreldis.2019.02.014","volume":"63","author":"G Vivacqua","year":"2019","unstructured":"Vivacqua, G. et al. Salivary alpha-synuclein in the diagnosis of Parkinson\u2019s disease and progressive supranuclear palsy. Parkinson. Relat. Disord. 63, 143\u2013148 (2019).","journal-title":"Parkinson. Relat. Disord."},{"key":"452_CR11","doi-asserted-by":"publisher","first-page":"1114","DOI":"10.1002\/mds.26605","volume":"31","author":"CH Adler","year":"2016","unstructured":"Adler, C. H. &amp; Beach, T. G. Neuropathological basis of nonmotor manifestations of Parkinson\u2019s disease. Mov. Disord. 31, 1114\u20131119 (2016).","journal-title":"Mov. Disord."},{"key":"452_CR12","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1007\/s00455-015-9612-7","volume":"30","author":"L Mu","year":"2015","unstructured":"Mu, L. et al. Alpha-synuclein pathology in sensory nerve terminals of the upper aerodigestive tract of Parkinson\u2019s Disease patients. Dysphagia 30, 404\u2013417 (2015).","journal-title":"Dysphagia"},{"key":"452_CR13","doi-asserted-by":"publisher","first-page":"1271","DOI":"10.1007\/s00455-021-10387-0","volume":"37","author":"P Wang","year":"2022","unstructured":"Wang, P. et al. Six-year follow-up of Dysphagia in patients with Parkinson\u2019s Disease. Dysphagia 37, 1271\u20131278 (2022).","journal-title":"Dysphagia"},{"key":"452_CR14","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1007\/s00455-020-10102-5","volume":"35","author":"DJ van Wamelen","year":"2020","unstructured":"van Wamelen, D. J. et al. Drooling in Parkinson\u2019s Disease: prevalence and progression from the non-motor international longitudinal study. Dysphagia 35, 955\u2013961 (2020).","journal-title":"Dysphagia"},{"key":"452_CR15","doi-asserted-by":"publisher","first-page":"619","DOI":"10.3233\/JPD-202459","volume":"11","author":"V Fleury","year":"2021","unstructured":"Fleury, V. et al. Oral dysbiosis and inflammation in Parkinson\u2019s disease. J. Parkinsons. Dis. 11, 619\u2013631 (2021).","journal-title":"J. Parkinsons. Dis."},{"key":"452_CR16","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.3390\/microorganisms9081616","volume":"9","author":"NS Rozas","year":"2021","unstructured":"Rozas, N. S., Tribble, G. D. &amp; Jeter, C. B. Oral factors that impact the oral microbiota in Parkinson\u2019s disease. Microorganisms 9, 1616 (2021).","journal-title":"Microorganisms"},{"key":"452_CR17","first-page":"1","volume":"13","author":"JT Nearing","year":"2022","unstructured":"Nearing, J. T. et al. Microbiome differential abundance methods produce different results across 38 datasets. Nat. Commun. 13, 1\u201310 (2022).","journal-title":"Nat. Commun."},{"key":"452_CR18","doi-asserted-by":"publisher","first-page":"140659","DOI":"10.1016\/j.bbapap.2021.140659","volume":"1869","author":"DC Granato","year":"2021","unstructured":"Granato, D. C. et al. Meta-omics analysis indicates the saliva microbiome and its proteins associated with the prognosis of oral cancer patients. Biochim. Biophys. Acta. Proteins Proteom. 1869, 140659 (2021).","journal-title":"Biochim. Biophys. Acta. Proteins Proteom."},{"key":"452_CR19","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.parkreldis.2017.02.026","volume":"38","author":"PAB Pereira","year":"2017","unstructured":"Pereira, P. A. B. et al. Oral and nasal microbiota in Parkinson\u2019s disease. Parkinson. Relat. Disord. 38, 61\u201367 (2017).","journal-title":"Parkinson. Relat. Disord."},{"key":"452_CR20","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.neuroscience.2021.10.011","volume":"480","author":"Z Li","year":"2022","unstructured":"Li, Z. et al. Oral, nasal, and gut microbiota in Parkinson\u2019s disease. Neuroscience 480, 65\u201378 (2022).","journal-title":"Neuroscience"},{"key":"452_CR21","doi-asserted-by":"publisher","first-page":"e0218252","DOI":"10.1371\/journal.pone.0218252","volume":"14","author":"D Mihaila","year":"2019","unstructured":"Mihaila, D. et al. The oral microbiome of early stage Parkinson\u2019s disease and its relationship with functional measures of motor and non-motor function. PLoS One 14, e0218252 (2019).","journal-title":"PLoS One"},{"key":"452_CR22","doi-asserted-by":"publisher","first-page":"1910","DOI":"10.1021\/jo3018473","volume":"78","author":"C Wu","year":"2013","unstructured":"Wu, C., Dunaway-Mariano, D. &amp; Mariano, P. S. Design, synthesis, and evaluation of inhibitors of Pyruvate Phosphate Dikinase. J. Org. Chem. 78, 1910\u20131922 (2013).","journal-title":"J. Org. Chem."