Abstract
Background
A disintegrin-like and metalloprotease with thrombospondin type I repeats 5 (ADAMTS5) is related to inflammation and regulates the extracellular matrix. This study aimed to investigate the plasma ADAMTS5 levels and the correlations between ADAMTS5 and pulmonary function parameters in patients with chronic obstructive pulmonary disease (COPD) and to test the efficiency of ADAMTS5 for COPD diagnosis.
Methods
Seventy-nine patients with COPD and 36 healthy subjects were recruited. The plasma ADAMTS5 levels of all subjects were detected by ELISA. The correlations between ADAMTS5 and pulmonary function parameters were analyzed. The multiple linear regression analysis with stepwise selection was used to explore the relationship between ADAMTS5 and pulmonary function parameters. Receiver-operating characteristic (ROC) curve was used to investigate the role of ADAMTS5 in the diagnosis of COPD.
Results
All patients with COPD were divided into acute exacerbation of COPD (AECOPD) group (n=45) and stable COPD (S-COPD) group (n=34). Additionally, healthy subjects were included in control group (n=36). Plasma ADAMTS5 levels in AECOPD or S-COPD groups were significantly higher than those in control group (83.49±17.10ng/mL vs 61.59±15.33ng/mL, p<0.001; 69.87±11.84ng/mL vs 61.59±15.33ng/mL, p=0.014, respectively). In addition, plasma ADAMTS5 levels in AECOPD group were significantly higher than in S-COPD group (p<0.001). Meanwhile, the ADAMTS5 was negatively correlated with FVC%, FEV1%, FEV1/FVC%, PEF%, or FEF25-75%. Importantly, the ADAMTS5 was associated with FVC% and FEV1/FVC%. In addition, the area under the ROC curve (AUC) of ADAMTS5 for the diagnosis of COPD was 0.789 and the optimal threshold was 63.22ng/mL, exhibiting the sensitivity and specificity of 83.54% and 75.00%, respectively. Moreover, the ADAMTSS5 was an independent risk factor for COPD.
Conclusion
The level of plasma ADAMTS5 is increased and independently associated with FVC% and FEV1/FVC% in COPD. The ADAMTS5 exhibits moderate diagnostic accuracy in COPD. The ADAMTS5 has the potential to serve as a promising biomarker for COPD diagnosis.
Keywords: chronic obstructive pulmonary disease, ADAMTS5, inflammation, pulmonary function
Introduction
Chronic obstructive pulmonary disease (COPD) is one of the most common respiratory diseases, characterized by sustained airflow limitation causing persistent respiratory manifestations, and ranks among the top three causes of death worldwide with high morbidity.1 Chronic airway inflammation and airway remodeling (AR) represent the core pathophysiological mechanisms of COPD.
The chronic airway inflammation in COPD is attributed to various inflammatory mediators, such as IL-1β and TNF-α. These mediators induce airway damage, thereby promoting COPD progression. Currently, various drugs targeting inflammatory cytokines, such as IL-5 and IL-13, represent important therapeutic strategies for COPD.2 However, the airway inflammation in COPD is complex, and current drugs can only delay COPD progression but cannot reverse the disease.
The AR marked by sustained airflow limitation is closely associated with increased extracellular matrix (ECM) accumulation.3 Chronic stimulation by inflammatory mediators in the airway results in excessive ECM deposition, leading to AR, which impairs pulmonary function and drives COPD progression. Theoretically, inhibiting inflammatory mediators related to ECM can, on the one hand, suppress the inflammatory response and, on the other hand, reduce ECM deposition, thereby alleviating AR.4 Accordingly, targeting inflammatory factors related to ECM represents a promising therapeutic strategy for COPD.
