Detection of interstitial pneumonia with autoimmune features and idiopathic pulmonary fibrosis are enhanced by involvement of matrix metalloproteinases levels and clinical diagnosis

Abstract Background Higher detection of interstitial pneumonia with autoimmune features (IPAF), and idiopathic pulmonary fibrosis (IPF), has significant diagnostic and therapeutic implications. Some matrix metalloproteinases (MMPs) have become reliable diagnostic biomarkers in IPAF and IPF in previous studies, yet relevant reliability remains to be recognized. Materials and Methods In this study, 36 ILDs patients, including 31 IPAF patients (Mean ± SD, 50.20 ± 5.10 years; 16 [51.6%] females) and five IPF patients (Mean ± SD, 61.20 ± 6.73 years; one [20.0%] females) were retrospectively enrolled. Serial serum samples were collected from patients with IPAF and IPF between January 2019 and December 2020. Notably, Serum MMPs levels were measured by U‐PLEX Biomarker Group 1(Human) Multiplex Assays (MSD, USA). Results A combination of MMPs and combinatorial biomarkers was strongly associated with clinical subjects in this study (AUC, 0.597 for Stability vs. Improvement and 0.756 for Stability vs. Exacerbation). Importantly, the AUC of MMP‐12 reaches 0.730 (p < 0.05, Stability AUC vs. Improvement AUC) while MMP‐13 reaches 0.741 (p < 0.05, Stability AUC vs. Exacerbation AUC) showed better performance than other MMPs in two comparisons. Conclusions Clinical risk factors and MMPs are strongly associated with either stratification of the disease of progression of IPAF or in two IPAF and IPF independent cohorts. To our knowledge, this is the first to illustrate that MMP‐12 and MMP‐13 may be expected to become typical promising biomarkers in Improvement – IPAF and Exacerbation – IPAF, respectively.


| INTRODUC TI ON
Interstitial lung diseases (ILDs), a heterogeneous set of diffuse parenchymal lung diseases, characterized by various degrees of inflammation of the pulmonary interstices, ultimately may result in pulmonary fibrosis and contribute to high morbidity and mortality. Interstitial pneumonia with autoimmune features (IPAF), an overlap classification between idiopathic interstitial pneumonia (IIPs), especially idiopathic pulmonary fibrosis (IPF), and connective tissue disease-associated interstitial lung disease (CTD-ILD); 1 currently, the proportion of IPAF varies between 7% and 34% of all ILDs, which mainly up to the group studied and the subjects recruited as the decades progressed. [2][3][4] Moreover, idiopathic pulmonary fibrosis (IPF) is also an interstitial lung disease/ a diffuse parenchymal lung disease characterized by chronic progressive pulmonary fibrosis generating a poor prognosis. 5 Interestingly, the argument about the survival and prognosis between interstitial pneumonia with autoimmune features (IPAF) and idiopathic pulmonary fibrosis (IPF) is still endless. Multiple studies have testified to the difference between them both. A study by Oldham et al. demonstrated that the IPAF subjects showed worse survival than the patients with CTD-ILD while displaying slightly better survival than patients with IPF. 6 However, a resemble study by Ahmad et al. 2 found no distinct difference among IPAF, IPF, and CTD-ILD, yet a recent view emphasized that patients enrolled in the study conforming with IPAF criteria prone to have a history of smoking similar to that of patients with IPF. 7 Matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases of an enzyme family and as the main set that catalyzes the normal turnover of the extracellular matrix (ECM) and regulates the activity of a group of endogenous proteins. 8 When under normal physiological conditions, it is essential to maintain the balance of tissue abnormalities. As the decades progressed, MMPs have been found to be significant in the area of precision medicine in several diseases as they may be used as biomarkers to detect an individual's disease susceptibility, condition, or progression. [9][10][11][12][13][14][15] The article by Yoshikazu Inoue et al. showed the study data in IPF: increased levels of MMP-1 (serum), MMP-7 (serum, BALF, and induced sputum) and other MMPs recognized in IPF. [16][17][18] In particular, previous studies showed that elevated MMP-7 was strongly connected with reduced survival in patients with IPF. [19][20][21] Unfortunately, until now, studies describing a change in level between matrix metalloproteinases (MMPs) and IPAF's subjects of worldwide scope were scarce. Meanwhile, previous research also showed that surfactant protein A (SP-A), Krebs von den Lungen-6 (KL-6), lactate dehydrogenase (LDH), Creactive protein (CRP), and total immunoglobulin E (tIgE) are also a correlation with matrix metalloproteinases (MMPs), but further confirmation need further investigated. Consequently, this article aims to identify clinical risk factors, cytokines especially serum matrix metalloproteinases (MMPs) associated with patients with IPAF and IPF, and provide guidance for the subsequent clinical diagnosis and treatment.

| Pulmonary function tests
Based on the advice of the ERS/ATS, pulmonary function tests were performed on a computerized spirometer (MasterScreen, Leibnizstrasse). The examination parameters included forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and carbon monoxide diffusing capacity (DLCO).

| Blood collection
In 36 patients with ILDs (IPAF and IPF), the initial main symptoms included active dyspnea, diffuse infiltrating shadow on X-ray chest radiograph, restricted ventilation disorder, reduced diffusion (DLCO) function, hypoxemia, etc. The fasting morning blood (5 ml) of the patients was collected through coagulation-promoting tubes within 24 h of the onset of the first respiratory symptoms. The collected samples were kept at room temperature for about 30 min and centrifuged at 3000 r/min for 10 min to obtain serum. Aliquots of serum were stored at −80°C to avoid repeated freeze-thaw.

