Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COPD

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.

sRAGE levels are decreased in plasma and sputum of COPD secondary to biomass-burning smoke and tobacco smoking: Differences according to the rs3134940 AGER variant

The receptor for advanced glycation end products (RAGE) and its gene (AGER) have been related to lung injury and inflammatory diseases, including chronic obstructive pulmonary disease (COPD). We aimed to evaluate the association of rs2071288, rs3134940, rs184003, and rs2070600 AGER single-nucleotide variants and the soluble-RAGE plasma and sputum levels with COPD secondary to biomass-burning smoke (BBS) and tobacco smoking. Four groups, including 2189 subjects, were analyzed: COPD secondary to BBS exposure (COPD-BBS, n = 342), BBS-exposed subjects without COPD (BBES, n = 774), tobacco smoking-induced COPD (COPD-TS, n = 434), and smokers without COPD (SWOC, n = 639). Allelic discrimination assays determined the AGER variants. The sRAGE was quantified in plasma (n = 240) and induced-sputum (n = 72) samples from a subgroup of patients using the ELISA technique. In addition, a meta-analysis was performed for the association of rs2070600 with COPD susceptibility. None of the studied genetic variants were found to be associated with COPD-BBS or COPD-TS. A marginal association was observed for the rs3134940 with COPD-BBS (p = 0.066). The results from the meta-analysis, including six case-control studies (n = 4149 subjects), showed a lack of association of rs2070600 with COPD susceptibility (p = 0.681), probably due to interethnic differences. The sRAGE plasma levels were lower in COPD-BBS compared to BBS and in COPD-TS compared to SWOC. The sRAGE levels were also lower in sputum samples from COPD-BBS than BBES. Subjects with rs3134940-TC genotypes exhibit lower sRAGE plasma levels than TT subjects, mainly from the COPD-BBS and SWOC groups. The AGER variants were not associated with COPD-BBS nor COPD-TS, but the sRAGE plasma and sputum levels are related to both COPD-BBS and COPD-TS and are influenced by the rs3134940 variant.

The Regulation of Fatty Acid Synthase by Exosomal miR-143-5p and miR-342-5p in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disease caused by an aberrant repair of injured alveolar epithelial cells. The maintenance of the alveolar epithelium and its regeneration after the damage is fueled by alveolar type II (ATII) cells. Injured cells release exosomes containing microRNAs (miRNAs), which can alter the recipient cells' function. Lung tissue, ATII cells, fibroblasts, plasma, and exosomes were obtained from naive patients with IPF, patients with IPF taking pirfenidone or nintedanib, and control organ donors. miRNA expression was analyzed to study their impact on exosome-mediated effects in IPF. High miR-143-5p and miR-342-5p levels were detected in ATII cells, lung tissue, plasma, and exosomes in naive patients with IPF. Decreased FASN (fatty acid synthase) and ACSL-4 (acyl-CoA-synthetase long-chain family member 4) expression was found in ATII cells. miR-143-5p and miR-342-5p overexpression or ATII cell treatment with IPF-derived exosomes containing these miRNAs lowered FASN and ACSL-4 levels. Also, this contributed to ATII cell injury and senescence. However, exosomes isolated from patients with IPF taking nintedanib or pirfenidone increased FASN expression in ATII cells compared with naive patients with IPF. Furthermore, fibroblast treatment with exosomes obtained from naive patients with IPF increased SMAD3, CTGF, COL3A1, and TGFβ1 expression. Our results suggest that IPF-derived exosomes containing miR-143-5p and miR-342-5p inhibited the de novo fatty acid synthesis pathway in ATII cells. They also induced the profibrotic response in fibroblasts. Pirfenidone and nintedanib improved ATII cell function and inhibited fibrogenesis. This study highlights the importance of exosomes in IPF pathophysiology.

