Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. Accord-ingly, with National Heart, Lung and Blood Institute support, we initiated the SPIROMICS Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global Initiative for Chronic Obstructive Lung Disease (GOLD) groups 0-2 or with Preserved Ratio Impaired Spirometry (PRISm); and an additional n=40 never-smoker controls. Participants undergo baseline and three-year follow-up visits, each including high-resolution computed tomography; respiratory oscillometry and spirometry (pre- and post-bronchodilator administration), exhaled breath condensate (baseline only); and extensive biospecimen collection, including sputum induction. Symptoms, interim healthcare utilization, and exacerbations are captured every six months via follow-up phone calls. An embedded bronchoscopy sub-study involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

Unifying considerations and evidence of macrophage activation mosaicism through human CSF1R and M1/M2 genes.

Addressing the mononuclear phagocyte system (MPS) and macrophage M1/M2 activation is important in diagnosing hematological disorders and inflammatory pathologies and designing therapeutic tools. CSF1R is a reliable marker to identify all circulating MPS cells and tissue macrophages in humans using a single surface protein. CSF1R permits the quantification and isolation of monocyte and dendritic cell (DC) subsets in conjunction with CD14, CD16, and CD1c and is stable across the lifespan and sexes in the absence of overt pathology. Beyond cell detection, measuring M1/M2 activation in humans poses challenges due to response heterogeneity, transient signaling, and multiple regulation steps for transcripts and proteins. MPS cells respond in a conserved manner to M1/M2 pathways such as interleukin-4 (IL-4), steroids, interferon-γ (IFNγ), and lipopolysaccharide (LPS), for which we propose an ad hoc modular gene expression tool. Signature analysis highlights macrophage activation mosaicism in experimental samples, an emerging concept that points to mixed macrophage activation states in pathology.

Molecular Endotypes of Idiopathic Pulmonary Fibrosis: A Latent Class Analysis of Two Multicenter Observational Cohorts.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes irreversible fibrosis of the lung parenchyma. Although antifibrotic therapy can slow IPF progression, treatment response is variable. There exists a critical need to develop a precision medicine approach to IPF. Objectives: To identify and validate biologically driven molecular endotypes of IPF. Methods: Latent class analysis (LCA) was independently performed in prospectively recruited discovery (n = 875) and validation (n = 347) cohorts. Twenty-five plasma biomarkers associated with fibrogenesis served as class-defining variables. The association between molecular endotype and 4-year transplant-free survival was tested using multivariable Cox regression adjusted for baseline confounders. Endotype-dependent differential treatment response to future antifibrotic exposure was then assessed in a pooled cohort of patients naive to antifibrotic therapy at the time of biomarker measurement (n = 555). Measurements and Main Results: LCA independently identified two latent classes in both cohorts (P < 0.0001). WFDC2 (WAP four-disulfide core domain protein 2) was the most important determinant of class membership across cohorts. Membership in class 2 was characterized by higher biomarker concentrations and a higher risk of death or transplant (discovery, hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.64-2.48; P < 0.001; validation, HR, 1.95; 95% CI, 1.34-2.82; P < 0.001). In pooled analysis, significant heterogeneity in treatment effect was observed between endotypes (P = 0.030 for interaction), with a favorable antifibrotic response in class 2 (HR, 0.64; 95% CI, 0.45-0.93; P = 0.018) but not in class 1 (HR, 1.19; 95% CI, 0.77-1.84; P = 0.422). Conclusions: In this multicohort study, we identified two novel molecular endotypes of IPF with divergent clinical outcomes and responses to antifibrotic therapy. Pending further validation, these endotypes could enable a precision medicine approach for future IPF clinical trials.

Association of Ground Glass Opacities with Systemic Inflammation and Progression of Emphysema.

