Kaixin Zhou

Background: Chronic obstructive pulmonary disease (COPD) is frequently underdiagnosed, and biomarkers that capture early molecular changes or predict progression remain lacking. Plasma extracellular vesicles (EVs) may provide disease-relevant circulating signals, but their proteomic changes across the COPD continuum remain unclear.Methods: We performed stage-resolved plasma EV proteomics in healthy controls, individuals with PreCOPD, and patients with GOLD I–IV COPD using data-independent acquisition mass spectrometry. Differential abundance, network analyses, and machine learning were integrated to identify candidate biomarkers, which were evaluated by ELISA and independent parallel reaction monitoring mass spectrometry. Associations with COPD severity and PreCOPD progression were further assessed using longitudinal, airway EV, single-cell transcriptomic, and lung tissue analyses.Findings: We identified 4,014 plasma EV-associated proteins and uncovered stage-dependent molecular remodelling across the COPD continuum, from early vesicular, ciliary, autophagic, and metabolic alterations to persistent mTORC1-associated stress signalling and increasingly prominent platelet, immune, and tissue-remodelling programmes. A five-protein EV signature comprising ARHGDIB, HSP90AB1, PDIA6, YES1, and YWHAQ discriminated COPD from Non-COPD with AUCs of 0.830 in the internal ELISA cohort and 0.885 in the independent PRM cohort, and reflected airflow-obstruction severity. Baseline EV ARHGDIB was independently associated with subsequent PreCOPD progression and discriminated progressors from non-progressors in the external longitudinal cohort with an AUC of 0.846. ARHGDIB was also increased in COPD airway EVs, while single-cell and tissue analyses implicated pulmonary T and NK cells as potential cellular sources.Interpretation: Plasma EV proteomics captures stage-related molecular changes across the COPD continuum and identifies biomarkers associated with disease severity and future progression. Circulating EV proteins may complement clinical assessment and progression-risk stratification, pending prospective multicentre validation.Funding: R&D Program of Guangzhou National Laboratory (SRPG22-019); State Key Laboratory of Respiratory Disease (SKLRD-OP-202306, SKLRD-OP-202713); National Natural Science Foundation of China (82500480).

Background: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, and acute exacerbations drive most of its burden. Around half of exacerbations are infection related, and penicillin-class antibiotics are widely used. However, penicillin allergy labels, often inaccurate, may divert prescribing towards broader-spectrum agents and worsen outcomes. We therefore examined whether such labels are associated with antibiotic prescribing patterns and subsequent risk of COPD exacerbations in a large cohort. Methods: We conducted a retrospective cohort study in the Kunshan Aging Research with E-health (KARE) database (2016– 2024). We included 14,900 patients with COPD aged ≥ 40 years. Exposure was a documented penicillin allergy label in the electronic medical record. Outcomes were the risk and rate of subsequent COPD exacerbations. Cox proportional hazards models estimated the association with time to first exacerbation, and negative binomial regression assessed exacerbation rates. Results: Of 14,900 patients, 722 (4.8%) had a penicillin allergy label. Overall, 2018 (13.5%) experienced at least one exacerbation during a median follow-up of 4.1 years. Compared with unlabeled patients, those with a penicillin allergy label received more broad-spectrum antibiotics and had a higher risk of exacerbations (adjusted hazard ratio 1.39, 95% confidence interval 1.17– 1.65) and higher exacerbation rates (adjusted incidence rate ratio 1.56, 95% confidence interval 1.25– 1.93). Conclusion: In this Chinese COPD cohort, penicillin allergy labels were associated with broader-spectrum antibiotic use and an increased burden of exacerbations. Systematic verification and de-labelling of penicillin allergy may help optimise antibiotic use and improve COPD outcomes.

Background: Chronic obstructive pulmonary disease (COPD) is an irreversible, progressive respiratory disease, and there is a lack of effective intervention strategies for high-risk populations. COPD pathogenesis is closely associated with apoptosis of lung cells. Fermented Cordyceps Preparation (FCP), a standardized traditional Chinese medicinal product, can improve lung function and exert anti-apoptotic effects by targeting caspase-3 (CASP3). However, real-world evidence regarding its preventive effect on COPD and the determinants of interindividual treatment response remains limited. Objective: We hypothesized that FCP could reduce incident COPD risk, and the genetic variation in CASP3 would regulate the preventive efficacy of FCP in a genotype-specific manner. This study aimed to validate this hypothesis and provide evidence for personalized COPD prevention. Methods: A prospective cohort study was conducted using electronic health record (EHR) and genomic data from the Kunshan Aging Research with E-health (KARE) cohort. A total of 4453 individuals were enrolled and stratified into the FCP Used Group (n=956) and FCP Unused Group (n=3497) after 1:4 propensity score matching (PSM). Kaplan-Meier survival analysis, multivariable Cox proportional hazards regression, and gene-environment interaction analysis were used to assess the association between FCP use and incident COPD, as well as the genotype-specific effect. Results: FCP use was significantly associated with a 27% reduction in incident COPD risk in the overall high-risk cohort (HR=0.73; P=0.01). Stratified analysis revealed that FCP exerted a robust preventive effect exclusively in CASP3 rs12108497 TT genotype carriers (HR=0.55; P<0.001), with no statistically significant benefit in CC or CT carriers. Notably, TT carriers in the untreated group exhibited higher baseline susceptibility to COPD (HR = 1.26; P = 0.02), and FCP intervention effectively neutralized this inherent genetic risk. A significant genotype-by-treatment interaction was observed (P for interaction = 0.02). Conclusions: This real-world study provides evidence that FCP use is associated with a reduced risk of incident COPD, with the CASP3 rs12108497 TT genotype identifying a subgroup deriving exceptional preventive benefit. These findings highlight the potential of FCP as a personalized preventive agent for COPD and provide a novel genetic stratification strategy for high-risk populations.