An association between plasma levels of α2-macroglobulin and α1-antitrypsin in PiMM and PiZZ individuals differing in COPD presentation

INTRODUCTION

Compared to normal PiMM, individuals with severe α1-antitrypsin (AAT) PiZZ (Glu342Lys) genotype deficiency are at higher risk of developing early-onset chronic obstructive pulmonary disease (COPD)/emphysema associated with Z-AAT polymers and neutrophilic inflammation. We aimed to investigate putative differences in plasma levels of acute phase proteins (APP) between PiMM and PiZZ subjects and to determine plasma Z-AAT polymer levels in PiZZ subjects.

MATERIALS AND METHODS

Nephelometric analysis of seven plasma APPs was performed in 67 PiMM and 44 PiZZ subjects, of whom 43 and 42, respectively, had stable COPD. Of the PiZZ-COPD patients, 21 received and 23 did not receive intravenous therapy with human AAT preparations (IV-AAT). Plasma levels of Z-AAT polymers were determined by Western blotting using specific mouse monoclonal antibodies (2C1 and LG96).

RESULTS

In addition to lower plasma AAT, PiZZ patients had higher α2-macroglobulin (A2MG) levels than PiMM patients. In contrast, PiZZ who received IV-AAT had higher AAT values but lower A2MG values than PiZZ without IV-AAT. Regardless of the AAT genotype, AAT levels were inversely correlated with A2MG, and the AAT/A2MG ratio was correlated with lung diffusion capacity (DCLO%). All PiZZ patients had circulating Z-AAT polymer levels that correlated directly with A2MG. In PiZZ without IV-AAT therapy polymer levels correlated inversely with the ratio of forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC).

CONCLUSION

Combined measurement of plasma AAT and A2MG levels may be of clinical value in assessing the progression of COPD and requires further attention.

The RAGE Axis: A Relevant Inflammatory Hub in Human Diseases

In 1992, a transcendental report suggested that the receptor of advanced glycation end-products (RAGE) functions as a cell surface receptor for a wide and diverse group of compounds, commonly referred to as advanced glycation end-products (AGEs), resulting from the non-enzymatic glycation of lipids and proteins in response to hyperglycemia. The interaction of these compounds with RAGE represents an essential element in triggering the cellular response to proteins or lipids that become glycated. Although initially demonstrated for diabetes complications, a growing body of evidence clearly supports RAGE's role in human diseases. Moreover, the recognizing capacities of this receptor have been extended to a plethora of structurally diverse ligands. As a result, it has been acknowledged as a pattern recognition receptor (PRR) and functionally categorized as the RAGE axis. The ligation to RAGE leads the initiation of a complex signaling cascade and thus triggering crucial cellular events in the pathophysiology of many human diseases. In the present review, we intend to summarize basic features of the RAGE axis biology as well as its contribution to some relevant human diseases such as metabolic diseases, neurodegenerative, cardiovascular, autoimmune, and chronic airways diseases, and cancer as a result of exposure to AGEs, as well as many other ligands.

Proteomic Networks and Related Genetic Variants Associated with Smoking and Chronic Obstructive Pulmonary Disease

Background

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

Methods

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a dimension reduction technique leveraging network topology, to produce summary scores of each proteomic network, referred to as NetSHy scores. We next performed genome-wide association study (GWAS) to identify variants associated with the NetSHy scores, or network quantitative trait loci (nQTLs). Finally, we evaluated the replicability of the networks in an independent cohort, SPIROMICS.

Results

We identified networks of 13 to 104 proteins for each phenotype and exposure in NHW and AA, and the derived NetSHy scores significantly associated with the variable of interests. Networks included known (sRAGE, ALPP, MIP1) and novel molecules (CA10, CPB1, HIS3, PXDN) and interactions involved in COPD pathogenesis. We observed 7 nQTL loci associated with NetSHy scores, 4 of which remained after conditional analysis. Networks for smoking status and emphysema, but not airflow obstruction, demonstrated a high degree of replicability across race groups and cohorts.

Conclusions

In this work, we apply state-of-the-art molecular network generation and summarization approaches to proteomic data from COPDGene participants to uncover protein networks associated with COPD phenotypes. We further identify genetic associations with networks. This work discovers protein networks containing known and novel proteins and protein interactions associated with clinically relevant COPD phenotypes across race groups and cohorts.

