{"doi":"10.1101/2025.08.27.25334445","title":"Nasopharyngeal microbiome composition and its clinical correlates in children hospitalized with severe pneumonia in East Africa","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Background</jats:title>\n                  <jats:p>Pneumonia remains the leading cause of infectious mortality in children under five, with the highest burden in sub-Saharan Africa. Dysbiosis in nasopharyngeal (NP) microbiota may influence pneumonia susceptibility and progression, but little is known about its composition or clinical relevance in low- and middle-income countries (LMICs). We characterized the NP microbiota of children hospitalized with severe pneumonia in East Africa and investigated associations with clinical outcomes.</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>We performed 16S rRNA partial gene sequencing of NP swabs collected at hospital admission from 876 children enrolled in the COAST trial across five sites in Kenya and Uganda. Clinical, demographic, and virological data were prospectively collected. Microbial profiles were analysed using hierarchical clustering, non-metric multidimensional scaling (NMDS), and multivariable regression to assess associations with respiratory viral infections, sepsis, cyanosis, bacteraemia, coma, HIV status, malnutrition, sickle cell disease (SCD), malaria, and mortality.</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Findings</jats:title>\n                  <jats:p>\n                    The nasopharyngeal microbiome was structured in six distinct clusters, each dominated by different genera, including\n                    <jats:italic>Staphylococcus</jats:italic>\n                    ,\n                    <jats:italic>Streptococcus</jats:italic>\n                    ,\n                    <jats:italic>Haemophilus</jats:italic>\n                    ,\n                    <jats:italic>Dolosigranulum</jats:italic>\n                    ,\n                    <jats:italic>Corynebacterium</jats:italic>\n                    , and\n                    <jats:italic>Moraxella</jats:italic>\n                    . NMDS revealed significant alignment between different microbiome clusters and key clinical outcomes: clusters dominated by\n                    <jats:italic>Corynebacterium</jats:italic>\n                    and\n                    <jats:italic>Dolosigranulum</jats:italic>\n                    were directionally associated with mortality (p &lt; 0.001). Notably,\n                    <jats:italic>Corynebacterium</jats:italic>\n                    abundance was elevated in children who died within 48 hours of admission, then declined over longer survival intervals, approaching levels observed in survivors.\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Interpretation</jats:title>\n                  <jats:p>\n                    These data provide one of the largest high-resolution surveys of the paediatric upper airway microbiome in Africa and identify microbial patterns associated with viral infection, HIV status, early death and bacteraemia. The unexpected association between\n                    <jats:italic>Corynebacterium</jats:italic>\n                    and mortality may reflect distinct species composition in LMIC settings, warranting further investigation using species-resolved metagenomics. These findings lay the groundwork for microbiome-based risk stratification in childhood pneumonia.\n                  </jats:p>\n                </jats:sec>","journal":null,"year":null,"id":639406,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1661223,"name":"Elijah T. Gicheru","orcid":null,"position":1,"is_corresponding":false},{"id":1592531,"name":"Maureen W. Mburu","orcid":null,"position":2,"is_corresponding":false},{"id":1661224,"name":"Mercy S. Sada","orcid":null,"position":3,"is_corresponding":false},{"id":1661225,"name":"Omar Nyawa","orcid":null,"position":4,"is_corresponding":false},{"id":800556,"name":"Martin Mutunga","orcid":null,"position":5,"is_corresponding":false},{"id":1661226,"name":"Clement Lewa","orcid":null,"position":6,"is_corresponding":false},{"id":1661227,"name":"Robinson Cheruiyot","orcid":null,"position":7,"is_corresponding":false},{"id":495162,"name":"Sarah Kiguli","orcid":"0000-0002-8764-4161","position":8,"is_corresponding":false},{"id":1661230,"name":"Peter Olupot-Olupot","orcid":null,"position":9,"is_corresponding":false},{"id":827872,"name":"Rita Muhindo","orcid":"0000-0003-4252-5924","position":10,"is_corresponding":false},{"id":1661232,"name":"Christabel Mogaka","orcid":null,"position":11,"is_corresponding":false},{"id":1661233,"name":"Thomas N Williams","orcid":null,"position":12,"is_corresponding":false},{"id":621548,"name":"Charles