김정은 (서울대학교)

조주연 (서울대학교)

곽낙원 (서울대학교 병원)

김정은 (서울대학교)

조주연 (서울대학교)

곽낙원 (서울대학교 병원)

Lipid dysregulation is a key factor in understanding the pathophysiology of pulmonary diseases, yet its role in nontuberculous mycobacterial pulmonary disease (NTM-PD) remains largely unexplored. This study aimed to characterize systemic and localized lipid alterations in NTM-PD by analyzing serum and lung tissue samples. Lipidomic analysis was performed on 23 lung specimens from seven patients with NTM-PD and 332 serum samples (134 from NTM-PD patients, 136 from non-NTM bronchiectasis patients, and 62 from healthy controls), identifying 960 lipid species across 650 lipid subclasses. Statistical and correlation analyses identified disease-specific lipid alterations and their associations with clinical indicators. Additionally, the machine learning-based classification model was built using serum levels of NTM-PD-associated lipid species.

Serum lipidomic data from healthy controls, NTM-PD, and BE patients revealed a specific increase in TG and PC-P levels in NTM-PD patients, while FA levels were decreased. Similarly, in lung tissue from NTM-PD patients, TG and PC-P levels increased with pulmonary lesions, whereas FA levels decreased. To assess whether serum lipid levels associated with severe pulmonary lesions could reflect disease severity in NTM-PD patients, additional analyses were conducted. The results demonstrated that lower serum TG levels significantly correlated with disease severity indicators, including smear-positive results and higher BACES scores, suggesting their potential role as a marker of disease progression.

The trend of decreasing TG levels with increasing disease severity in serum and lung tissue aligns closely with findings from previous clinical studies reporting reduced BMI in severe NTM cases. Also, a machine learning-based classification model trained on NTM-PD-associated serum lipid species effectively distinguished NTM-PD patients from healthy controls. These findings suggest that decreasing TG levels reflect the catabolic state and energy imbalance observed in advanced NTM-PD, highlighting lipid dysregulation as a key contributor to disease pathogenesis and progression.