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.

Precision Approaches to Chronic Obstructive Pulmonary Disease Management

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. COPD heterogeneity has hampered progress in developing pharmacotherapies that affect disease progression. This issue can be addressed by precision medicine approaches, which focus on understanding an individual's disease risk, and tailoring management based on pathobiology, environmental exposures, and psychosocial issues. There is an urgent need to identify COPD patients at high risk for poor outcomes and to understand at a mechanistic level why certain individuals are at high risk. Genetics, omics, and network analytic techniques have started to dissect COPD heterogeneity and identify patients with specific pathobiology. Drug repurposing approaches based on biomarkers of specific inflammatory processes (i.e., type 2 inflammation) are promising. As larger data sets, additional omics, and new analytical approaches become available, there will be enormous opportunities to identify high-risk individuals and treat COPD patients based on their specific pathophysiological derangements. These approaches show great promise for risk stratification, early intervention, drug repurposing, and developing novel therapeutic approaches for COPD.

Baseline characteristics from a 3-year longitudinal study to phenotype subjects with COPD: the FOOTPRINTS study

BACKGROUND

FOOTPRINTS® is a prospective, longitudinal, 3-year study assessing the association between biomarkers of inflammation/lung tissue destruction and chronic obstructive pulmonary disease (COPD) severity and progression in ex-smokers with mild-to-severe COPD. Here, we present baseline characteristics and select biomarkers of study subjects.

METHODS

The methodology of FOOTPRINTS® has been published previously. The study population included ex-smokers with a range of COPD severities (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages 1-3), ex-smokers with COPD and alpha-1-antitrypsin deficiency (A1ATD) and a control group of ex-smokers without airflow limitation (EwAL). At study entry, data were collected for: demographics, disease characteristics, history of comorbidities and COPD exacerbations, symptoms, lung function and volume, exercise capacity, soluble biomarkers, and quantitative and qualitative computed tomography. Baseline data are presented with descriptive statistical comparisons for soluble biomarkers in the individual GOLD and A1ATD groups versus EwAL.

RESULTS

In total, 463 subjects were enrolled. The per-protocol set comprised 456 subjects, mostly male (64.5%). The mean (standard deviation) age was 60.7 (6.9) years. At baseline, increasing pulmonary symptoms, worse lung function, increased residual volume, reduced diffusing capacity of the lung for carbon monoxide (DLco) and greater prevalence of centrilobular emphysema were observed with increasing disease severity amongst GOLD 1-3 subjects. Subjects with A1ATD (n = 19) had similar lung function parameters to GOLD 2-3 subjects, a high residual volume comparable to GOLD 3 subjects, and similar air trapping to GOLD 2 subjects. Compared with EwAL (n = 61), subjects with A1ATD had worse lung function, increased residual volume, reduced DLco, and a greater prevalence of confluent or advanced destructive emphysema. The soluble inflammatory biomarkers white blood cell count, fibrinogen, high-sensitivity C-reactive protein and plasma surfactant protein were higher in GOLD 1-3 groups than in the EwAL group. Interleukin-6 was expressed less often in EwAL subjects compared with subjects in the GOLD and A1ATD groups. Soluble receptor for advanced glycation end product was lowest in GOLD 3 subjects, indicative of more severe emphysema.

CONCLUSIONS

These findings provide context for upcoming results from FOOTPRINTS®, which aims to establish correlations between biomarkers and disease progression in a representative COPD population.

TRIAL REGISTRATION NUMBER

NCT02719184, study start date 13/04/2016.

Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease which is characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypic complexity of COPD, traditional diagnostic methods provide limited information and pose a great challenge to clinical management. In recent years, with the development of omics technologies, proteomics, metabolomics, transcriptomics, etc., have been widely used in the study of COPD, providing great help to discover new biomarkers and elucidate the complex mechanisms of COPD. In this review, we summarize the prognostic biomarkers of COPD based on proteomic studies in recent years and evaluate their association with COPD prognosis. Finally, we present the prospects and challenges of COPD prognostic-related studies. This review is expected to provide cutting-edge evidence in prognostic evaluation of clinical patients with COPD and to inform future proteomic studies on prognostic biomarkers of COPD.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease

The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV1 decline: results from COPDGene and SPIROMICS

Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.