A disintegrin-like and metalloprotease with thrombospondin type I repeats 5 (ADAMTS5) is a metalloprotease with platelet reactive protein motif, belonging to one of families of ADAMTS.5 The ADAMTS families can be divided into five functional subgroups: proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15, and 20), N-terminal procollagen signal peptidases (ADAMTS2, 3, and 14), cartilage oligomeric matrix protein cleavage enzymes (ADAMTS7 and 12), vascular hemophilia factor proteases (ADAMTS13), and a group of orphan metalloproteinases (MMP) with unknown substrates (ADAMTS6, 10, 16, 17, 18, and 19).6 It is reported that the ADAMTS family is closely related to osteoarthritis.5 Increasing studies suggest that several members of the ADAMTS family, such as ADAMTS4, 5, 7, play an important role in inflammatory responses.7,8 The ADAMTS4, 7 is mainly involved in cardiovascular diseases.9,10 Meanwhile, the ADAMTS5, as an important regulator of inflammation, regulates ECM imbalance together with inflammatory cytokines such as IL-1β and TNF-α.11,12 It is reported that the ADAMTS5 increases to regulate the ECM in pulmonary fibrosis.13 In addition, study showed that the level of ADAMTS5 increases in hypoxic conditions,14 although the mechanism is unclear. However, the change of ADAMTS5 level currently remains unclear in COPD though the hypoxic condition is closely associated with COPD.
Currently, the diagnosis of COPD mainly relies on pulmonary function testing.15 However, pulmonary function test cannot fully reflect the severity of airway inflammation. Before pulmonary function impairment occurs, airway inflammation has often persisted for a long time, which is not conducive to the early intervention of COPD.16,17 Furthermore, the pulmonary function test requires a high level of cooperation. Patients with poor cooperation are unable to perform the pulmonary function test, which hinders the diagnosis of COPD. Accordingly, exploring airway inflammation biomarkers for COPD diagnosis is warranted.18 However, biomarkers for the diagnosis of COPD currently remain limited. Many established COPD biomarkers, such as hypoxia-inducible factor 1α (HIF-1α), matrix metalloproteinase 9 (MMP9), and matrix metalloproteinase 12 (MMP12), exhibit similar characteristics to ADAMTS5.19–21 However, the diagnostic value of these markers for COPD is limited.22,23 Although several studies have investigated the role of ADAMTS5 in inflammatory and ECM remodeling, its potential as a biomarker for COPD has not yet been explored. To date, no clinical studies have explored the diagnosis efficiency of ADAMTS5 for COPD and the relationship between ADAMTS5 and pulmonary function parameters. This study aimed to investigate the diagnostic value of ADAMTS5 in COPD and the relationship between ADAMTS5 and pulmonary function parameters.
Methods
Subjects
This was a single-center and cross-sectional observational study. Inpatients with acute exacerbation of COPD (AECOPD) and outpatients with stable COPD (S-COPD) who came to the clinic for regular follow-up were recruited in the First Affiliated Hospital of Kunming Medical University from October 2022 to June 2024. All patients diagnosed with COPD fulfilled the diagnostic criteria established by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines: the patients with expiratory volume in 1s (FEV1%) predicted/forced vital capacity (FVC%) predicted (FEV1/FVC%) ratio of less than 0.7 post-bronchodilator administration were diagnosed as COPD.15 Healthy subjects were recruited from the Health Examination Center of the First Affiliated Hospital of Kunming Medical University. All subjects with 18–85 years old were included. The subjects with a history of metabolic diseases, heart failure, cerebrovascular disease, kidney disease, immune system disease, or diabetes mellitus were excluded. In addition, subjects with a history of asthma, asthma–COPD overlap (ACO), bronchiectasis, or combined pulmonary fibrosis and emphysema (CPFE) were excluded. The subjects who had been treated with oral or intravenous glucocorticoid within 2 months before enrollment were excluded. Meanwhile, the AECOPD patients who required immediate systemic glucocorticoid treatment upon admission were excluded because the fasting blood samples could not be obtained before systemic corticosteroid therapy. S-COPD patients with a history of acute exacerbation within the last 2 months were excluded. All patients with S-COPD did not adjust inhalation therapy within 2 months before enrollment. G*power was used to calculate the sample size of subjects. The flow diagram of participant recruitment was listed in Figure 1.