RATIONAL: Ground glass opacities (GGO) in the absence of interstitial lung disease are understudied. OBJECTIVE: To assess the association of GGO with white blood cells (WBCs) and progression of quantified chest CT emphysema. METHODS: We analyzed data of participants in the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS). Chest radiologists and pulmonologists labeled regions of the lung as GGO and adaptive multiple feature method (AMFM) trained the computer to assign those labels to image voxels and quantify the volume of the lung with GGO (%GGOAMFM). We used multivariable linear regression, zero-inflated negative binomial, and proportional hazards regression models to assess the association of %GGOAMFM with WBC, changes in %emphysema, and clinical outcomes. MEASUREMENTS AND MAIN RESULTS: Among 2,714 participants, 1,680 had COPD and 1,034 had normal spirometry. Among COPD participants, based on the multivariable analysis, current smoking and chronic productive cough was associated with higher %GGOAMFM. Higher %GGOAMFM was cross-sectionally associated with higher WBCs and neutrophils levels. Higher %GGOAMFM per interquartile range at visit 1 (baseline) was associated with an increase in emphysema at one-year follow visit by 11.7% (Relative increase; 95%CI 7.5-16.1%;P<0.001). We found no association between %GGOAMFM and one-year FEV1 decline but %GGOAMFM was associated with exacerbations and all-cause mortality during a median follow-up time of 1,544 days (Interquartile Interval=1,118-2,059). Among normal spirometry participants, we found similar results except that %GGOAMFM was associated with progression to COPD at one-year follow-up. CONCLUSIONS: Our findings suggest that GGOAMFM is associated with increased systemic inflammation and emphysema progression.

Pre-surgical cryoablation in ≤ 2 cm ER + /HER2-tumors. Prognostic factors for the presence of residual invasive carcinoma.

BACKGROUND: Breast cancer remains the most commonly diagnosed cancer in women. Breast-conserving surgery (BCS) is the standard approach for small low-risk tumors. If the efficacy of cryoablation is demonstrated, it could provide a minimally invasive alternative to surgery. PURPOSE: To determine the success of ultrasound-guided cryoablation in achieving the absence of Residual Invasive Cancer (RIC) for patients with ER + /HER2- tumors ≤ 2cm and sonographically negative axillary nodes. MATERIALS AND METHODS: This prospective study was carried out from April 2021 to June 2023, and involved 60 preoperative cryoablation procedures on ultrasound-visible, node-negative (cN0) infiltrating ductal carcinomas (IDC). Standard diagnostic imaging included mammography and tomosynthesis, supplemented by ultrasound-guided biopsy. MRI was performed in patients with associated intraductal carcinoma (DCIS) and an invasive component on core needle biopsy (18 out of 22 cases). All tumors were tagged with ferromagnetic seeds. A triple-phase protocol (freezing-thawing-freezing) with Argon was used, with an average procedure duration of 40 min. A logistic regression model was applied to determine significant correlation between RIC and the study variables. RESULTS: Fifty-nine women (mean age 63 ± 8 years) with sixty low-risk unifocal IDC underwent cryoablation prior to surgery. Pathological examination of lumpectomy specimens post-cryoablation revealed RIC in only one of 38 patients with pure IDC and in 4 of 22 mixed IDC/DCIS cases. All treated tumors had clear surgical margins, with no significant procedural complications. CONCLUSIONS: Cryoablation was effective in eradicating 97% of pure infiltrating ER + /HER2-tumors ≤ 2cm, demonstrating its potential as a surgical alternative in selected patients.

Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care.