Significant Interrelations among Serum Annexin A1, Soluble Receptor for Advanced Glycation End Products (sRAGE) and rs2070600 in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a major cause of death and morbidity; it may be accompanied by oxidative stress and inflammation with or without underlying genetic etiology. Finding circulating biomarkers for COPD that can help early diagnosis and predict exacerbation and association with respiratory functions has been challenging. There were 40 healthy participants and 60 COPD patients in this research. The rs2070600 gene variant was examined by PCR-RFLP. Circulating sRAGE and annexin A1 levels were determined by ELISA. GSH and MDA were determined by spectrophotometry. In COPD patients, sRAGE serum levels were substantially lower, but conversely, annexin A1 levels were much greater than in controls. The rs2070600 gene polymorphism's strong association with COPD was demonstrated by genotyping and allelic frequency distribution. The GA genotype was most distributed in COPD, and it was strongly linked to lower serum sRAGE levels. The interrelation between annexin A1, sRAGE, and COPD could be explained through effects on inflammatory mediators' pathways. The rs2070600 gene polymorphism was found to significantly enhance the risk of COPD. Serum sRAGE and annexin A1 may be considered potential diagnostic tools for COPD. Through impacts on GSH and MDA levels that alter the release of inflammatory factors and, therefore, lung damage, it is possible to explain the relationship between annexin A1, sRAGE, and COPD.

Biomarkers in Systemic Juvenile Idiopathic Arthritis, Macrophage Activation Syndrome and Their Importance in COVID Era

Systemic juvenile idiopathic arthritis (sJIA) and its complication, macrophage activation syndrome (sJIA-MAS), are rare but sometimes very serious or even critical diseases of childhood that can occasionally be characterized by nonspecific clinical signs and symptoms at onset-such as non-remitting high fever, headache, rash, or arthralgia-and are biologically accompanied by an increase in acute-phase reactants. For a correct positive diagnosis, it is necessary to rule out bacterial or viral infections, neoplasia, and other immune-mediated inflammatory diseases. Delays in diagnosis will result in late initiation of targeted therapy. A set of biomarkers is useful to distinguish sJIA or sJIA-MAS from similar clinical entities, especially when arthritis is absent. Biomarkers should be accessible to many patients, with convenient production and acquisition prices for pediatric medical laboratories, as well as being easy to determine, having high sensitivity and specificity, and correlating with pathophysiological disease pathways. The aim of this review was to identify the newest and most powerful biomarkers and their synergistic interaction for easy and accurate recognition of sJIA and sJIA-MAS, so as to immediately guide clinicians in correct diagnosis and in predicting disease outcomes, the response to treatment, and the risk of relapses. Biomarkers constitute an exciting field of research, especially due to the heterogeneous nature of cytokine storm syndromes (CSSs) in the COVID era. They must be selected with utmost care-a fact supported by the increasingly improved genetic and pathophysiological comprehension of sJIA, but also of CSS-so that new classification systems may soon be developed to define homogeneous groups of patients, although each with a distinct disease.

Unique and shared systemic biomarkers for emphysema in Alpha-1 Antitrypsin deficiency and chronic obstructive pulmonary disease

BACKGROUND

Alpha-1 Antitrypsin (AAT) deficiency (AATD), the most common genetic cause of emphysema presents with unexplained phenotypic heterogeneity in affected subjects. Our objectives to identify unique and shared AATD plasma biomarkers with chronic obstructive pulmonary disease (COPD) may explain AATD phenotypic heterogeneity.

