The Proteomic Profile of Interstitial Lung Abnormalities

Axelsson, Gísli Thor; Guðmundsson, Gunnar; Pratte, Kathrine A; Aspelund, Thor; Putman, Rachel K.; Sanders, Jason L.; Guðmundsson, Elías F.; Hatabu, Hiroto; Guðmundsdóttir, Valborg; Guðjónsson, Alexander; Hino, Takuya; Hida, Tomoyuki; Hobbs, Brian D.; Cho, Michael H.; Silverman, Edwin K.; Bowler, Russell P.; Launer, Lenore J.; Jennings, Lori L.; Hunninghake, Gary M.; Emilsson, Valur; Gudnason, Vilmundur

doi:10.1164/rccm.202110-2296oc

Cited by 14 publications

(7 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the current issue of the Journal Axelsson and colleagues (pp. 337–346 ) present data from an unbiased proteomic analysis, utilizing an aptamer-based platform, performed in two independent prospective cohorts; the AGES (Age, Gene/Environment Susceptibility)-Reykjavik study and the Genetic Epidemiology of COPD (COPDgene) study ( 15 ). In total, the authors measured >4000 proteins in baseline blood samples from >10,000 individuals.…”

mentioning

confidence: 99%

Biomarkers for Interstitial Lung Abnormalities: A Stepping-stone Toward Idiopathic Pulmonary Fibrosis Prevention?

Maher

2022

Am J Respir Crit Care Med

View full text Add to dashboard Cite

mentioning

confidence: 99%

Biomarkers for Interstitial Lung Abnormalities: A Stepping-stone Toward Idiopathic Pulmonary Fibrosis Prevention?

Maher

2022

Am J Respir Crit Care Med

View full text Add to dashboard Cite

“…High-resolution computed tomography (HRCT) plays a crucial role in the diagnosis and classification of ILD, enabling the identification of specific radiological patterns [ 1 ]. Biomarkers [ 7 , 8 ] and genetic factors [ 9 ] have been investigated to improve diagnostic accuracy, predict disease progression, and guide treatment decisions. Therapeutic options for ILD include pharmacological interventions, such as antifibrotic agents for IPF, immunosuppressive therapies for CTD-ILD, and avoidance of offending antigens in HP, as well as supportive measures such as oxygen supplementation and pulmonary rehabilitation [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

The Role of Lung Microbiome in Fibrotic Interstitial Lung Disease—A Systematic Review

Puiu,

Motoc,

Lucaciu

et al. 2024

Biomolecules

View full text Add to dashboard Cite

Interstitial Lung Disease (ILD) involves lung disorders marked by chronic inflammation and fibrosis. ILDs include pathologies like idiopathic pulmonary fibrosis (IPF), connective tissue disease-associated ILD (CTD-ILD), hypersensitivity pneumonitis (HP) or sarcoidosis. Existing data covers pathogenesis, diagnosis (especially using high-resolution computed tomography), and treatments like antifibrotic agents. Despite progress, ILD diagnosis and management remains challenging with significant morbidity and mortality. Recent focus is on Progressive Fibrosing ILD (PF-ILD), characterized by worsening symptoms and fibrosis on HRCT. Prevalence is around 30%, excluding IPF, with a poor prognosis. Early diagnosis is crucial for optimizing outcomes in PF-ILD individuals. The lung microbiome comprises all the microorganisms that are in the respiratory tract. Relatively recent research try to evaluate its role in respiratory disease. Healthy lungs have a diverse microbial community. An imbalance in bacterial composition, changes in bacterial metabolic activities, or changes in bacterial distribution within the lung termed dysbiosis is linked to conditions like COPD, asthma and ILDs. We conducted a systematic review of three important scientific data base using a focused search strategy to see how the lung microbiome is involved in the progression of ILDs. Results showed that some differences in the composition and quality of the lung microbiome exist in ILDs that show progressive fibrosing phenotype. The results seem to suggest that the lung microbiota could be involved in ILD progression, but more studies showing its exact pathophysiological mechanisms are needed.

show abstract

“…Accurate prediction of new-onset HF allowing for the identification of high-risk individuals, offers early focused intervention and hence improved patient outcomes. Deep serum proteomics has revealed links between circulating proteins and diseases of various aetiologies, [13][14][15][16][17][18][19] with recent discoveries fueled by aptamer-based affinity methods in particular. 13,16,[20][21][22] In the current study, levels of 4782 serum proteins encoded by 4137 distinct genes, including the most reliable clinical diagnostic biomarker for HF, N-terminal pro-B-type natriuretic peptide (NT-proBNP), 1 measured in the prospective population-based Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS) cohort, were examined individually and in the context of multiple clinical variables for prediction of future HF events.…”

Section: Introductionmentioning

confidence: 99%

Proteomic prediction of incident heart failure and its main subtypes

Emilsson,

Jonsson,

Austin

et al. 2023

European J of Heart Fail

View full text Add to dashboard Cite

AimTo examine the ability of serum proteins in predicting future heart failure (HF) events, including HF with reduced or preserved ejection fraction (HFrEF or HFpEF), in relation to event time, and with or without considering established HF‐associated clinical variables.Methods and resultsIn the prospective population‐based Age, Gene/Environment Susceptibility Reykjavik Study (AGES‐RS), 440 individuals developed HF after their first visit with a median follow‐up of 5.45 years. Among them, 167 were diagnosed with HFrEF and 188 with HFpEF. A least absolute shrinkage and selection operator regression model with non‐parametric bootstrap were used to select predictors from an analysis of 4782 serum proteins, and several pre‐established clinical parameters linked to HF. A subset of 8–10 distinct or overlapping serum proteins predicted different future HF outcomes, and C‐statistics were used to assess discrimination, revealing proteins combined with a C‐index of 0.80 for all incident HF, 0.78 and 0.80 for incident HFpEF or HFrEF, respectively. In the AGES‐RS, protein panels alone encompassed the risk contained in the clinical information and improved the performance characteristics of prediction models based on N‐terminal pro‐B‐type natriuretic peptide and clinical risk factors. Finally, the protein predictors performed particularly well close to the time of an HF event, an outcome that was replicated in the Cardiovascular Health Study.ConclusionA small number of circulating proteins accurately predicted future HF in the AGES‐RS cohort of older adults, and they alone encompass the risk information found in a collection of clinical data. Incident HF events were predicted up to 8 years, with predictor performance significantly improving for events occurring less than 1 year ahead, a finding replicated in an external cohort study.

show abstract

The Proteomic Profile of Interstitial Lung Abnormalities

Cited by 14 publications

References 46 publications

Biomarkers for Interstitial Lung Abnormalities: A Stepping-stone Toward Idiopathic Pulmonary Fibrosis Prevention?

Biomarkers for Interstitial Lung Abnormalities: A Stepping-stone Toward Idiopathic Pulmonary Fibrosis Prevention?

The Role of Lung Microbiome in Fibrotic Interstitial Lung Disease—A Systematic Review

Proteomic prediction of incident heart failure and its main subtypes

Contact Info

Product

Resources

About