Lung Transcriptomics Links Emphysema to Barrier Dysfunction and Macrophage Subpopulations.

RATIONALE: While many studies have examined gene expression in lung tissue, the gene regulatory processes underlying emphysema are still not well understood. Finding efficient non-imaging screening methods and disease-modifying therapies has been challenging, but knowledge of the transcriptomic features of emphysema may help in this effort. OBJECTIVES: Our goals were to identify emphysema-associated biological pathways through transcriptomic analysis of bulk lung tissue, to determine the lung cell types in which these emphysema-associated pathways are altered, and to detect unique and overlapping transcriptomic signatures in blood and lung samples. METHODS: Using RNA-sequencing data from 446 samples in the Lung Tissue Research Consortium (LTRC) and 3,606 blood samples from the COPDGene study, we examined the transcriptomic features of chest computed tomography-quantified emphysema. We also leveraged publicly available lung single-cell RNA-sequencing data to identify cell types showing COPD-associated differential expression of the emphysema pathways found in the bulk analyses. MEASUREMENTS AND MAIN RESULTS: In the bulk lung RNA-seq analysis, 1,087 differentially expressed genes and 34 dysregulated pathways were significantly associated with emphysema. We observed alternative splicing of several genes and increased activity in pluripotency and cell barrier function pathways. Lung tissue and blood samples shared differentially expressed genes and biological pathways. Multiple lung cell types displayed dysregulation of epithelial barrier function pathways, and distinct pathway activities were observed among various macrophage subpopulations. CONCLUSIONS: This study identified emphysema-related changes in gene expression and alternative splicing, cell-type specific dysregulated pathways, and instances of shared pathway dysregulation between blood and lung.

HHIP protein interactions in lung cells provide insight into COPD pathogenesis.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. The primary causes of COPD are environmental, including cigarette smoking; however, genetic susceptibility also contributes to COPD risk. Genome-Wide Association Studies (GWASes) have revealed more than 80 genetic loci associated with COPD, leading to the identification of multiple COPD GWAS genes. However, the biological relationships between the identified COPD susceptibility genes are largely unknown. Genes associated with a complex disease are often in close network proximity, i.e. their protein products often interact directly with each other and/or similar proteins. In this study, we use affinity purification mass spectrometry (AP-MS) to identify protein interactions with HHIP , a well-established COPD GWAS gene which is part of the sonic hedgehog pathway, in two disease-relevant lung cell lines (IMR90 and 16HBE). To better understand the network neighborhood of HHIP , its proximity to the protein products of other COPD GWAS genes, and its functional role in COPD pathogenesis, we create HUBRIS, a protein-protein interaction network compiled from 8 publicly available databases. We identified both common and cell type-specific protein-protein interactors of HHIP. We find that our newly identified interactions shorten the network distance between HHIP and the protein products of several COPD GWAS genes, including DSP, MFAP2, TET2 , and FBLN5 . These new shorter paths include proteins that are encoded by genes involved in extracellular matrix and tissue organization. We found and validated interactions to proteins that provide new insights into COPD pathobiology, including CAVIN1 (IMR90) and TP53 (16HBE). The newly discovered HHIP interactions with CAVIN1 and TP53 implicate HHIP in response to oxidative stress.

Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function.

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

Joint clinical and molecular subtyping of COPD with variational autoencoders.

Chronic Obstructive Pulmonary Disease (COPD) is a complex, heterogeneous disease. Traditional subtyping methods generally focus on either the clinical manifestations or the molecular endotypes of the disease, resulting in classifications that do not fully capture the disease's complexity. Here, we bridge this gap by introducing a subtyping pipeline that integrates clinical and gene expression data with variational autoencoders. We apply this methodology to the COPDGene study, a large study of current and former smoking individuals with and without COPD. Our approach generates a set of vector embeddings, called Personalized Integrated Profiles (PIPs), that recapitulate the joint clinical and molecular state of the subjects in the study. Prediction experiments show that the PIPs have a predictive accuracy comparable to or better than other embedding approaches. Using trajectory learning approaches, we analyze the main trajectories of variation in the PIP space and identify five well-separated subtypes with distinct clinical phenotypes, expression signatures, and disease outcomes. Notably, these subtypes are more robust to data resampling compared to those identified using traditional clustering approaches. Overall, our findings provide new avenues to establish fine-grained associations between the clinical characteristics, molecular processes, and disease outcomes of COPD.

Tunable electronic properties and optoelectronic characteristics of MoGe2N4/SiC van der Waals heterostructure.