N. Agoti","orcid":"0000-0002-2160-567X","position":13,"is_corresponding":false},{"id":827877,"name":"Kathryn Maitland","orcid":"0000-0002-0007-0645","position":14,"is_corresponding":false},{"id":1661235,"name":"Charles J. Sande","orcid":null,"position":15,"is_corresponding":false},{"id":1592527,"name":"Timothy O. Makori","orcid":"0000-0003-4482-9729","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Nasopharyngeal microbiome composition and its clinical correlates in children hospitalized with severe pneumonia in East Africa","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Background</jats:title>\n                  <jats:p>Pneumonia remains the leading cause of infectious mortality in children under five, with the highest burden in sub-Saharan Africa. Dysbiosis in nasopharyngeal (NP) microbiota may influence pneumonia susceptibility and progression, but little is known about its composition or clinical relevance in low- and middle-income countries (LMICs). We characterized the NP microbiota of children hospitalized with severe pneumonia in East Africa and investigated associations with clinical outcomes.</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>We performed 16S rRNA partial gene sequencing of NP swabs collected at hospital admission from 876 children enrolled in the COAST trial across five sites in Kenya and Uganda. Clinical, demographic, and virological data were prospectively collected. Microbial profiles were analysed using hierarchical clustering, non-metric multidimensional scaling (NMDS), and multivariable regression to assess associations with respiratory viral infections, sepsis, cyanosis, bacteraemia, coma, HIV status, malnutrition, sickle cell disease (SCD), malaria, and mortality.</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Findings</jats:title>\n                  <jats:p>\n                    The nasopharyngeal microbiome was structured in six distinct clusters, each dominated by different genera, including\n                    <jats:italic>Staphylococcus</jats:italic>\n                    ,\n                    <jats:italic>Streptococcus</jats:italic>\n                    ,\n                    <jats:italic>Haemophilus</jats:italic>\n                    ,\n                    <jats:italic>Dolosigranulum</jats:italic>\n                    ,\n                    <jats:italic>Corynebacterium</jats:italic>\n                    , and\n                    <jats:italic>Moraxella</jats:italic>\n                    . NMDS revealed significant alignment between different microbiome clusters and key clinical outcomes: clusters dominated by\n                    <jats:italic>Corynebacterium</jats:italic>\n                    and\n                    <jats:italic>Dolosigranulum</jats:italic>\n                    were directionally associated with mortality (p &lt; 0.001). Notably,\n                    <jats:italic>Corynebacterium</jats:italic>\n                    abundance was elevated in children who died within 48 hours of admission, then declined over longer survival intervals, approaching levels observed in survivors.\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Interpretation</jats:title>\n                  <jats:p>\n                    These data provide one of the largest high-resolution surveys of the paediatric upper airway microbiome in Africa and identify microbial patterns associated with viral infection, HIV status, early death and bacteraemia. The unexpected association between\n                    <jats:italic>Corynebacterium</jats:italic>\n                    and mortality may reflect distinct species composition in LMIC settings, warranting further investigation using species-resolved metagenomics. These findings lay the groundwork for microbiome-based risk stratification in childhood pneumonia.\n                  </jats:p>\n                </jats:sec>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":null,"pmcid":null,"openalex_id":null,"authors":[],"funders":[{"funder_name":"Wellcome Trust","grant_id":"102231","title":null}],"total_grants":1,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"cc-by-nc","oa_locations":[{"url":"https://www.medrxiv.org/content/medrxiv/early/2025/08/29/2025.08.27.25334445.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2025.08.27.25334445","host_type":"publisher"},{"url":"https://europepmc.org/article/PPR/PPR1074653","host_type":"Europe_PMC"},{"url":"https://europepmc.org/api/fulltextRepo?pprId=PPR1074653&type=FILE&fileName=EMS208385-pdf.pdf&mimeType=application/pdf","host_type":"Europe_PMC"}],"fields_of_study":[],"mesh_terms":[],"keywords":[],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T00:17:34.202885Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}