},{"key":"452_CR23","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1128\/jb.124.1.55-61.1975","volume":"124","author":"T Yamada","year":"1975","unstructured":"Yamada, T. &amp; Carlsson, J. Regulation of lactate dehydrogenase and change of fermentation products in streptococci. J. Bacteriol. 124, 55\u201361 (1975).","journal-title":"J. Bacteriol."},{"key":"452_CR24","doi-asserted-by":"publisher","first-page":"1039","DOI":"10.1042\/BST0391039","volume":"39","author":"BC Krasity","year":"2011","unstructured":"Krasity, B. C., Troll, J. V., Weiss, J. P. &amp; McFall-Ngai, M. J. LBP\/BPI proteins and their relatives: conservation over evolution and roles in mutualism. Biochem. Soc. Trans. 39, 1039\u20131044 (2011).","journal-title":"Biochem. Soc. Trans."},{"key":"452_CR25","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/j.bbi.2020.01.018","volume":"87","author":"RS Wijeyekoon","year":"2020","unstructured":"Wijeyekoon, R. S. et al. Peripheral innate immune and bacterial signals relate to clinical heterogeneity in Parkinson\u2019s disease. Brain. Behav. Immun. 87, 473\u2013488 (2020).","journal-title":"Brain. Behav. Immun."},{"key":"452_CR26","doi-asserted-by":"publisher","first-page":"1689","DOI":"10.1002\/mds.21507","volume":"22","author":"M Emre","year":"2007","unstructured":"Emre, M. et al. Clinical diagnostic criteria for dementia associated with Parkinson\u2019s disease. Mov. Disord. 22, 1689\u20131707 (2007).","journal-title":"Mov. Disord."},{"key":"452_CR27","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1002\/mds.24893","volume":"27","author":"I Litvan","year":"2012","unstructured":"Litvan, I. et al. Diagnostic criteria for mild cognitive impairment in Parkinson\u2019s disease: movement disorder society task force guidelines. Mov. Disord. 27, 349\u2013356 (2012).","journal-title":"Mov. Disord."},{"key":"452_CR28","doi-asserted-by":"publisher","first-page":"e0235821","DOI":"10.1128\/spectrum.02358-21","volume":"10","author":"M Arikan","year":"2022","unstructured":"Arikan, M. et al. Axillary microbiota is associated with cognitive impairment in Parkinson\u2019s disease patients. Microbiol. Spectr. 10, e0235821 (2022).","journal-title":"Microbiol. Spectr."},{"key":"452_CR29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-55663-0","volume":"9","author":"MC Beker","year":"2019","unstructured":"Beker, M. C. et al. Interaction of melatonin and Bmal1 in the regulation of PI3K\/AKT pathway components and cellular survival. Sci. Rep. 9, 19082 (2019).","journal-title":"Sci. Rep."},{"key":"452_CR30","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1093\/bioinformatics\/btx617","volume":"34","author":"N Weber","year":"2018","unstructured":"Weber, N. et al. Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis. Bioinformatics 34, 1411\u20131413 (2018).","journal-title":"Bioinformatics"},{"key":"452_CR31","doi-asserted-by":"publisher","first-page":"590","DOI":"10.1093\/nar\/gks1219","volume":"41","author":"C Quast","year":"2013","unstructured":"Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41, 590\u2013596 (2013).","journal-title":"Nucleic Acids Res"},{"key":"452_CR32","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-018-0605-2","volume":"6","author":"NM Davis","year":"2018","unstructured":"Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A. &amp; Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 226 (2018).","journal-title":"Microbiome"},{"key":"452_CR33","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1038\/s41587-019-0209-9","volume":"37","author":"E Bolyen","year":"2019","unstructured":"Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852\u2013857 (2019).","journal-title":"Nat. Biotechnol."},{"key":"452_CR34","doi-asserted-by":"publisher","first-page":"e61217","DOI":"10.1371\/journal.pone.0061217","volume":"8","author":"PJ McMurdie","year":"2013","unstructured":"McMurdie, P. J. &amp; Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).","journal-title":"PLoS One"},{"key":"452_CR35","doi-asserted-by":"publisher","first-page":"e1009442","DOI":"10.1371\/journal.pcbi.1009442","volume":"17","author":"H Mallick","year":"2021","unstructured":"Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e1009442 (2021).","journal-title":"PLoS Comput. Biol."},{"key":"452_CR36","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2011-12-6-r60","volume":"12","author":"N Segata","year":"2011","unstructured":"Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011).","journal-title":"Genome Biol."},{"key":"452_CR37","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17041-7","volume":"11","author":"H Lin","year":"2020","unstructured":"Lin, H. &amp; Peddada, S. Das Analysis of compositions of microbiomes with bias correction. Nat. Commun. 