The assembly of van der Waals (vdW) heterostructure with easily regulated electronic properties provides a new way for the expansion of two-dimensional materials and promotes the development of optoelectronics, sensors, switching devices and other fields. In this work, a systematic investigation of the electronic properties of MoGe2N4/SiC heterostructures using density functional theory has been conducted, along with the modulation of electronic properties by vertical strain and the potential application prospects in optoelectronic devices. The results show that MoGe2N4/SiC heterostructure has excellent dynamic and thermal stability and belongs to type-II band alignment semiconductors. This is extremely beneficial for the separation of photo-generating electron-hole pairs, so it has important significance for the development of photovoltaic materials. In addition, under the control of vertical strain, the semiconductor-metal transition occurs in the MoGe2N4/SiC heterostructure when the compressive strain reaches 6%. In the case of compressive strain less than 6% and tensile strain, the MoGe2N4/SiC heterostructure maintains the type-II band alignment semiconductor characteristics. Meanwhile, we find that the MoGe2N4/SiC heterostructure has optical absorption coefficients of up to 105in the visible and ultraviolet light ranges, which can improve the absorption coefficients of the MoGe2N4and SiC monolayer in some visible light regions. Finally, the optical conductivity of the MoGe2N4/SiC heterostructure exhibits significant anisotropy, with the armchair direction displaying higher conductivity within the orange light range. In conclusion, the formation of vdW heterostructure by vertically stacking MoGe2N4and SiC monolayers can effectively improve their electronic and optical properties, which provides a valuable reference for the future development of electronic devices and photovoltaic materials.

Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema.

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.

The multiple reference range of mean uterine artery pulsatility index for natural and in vitro fertilization singletons during 11-14 gestational weeks.

Background: Ultrasonography of the uterine artery (UtA) in the first and second trimesters of pregnancy can assess uterine-placental blood perfusion and guide early clinical prevention. Establishing normal ranges of the UtA pulsatility index (UtA-PI) at 11-14 weeks of pregnancy is helpful for the early identification of high-risk pregnant women and improving the prognosis. This study aimed to establish a reference range of UtA-PI based on crown-rump length (CRL) for spontaneous and in vitro fertilization (IVF) singleton pregnancy during 11-14 weeks, respectively. Methods: A prospective study was performed at Peking Union Medical College Hospital. Healthy, low-risk women with a singleton pregnancy at 11-14 gestational weeks were consecutively recruited for this study from December 2017 to December 2020. All participants underwent routine prenatal ultrasound examination. The CRL of the fetus and the UtA-PI were measured in both uterine arteries, and average values were calculated. The LMS method was used to fit the percentile (P)5, P10, P25, P50, P75, P90, and P95 curves of the UtA-PI value of spontaneous and IVF singleton pregnancy with CRL changes, respectively. Results: A total of 1,962 pregnant women with normal fetuses were included in this study, including 1,792 pregnancies conceived naturally and 170 IVF fetuses. The UtA-PI reference range in the spontaneous pregnancy group was consistently higher than that in the IVF group during 11-14 weeks, and showed a statistically significant difference in UtA-PI for spontaneous and IVF pregnancies (P<0.001). According to the LMS method, each percentile curve of UtA-PI decreased with the increase of CRL in both the natural pregnancy group and the IVF group. The P95 range of UtA-PI for pregnant women with naturally conceived and IVF pregnancy was 2.74 to 2.11 and 2.50 to 1.94, respectively. The overall change of UtA-PI differentials of the two groups showed a downward trend and decreased slightly with the increase of CRL. Conclusions: This study provided a single-center, large sample of data and constructed a CRL-based reference value of UtA-PI for spontaneous and IVF singleton pregnancy, which provides a reliable basis for early UtA evaluation and early clinical decision-making during 11-14 gestational weeks.

Studying the Adsorption of Gas Molecules and Defects on Modulating the Electronic Transport Characteristics of Monolayer Penta-BN2-Based Devices.

