Journal article
Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema
American journal of respiratory and critical care medicine, Vol.209(3), pp.273-287
02/01/2024
DOI: 10.1164/rccm.202301-0067OC
PMID: 37917913
Abstract
Rationale
Emphysema is a chronic obstructive pulmonary disease phenotype with important prognostic implications. Identifying blood-based biomarkers of emphysema will facilitate early diagnosis and development of targeted therapies.
Objectives
To discover blood omics biomarkers for chest computed tomography–quantified emphysema and develop predictive biomarker panels.
Methods
Emphysema blood biomarker discovery was performed using differential gene expression, alternative splicing, and protein association analyses in a training sample of 2,370 COPDGene participants with available blood RNA sequencing, plasma proteomics, and clinical data. Internal validation was conducted in a COPDGene testing sample (n = 1,016), and external validation was done in the ECLIPSE study (n = 526). Because low body mass index (BMI) and emphysema often co-occur, we performed a mediation analysis to quantify the effect of BMI on gene and protein associations with emphysema. Elastic net models with bootstrapping were also developed in the training sample sequentially using clinical, blood cell proportions, RNA-sequencing, and proteomic biomarkers to predict quantitative emphysema. Model accuracy was assessed by the area under the receiver operating characteristic curves for subjects stratified into tertiles of emphysema severity.
Measurements and Main Results
Totals of 3,829 genes, 942 isoforms, 260 exons, and 714 proteins were significantly associated with emphysema (false discovery rate, 5%) and yielded 11 biological pathways. Seventy-four percent of these genes and 62% of these proteins showed mediation by BMI. Our prediction models demonstrated reasonable predictive performance in both COPDGene and ECLIPSE. The highest-performing model used clinical, blood cell, and protein data (area under the receiver operating characteristic curve in COPDGene testing, 0.90; 95% confidence interval, 0.85–0.90).
Conclusions
Blood transcriptome and proteome-wide analyses revealed key biological pathways of emphysema and enhanced the prediction of emphysema.
Details
- Title: Subtitle
- Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema
- Creators
- Rahul Suryadevara - Channing Division of Network MedicineAndrew Gregory - Channing Division of Network MedicineRobin Lu - Channing Division of Network MedicineZhonghui Xu - Channing Division of Network MedicineAria Masoomi - Northeastern UniversitySharon M Lutz - Harvard Pilgrim Health CareSeth Berman - Channing Division of Network MedicineJeong H Yun - Pulmonary and Critical Care AssociatesAabida Saferali - Channing Division of Network MedicineMin Hyung Ryu - Channing Division of Network MedicineMatthew Moll - VA Boston Healthcare SystemDon D Sin - University of British ColumbiaCraig P Hersh - Pulmonary and Critical Care AssociatesEdwin K Silverman - Pulmonary and Critical Care AssociatesJennifer Dy - Northeastern UniversityKatherine A Pratte - Department of Biostatistics andRussell P Bowler - National Jewish HealthPeter J Castaldi - Brigham and Women's HospitalAdel Boueiz - Pulmonary and Critical Care AssociatesCOPDGene investigatorsAbbie Begnaud (Contributor) - Internal Medicine
- Resource Type
- Journal article
- Publication Details
- American journal of respiratory and critical care medicine, Vol.209(3), pp.273-287
- DOI
- 10.1164/rccm.202301-0067OC
- PMID
- 37917913
- ISSN
- 1073-449X
- eISSN
- 1535-4970
- Grant note
- U01 HL089856 / NHLBI NIH HHS U01 HL089897 / NHLBI NIH HHS P01 HL114501 / NHLBI NIH HHS R01 HL133135 / NHLBI NIH HHS R01 HL124233 / NHLBI NIH HHS R01 HL147326 / NHLBI NIH HHS K08 HL141601 / NHLBI NIH HHS R01 HL167072 / NHLBI NIH HHS K08 HL136928 / NHLBI NIH HHS K08 HL146972 / NHLBI NIH HHS
- Language
- English
- Date published
- 02/01/2024
- Academic Unit
- Psychiatry; Internal Medicine
- Record Identifier
- 9985179908302771
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