Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/36583
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dc.contributor.authorMarçalo, R. F. Santospt_PT
dc.contributor.authorRodrigues, G.pt_PT
dc.contributor.authorCórdova, T.pt_PT
dc.contributor.authorNeves, V.pt_PT
dc.contributor.authorNeto, S.pt_PT
dc.contributor.authorPinheiro, M.pt_PT
dc.contributor.authorSantos, M. A. S.pt_PT
dc.contributor.authorSimão, P.pt_PT
dc.contributor.authorMendes, A.pt_PT
dc.contributor.authorAndrade, L.pt_PT
dc.contributor.authorMarques, A.pt_PT
dc.contributor.authorMoura, G. R.pt_PT
dc.date.accessioned2023-03-16T16:20:17Z-
dc.date.available2023-03-16T16:20:17Z-
dc.date.issued2022-12-01-
dc.identifier.issn0903-1936-
dc.identifier.urihttp://hdl.handle.net/10773/36583-
dc.description.abstractPeople with COPD vary substantially on their pulmonary (e.g., airway obstruction) and extra-pulmonary (e.g., symptoms, functional status) manifestations. The aim of this study was to relate this high heterogeneity to the patient’s genetic Background, namely focusing on polymorphisms associated with COPD and COPD-associated phenotypes and features. Summary statistics for COPD and COPD-associated phenotypes and features (emphysema, FEV1, FEV1/FVC, smoking, BMI, asthma, airway responsiveness, coronary heart disease, blood pressure, pulmonary artery enlargement, resting heart rate and resting oxygen saturation) were obtained from GWAS Catalog (https://www.ebi.ac.uk/gwas/ accessed in August 2021). A local COPD cohort was genotyped using Global Screening Arrays (GSA-Illumina) and polygenic risk scores were calculated per phenotype/feature. A cluster analysis was then carried out to determine how patients would group according to their assessed genetic risks. The study currently includes 255 participants with COPD (68 [61, 74] years old; 79.61% male; FEV1/FVC 53.02 [41.24, 61.94]). Our preliminary results show that people cluster into 3 main groups based on their genetic risk for emphysema, followed by COPD, whilst their clinical characteristics remained similar among groups. Future work is currently being conducted to further explore these clusters and perform their validation. This work was funded by FEDER funds through COMPETE 2020, Operational Programme for Competitiveness and Internationalization (POCI-01-0145-FEDER-028806), CENTRO 2020 (CENTRO-01-0246-FEDER-000018; CENTRO-08-5864-FSE-000039) and by Fundação para a Ciência e a Tecnologia (UI/BD/151337/2021). The iBiMED is supported by FCT funds under UIDP/04501/2020.pt_PT
dc.language.isoengpt_PT
dc.publisherEuropean Respiratory Societypt_PT
dc.relationPOCI-01-0145-FEDER-028806pt_PT
dc.relationCENTRO-01-0246-FEDER-000018pt_PT
dc.relationCENTRO-08-5864-FSE-000039pt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/OE/UI%2FBD%2F151337%2F2021/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04501%2F2020/PTpt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectCOPDpt_PT
dc.subjectGenomicspt_PT
dc.subjectGeneticspt_PT
dc.titleCOPD: can genetic Background inform about disease heterogeneity?pt_PT
dc.typeconferenceObjectpt_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
ua.event.date4-6 setembro, 2022pt_PT
degois.publication.issuesuppl 66pt_PT
degois.publication.titleEuropean Respiratory Journal. ERS International Congress 2022pt_PT
degois.publication.volume60pt_PT
dc.identifier.doi10.1183/13993003.congress-2022.1811pt_PT
dc.identifier.essn1399-3003-
dc.identifier.articlenumber1811pt_PT
Appears in Collections:ESSUA - Comunicações
DCM - Comunicações
IBIMED - Comunicações
Lab3R - Comunicações



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