Two-dimensional atomic layer materials, as an important part of the post-Moore era, have recently become an ideal choice for the preparation of high-efficiency, low-power, and miniaturized gas sensors. In this work, our study utilized density functional theory and the nonequilibrium Green's function method to investigate the electronic properties of the pentagonal BN2 (P-BN2) monolayer, as well as its gas-sensing properties for organic and inorganic gases. We also investigated how defects affect the quantum transport properties of the P-BN2-based device. Our findings demonstrate that the CO, H2S, NH3, SO2, C2H5OH, C3H6OH, CH3OH, and CH4 undergo physisorption on the P-BN2 monolayer, while NO, NO2, C2H2, C2H4, and HCHO undergo chemisorption. Then, we analyzed the impact of gas molecules chemisorbed on the P-BN2 monolayer on the electronic transport properties of the P-BN2-based gas sensor. When these five gas molecules are adsorbed, the current of the P-BN2-based gas sensor is greatly reduced. In addition, the effect of defects on the quantum transport properties of the P-BN2-based device is investigated. The results indicate that defects of N, B, and BN atoms lead to a decrease in the current of P-BN2-based nanodevices. Moreover, both the adsorption of gas molecules and the formation of vacancy defects leading to a decrease in device current can be revealed by the local device density of states near the zero-bias Fermi level, elucidating their microscopic mechanisms. Finally, gas molecules can also cause a decrease in the current of defect systems. These theoretical studies are of great significance for exploring two-dimensional atomic layer materials as high-efficiency gas sensors.

Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD.

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and blood transcriptome patterns have not been fully described. Objections: The objective of this study was to identify novel relationships between lung structural changes measured by chest computed tomography (CT) and blood transcriptome patterns measured by blood RNA sequencing (RNA-seq). Methods: CT scan images and blood RNA-seq gene expression from 1223 participants in the COPD Genetic Epidemiology (COPDGene®) study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we labeled image-expression axes (IEAs). We related IEAs to COPD-related measurements and prospective health outcomes through regression and Cox proportional hazards models and tested them for biological pathway enrichment. Results: We identified 2 distinct IEAs: IEAemph which captures an emphysema-predominant process with a strong positive correlation to CT emphysema and a negative correlation to forced expiratory volume in 1 second and body mass index (BMI); and IEAairway which captures an airway-predominant process with a positive correlation to BMI and airway wall thickness and a negative correlation to emphysema. Pathway enrichment analysis identified 29 and 13 pathways significantly associated with IEAemph and IEAairway, respectively (adjusted p<0.001). Conclusions: Integration of CT scans and blood RNA-seq data identified 2 IEAs that capture distinct inflammatory processes associated with emphysema and airway-predominant COPD.

Blood Gene Expression and Immune Cell Subtypes Associated with Chronic Obstructive Pulmonary Disease Exacerbations.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AE-COPDs) are associated with a significant disease burden. Blood immune phenotyping may improve our understanding of a COPD endotype at increased risk of exacerbations. Objective: To determine the relationship between the transcriptome of circulating leukocytes and COPD exacerbations. Methods: Blood RNA sequencing data (n = 3,618) from the COPDGene (Genetic Epidemiology of COPD) study were analyzed. Blood microarray data (n = 646) from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study were used for validation. We tested the association between blood gene expression and AE-COPDs. We imputed the abundance of leukocyte subtypes and tested their association with prospective AE-COPDs. Flow cytometry was performed on blood in SPIROMICS (Subpopulations and Intermediate Outcomes in COPD Study) (n = 127), and activation markers for T cells were tested for association with prospective AE-COPDs. Measurements and Main Results: Exacerbations were reported 4,030 and 2,368 times during follow-up in COPDGene (5.3 ± 1.7 yr) and ECLIPSE (3 yr), respectively. We identified 890, 675, and 3,217 genes associated with a history of AE-COPDs, persistent exacerbations (at least one exacerbation per year), and prospective exacerbation rate, respectively. In COPDGene, the number of prospective exacerbations in patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stage ⩾2) was negatively associated with circulating CD8+ T cells, CD4+ T cells, and resting natural killer cells. The negative association with naive CD4+ T cells was replicated in ECLIPSE. In the flow-cytometry study, an increase in CTLA4 on CD4+ T cells was positively associated with AE-COPDs. Conclusions: Individuals with COPD with lower circulating lymphocyte counts, particularly decreased CD4+ T cells, are more susceptible to AE-COPDs, including persistent exacerbations.

Genomic Surveillance of SARS-CoV-2 Variants That Emerged in South and Southeast Asia during Early 2022.