METHODS

The plasma or serum of 5,924 subjects from four AATD and COPD cohorts were analyzed on SomaScan V4.0 platform. Using multivariable linear regression, inverse variance random-effects meta-analysis, and Least Absolute Shrinkage and Selection Operator (LASSO) regression we tested the association between 4,720 individual proteins or combined in a protein score with emphysema measured by 15th percentile lung density (PD15) or diffusion capacity (DLCO) in distinct AATD genotypes (Pi*ZZ, Pi*SZ, Pi*MZ) and non-AATD, PiMM COPD subjects. AAT SOMAmer accuracy for identifying AATD was tested using receiver operating characteristic curve analysis.

FINDINGS

In PiZZ AATD subjects, 2 unique proteins were associated with PD15 and 98 proteins with DLCO. Of those, 68 were also associated with DLCO in COPD also and enriched for three cellular component pathways: insulin-like growth factor, lipid droplet, and myosin complex. PiMZ AATD subjects shared similar proteins associated with DLCO as COPD subjects. Our emphysema protein score included 262 SOMAmers and predicted emphysema in AATD and COPD subjects. SOMAmer AAT level <7.99 relative fluorescence unit (RFU) had 100% sensitivity and specificity for identifying Pi*ZZ, but it was lower for other AATD genotypes.

INTERPRETATION

Using SomaScan, we identified unique and shared plasma biomarkers between AATD and COPD subjects and generated a protein score that strongly associates with emphysema in COPD and AATD. Furthermore, we discovered unique biomarkers associated with DLCO and emphysema in PiZZ AATD.

FUNDING

This work was supported by a grant from the Alpha-1 Foundation to RPB. COPDGene was supported by Award U01 HL089897 and U01 HL089856 from the National Heart, Lung, and Blood Institute. Proteomics for COPDGene was supported by NIH 1R01HL137995. GRADS was supported by Award U01HL112707, U01 HL112695 from the National Heart, Lung, and Blood Institute, and UL1TRR002535 to CCTSI; QUANTUM-1 was supported by the National Heart Lung and Blood Institute, the Office of Rare Diseases through the Rare Lung Disease Clinical Research Network (1 U54 RR019498-01, Trapnell PI), and the Alpha-1 Foundation. COPDGene is also supported by the COPD Foundation through contributions made to an Industry Advisory Board that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, and Sunovion.

Advanced Glycation End Products in Health and Disease

Advanced glycation end products (AGEs), formed through the nonenzymatic reaction of reducing sugars with the side-chain amino groups of lysine or arginine of proteins, followed by further glycoxidation reactions under oxidative stress conditions, are involved in the onset and exacerbation of a variety of diseases, including diabetes, atherosclerosis, and Alzheimer’s disease (AD) as well as in the secondary stages of traumatic brain injury (TBI). AGEs, in the form of intra- and interprotein crosslinks, deactivate various enzymes, exacerbating disease progression. The interactions of AGEs with the receptors for the AGEs (RAGE) also result in further downstream inflammatory cascade events. The overexpression of RAGE and the AGE-RAGE interactions are especially involved in cases of Alzheimer’s disease and other neurodegenerative diseases, including TBI and amyotrophic lateral sclerosis (ALS). Maillard reactions are also observed in the gut bacterial species. The protein aggregates found in the bacterial species resemble those of AD and Parkinson’s disease (PD), and AGE inhibitors increase the life span of the bacteria. Dietary AGEs alter the gut microbiota composition and elevate plasma glycosylation, thereby leading to systemic proinflammatory effects and endothelial dysfunction. There is emerging interest in developing AGE inhibitor and AGE breaker compounds to treat AGE-mediated pathologies, including diabetes and neurodegenerative diseases. Gut-microbiota-derived enzymes may also function as AGE-breaker biocatalysts. Thus, AGEs have a prominent role in the pathogenesis of various diseases, and the AGE inhibitor and AGE breaker approach may lead to novel therapeutic candidates.

Mechanisms Linking COPD to Type 1 and 2 Diabetes Mellitus: Is There a Relationship between Diabetes and COPD?

