Lipid biomarkers for differentiating asthma-COPD overlap: Insights from LC-MS-based lipidomics

Area of Science:

• Pulmonary Medicine
• Biochemistry
• Metabolomics

Background:

• Asthma-COPD overlap (ACO) presents a complex clinical picture with severe symptoms and poorer outcomes compared to asthma or COPD alone.
• Lipid metabolism is integral to lung inflammation and function, suggesting its role in ACO pathophysiology.
• Identifying specific lipid biomarkers could improve understanding and diagnosis of ACO.

Purpose of the Study:

• To compare serum lipid profiles in patients with ACO, asthma, and COPD.
• To identify specific lipid markers that can distinguish ACO from asthma and COPD.

Main Methods:

• Serum samples from ACO, asthma, and COPD patients were analyzed using liquid chromatography-mass spectrometry (LC-MS)-based lipidomics.
• Multivariate and univariate statistical analyses were employed to identify differential lipid signatures.
• A Random Forest model integrated clinical and lipidomic data for classification.

Main Results:

• A total of 22 lipid classes and 1185 lipid species were identified.
• Distinct lipid profiles separated ACO from asthma and COPD, with hexosylceramides (HCERs) being significantly altered.
• Specific HCERs (e.g., HCER(d18:0/24:1)+H, HCER(d18:0/20:0)+H) demonstrated high accuracy in differentiating ACO and correlated inversely with FEV1 and FEV1/FVC.

Conclusions:

• ACO exhibits unique serum lipidomic alterations compared to asthma and COPD, with HCERs as key distinguishing features.
• The identified HCERs show promise as potential biomarkers for ACO.
• Further validation in larger cohorts is necessary to confirm these exploratory findings.