Dataset Information

Dynamic and prognostic proteomic associations with FEV₁ decline in chronic obstructive pulmonary disease.

ABSTRACT:

Rationale

Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need.

Objective

Identify prognostic and dynamic plasma protein biomarkers of COPD progression.

Methods

We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung. Using SPIROMICS as a discovery cohort, linear mixed models identified baseline proteins that predicted future change in FEV₁ (prognostic model) and proteins whose expression changed with change in lung function (dynamic model). Findings were replicated in COPDGene and MESA-Lung. Using the COPD-enriched cohorts, Gene Set Enrichment Analysis (GSEA) identified proteins shared between COPDGene and SPIROMICS. Metascape identified significant associated pathways.

Measurements and main results

The prognostic model found 7 significant proteins in common (p < 0.05) among all 3 cohorts. After applying false discovery rate (adjusted p < 0.2), leptin remained significant in all three cohorts and growth hormone receptor remained significant in the two COPD cohorts. Elevated baseline levels of leptin and growth hormone receptor were associated with slower rate of decline in FEV₁. Twelve proteins were nominally but not FDR significant in the dynamic model and all were distinct from the prognostic model. Metascape identified several immune related pathways unique to prognostic and dynamic proteins.

Conclusion

We identified leptin as the most reproducible COPD progression biomarker. The difference between prognostic and dynamic proteins suggests disease activity signatures may be different from prognosis signatures.

SUBMITTER: Ruvuna L

PROVIDER: S-EPMC11326337 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic and prognostic proteomic associations with FEV<sub>1</sub> decline in chronic obstructive pulmonary disease.

Ruvuna Lisa L Hijazi Kahkeshan K Guzman Daniel E DE Guo Claire C Loureiro Joseph J Khokhlovich Edward E Morris Melody M Obeidat Ma'en M Pratte Katherine A KA DiLillo Katarina M KM Sharma Sunita S Kechris Katerina K Anzueto Antonio A Barjaktarevic Igor I Bleecker Eugene R ER Casaburi Richard R Comellas Alejandro A Cooper Christopher B CB DeMeo Dawn L DL Foreman Marilyn M Flenaugh Eric L EL Han MeiLan K MK Hanania Nicola A NA Hersh Craig P CP Krishnan Jerry A JA Labaki Wassim W WW Martinez Fernando J FJ O'Neal Wanda K WK Paine Robert R Peters Stephen P SP Woodruff Prescott G PG Wells J Michael JM Wendt Christine H CH Arnold Kelly B KB Barr R Graham RG Curtis Jeffrey L JL Ngo Debby D Bowler Russell P RP

medRxiv : the preprint server for health sciences 20240808

<h4>Rationale</h4>Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need.<h4>Objective</h4>Identify prognostic and dynamic plasma protein biomarkers of COPD progression.<h4>Methods</h4>We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Ath ...[more]

PMID: 39148837

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Dataset Information

Dynamic and prognostic proteomic associations with FEV₁ decline in chronic obstructive pulmonary disease.

Rationale

Objective

Methods

Measurements and main results

Conclusion

Publications

Dynamic and prognostic proteomic associations with FEV<sub>1</sub> decline in chronic obstructive pulmonary disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Dynamic and prognostic proteomic associations with FEV1 decline in chronic obstructive pulmonary disease.

Rationale

Objective

Methods

Measurements and main results

Conclusion

Publications

Dynamic and prognostic proteomic associations with FEV<sub>1</sub> decline in chronic obstructive pulmonary disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dynamic and prognostic proteomic associations with FEV₁ decline in chronic obstructive pulmonary disease.