Chronic obstructive pulmonary disease (COPD) patients frequently suffer from multiple comorbidities, resulting in poor outcomes for these patients. Diabetes is observed at a higher frequency in COPD patients than in the general population. Both type 1 and 2 diabetes mellitus are associated with pulmonary complications, and similar therapeutic strategies are proposed to treat these conditions. Epidemiological studies and disease models have increased our knowledge of these clinical associations. Several recent genome-wide association studies have identified positive genetic correlations between lung function and obesity, possibly due to alterations in genes linked to cell proliferation; embryo, skeletal, and tissue development; and regulation of gene expression. These studies suggest that genetic predisposition, in addition to weight gain, can influence lung function. Cigarette smoke exposure can also influence the differential methylation of CpG sites in genes linked to diabetes and COPD, and smoke-related single nucleotide polymorphisms are associated with resting heart rate and coronary artery disease. Despite the vast literature on clinical disease association, little direct mechanistic evidence is currently available demonstrating that either disease influences the progression of the other, but common pharmacological approaches could slow the progression of these diseases. Here, we review the clinical and scientific literature to discuss whether mechanisms beyond preexisting conditions, lifestyle, and weight gain contribute to the development of COPD associated with diabetes. Specifically, we outline environmental and genetic confounders linked with these diseases.

Soluble RAGE in COPD, with or without coexisting obstructive sleep apnoea

BACKGROUND

Hypoxia can reduce the levels of soluble receptor for advanced glycation end-products (sRAGE), a new anti-inflammatory biomarker of COPD. We assessed sRAGE in patients with hypoxia-related diseases such as COPD, OSA and OSA-COPD overlap.

METHODS

Plasma levels of sRAGE were measured in 317 subjects at baseline (57 heathy nonsmokers [HNS], 84 healthy smokers [HS], 79 OSA, 62 COPD and 35 OSA-COPD overlap patients) and in 294 subjects after one year of follow-up (50 HNS, 74 HS, 77 OSA, 60 COPD and 33 overlap).

RESULTS

After adjusting for age, sex, smoking status and body mass index, sRAGE levels showed a reduction in OSA (- 12.5%, p = 0.005), COPD (- 14.8%, p < 0.001) and OSA-COPD overlap (- 12.3%, p = 0.02) compared with HNS. There were no differences when comparing sRAGE plasma levels between overlap patients and those with OSA or COPD alone. At follow-up, sRAGE levels did not change significantly in healthy subjects, COPD and OSA or OSA-COPD overlap nontreated with continuous positive airway pressure (CPAP). Moreover, in patients with OSA and OSA-COPD overlap who were treated with CPAP, sRAGE increased significantly.

CONCLUSIONS

The levels of sRAGE are reduced in COPD and OSA. Treatment with CPAP appears to improve sRAGE levels in patients with OSA who also had COPD.

SARS-CoV-2 Causes Lung Inflammation through Metabolic Reprogramming and RAGE

Clinical studies indicate that patients infected with SARS-CoV-2 develop hyperinflammation, which correlates with increased mortality. The SARS-CoV-2/COVID-19-dependent inflammation is thought to occur via increased cytokine production and hyperactivity of RAGE in several cell types, a phenomenon observed for other disorders and diseases. Metabolic reprogramming has been shown to contribute to inflammation and is considered a hallmark of cancer, neurodegenerative diseases, and viral infections. Malfunctioning glycolysis, which normally aims to convert glucose into pyruvate, leads to the accumulation of advanced glycation end products (AGEs). Being aberrantly generated, AGEs then bind to their receptor, RAGE, and activate several pro-inflammatory genes, such as IL-1b and IL-6, thus, increasing hypoxia and inducing senescence. Using the lung epithelial cell (BEAS-2B) line, we demonstrated that SARS-CoV-2 proteins reprogram the cellular metabolism and increase pyruvate kinase muscle isoform 2 (PKM2). This deregulation promotes the accumulation of AGEs and senescence induction. We showed the ability of the PKM2 stabilizer, Tepp-46, to reverse the observed glycolysis changes/alterations and restore this essential metabolic process.

Chronic obstructive pulmonary disease risk assessment tools: is one better than the others?