Figure 1.
The flow diagram of participant recruitment.
Abbreviations: COPD, chronic obstructive pulmonary disease; AECOPD, acute exacerbation of COPD; S-COPD, stable COPD.
A systematic physical examination was performed in subjects. Height and weight were measured and body mass index (BMI) was calculated. Demographic characteristics of all subjects were obtained.
Pulmonary Function Tests
The pulmonary function parameters, including FVC%, FEV1%, FEV1/FVC% ratio, peak expiratory flow (PEF%) predicted, and ratio of expiratory flow at 25% forced expiratory flow to expiratory flow at 75% forced expiratory flow (FEF25-75%), were measured by the Pulmonary Function Laboratory of the First Affiliated Hospital of Kunming Medical University. The predicted values were obtained based on the height and weight of the subjects.
This study was approved by the Ethics Committee of Kunming Medical University (Date October 21, 2022/No. (2022) L-237) and the patients’ informed consent was obtained before enrollment.
Hematology Testing
The venous blood was obtained from all subjects after fasting for more than 8 hours and was centrifuged at 4°C for 20 minutes under 2000 rpm. All blood samples were collected prior to the initiation of systemic corticosteroid therapy. The plasma was stored at −80°C for detection. Plasma ADAMTS5 concentrations were detected using an ELISA kit (CUSABIO, China). The detection range of the ADAMTS5 kit was from 15.6ng/mL to 1000ng/mL and the sensitivity of the ADAMTS5 kit is 3.90ng/mL. Test items, including alanine amino transferase (ALT), aspartate amino transferase (AST), creatinine (Cr), total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL) and low density lipoprotein (LDL), were tested by the Laboratory of the First Affiliated Hospital of Kunming Medical University.
Statistical Analysis
Data were present as mean ± SD. The single sample Kolmogorov–Smirnova was used to detect whether the data distribution was normal or not. Non-paired t-test was used for comparison of normally distributed data, while rank sum test was used for non-normally distributed data. Spearman analysis and linear regression analysis with stepwise were used to detect the relationship between ADAMTS5 and other factors. Statistical analysis was performed using IBM SPSS Statistics 24.0 and MedCalc. Sigma plot 10.0 was used for drawing.
Results
A total of 79 patients with COPD were enrolled in this study and divided into two groups, AECOPD group (n=45) and S-COPD group (n=34). In addition, the healthy subjects were included in control group (n=36). There was no difference in age, gender, or BMI among the three groups (Table 1).
Table 1.
Demographics, Hematology, and Pulmonary Function Parameters of Subjects
| Control Group n=36 |
AECOPD n=45 |
S-COPD n=34 |
|
|---|---|---|---|
| Age (years) | 59.33±12.47 | 62.71±8.31 | 60.64±10.46 |
| Gender (male, %) | 21 (58.33%) | 32 (71.11%) | 21 (61.76%) |
| BMI (kg/m2) | 24.32±3.81 | 22.93±3.47 | 24.42±3.56 |
| ALT (IU/L) | 33.94±10.26 | 32.07±10.14 | 31.72±12.71 |
| AST (IU/L) | 29.84±6.02 | 30.87±5.52 | 30.34±5.69 |
| Cr (μmol/L) | 74.10±9.56 | 77.95±9.66 | 77.37±10.72 |
| TC (mmol/L) | 3.68±1.08 | 3.36±1.09 | 3.34±1.06 |
| TG (mmol/L) | 1.79±0.51 | 1.80±0.70 | 1.82±0.66 |
| HDL (mmol/L) | 3.11±1.53 | 2.71±0.95 | 2.69±1.06 |
| LDL (mmol/L) | 2.18±0.81 | 2.17±0.97 | 2.13±0.86 |
| FVC% (%) | 126.78±19.71 | 111.89±17.54* | 104.14±19.03* |
| FEV1% (%) | 127.08±19.53 | 69.36±18.48* | 75.20±19.84* |
| FEV1/FVC% (%) | 82.76±5.32 | 49.57±11.42* | 58.12±10.05*,# |
| PEF% (%) | 132.55±20.65 | 66.51±20.63* | 85.32±25.10*,# |
| FEF25-75% (%) | 95.81±26.88 | 22.09±9.04* | 28.62±11.92*,# |
| ADAMTS5 (pg/mL) | 61.59±15.33 | 83.49±17.10* | 69.87±11.84*,# |
| GOLD stage (I-II/III-IV, n/n) | – | 37/8 | 30/4 |
| Treatment before enrollment | |||
| LABA+LAMA+ICS (n) | – | 3 | 5 |
| LABA+LAMA (n) | – | 9 | 14 |
| LABA+ICS (n) | – | 0 | 1 |
| LAMA (n) | – | 5 | 3 |
| SABA (n) | – | 2 | 0 |
| No treatment (n) | – | 26 | 11 |
Notes: *p<0.05 vs control group. #p<0.05 vs AECOPD group.