The continuously emerging new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have made the global coronavirus disease 2019 (COVID-19) pandemic unpredictable. Since the beginning of the pandemic, densely populated South and Southeast Asia have suffered great losses due to multiple COVID-19 surges because of vaccine and other medical resource shortages. Therefore, it is crucial to closely monitor the SARS-CoV-2 epidemic and to understand the evolutionary and transmission characteristics of SARS-CoV-2 in these regions. Here, we document the evolution of epidemic strains in the Philippines, Pakistan, and Malaysia from late 2021 to early 2022. Our results confirmed the circulation of at least five SARS-CoV-2 genotypes in these countries in January 2022, when Omicron BA.2, with a detection rate of 69.11%, replaced Delta B.1.617 as the dominant strain. Single-nucleotide polymorphism analysis indicated the distinct evolutionary directions of the Omicron and Delta isolates, with S, Nsp1, and Nsp6 genes potentially playing a significant role in the host adaptation of the Omicron strain. These findings are able to provide insights for predicting the evolutionary direction of SARS-CoV-2 in terms of variant competition, developing multi-part vaccines, and to support the evaluation and adjustment of current surveillance, prevention, and control strategies in South and Southeast Asia.

Heterogeneity and Progression of Chronic Obstructive Pulmonary Disease: Emphysema-Predominant and Non-Emphysema-Predominant Disease.

While variation in emphysema severity between patients with chronic obstructive pulmonary disease (COPD) is well-recognized, clinically applicable definitions of the emphysema-predominant disease (EPD) and non-emphysema-predominant disease (NEPD) subtypes have not been established. To study the clinical relevance of the EPD and NEPD subtypes, we tested the association of these subtypes with prospective decline in forced expiratory volume in 1 second (FEV1) and mortality among 3,427 subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric grade 2-4 COPD at baseline in the Genetic Epidemiology of COPD (COPDGene) Study, an ongoing national multicenter study that started in 2007. NEPD was defined as airflow obstruction with less than 5% computed tomography (CT) quantitative densitometric emphysema at -950 Hounsfield units, and EPD was defined as airflow obstruction with 10% or greater CT emphysema. Mixed-effects models for FEV1 demonstrated larger average annual FEV1 loss in EPD subjects than in NEPD subjects (-10.2 mL/year; P < 0.001), and subtype-specific associations with FEV1 decline were identified. Cox proportional hazards models showed higher risk of mortality among EPD patients versus NEPD patients (hazard ratio = 1.46, 95% confidence interval: 1.34, 1.60; P < 0.001). To determine whether the NEPD/EPD dichotomy is captured by previously described COPDGene subtypes, we used logistic regression and receiver operating characteristic (ROC) curve analysis to predict NEPD/EPD membership using these previous subtype definitions. The analysis generally showed excellent discrimination, with areas under the ROC curve greater than 0.9. The NEPD and EPD COPD subtypes capture important aspects of COPD heterogeneity and are associated with different rates of disease progression and mortality.

Nonvolatile Electrical Control and Reversible Gas Capture by Ferroelectric Polarization Switching in 2D FeI2/In2S3 van der Waals Heterostructures.

Nonvolatile electrical control is the core of future magnetoelectric nanodevices. In this work, we systematically explore both the electronic structures and transport properties of multiferroic van der Waals (vdW) heterostructures consisting of a ferromagnetic FeI2 monolayer and a ferroelectric In2S3 monolayer using density functional theory and the nonequilibrium Green's function method. The results reveal that the FeI2 monolayer can be reversibly switched between semiconducting and half-metallic properties by nonvolatile control of the In2S3 ferroelectric polarization states. Correspondingly, the proof-of-concept two-probe nanodevice based on the FeI2/In2S3 vdW heterostructure exhibits a significant valving effect by modulating the ferroelectric switching. Moreover, it is also found that the preference of nitrogen-containing gases such as NH3, NO, and NO2 for adsorption on the surface of FeI2/In2S3 vdW heterostructures strongly depends on the polarization direction of the ferroelectric layer. In particular, the FeI2/In2S3 heterostructure shows reversible capture behavior for NH3. As a result, the FeI2/In2S3 vdW heterostructure-based gas sensor demonstrates high selectivity and sensitivity. These findings may open up a new route for the application of multiferroic heterostructures to spintronics, nonvolatile memories, and gas sensors.

Phase I study of LZM005 in patients with HER2-positive metastatic breast cancer.