PURPOSE OF REVIEW

Risk assessment tools are essential in COPD care to help clinicians identify patients at higher risk of accelerated lung function decline, respiratory exacerbations, hospitalizations, and death.

RECENT FINDINGS

Conventional methods of assessing risk have focused on spirometry, patient-reported symptoms, functional status, and a combination of these tools in composite indices. More recently, qualitatively and quantitatively assessed chest imaging findings, such as emphysema, large and small airways disease, and pulmonary vascular abnormalities have been associated with poor long-term outcomes in COPD patients. Although several blood and sputum biomarkers have been investigated for risk assessment in COPD, most still warrant further validation. Finally, novel remote digital monitoring technologies may be valuable to predict exacerbations but their large-scale performance, ease of implementation, and cost effectiveness remain to be determined.

SUMMARY

Given the complex heterogeneity of COPD, any single metric is unlikely to fully capture the risk of poor long-term outcomes. Therefore, clinicians should review all available clinical data, including spirometry, symptom severity, functional status, chest imaging, and bloodwork, to guide personalized preventive care of COPD patients. The potential of machine learning tools and remote monitoring technologies to refine COPD risk assessment is promising but remains largely untapped pending further investigation.

Association between plasma sRAGE and emphysema according to the genotypes of AGER gene

Background

Higher soluble receptor for advanced glycation end product (sRAGE) levels are considered to be associated with severe emphysema. However, the relationship remains uncertain when the advanced glycation end-product specific receptor (AGER) gene is involved. We aimed to analyse the association between sRAGE levels and emphysema according to the genotypes of rs2070600 in the AGER gene.

Methods

We genotyped rs2070600 and measured the plasma concentration of sRAGE in each participant. Emphysema was quantified based on the chest computed tomography findings. We compared sRAGE levels based on the presence or absence and severity of emphysema in each genotype. Multiple logistic and linear regression models were used for the analyses.

Results

A total of 436 participants were included in the study. Among them, 64.2% had chronic obstructive pulmonary disease and 34.2% had emphysema. Among the CC-genotyped participants, the sRAGE level was significantly higher in participants without emphysema than in those with emphysema (P < 0.001). In addition, sRAGE levels were negatively correlated with emphysema severity in CC-genotyped patients (r = − 0.268 P < 0.001). Multiple regression analysis revealed that sRAGE was an independent protective factor for the presence of emphysema (adjusted odds ratio, 0.24; 95% confidence interval (CI) 0.11–0.51) and severity of emphysema (β = − 3.28, 95% CI − 4.86 to − 1.70) in CC-genotyped participants.

Conclusion

Plasma sRAGE might be a biomarker with a protective effect on emphysema among CC-genotyped patients of rs2070600 on the AGER gene. This is important in determining the target group for the future prediction and treatment of emphysema.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01848-9.

Plasma sRAGE levels strongly associate with centrilobular emphysema assessed by HRCT scans

Background

There is a strong need for biomarkers to better characterize individuals with COPD and to take into account the heterogeneity of COPD. The blood protein sRAGE has been put forward as promising biomarker for COPD in general and emphysema in particular. Here, we measured plasma sRAGE levels using quantitative LC–MS and assessed whether the plasma sRAGE levels associate with (changes in) lung function, radiological emphysema parameters, and radiological subtypes of emphysema.

Methods

Three hundred and twenty-four COPD patients (mean FEV₁: 63%predicted) and 185 healthy controls from the COPDGene study were selected. Plasma sRAGE was measured by immunoprecipitation in 96-well plate methodology to enrich sRAGE, followed by targeted quantitative liquid chromatography-mass spectrometry. Spirometry and HRCT scans (inspiration and expiration) with a 5-year follow-up were used; both subjected to high quality control standards.

Results

Lower sRAGE values significantly associated with the presence of COPD, the severity of airflow obstruction, the severity of emphysema on HRCT, the heterogeneous distribution of emphysema, centrilobular emphysema, and 5-year progression of emphysema. However, sRAGE values did not associate with airway wall thickness or paraseptal emphysema.

