{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T09:46:09Z","timestamp":1792835169555,"version":"4.5.0"},"reference-count":50,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T00:00:00Z","timestamp":1722124800000},"content-version":"vor","delay-in-days":27,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010767","name":"Innovative Medicines Initiative","doi-asserted-by":"publisher","award":["115010"],"award-info":[{"award-number":["115010"]}],"id":[{"id":"10.13039\/501100010767","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Clinical &amp;amp; Translational Med"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Clustering approaches using single\n                      <jats:italic>omics<\/jats:italic>\n                      platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi\u2010omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To determine whether multi\u2010omics integration of sputum leads to improved granularity of the molecular classification of severe asthma.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed six \u2010\n                      <jats:italic>omics<\/jats:italic>\n                      data blocks\u2013microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing\u2013from induced sputum samples of 57 severe asthma patients, 15 mild\u2010moderate asthma patients, and 13 healthy volunteers in the U\u2010BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi\u2010omics datasets of the 72 asthmatics.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Five stable omics\u2010associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex\/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant\n                      <jats:italic>Moraxella catarrhalis<\/jats:italic>\n                      and\n                      <jats:italic>Haemophilus influenzae<\/jats:italic>\n                      . OAC4 was associated with pathways linked to IL\u201022 cytokine activation, with the prediction of therapeutic response to anti\u2010IL22 antibody therapy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Multi\u2010omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high\u2010dimensional interactions will contribute to a more comprehensive understanding of complex endotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Unsupervised clustering on sputum multi\u2010omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\n                            One severe neutrophilic asthma cluster was linked to\n                            <jats:italic>Moraxella catarrhalis<\/jats:italic>\n                            and to a lesser extent\n                            <jats:italic>Haemophilus influenzae<\/jats:italic>\n                            while the second cluster to activation of IL\u201022.\n                          <\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ctm2.1771","type":"journal-article","created":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T03:40:05Z","timestamp":1722138005000},"source":"Crossref","is-referenced-by-count":38,"title":["Endotypes of severe neutrophilic and eosinophilic asthma from multi\u2010omics integration of U\u2010BIOPRED sputum samples"],"prefix":"10.1002","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2479-3861","authenticated-orcid":false,"given":"Nazanin Zounemat","family":"Kermani","sequence":"first","affiliation":[{"name":"National Heart and Lung Institute Imperial College London  London UK"},{"name":"Data Science Institute Imperial College London London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuan\u2010Xing","family":"Li","sequence":"additional","affiliation":[{"name":"Respiratory Medicine Unit Department of Medicine &amp; Centre for Molecular Medicine Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Versi","sequence":"additional","affiliation":[{"name":"National Heart and Lung Institute Imperial College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusef","family":"Badi","sequence":"additional","affiliation":[{"name":"National Heart and Lung 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