Depression is recognized as a significant public health issue in the United States. The National Survey on Drug Use and Health reports that 21.0 million adults aged 18 or older had major depressive disorder in 2020, including 14.8 million experiencing a major depressive episode with severe impairment. The aim is to predict the positivity of Patient Health Questionnaire-2 (PHQ-2) outcomes among patients in primary care settings by analyzing a range of variables, including socioeconomic status, demographic characteristics, and health behaviors, thereby identifying those at increased risk for depression. Employing a machine learning approach, the study utilizes retrospective data from electronic health records across 15 primary care clinics in South Florida to explore the relationship between social determinants of health (SDoH), including area of deprivation index (ADI) and PHQ-2 positivity. The study encompasses 15 primary care clinics located in South Florida, where a diverse patient population receives care. Analysis included 94,572 patient visits; 74,636 records were included in the study. If a zip+4 was not available or an ADI score did not exist, the visit was not included in the final analysis. Screening involved the PHQ-2, assessing depressed mood and anhedonia, with a cutoff >2 indicating positive screening. ADI was used to assess SDoH by matching patients' residential postal codes to ADI national percentiles. Demographics, sexual history, tobacco use, caffeine intake, and community involvement were also evaluated in the study. Over 40 machine learning algorithms were explored for their accuracy in predicting PHQ-2 outcomes, using software tools including Scikit-learn and stats models in Python. Variables were normalized, scored, and then subjected to predictive regression models, with Random Forest showing outstanding performance. Feature engineering and correlation analysis identified ADI, age, education, visit type, coffee intake, and marital status as significant predictors of PHQ-2 positivity. The area under the curve and model accuracies varied across clinics, with specific clinics showing higher predictive accuracy and others (p > .05). The study concludes that the ADI, as a proxy for SDoH, alongside other individual factors, can predict PHQ-2 positivity. Health organizations can use this information to anticipate health needs and resource allocation.

[Pharmacological intervention in the medication review of institutionalised elderly patients under polypharmacy]. / Intervención farmacéutica en la revisión del tratamiento en pacientes mayores polimedicados institucionalizados.

OBJECTIVE: To describe the Drug-Related Problems (DRP) and their resolution after pharmacological review in institutionalised elderly patients under polypharmacy. DESIGN: Descriptive, retrospective cohort study from January to October of 2022. LOCATION: Twelve nursing homes at the Community of Madrid. PARTICIPANTS: 295 patients aged 65 or older taking at least 5 chronic medications prescribed prior to the treatment review. INTERVENTIONS: Medication reviews carried out by the pharmacist and agreed upon in face-to-face meetings between the primary care doctor, the nursing home doctor and the pharmacist. MAIN MEASUREMENTS: Detected DRP, types and resolution. A age, sex, and number of medications before and after the intervention. Pharmacological subgroups according to anatomical therapeutic chemical classification system (ATC) and active pharmaceutical ingredients involved in the detected DRPs. RESULTS: 1425 DRP were detected, with a mean of 4.85 (SD 3.33) DRPs/patient. The most frequent DRP was reconciliation error (32.52%), followed by pharmaceutical regimen and dosaje. Among the 1425 improvement proposals, 86.73% of them were accepted.Significant statistically differences were observed between the number of medications per patient prior to the pharmacotherapy review (12.29) and after it (10.20), obtaining an average difference of 2.09 (95%CI: 1.98-2.21; P<.001). CONCLUSIONS: It is found that the intervention of multidisciplinary team in which the pharmacist performs a revision of the medication decreased the number of prescribed medications. Therefore, it reduces polymedication and its associated risks.

Air Pollution Exposure and Interstitial Lung Features in SPIROMICS Participants with COPD.