The prognosis of human epidermal growth factor receptor 2 (HER2) positive metastatic breast cancer (MBC) remained unsatisfactory currently, more anti-HER2 agents are needed. Here we report a phase I study that evaluated the safety, activity, and biomarkers of LZM005, a HER2 antibody, used as a monotherapy or in combination with trastuzumab plus docetaxel in patients with HER2-positive MBC. From October 2017 to December 2019, 34 patients received LZM005 (14 monotherapy, 20 combination therapy). No DLT was observed. The common adverse events (AEs) in phase Ia included diarrhea (21.4%), infusion reaction (21.4%), and hypertriglyceridemia (21.4%), while those in phase Ib were leukopenia (85.0%), neutropenia (75.0%), anemia (60.0%), diarrhea (60.0%), and rash/pruritus (50.0%). All AEs were manageable. In phase Ia, partial response (PR) was achieved in one case (1/14, overall response rate [ORR]: 7.1%); the disease control rate was 42.90% (6/14). In phase Ib, 11 patients (55.0%) achieved PR, and eight (40.0%) had stable disease. The ORR was 100% (6/6) in trastuzumab-naive and 35.7% (5/14) in trastuzumab-pretreated patients. Biomarker analysis showed that chromatin remodeling genes KMT2B and BRWD1 were associated with better progression-free survival. LZM005 is well tolerated and shows potent activity in patients with HER2-positive MBC.

High gas sensing performance of inorganic and organic molecule sensing devices based on the BC3N2 monolayer.

Recently, a novel two-dimensional (2D) BC3N2 monolayer has gained a lot of attention due to its graphene-like structure, and it was first reported by using the particle swarm optimization algorithm and ab initio calculations. Combining density functional theory with the non-equilibrium Green's function method, a 2D BC3N2-based nanodevice has been theoretically constructed and the gas sensing performance of the BC3N2 monolayer for inorganic and organic molecules has been extensively investigated. The results revealed that the BC3N2 monolayer remains metallic with thermodynamic stability. Meanwhile, the results of sensing performance analysis show that the inorganic molecules CO, NO, and NO2 and organic molecules C2H2 and HCHO have strong chemical interactions with BC3N2 and were chemically adsorbed onto BC3N2. In contrast, the interactions between NH3, SO2, CH4, C2H4 and CH3OH and BC3N2 are very weak and these molecules adopt physical adsorption. In the case of chemisorption, the electronic transport behaviors of the 2D BC3N2 devices are sensitive to molecules, and the gas sensitivity of BC3N2 is strongly anisotropic, especially for organic C2H2 with the gas sensing ratios from 7.30 to 10.43 (from 2.51 to 2.79) under different bias voltages along the zigzag (armchair) direction. For inorganic molecules, the gas sensing device is not particularly sensitive, and the maximum gas sensing ratio is only 1.36 for CO. Meanwhile, the large anisotropic gas sensitivity can reach up to 2.66/6.22 for electron transport along the armchair and zigzag directions for CO/C2H2 in the BC3N2-based sensing devices. Accordingly, the high gas sensitivity can be disclosed by displaying the scattering state around the Fermi level at different bias voltages during the transport process. As a result, BC3N2 could be used in 2D gas sensing devices, especially for sensing organic molecule C2H2.

Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiological measures to identify four COPD-related subtypes: 'relatively resistant smokers (RRS)', 'mild upper lobe-predominant emphysema (ULE)', 'airway-predominant disease (AD)' and 'severe emphysema (SE)'. In the current study, we examined the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers. METHODS: We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster associations to 5-year prospective changes in spirometric and radiological measures and to gene expression and protein levels. We used Cox-proportional hazard test to test for cluster associations to prospective exacerbations, comorbidities and mortality. RESULTS: The RRS, ULE, AD and SE clusters represented 39%, 15%, 26% and 20% of the studied cohort at baseline, respectively. The SE cluster had the greatest 5-year FEV1 (forced expiratory volume in 1 s) and emphysema progression, and the highest risks of exacerbations, cardiovascular disease and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the SE cluster had an elevated respiratory mortality risk, while the ULE, AD and SE clusters had elevated all-cause mortality risks. These clusters also demonstrated differential protein and gene expression biomarker associations, mostly related to inflammatory and immune processes. CONCLUSION: COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality and associations to transcriptomic and proteomic biomarkers. These findings emphasise the clinical and biological relevance of these subtypes, which call for more study for translation into clinical practice. TRAIL REGISTRATION NUMBER: NCT00608764.

Machine Learning Prediction of Progression in Forced Expiratory Volume in 1 Second in the COPDGene® Study.