Abbreviations: AECOPD, acute exacerbation of COPD; S-COPD, stable COPD; BMI, body mass index; ALT, alanine amino transferase; AST, aspartate amino transferase; Cr, creatinine; TC, total cholesterol; TG, triglyceride; HDL, high density lipoprotein; LDL, low density lipoprotein; FVC%, forced vital capacity percentage; FEV1%, forced expiratory volume in one second percentage; PEF%, percentage; FEF25-75%, ratio of 25% to 75% FVC; ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; GOLD, Global Initiative for Chronic Obstructive Lung Disease; LABA, Long-Acting Beta2-Agonist; LAMA, Long-Acting Muscarinic Antagonist; ICS, Inhaled Corticosteroid; SABA, Short-Acting Beta2-Agonist.
Plasma ADAMTS5 levels in AECOPD or S-COPD groups were significantly higher than those in control group (83.49±17.10ng/mL vs 61.59±15.33 ng/mL, p<0.001; 69.87±11.84 ng/mL vs 61.59±15.33, p=0.014, respectively). In addition, plasma ADAMTS5 levels in AECOPD group were significantly higher than in S-COPD group (83.49±17.10ng/mL vs 69.87±11.84ng/mL, p<0.001) (Figure 2).
Figure 2.
The levels of plasma ADAMTS5 in subjects.
Abbreviations: ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; AECOPD, acute exacerbation of chronic obstructive pulmonary disease; S-COPD, stable chronic obstructive pulmonary disease.
In order to determine the correlation between ADAMTS5 and pulmonary function parameters, the correlation analysis was conducted. The results of correlation analysis showed that plasma ADAMTS5 levels were negatively correlated with FVC%, FEV1%, FEV1/FVC%, PEF%, FEF25-75%, and TG, while positively correlated with Cr with or without adjustment for age, gender, and BMI (Table 2). Multiple linear regression analysis with stepwise showed that ADAMTS5 levels were negatively associated with FVC%, FEV1/FVC%, and TG (Table 3).
Table 2.
Spearman Correlations Between ADAMTS5 and the Other Factors
| r | P value | r# | P value | |
|---|---|---|---|---|
| Age | 0.168 | 0.072 | ||
| Gender | −0.156 | 0.096 | ||
| BMI | −0.162 | 0.084 | ||
| ALT | 0.090 | 0.336 | 0.078 | 0.413 |
| AST | −0.016 | 0.863 | −0.054 | 0.572 |
| Cr | 0.190 | 0.042* | 0.193 | 0.041* |
| TC | −0.113 | 0.229 | −0.047 | 0.620 |
| TG | −0.319 | 0.001* | −0.347 | 0.000* |
| HDL | −0.039 | 0.675 | −0.083 | 0.386 |
| IDL | 0.091 | 0.334 | 0.114 | 0.230 |
| FVC% | −0.327 | 0.000* | −0.309 | 0.001* |
| FEV1% | −0.546 | 0.000* | −0.448 | 0.000* |
| FEV1/FVC% | −0.462 | 0.000* | −0.435 | 0.000* |
| PEF% | −0.497 | 0.000* | −0.397 | 0.000* |
| FEF25-75% | −0.549 | 0.000* | −0.409 | 0.000* |
Notes: r# adjusting for age, gender, BMI; *p<0.05.
