Back to Authors

Zhang, Chengyue

0009-0009-4537-8107

Mayo Clinic

Mass General Brigham

Citations 2

Multi-trait polygenic scores for COPD and COPD exacerbations implicate druggable proteins
Zhang, Chengyue , He, Yixuan, Zhang, Jingzhou, Feldman, William B. , Ding, Yi , Pasaniuc, Bogdan, Chang, Diana, Chen, Qingwen , Lasky-Su, Jessica, Hecker, Julian, Tobin, Martin D., Chen, Jing , Kalra, S. , Pratte, Katherine A., Im, Hae Kyung, Wan, Emily S., Manichaikul, Ani, Silverman, Edwin K., Bowler, Russell P., Lange, Leslie A., Ortega, Victor E., Cho, Michael H., Moll, Matthew R., Konigsberg, Iain R. , Zhang, Jingzhou , Chikowore, Tinashe , Hu, Xiaowei , Paşaniuc, Bogdan , Lasky‐Su, Jessica , Tobin, Martin D. , Pratte, Katherine , Wan, Emily S. , Manichaikul, Ani , Silverman, Edwin K. , Bowler, Russell P. , Lange, Leslie A., Ortega, Victor E. , Martin, Alicia R. , Cho, Michael H. , Moll, Matt

JCI Insight | February 19, 2026 | Volume: 11 | Issue: 7 | Pages: No page available

10.1172/jci.insight.199951 Get It

BACKGROUND We constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting. METHODS PRSmix + , a multi-trait PRS framework, is used to train a composite PRS (PRS multi ) in COPDGene non-Hispanic White participants ( n = 6,647). Associations of PRS multi with COPD status (GOLD 2–4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American ( n = 2,466), ECLIPSE ( n = 1,858), Mass General Brigham Biobank ( n = 15,152), and All of Us ( n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRS multi and were validated with proteomic data in COPDGene ( n = 5,173) and UK Biobank ( n = 5,012). RESULTS PRSmix + selected 7 traits for PRS multi . In multivariable models, PRS multi was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28–1.94]) and exacerbation frequency (meta-analysis RE β 0.21 [95% CI: 0.11–0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRS multi outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION COPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.
Polygenic Risk Score Added to Conventional Case Finding to Identify Undiagnosed Chronic Obstructive Pulmonary Disease
Zhang, Jingzhou , Hobbs, Brian D. , Silverman, Edwin K., Sparrow, David , Ortega, Victor E. , Xu, Hanfei , Zhang, Chengyue , Cho, Michael H., Hobbs, Brian D , Silverman, Edwin K. , Dupuis, Josée , Walkey, Allan J. , O’Connor, George T. , Cho, Michael H. , Moll, Matthew , Zhang, Chengyue

JAMA | January 22, 2025 | Volume: 333 | Issue: 9 | Pages: 784

10.1001/jama.2024.24212 Get It

ImportanceChronic obstructive pulmonary disease (COPD) is often undiagnosed. Although genetic risk plays a significant role in COPD susceptibility, its utility in guiding spirometry testing and identifying undiagnosed cases is unclear.ObjectiveTo determine whether a COPD polygenic risk score (PRS) enhances the identification of undiagnosed COPD beyond a case-finding questionnaire (eg, the Lung Function Questionnaire) using conventional risk factors and respiratory symptoms.Design, Setting, and ParticipantsThis cross-sectional analysis of participants 35 years or older who reported no history of physician-diagnosed COPD was conducted using data from 2 observational studies: the community-based Framingham Heart Study (FHS) and the COPD-enriched Genetic Epidemiology of COPD (COPDGene) study.ExposuresModified Lung Function Questionnaire (mLFQ) scores and COPD PRS.Main Outcomes and MeasuresThe primary outcome was spirometry-defined moderate to severe COPD (forced expiratory volume in the first second of expiration/forced vital capacity [FEV1/FVC] <0.7 and FEV1 [percent predicted] <80%). The performance of logistic models was assessed using the PRS, mLFQ score, and PRS plus mLFQ score for predicting spirometry-defined COPD.ResultsAmong 3385 FHS participants (median age, 52.0 years; 45.9% male) and 4095 COPDGene participants (median age, 56.8 years; 55.5% male) who reported no history of COPD, 160 (4.7%) FHS and 775 (18.9%) COPDGene participants had spirometry-defined COPD. Adding the PRS to the mLFQ score significantly improved the area under the curve from 0.78 to 0.84 (P < .001) in FHS, 0.69 to 0.72 (P = .04) in COPDGene non-Hispanic African American, and 0.75 to 0.78 (P < .001) in COPDGene non-Hispanic White participants. At a risk threshold for spirometry referral of 10%, the addition of the PRS to the mLFQ score correctly reclassified 13.8% (95% CI, 6.6%-21.0%) of COPD cases in FHS, but not in COPDGene.Conclusions and RelevanceA COPD PRS enhances the identification of undiagnosed COPD beyond a conventional case-finding approach in the general population. Further research is needed to assess its impact on COPD diagnosis and outcomes.