OBJECTIVE: mtDNA copy number (CN) reflects mitochondrial function, but prior studies have reported inconsistent associations with type 2 diabetes risk, ranging from inverse to positive or null findings. We hypothesized that mtDNA-CN is nonlinearly associated with incident type 2 diabetes. RESEARCH DESIGN AND METHODS: We included 34,835 adults without diabetes from the Kunshan Aging Research With E-Health (KARE) cohort and 289,338 from the UK Biobank (UKB). Associations between blood mtDNA-CN and incident type 2 diabetes were evaluated using Cox proportional hazards and restricted cubic spline models stratified by age. RESULTS: A U-shaped association was observed in the KARE cohort (P < 0.001), in which the hazard ratios (95% CIs) across increasing mtDNA-CN quartiles were 1.00 (reference), 0.94 (0.88–1.00), 0.85 (0.79–0.91), and 0.93 (0.87–1.00). In contrast, the UKB cohort exhibited a predominantly inverse linear trend. Age-stratified analyses revealed that this U-shaped association was particularly evident in younger participants (aged <65 years in KARE and <50 years in UKB), indicating elevated diabetes risk at both low and high mtDNA-CN levels. Additionally, mtDNA-CN declined with age in both cohorts, with an accelerated decrease beyond ∼65 years in KARE and ∼50 years in UKB. CONCLUSIONS: Blood mtDNA-CN showed a U-shaped association with incident type 2 diabetes in younger individuals.

Background: Steroid-sensitive nephrotic syndrome (SSNS) is a relatively rare glomerular disease with considerable clinical and genetic heterogeneity. Although efforts have been made to explore the genetic determinants of SSNS, the underlying genetic architecture has still been hampered by limited sample size and remains to be elucidated. Methods: We conducted a genome-wide association study involving 510 sporadic pediatrics of SSNS and 1062 controls with Chinese ancestry, followed by a transethnic meta-analysis involving 2942 cases and 37 041 controls. We evaluated the colocalization probability between single-cell expression quantitative trait loci, plasma protein quantitative trait loci, and the novel loci using the colocalization method. We explored the potential causal effects using Mendelian randomization (MR) and assessed the clinical associations of polygenic risk scores (PRS) for SSNS. Results: Two novel genome-wide significant signals, rs4309200 from M6PR-KLRG1 (P = 4.70 × 10−9, OR = 1.23, 95%CI = 1.16–1.30) and rs9303279 from GSDMB-ORMDL3 (P = 7.25 × 10−9, OR = 0.82, 95%CI = 0.75–0.89), both highly related to immunological function, were identified for SSNS. Colocalization and MR analyses revealed that a genetic tendency toward higher M6PR expression in NK and CD4+ T cells with an effector memory or central memory phenotype (CD4 ET) was associated with an increased risk of SSNS (NK: PPH4 = 0.93; P = 2.04 × 10−4, OR = 1.60; CD4 ET: PPH4 = 0.91; P = 8.14 × 10−3, OR = 2.28), whereas higher ORMDL3 expression in B memory and CD4 ET cells was associated with a lower risk of SSNS (B memory: PPH4 = 0.93; P = 3.83 × 10−8, OR = 0.61; CD4 ET: PPH4 = 0/92; P = 1.82 × 10−9, OR = 0.49). The clinical correlation analysis confirmed that a higher PRS is associated with an earlier age of onset, and the rs56117924 from the NPHS1 gene may predominantly drive this association. Conclusion: We identified two novel immune-related loci associated with susceptibility to SSNS, nominating M6PR and ORMDL3 as potential contributors to SSNS risk in a cell-type-specific manner, and confirmed the association of PRS with earlier disease onset. These findings expand our knowledge of the genetic architecture of SSNS and highlight the importance of large-scale collaborations in uncovering genetic associations related to SSNS.

Validated frameworks for defining chronic obstructive pulmonary disease (COPD) using real-world electronic health records (EHR) data in non-European popula

Type 2 diabetes is a global health burden driven by genetic and environmental factors. Continuous glucose monitoring (CGM) can effectively guide lifestyle interventions in non-diabetic. However, predefined CGM metrics fail to fully capture the dysglycemic information contained in the highdimensional time-series CGM data. This study employed deep learning to learn dysglycemia features from CGM data associated with diabetes and derived a digital biomarker of dysglycemia, validated against traditional dysglycemic biomarkers and diabetes polygenic risk score (PRS). Output of the deep learning model, called the deep learning-score, was significantly associated with multiple existing dysglycemic biomarkers and PRS of diabetes (P = 0.007). Moreover, existing CGM metrics were not associated with prevalent diabetes after adjusting for the deep learning-score, while the deep learning-score remained significantly associated with prevalent diabetes (P < 0.001) in a regression analysis. This digital biomarker demonstrated potential for providing dynamic feedback on dysglycemia and improving long-term intervention adherence.