Abbreviations: ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; BMI, body mass index; ALT, alanine amino transferase; AST, aspartate amino transferase; Cr, creatinine; TC, total cholesterol; TG, triglyceride; HDL, high density lipoprotein; LDL, low density lipoprotein; FVC%, forced vital capacity percentage; FEV1%, forced expiratory volume in one second percentage; PEF%, peak expiratory flow percentage; FEF25-75%, ratio of 25% to 75% FVC.
Table 3.
Stepwise Multiple Regression Models of ADAMTS5 Levels in the Control, AECOPD and S-COPD Groups (Adjusted R2=0.375)
| B (SE) | β | P value | |
|---|---|---|---|
| Constant | −138.162 (9.046) | 0.000 | |
| FVC% | −0.169 (0.068) | −0.197 | 0.015 |
| FEV1/FVC% | −0.433 (0.082) | −0.417 | 0.000 |
| TG | −10.665 (2.099) | −0.380 | 0.000 |
Notes: Independent variables considered: age, gender, BMI, Cr, TG, FEV1%, FVC%, FEV1/FVC%, PEF%, FEF25-75%.
Abbreviations: AECOPD, acute exacerbation of COPD; S-COPD, Stable COPD; ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; FVC%, forced vital capacity percentage; FEV1%, forced expiratory volume in one second percentage; TG, triglyceride; BMI, body mass index; Cr, creatinine; PEF%, percentage; FEF25-75%, ratio of 25% to 75% FVC.
In order to determine the diagnostic value of ADAMTS5 for COPD, a ROC curve was plotted to determine the efficiency of ADAMTS5 in diagnosing COPD (Figure 3). The area under the ROC curve (AUC) of ADAMTS5 for COPD diagnosis was 0.789. The sensitivity was 83.54% and the specificity was 75.00% with optimal threshold (63.22ng/mL). In addition, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 88.00%, 67.50%, 3.34, and 0.22, respectively (Table 4).
Figure 3.
The ROC curve of ADAMTS5 for diagnosis of COPD.
Abbreviations: ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; COPD, chronic obstructive pulmonary disease.
Table 4.
The Efficiency of ADAMTS5 in Diagnosing COPD or AECOPD
| The Efficiency of ADAMTS5 in Diagnosing COPD | The Efficiency of ADAMTS5 in Diagnosing AECOPD | |||
|---|---|---|---|---|
| Value | 95% CI | Value | 95% CI | |
| OT (ng/mL) | 63.22 | – | 78.84 | – |
| AUC | 0.789 | 0.703 to 0.860 | 0.809 | 0.725 to 0.876 |
| Sensitivity (%) | 83.54 | 73.50 to 90.90 | 82.22 | 67.90 to 92.00 |
| Specificity (%) | 75.00 | 57.80 to 87.90 | 87.14 | 77.00 to 93.90 |
| PPV (%) | 88.00 | 78.40 to 94.40 | 80.40 | 66.10 to 90.60 |
| NPV (%) | 67.50 | 50.6 to 81.6 | 88.40 | 78.40 to 94.90 |
| PLR | 3.34 | 2.7 to 4.10 | 6.40 | 5.40 to 7.50 |
| NLR | 0.22 | 0.10 to 0.50 | 0.20 | 0.08 to 0.50 |
Abbreviations: ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; COPD, chronic obstructive pulmonary disease; AECOPD, acute exacerbation COPD; OT, optimal threshold; PPV, positive predictive value; NPV, negative predictive value; PLR, positive likelihood ratio; NLR, negative likelihood ratio.