Background: The heterogeneous nature of chronic obstructive pulmonary disease (COPD) complicates the identification of the predictors of disease progression. We aimed to improve the prediction of disease progression in COPD by using machine learning and incorporating a rich dataset of phenotypic features. Methods: We included 4496 smokers with available data from their enrollment and 5-year follow-up visits in the COPD Genetic Epidemiology (COPDGene®) study. We constructed linear regression (LR) and supervised random forest models to predict 5-year progression in forced expiratory in 1 second (FEV1) from 46 baseline features. Using cross-validation, we randomly partitioned participants into training and testing samples. We also validated the results in the COPDGene 10-year follow-up visit. Results: Predicting the change in FEV1 over time is more challenging than simply predicting the future absolute FEV1 level. For random forest, R-squared was 0.15 and the area under the receiver operator characteristic (ROC) curves for the prediction of participants in the top quartile of observed progression was 0.71 (testing) and respectively, 0.10 and 0.70 (validation). Random forest provided slightly better performance than LR. The accuracy was best for Global initiative for chronic Obstructive Lung Disease (GOLD) grades 1-2 participants, and it was harder to achieve accurate prediction in advanced stages of the disease. Predictive variables differed in their relative importance as well as for the predictions by GOLD. Conclusion: Random forest, along with deep phenotyping, predicts FEV1 progression with reasonable accuracy. There is significant room for improvement in future models. This prediction model facilitates the identification of smokers at increased risk for rapid disease progression. Such findings may be useful in the selection of patient populations for targeted clinical trials.

Efficacy of heterologous boosting against SARS-CoV-2 using a recombinant interferon-armed fusion protein vaccine (V-01): a randomized, double-blind and placebo-controlled phase III trial.

Waning of neutralizing titres along with decline of protection efficacy after the second dose of COVID-19 vaccines was observed, including China-made inactivated vaccines. Efficacy of a heterologous boosting using one dose of a recombinant SARS-CoV-2 fusion protein vaccine (V-01) in inactivated vaccine-primed population was studied, aimed to restore the immunity. A randomized, double-blind and placebo-controlled phase III trial was conducted in healthy people aged 18 years or older in Pakistan and Malaysia. Each eligible participant received one dose of the V-01 vaccine developed by Livzon Mabpharm Inc. or placebo within the 3-6 months after the two-dose primary regimen, and was monitored for safety and efficacy. The primary endpoint was protection against confirmed symptomatic SARS-CoV-2 infection. A total of 10,218 participants were randomly assigned to receive a vaccine or placebo. Virus-neutralizing antibodies were assessed in 419 participants. A dramatic increase (11.3-fold; 128.3-1452.8) of neutralizing titres was measured in the V-01 group at 14 days after the booster. Over two months of surveillance, vaccine efficacy was 47.8% (95%CI: 22.6-64.7) according to the intention-to-treat principle. The most common adverse events were transient, mild-to-moderate pain at the injection site, fever, headache, and fatigue. Serious adverse events occurred almost equally in V-01 (0.12%) and placebo (0.16%) groups. The heterologous boosting with the V-01 vaccine was safe and efficacious, which could elicit robust humoral immunity under the epidemic of the Omicron variant.Trial registration: ClinicalTrials.gov identifier: NCT05096832.

Proteoglycans: Systems-Level Insight into Their Expression in Healthy and Diseased Placentas.

Proteoglycan macromolecules play key roles in several physiological processes (e.g., adhesion, proliferation, migration, invasion, angiogenesis, and apoptosis), all of which are important for placentation and healthy pregnancy. However, their precise roles in human reproduction have not been clarified. To fill this gap, herein, we provide an overview of the proteoglycans' expression and role in the placenta, in trophoblast development, and in pregnancy complications (pre-eclampsia, fetal growth restriction), highlighting one of the most important members of this family, syndecan-1 (SDC1). Microarray data analysis showed that of 34 placentally expressed proteoglycans, SDC1 production is markedly the highest in the placenta and that SDC1 is the most upregulated gene during trophoblast differentiation into the syncytiotrophoblast. Furthermore, placental transcriptomic data identified dysregulated proteoglycan genes in pre-eclampsia and in fetal growth restriction, including SDC1, which is supported by the lower concentration of syndecan-1 in maternal blood in these syndromes. Overall, our clinical and in vitro studies, data analyses, and literature search pointed out that proteoglycans, as important components of the placenta, may regulate various stages of placental development and participate in the maintenance of a healthy pregnancy. Moreover, syndecan-1 may serve as a useful marker of syncytialization and a prognostic marker of adverse pregnancy outcomes. Further studies are warranted to explore the role of proteoglycans in healthy and complicated pregnancies, which may help in diagnostic or therapeutic developments.