RATIONALE: It is unknown whether air pollution is associated with radiographic features of interstitial lung disease in individuals with chronic obstructive pulmonary disease (COPD). OBJECTIVES: To determine whether air pollution increases prevalence of interstitial lung abnormalities (ILA) or percent high-attenuation area (HAA) on computed tomography (CT) in individuals with a heavy smoking history and COPD. METHODS: We performed a cross-sectional study of SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), focused on current or former smokers with COPD. 10-year exposure to particulate matter < 2.5 µm (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone (O3) prior to enrollment CTs (completed between 2010-2015) were estimated with validated spatiotemporal models at residential addresses. We applied adjusted multivariable modified Poisson regression and linear regression to investigate associations between pollution exposure and relative risk of ILA or increased percent HAA (between -600 and -250 Hounsfield units) respectively. We assessed for effect modification by MUC5B-promoter polymorphism (GT/TT vs GG at rs3705950), smoking status, sex, and percent emphysema. RESULTS: Among 1272 participants with COPD assessed for HAA, 424 were current smokers, 249 were carriers of the variant MUC5B allele (GT/TT). 519 participants were assessed for ILA. We found no association between pollution exposure and ILA or HAA. Associations between pollutant exposures and risk of ILA were modified by the presence of MUC5B polymorphism (p-value interaction term for NOx = 0.04 and PM2.5 = 0.05) and smoking status (p-value interaction term for NOx = 0.05, NO2 = 0.01, and O3 = 0.05). With higher exposure to NOx and PM2.5, MUC5B variant carriers had increased risk of ILA (Relative Risk [RR] per 26ppb NOx 2.41; 95% Confidence Interval [CI] 0.97 to 6.0) and RR per 4 µg·m-3 PM2.5 1.43; 95% CI 0.93 to 2.2). With higher exposure to NO2, former smokers had increased risk of ILA (RR per 10ppb 1.64; 95% CI 1.0 to 2.7). CONCLUSIONS: Exposure to ambient air pollution was not associated with interstitial features on CT in this population of heavy smokers with COPD. MUC5B modified the association between pollution and ILA, suggesting that gene-environment interactions may influence prevalence of interstitial lung features in COPD.

Genetics and Genomics of Pulmonary Fibrosis: Charting the Molecular Landscape and Shaping Precision Medicine.

Recent genetic and genomic advancements have elucidated the complex etiology of idiopathic pulmonary fibrosis (IPF) and other progressive fibrotic interstitial lung diseases (ILDs), emphasizing the contribution of heritable factors. This state-of-the-art review synthesizes evidence on significant genetic contributors to pulmonary fibrosis (PF), including rare genetic variants and common SNPs. The MUC5B promoter variant is unusual, a common SNP that markedly elevates the risk of early and established PF. We address the utility of genetic variation in enhancing understanding of disease pathogenesis and clinical phenotypes, improving disease definitions, and informing prognosis and treatment response. Critical research gaps are highlighted, particularly the underrepresentation of non-European ancestries in PF genetic studies and the exploration of PF phenotypes beyond usual interstitial pneumonia/IPF. We discuss the role of telomere length, often critically short in PF, and its link to progression and mortality, underscoring the genetic complexity involving telomere biology genes (TERT, TERC) and others like SFTPC and MUC5B. In addition, we address the potential of gene-by-environment interactions to modulate disease manifestation, advocating for precision medicine in PF. Insights from gene expression profiling studies and multiomic analyses highlight the promise for understanding disease pathogenesis and offer new approaches to clinical care, therapeutic drug development, and biomarker discovery. Finally, we discuss the ethical, legal, and social implications of genomic research and therapies in PF, stressing the need for sound practices and informed clinical genetic discussions. Looking forward, we advocate for comprehensive genetic testing panels and polygenic risk scores to improve the management of PF and related ILDs across diverse populations.

A multidimensional classifier to support lung transplant referral in patients with pulmonary fibrosis.

BACKGROUND: Lung transplantation remains the sole curative option for patients with idiopathic pulmonary fibrosis (IPF), but donor organs remain scarce, and many eligible patients die before transplant. Tools to optimize the timing of transplant referrals are urgently needed. METHODS: Least absolute shrinkage and selection operator was applied to clinical and proteomic data generated as part of a prospective cohort study of interstitial lung disease (ILD) to derive clinical, proteomic, and multidimensional logit models of near-term death or lung transplant within 18 months of blood draw. Model-fitted values were dichotomized at the point of maximal sensitivity and specificity, and decision curve analysis was used to select the best-performing classifier. We then applied this classifier to independent IPF and non-IPF ILD cohorts to determine test performance characteristics. Cohorts were restricted to patients aged ≤72 years with body mass index 18 to 32 to increase the likelihood of transplant eligibility. RESULTS: IPF derivation, IPF validation, and non-IPF ILD validation cohorts consisted of 314, 105, and 295 patients, respectively. A multidimensional model comprising 2 clinical variables and 20 proteins outperformed stand-alone clinical and proteomic models. Following dichotomization, the multidimensional classifier predicted near-term outcome with 70% sensitivity and 92% specificity in the IPF validation cohort and 70% sensitivity and 80% specificity in the non-IPF ILD validation cohort. CONCLUSIONS: A multidimensional classifier of near-term outcomes accurately discriminated this end-point with good test performance across independent IPF and non-IPF ILD cohorts. These findings support refinement and prospective validation of this classifier in transplant-eligible individuals.