Conclusions

Rather than being a general COPD biomarker, sRAGE is especially a promising biomarker for centrilobular emphysema. Follow-up studies should elucidate whether sRAGE can be used as a biomarker for other COPD phenotypes as well.

The Decrease in Serum sRAGE Levels Upon Smoking is Associated with Activated Neutrophils

The serum level of the soluble Receptor for Advanced Glycation End-products (sRAGE) is a promising blood biomarker for the development, severity, and progression of chronic obstructive pulmonary disease (COPD). However, cigarette smoking causes a nearly instant drop in circulating sRAGE levels, strongly impacting on the variability in sRAGE levels. In the current study, we investigated the possible mechanism behind the sudden drop in sRAGE upon smoking. We showed that the number of activated neutrophils in blood significantly increases within two hours upon smoking three cigarettes within one hour. Furthermore, an increased expression of the leukocyte activation marker CD11b, which is a known ligand for RAGE, was observed upon smoking. Additionally, the in vitro activation of neutrophils increased their capacity to bind sRAGE. Together, these data indicate that smoking activates neutrophils in the circulation with concomitant upregulation of the RAGE ligand CD11b, leading to reduced levels of sRAGE in serum.

Adsorptive Microtiter Plates As Solid Supports in Affinity Purification Workflows

Affinity ligands such as antibodies are widely used in (bio)medical research for purifying proteins from complex biological samples. These ligands are generally immobilized onto solid supports which facilitate the separation of a captured protein from the sample matrix. Adsorptive microtiter plates are commonly used as solid supports prior to immunochemical detection (e.g., immunoassays) but hardly ever prior to liquid chromatography–mass spectrometry (LC-MS-)-based detection. Here, we describe the use of adsorptive microtiter plates for protein enrichment prior to LC-MS detection, and we discuss opportunities and challenges of corresponding workflows, based on examples of targeted (i.e., soluble receptor for advanced glycation end-products (sRAGE) in human serum) and discovery-based workflows (i.e., transcription factor p65 (NF-κB) in lysed murine RAW 264.7 macrophages and peptidyl-prolyl cis–trans isomerase FKBP5 (FKBP5) in lysed human A549 alveolar basal epithelial cells). Thereby, we aim to highlight the potential usefulness of adsorptive microtiter plates in affinity purification workflows prior to LC-MS detection, which could increase their usage in mass spectrometry-based protein research.

Genetic evidence for a causative effect of airflow obstruction on left ventricular filling: a Mendelian randomisation study

Background

Observational studies on the general population have suggested that airflow obstruction associates with left ventricular (LV) filling. To limit the influence of environmental risk factors/exposures, we used a Mendelian randomisation (MR) approach based on common genetic variations and tested whether a causative relation between airflow obstruction and LV filling can be detected.

Methods

We used summary statistics from large genome-wide association studies (GWAS) on the ratio of forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC) measured by spirometry and the LV end-diastolic volume (LVEDV) as assessed by cardiac magnetic resonance imaging. The primary MR was based on an inverse variance weighted regression. Various complementary MR methods and subsets of the instrument variables were used to assess the plausibility of the findings.

Results

We obtained consistent evidence in our primary MR analysis and subsequent sensitivity analyses that reducing airflow obstruction leads to increased inflow to the LV (odds ratio [OR] from inverse variance weighted regression 1.05, 95% confidence interval [CI] 1.01–1.09, P = 0.0172). Sensitivity analyses indicated a certain extent of negative horizontal pleiotropy and the estimate from biased-corrected MR-Egger was adjusted upward (OR 1.2, 95% CI 1.09–1.31, P < 0.001). Prioritisation of single genetic variants revealed rs995758, rs2070600 and rs7733410 as major contributors to the MR result.

Conclusion

Our findings indicate a causal relationship between airflow obstruction and LV filling in the general population providing genetic context to observational associations. The results suggest that targeting (even subclinical) airflow obstruction can lead to direct cardiac improvements, demonstrated by an increase in LVEDV. Functional annotation of single genetic variants contributing most to the causal effect estimate could help to prioritise biological underpinnings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01795-9.