Matthew Moll, Julian Hecker, John Platig, Jingzhou Zhang, Auyon J Ghosh, Katherine A Pratte, Rui-Sheng Wang, Davin Hill, Iain R Konigsberg, Joe W Chiles, Craig P Hersh, Peter J Castaldi, Kimberly Glass, Jennifer G Dy, Don D Sin, Ruth Tal-Singer, Majd Mouded, Stephen I Rennard, Gary P Anderson, Gregory L Kinney, Russell P Bowler, Jeffrey L Curtis, Merry-Lynn McDonald, Edwin K Silverman, Brian D Hobbs, Michael H Cho
{"title":"在 COPDGene 和 ECLIPSE 队列研究中,多基因和转录风险评分可识别慢性阻塞性肺病亚型。","authors":"Matthew Moll, Julian Hecker, John Platig, Jingzhou Zhang, Auyon J Ghosh, Katherine A Pratte, Rui-Sheng Wang, Davin Hill, Iain R Konigsberg, Joe W Chiles, Craig P Hersh, Peter J Castaldi, Kimberly Glass, Jennifer G Dy, Don D Sin, Ruth Tal-Singer, Majd Mouded, Stephen I Rennard, Gary P Anderson, Gregory L Kinney, Russell P Bowler, Jeffrey L Curtis, Merry-Lynn McDonald, Edwin K Silverman, Brian D Hobbs, Michael H Cho","doi":"10.1016/j.ebiom.2024.105429","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.</p><p><strong>Methods: </strong>We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.</p><p><strong>Findings: </strong>We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined \"high activity\" (low PRS, high TRS) and \"severe risk\" (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. \"High activity\" but not \"severe risk\" participants had greater prospective FEV<sub>1</sub> decline (COPDGene: -51 mL/year; ECLIPSE: -40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.</p><p><strong>Interpretation: </strong>Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.</p><p><strong>Funding: </strong>National Institutes of Health.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"110 ","pages":"105429"},"PeriodicalIF":9.7000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570824/pdf/","citationCount":"0","resultStr":"{\"title\":\"Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes in the COPDGene and ECLIPSE cohort studies.\",\"authors\":\"Matthew Moll, Julian Hecker, John Platig, Jingzhou Zhang, Auyon J Ghosh, Katherine A Pratte, Rui-Sheng Wang, Davin Hill, Iain R Konigsberg, Joe W Chiles, Craig P Hersh, Peter J Castaldi, Kimberly Glass, Jennifer G Dy, Don D Sin, Ruth Tal-Singer, Majd Mouded, Stephen I Rennard, Gary P Anderson, Gregory L Kinney, Russell P Bowler, Jeffrey L Curtis, Merry-Lynn McDonald, Edwin K Silverman, Brian D Hobbs, Michael H Cho\",\"doi\":\"10.1016/j.ebiom.2024.105429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.</p><p><strong>Methods: </strong>We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.</p><p><strong>Findings: </strong>We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined \\\"high activity\\\" (low PRS, high TRS) and \\\"severe risk\\\" (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. \\\"High activity\\\" but not \\\"severe risk\\\" participants had greater prospective FEV<sub>1</sub> decline (COPDGene: -51 mL/year; ECLIPSE: -40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.</p><p><strong>Interpretation: </strong>Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. 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Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes in the COPDGene and ECLIPSE cohort studies.
Background: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.
Methods: We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.
Findings: We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined "high activity" (low PRS, high TRS) and "severe risk" (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. "High activity" but not "severe risk" participants had greater prospective FEV1 decline (COPDGene: -51 mL/year; ECLIPSE: -40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.
Interpretation: Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.
EBioMedicineBiochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
CiteScore
17.70
自引率
0.90%
发文量
579
审稿时长
5 weeks
期刊介绍:
eBioMedicine is a comprehensive biomedical research journal that covers a wide range of studies that are relevant to human health. Our focus is on original research that explores the fundamental factors influencing human health and disease, including the discovery of new therapeutic targets and treatments, the identification of biomarkers and diagnostic tools, and the investigation and modification of disease pathways and mechanisms. We welcome studies from any biomedical discipline that contribute to our understanding of disease and aim to improve human health.