Zinpentraxin Alfa for Idiopathic Pulmonary Fibrosis: The Randomized Phase III STARSCAPE Trial.

Rationale: A phase II trial reported clinical benefit over 28 weeks in patients with idiopathic pulmonary fibrosis (IPF) who received zinpentraxin alfa. Objectives: To investigate the efficacy and safety of zinpentraxin alfa in patients with IPF in a phase III trial. Methods: This 52-week phase III, double-blind, placebo-controlled, pivotal trial was conducted at 275 sites in 29 countries. Patients with IPF were randomized 1:1 to intravenous placebo or zinpentraxin alfa 10 mg/kg every 4 weeks. The primary endpoint was absolute change from baseline to Week 52 in FVC. Secondary endpoints included absolute change from baseline to Week 52 in percent predicted FVC and 6-minute walk distance. Safety was monitored via adverse events. Post hoc analysis of the phase II and phase III data explored changes in FVC and their impact on the efficacy results. Measurements and Main Results: Of 664 randomized patients, 333 were assigned to placebo and 331 to zinpentraxin alfa. Four of the 664 randomized patients were never administered study drug. The trial was terminated early after a prespecified futility analysis that demonstrated no treatment benefit of zinpentraxin alfa over placebo. In the final analysis, absolute change from baseline to Week 52 in FVC was similar between placebo and zinpentraxin alfa (-214.89 ml and -235.72 ml; P = 0.5420); there were no apparent treatment effects on secondary endpoints. Overall, 72.3% and 74.6% of patients receiving placebo and zinpentraxin alfa, respectively, experienced one or more adverse events. Post hoc analysis revealed that extreme FVC decline in two placebo-treated patients resulted in the clinical benefit of zinpentraxin alfa reported by phase II. Conclusions: Zinpentraxin alfa treatment did not benefit patients with IPF over placebo. Learnings from this program may help improve decision making around trials in IPF. Clinical trial registered with www.clinicaltrials.gov (NCT04552899).

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

Rationale: Distinguishing connective tissue disease-associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. Objectives: To identify proteins that separate and classify patients with CTD-ILD and those with IPF. Methods: Four registries with 1,247 patients with IPF and 352 patients with CTD-ILD were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using recursive feature elimination to construct a proteomic classifier. Multiple machine learning models, including support vector machine, LASSO (least absolute shrinkage and selection operator) regression, random forest, and imbalanced Random Forest, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. Measurements and Main Results: A classifier with 37 proteins (proteomic classifier 37 [PC37]) was enriched in the biological process of bronchiole development and smooth muscle proliferation and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver operating characteristic curve analyses of these scores demonstrated consistent areas under the curve of 0.85-0.90 in the test cohort and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6-80.4% sensitivity and 76-84.4% specificity in the test cohort and 93.5-96.1% sensitivity and 69.5-77.6% specificity in the single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194 of 248) accuracy in the test cohort and 82.9% (208 of 251) in the single-sample classification dataset. Conclusions: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Many of the identified proteins are involved in immune pathways. We further developed a novel approach for single-sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision making.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium.

Importance: Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. Objective: To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. Design, Setting, and Participants: This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Exposure: Early-life exposures to PM2.5 and NO2 according to participants' birth address. Main Outcomes and Measures: Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Results: Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). Conclusions and Relevance: In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Meaningful Endpoints for Idiopathic Pulmonary Fibrosis (IPF) Clinical Trials: Emphasis on 'Feels, Functions, Survives'. Report of a Collaborative Discussion in a Symposium with Direct Engagement from Representatives of Patients, Investigators, the National Institutes of Health, a Patient Advocacy Organization, and a Regulatory Agency.