We evaluated the efficiency of ADAMTS5 in identifying AECOPD from patients with COPD (Figure 4). The AUC of ADAMTS5 for identifying AECOPD was 0.809. The sensitivity was 82.22% and the specificity was 87.14% with optimal threshold (78.84ng/mL). In addition, PPV, NPV, PLR, and NLR were 80.40%, 88.40%, 6.40, and 0.20, respectively (Table 4).
Figure 4.
The ROC curve of ADAMTS5 for identifying AECOPD.
Abbreviations: ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; AECOPD, acute exacerbation of chronic obstructive pulmonary disease.
Multivariate logistic regression was performed to determine the risk factor for COPD. The results showed ADAMTSS5 was an independent risk factor for COPD (Table 5).
Table 5.
The Results of Multivariate Logistic Regression for the Independent Predictor of COPD
| B | SE | Wald value | Exp(B) | 95% CI | P value | ||
|---|---|---|---|---|---|---|---|
| ADAMTS5 | 0.045 | 0.020 | 5.058 | 1.046 | 1.006 | 1.088 | 0.025 |
| HDL | −0.225 | 0.197 | 1.301 | 0.799 | 0.543 | 1.175 | 0.254 |
| Constant | −2.373 | 1.468 | 2.615 | 0.093 | – | – | 0.106 |
Note: Variables include: HDL, ADAMTS5.
Abbreviations: COPD, chronic obstructive pulmonary disease; ADAMTS5, a disintegrin-like and metalloprotease with thrombospondin type I repeats 5; HDL, high density lipoprotein.
Discussion
For the first time, this study showed that plasma ADAMTS5 levels were increased in patients with COPD and negatively associated with FVC% and FEV1/FVC%.
Several inflammatory factors promote the expression of ADAMTS5, such as IL-1β.18 It is confirmed that IL-1β is elevated in COPD,24 and the IL-1β regulated ADAMTS5 expression in human osteoarthritis.25 In addition, study showed that the level of ADAMTS5 increases in hypoxic conditions which commonly present in COPD.14 Accordingly, we speculated that the augment of ADAMTS5 in COPD may be caused by IL-1β or hypoxic conditions in this study, though we failed to explore the change of IL-1β in this study.
Pulmonary function test is the most important diagnostic method for COPD. However, pulmonary function testing demands considerable patient cooperation, posing substantial challenges for elderly patients and individuals with mental disorders. Importantly, pulmonary function test is often underutilized or incorrectly performed in primary care settings,26 leading to delayed COPD diagnosis and subsequent treatment. Accordingly, growing researches are attempting to identify novel biomarkers for COPD diagnosis.27
ADAMTS5 is an important regulator of ECM. Research suggests that the regulator of ECM, such as MMP9, is helpful for the diagnosis of COPD.22 It is reported that the sensitivity of MMP9 for diagnosing COPD is 70.0%, while the specificity is 100%.22 The results of this study showed that the sensitivity of ADAMTS5 for diagnosing COPD was 83.54%, and the specificity was 75%. This suggests that the diagnostic sensitivity of ADAMTS5 for COPD is higher than that of MMP9, while its specificity is lower than that of MMP9. In addition, MMP12 is another regulator of ECM. MMP12 levels increase in the bronchoalveolar lavage fluid or serum of patients with COPD,28,29 and serum MMP12 was negatively correlated with FEV1% and FEF25-75%.30 In this study, ADAMTS5 was also negatively correlated with FEV1% and FEF25-75%. Moreover, this study presented that FVC% and FEV1/FVC% were negatively associated with ADAMTS5. It is reported that the excessive deposition of ECM and abnormal increase of airway inflammation commonly cause congestion of the airway mucosa and the deformation and distortion of the airway in COPD, leading to the decrease of FVC% and FEV1/FVC%.31,32 Studies suggest that the ADAMTS5 directly degrades aggrecan and collagen to change the structure and composition of the ECM.33 Meanwhile, ADAMTS5 is closely related to the inflammation.7 Accordingly, the association between ADAMTS5 and FEV1/FVC% may be related to the effect of ADAMTS5 on pulmonary ECM and/or inflammation in COPD. It was seems that the ADAMTS5 was related with the AR and airway inflammation in COPD.