11, 3514 (2020).","journal-title":"Nat. Commun."},{"key":"452_CR38","doi-asserted-by":"crossref","unstructured":"Wickham, H. ggplot2 edn 1, Vol. 10 (Springer New York, 2009).","DOI":"10.1007\/978-0-387-98141-3_1"},{"key":"452_CR39","doi-asserted-by":"publisher","unstructured":"Zhu, J. et al. Over 50,000 Metagenomically assembled draft genomes for the human oral microbiome reveal new taxa. Genom. Proteom. Bioinform. https:\/\/doi.org\/10.1016\/j.gpb.2021.05.001 (2021).","DOI":"10.1016\/j.gpb.2021.05.001"},{"key":"452_CR40","doi-asserted-by":"publisher","first-page":"D506","DOI":"10.1093\/nar\/gky1049","volume":"47","author":"UniProt Consortium.","year":"2019","unstructured":"UniProt Consortium. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 47, D506\u2013D515 (2019).","journal-title":"Nucleic Acids Res."},{"key":"452_CR41","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-022-02753-4","volume":"23","author":"S Ma","year":"2022","unstructured":"Ma, S. et al. Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin. Genome Biol. 23, 208 (2022).","journal-title":"Genome Biol."},{"key":"452_CR42","doi-asserted-by":"publisher","first-page":"2752","DOI":"10.1002\/pmic.201000679","volume":"11","author":"T Schneider","year":"2011","unstructured":"Schneider, T. et al. Structure and function of the symbiosis partners of the lung lichen (Lobaria pulmonaria L. Hoffm.) analyzed by metaproteomics. Proteomics 11, 2752\u20132756 (2011).","journal-title":"Proteomics"},{"key":"452_CR43","doi-asserted-by":"publisher","first-page":"D309","DOI":"10.1093\/nar\/gky1085","volume":"47","author":"J Huerta-Cepas","year":"2019","unstructured":"Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309\u2013D314 (2019).","journal-title":"Nucleic Acids Res."},{"key":"452_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15252\/msb.20178124","volume":"14","author":"R Argelaguet","year":"2018","unstructured":"Argelaguet, R. et al. Multi\u2010omics factor analysis\u2014a framework for unsupervised integration of multi\u2010omics data sets. Mol. Syst. Biol. 14, 1\u201313 (2018).","journal-title":"Mol. Syst. Biol."},{"key":"452_CR45","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-020-02015-1","volume":"21","author":"R Argelaguet","year":"2020","unstructured":"Argelaguet, R. et al. MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data. Genome Biol. 21, 111 (2020).","journal-title":"Genome Biol."}],"container-title":["npj Biofilms and Microbiomes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41522-023-00452-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41522-023-00452-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41522-023-00452-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T20:07:12Z","timestamp":1700338032000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41522-023-00452-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,18]]},"references-count":45,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["452"],"URL":"https:\/\/doi.org\/10.1038\/s41522-023-00452-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2022.12.29.22284030","asserted-by":"object"}]},"ISSN":["2055-5008"],"issn-type":[{"value":"2055-5008","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,18]]},"assertion":[{"value":"30 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"86"}}</enrichment>
    <enrichment key="local_crossrefDocumentType">journal-article</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <enrichment key="date_peer_review">16.01.2025</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Muzaffer Arıkan</author>
    <author>Tuğçe Kahraman Demir</author>
    <author>Zeynep Yıldız</author>
    <author>Özkan Ufuk Nalbantoğlu</author>
    <author>Nur Damla Korkmaz</author>
    <author>Nesrin H. Yılmaz</author>
    <author>Aysu Şen</author>
    <author>Mutlu Özcan</author>
    <author>Thilo Muth</author>
    <author>Lütfü Hanoğlu</author>
    <author>Süleyman Yıldırım</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cognitive impairment (CI)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parkinson’s disease (PD)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Metaproteogenomic analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Saliva sample</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">VP Vizepräsident</collection>
    <collection role="institutes" number="">VP.1 eScience</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/62422/s41522-023-00452-x.pdf</file>
    <file>https://opus4.kobv.de/opus4-bam/files/62422/s41522_023_00452_MOESM1_ESM.pdf</file>
  </doc>
</export-example>