Background: Idiopathic pulmonary fibrosis (IPF) carries significant mortality and unpredictable progression, with limited therapeutic options. Designing trials with patient-meaningful endpoints, enhancing the reliability and interpretability of results, and streamlining the regulatory approval process are of critical importance to advancing clinical care in IPF. Methods: A landmark in-person symposium in June 2023 assembled 43 participants from the US and internationally, including patients with IPF, investigators, and regulatory representatives, to discuss the immediate future of IPF clinical trial endpoints. Patient advocates were central to discussions, which evaluated endpoints according to regulatory standards and the FDA's 'feels, functions, survives' criteria. Results: Three themes emerged: 1) consensus on endpoints mirroring the lived experiences of patients with IPF; 2) consideration of replacing forced vital capacity (FVC) as the primary endpoint, potentially by composite endpoints that include 'feels, functions, survives' measures or FVC as components; 3) support for simplified, user-friendly patient-reported outcomes (PROs) as either components of primary composite endpoints or key secondary endpoints, supplemented by functional tests as secondary endpoints and novel biomarkers as supportive measures (FDA Guidance for Industry (Multiple Endpoints in Clinical Trials) available at: https://www.fda.gov/media/162416/download). Conclusions: This report, detailing the proceedings of this pivotal symposium, suggests a potential turning point in designing future IPF clinical trials more attuned to outcomes meaningful to patients, and documents the collective agreement across multidisciplinary stakeholders on the importance of anchoring IPF trial endpoints on real patient experiences-namely, how they feel, function, and survive. There is considerable optimism that clinical care in IPF will progress through trials focused on patient-centric insights, ultimately guiding transformative treatment strategies to enhance patients' quality of life and survival.

Proteomic Biomarkers of Quantitative Interstitial Abnormalities in COPDGene and CARDIA Lung Study.

Rationale: Quantitative interstitial abnormalities (QIAs) are early measures of lung injury automatically detected on chest computed tomography scans. QIAs are associated with impaired respiratory health and share features with advanced lung diseases, but their biological underpinnings are not well understood. Objectives: To identify novel protein biomarkers of QIAs using high-throughput plasma proteomic panels within two multicenter cohorts. Methods: We measured the plasma proteomics of 4,383 participants in an older, ever-smoker cohort (COPDGene [Genetic Epidemiology of Chronic Obstructive Pulmonary Disease]) and 2,925 participants in a younger population cohort (CARDIA [Coronary Artery Disease Risk in Young Adults]) using the SomaLogic SomaScan assays. We measured QIAs using a local density histogram method. We assessed the associations between proteomic biomarker concentrations and QIAs using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, and study center (Benjamini-Hochberg false discovery rate-corrected P ⩽ 0.05). Measurements and Main Results: In total, 852 proteins were significantly associated with QIAs in COPDGene and 185 in CARDIA. Of the 144 proteins that overlapped between COPDGene and CARDIA, all but one shared directionalities and magnitudes. These proteins were enriched for 49 Gene Ontology pathways, including biological processes in inflammatory response, cell adhesion, immune response, ERK1/2 regulation, and signaling; cellular components in extracellular regions; and molecular functions including calcium ion and heparin binding. Conclusions: We identified the proteomic biomarkers of QIAs in an older, smoking population with a higher prevalence of pulmonary disease and in a younger, healthier community cohort. These proteomics features may be markers of early precursors of advanced lung diseases.

Circulating biomarkers of airflow limitation across the life span.