This study showed that the AUC of ADAMTS5 for the diagnosis of COPD was 0.789, which indicate that plasma ADAMTS5 level exhibit moderate diagnostic accuracy in COPD. Accordingly, ADAMTS5 may be useful for screening of COPD.
Identifying acute exacerbations of COPD and providing treatment is crucial for patients with COPD. Currently, the distinction of acute exacerbation of COPD mainly relies on the worsening of the patient’s symptoms. However, symptoms often have a strong subjective nature and may not fully reflect the acute exacerbation of airway inflammation. In addition, many other respiratory or non-respiratory diseases may present with similar symptoms.34 Accordingly, symptom-based identification of acute exacerbations is inherently limited. Increasing researchers are thus exploring inflammatory biomarkers as objective indicators for acute exacerbations of COPD.27 This study showed that the AUC of ADAMTS5 for identifying acute exacerbations of COPD is 0.811, exhibiting the sensitivity of 82.20% and specificity of 85.30%, which suggested that ADAMTS5 is helpful for identification of acute exacerbations of COPD.
This study presented that ADAMTS5 was negatively associated with TG. It is reported that the ADAMTS5 reduces brown adipose tissue mass and inhibits browning of white adipose, which suggests that selective targeting of ADAMTS5 may be a novel therapeutic strategy for metabolic diseases.35 As is well known, brown adipose tissue significantly accelerates the clearance of TG in the circulation.36 Accordingly, we speculated that the negative association between ADAMTS5 and TG may be caused by the ADAMTS5 reducing the brown adipose tissue.
There are several limitations. Firstly, this was a cross-sectional study and patients were recruited from a single medical center and single ethnic population, and the sample size was small. Secondly, the changes in ADAMTS5 during the acute exacerbation period and the stable period were not detected in the same group of patients. Thirdly, we cannot fully exclude potential selection bias and unmeasured confounding from medication use (eg, corticosteroids, bronchodilators). Fourthly, the absence of smoker history limits the ability to differentiate smoking effects from COPD pathology. Fifthly, the lack of external validation in an independent cohort weakens robustness. Finally, we did not perform mechanistic experiments to clarify the biological role of ADAMTS5 in COPD. Future studies should elucidate the pathways through which ADAMTS5 contributes to ECM remodeling and inflammation in COPD.
Conclusion
The plasma ADAMTS5 levels are associated with reduced pulmonary function and demonstrate moderate diagnostic performance in distinguishing patients with COPD from individuals without COPD. ADAMTS5 has the potential to serve as a promising biomarker for COPD diagnosis. However, larger prospective multicenter studies are needed to confirm these findings and to evaluate the feasibility of ADAMTS5 as a clinically applicable biomarker.
Funding Statement
This work was funded by the National Natural Science Foundation of China (grant no. 82160007), Young-middle-aged Academic and Technical Leaders Reserve Talent Program of Yunnan Province (grant no. 202305AC160017), “Xingdian Talents” Support Project of Yunnan Province (Shibo Sun, Yuanyuan Zheng, and Rei Wei), National College Student Innovation Fund (grant no. 202410678030), Health Commission of Yunnan Province - Clinical Medical Center for Emergency Traumatic Disease (2024YNLCYXZX0001), and 535 Talent Project of First Affiliated Hospital of Kunming Medical University (grant no. 2023535D12). The content is solely the responsibility of the authors and does not necessarily represent the official views of the above funds.
Data Sharing Statement
The data in this study are available from the corresponding author on reasonable request.
Ethics Approval and Consent to Participate
This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of Kunming Medical University (Date October 21, 2022/No. (2022) L-237) and the patients’ informed consent was obtained before enrollment.
Consent for Publication
The participant has provided consent for publication of the case report and accompanying images.
Disclosure
The authors declare no competing interests in this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data in this study are available from the corresponding author on reasonable request.