BACKGROUND: Airflow limitation is a hallmark of chronic obstructive pulmonary disease, which can develop through different lung function trajectories across the life span. There is a need for longitudinal studies aimed at identifying circulating biomarkers of airflow limitation across different stages of life. OBJECTIVES: This study sought to identify a signature of serum proteins associated with airflow limitation and evaluate their relation to lung function longitudinally in adults and children. METHODS: This study used data from 3 adult cohorts (TESAOD [Tucson Epidemiological Study of Airway Obstructive Disease], SAPALDIA [Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults], LSC [Lovelace Smoker Cohort]) and 1 birth cohort (TCRS [Tucson Children's Respiratory Study]) (N = 1940). In TESAOD, among 46 circulating proteins, we identified those associated with FEV1/forced vital capacity (FVC) percent (%) predicted levels and generated a score based on the sum of their z-scores. Cross-sectional analyses were used to test the score for association with concomitant lung function. Longitudinal analyses were used to test the score for association with subsequent lung function growth in childhood and decline in adult life. RESULTS: After false discovery rate adjustment, serum levels of 5 proteins (HP, carcinoembryonic antigen, ICAM1, CRP, TIMP1) were associated with percent predicted levels of FEV1/FVC and FEV1 in TESAOD. In cross-sectional multivariate analyses the 5-biomarker score was associated with FEV1 % predicted in all adult cohorts (meta-analyzed FEV1 decrease for 1-SD score increase: -2.9%; 95% CI: -3.9%, -1.9%; P = 2.4 × 10-16). In multivariate longitudinal analyses, the biomarker score at 6 years of age was inversely associated with FEV1 and FEV1/FVC levels attained by young adult life (P = .02 and .005, respectively). In adults, persistently high levels of the biomarker score were associated with subsequent accelerated decline of FEV1 and FEV1/FVC (P = .01 and .001). CONCLUSIONS: A signature of 5 circulating biomarkers of airflow limitation was associated with both impaired lung function growth in childhood and accelerated lung function decline in adult life, indicating that these proteins may be involved in multiple lung function trajectories leading to chronic obstructive pulmonary disease.

The Kir2.1E299V mutation increases atrial fibrillation vulnerability while protecting the ventricles against arrhythmias in a mouse model of short QT syndrome type 3.

AIMS: Short QT syndrome type 3 (SQTS3) is a rare arrhythmogenic disease caused by gain-of-function mutations in KCNJ2, the gene coding the inward rectifier potassium channel Kir2.1. We used a multidisciplinary approach and investigated arrhythmogenic mechanisms in an in-vivo model of de-novo mutation Kir2.1E299V identified in a patient presenting an extremely abbreviated QT interval and paroxysmal atrial fibrillation. METHODS AND RESULTS: We used intravenous adeno-associated virus-mediated gene transfer to generate mouse models, and confirmed cardiac-specific expression of Kir2.1WT or Kir2.1E299V. On ECG, the Kir2.1E299V mouse recapitulated the QT interval shortening and the atrial-specific arrhythmia of the patient. The PR interval was also significantly shorter in Kir2.1E299V mice. Patch-clamping showed extremely abbreviated action potentials in both atrial and ventricular Kir2.1E299V cardiomyocytes due to a lack of inward-going rectification and increased IK1 at voltages positive to -80 mV. Relative to Kir2.1WT, atrial Kir2.1E299V cardiomyocytes had a significantly reduced slope conductance at voltages negative to -80 mV. After confirming a higher proportion of heterotetrameric Kir2.x channels containing Kir2.2 subunits in the atria, in-silico 3D simulations predicted an atrial-specific impairment of polyamine block and reduced pore diameter in the Kir2.1E299V-Kir2.2WT channel. In ventricular cardiomyocytes, the mutation increased excitability by shifting INa activation and inactivation in the hyperpolarizing direction, which protected the ventricle against arrhythmia. Moreover, Purkinje myocytes from Kir2.1E299V mice manifested substantially higher INa density than Kir2.1WT, explaining the abbreviation in the PR interval. CONCLUSION: The first in-vivo mouse model of cardiac-specific SQTS3 recapitulates the electrophysiological phenotype of a patient with the Kir2.1E299V mutation. Kir2.1E299V eliminates rectification in both cardiac chambers but protects against ventricular arrhythmias by increasing excitability in both Purkinje-fiber network and ventricles. Consequently, the predominant arrhythmias are supraventricular likely due to the lack of inward rectification and atrial-specific reduced pore diameter of the Kir2.1E299V-Kir2.2WT heterotetramer.