| Statistical analysis
All Statistical analyses were performed using SPSS 26.0 and R (R Development Core Team). p values < 0.05 were considered statistically significant. In this study, t test was used for univariate analysis.
In multivariate analysis, unadjusted and adjusted logistic regression models were used to evaluate the comparison between Stability and Improvement (or Exacerbation), respectively. The selected variables of interest (MMPs and other investigational biomarkers) were adjusted in the IPAF and IPF's logistic regression model. To evaluate the ability of a combinatorial signature to identify the presence of IPAF, we first used clinical risk factors (age, sex, BMI, and smoking history) associated with IPAF in this study. Subsequently, we took selected biomarkers (MMPs, SP-A, KL-6, LDH, CRP, and tIgE) into consideration for further investigation. Given the variability and potential data loss in this cohort, respiratory symptoms were excluded from our exploratory modeling. Likewise, the IPF cohort followed the same research as the IPAF.
Receiver operating characteristic (ROC) curves were generated to determine whether combining these MMPs and other investigational biomarkers effectively identified patients with IPAF, including Stability AUC versus Improvement AUC and Stability AUC versus Exacerbation AUC, and then generated the area under the curve (AUC) for each biomarker of interest. Further, we determined whether the features of clinical significance were found by comparing the severity of progression on MMPs and other investigational biomarkers in the IPAF cohort. Regretfully, the significance of clinical indications can be performed in the IPAF cohort but not yet evaluated in the IPF cohort so the number of patients was insufficient for ROC curves. We believe that the utility of diagnostic tests derived from these variables lies in their ability to distinguish the severity of patients with IPAF. Therefore, we grasped a risk situation for Stability AUC versus Improvement AUC and Stability AUC versus Exacerbation AUC in the IPAF cohort.  Figure 1A). Of five IPF subjects, all of them also undergo medication resembling the IPAF cohort; 4 (80.0%) had a history of medicine, 2 (40.0%) had comorbidities, and 1 (20.0%) had a history of smoking.

| RE SULT
On the strength of this assessment, 1 (20.0%) in Stability, 2 (40.0%) in Improvement, and 2 (40.0%) in Exacerbation ( Figure 1B). Baseline characteristics of IPAF and IPF cohorts are summarized in Table 1. In comparison amid the IPAF and IPF cohorts, patients with IPAF were inclined to be on medication (methylprednisolone, acetylcysteine, and pirfenidone). In contrast, there was no evident statistical significance in the IPF cohort.

| Clinical risk factors
Based on the t test, we found older age, female sex, BMI (>24), and even ever-smoker associated with IPAF and IPF (Table 1), among which, seems that when accepted medical treatment, the clinical performance of females is better than that of male in the severity of IPAF (Table 2, Figure 2).

| Medication use
In the IPAF cohort, subjects tended to use methylprednisolone (83.9%), followed by acetylcysteine and pirfenidone, whereas in IPF patients seemed to preferentially use acetylcysteine (80.0%) ( Table 1). We also found that baseline characteristics of IPAF subjects stratified by severity in Table 2 all preferred Methylprednisolone. However, in the terms of outcomes for patients, methylprednisolone is not effective enough. Interestingly, acetylcysteine was used more frequently in patients with Stability-IPAF and Improvement-IPAF (Table 2).
In humans, this biomarker has a complex relationship with various disease processes, including atherosclerosis, hepatic fibrosis, and interstitial lung fibrosis. In accordance with the IPAF cohort,  (Table 3). When using MMPs as a total factor, the AUC increased to 0.619 and 0.643 for Stability AUC versus Improvement AUC and Stability AUC versus Exacerbation AUC in the IPAF cohort (p < 0.05 for the difference between the curves).
Moreover, we found that MMP-2 and MMP-9 had a better utility in Stability AUC-Improvement AUC than Stability AUC-Exacerbation AUC; nevertheless, MMP-3, MMP-7, and MMP-13 obtained a converse outcome between this comparison ( Figure 3). When adding MMPs to combinatorial biomarkers (SP-A, KL-6, LDH, CRP, tIgE), the ROC curve of Stability AUC-Improvement AUC followed similarly, but Stability AUC-Exacerbation AUC showed a stronger identification trend. Interestingly, the AUC of the MMP-12 ranged from 0.730 to 0.737 in Stability AUC versus Improvement AUC and Stability AUC versus Exacerbation AUC, with the strongest correlation in disease progression (Table 3).
Notably, in the IPF cohort, a great deal of previous research into MMPs has focused on levels of MMP-3, MMP-7, MMP-8, MMP-9, MMP-12, and MMP-13. 23,24 Due to patients with IPF enrolled being rare, the effect of MMPs in this cohort is needed to be proved in future studies.

| Other investigational biomarkers
Levels of KL-6 and SP-A significantly increased with the severity of IPAF, among which, KL-6 levels peaked in the IPAF cohort.
Meanwhile, CRP and tIgE may be significantly stronger associated with IPF based on the t test (Table 1). However, owing to a small number of patients enrolled in the IPF cohort, this finding remains to be verified. Multivariable logistic regression analyses adjusting for five investigational biomarkers in IPAF Subjects stratified by severity F I G U R E 1 Study enrollment in IPAF (A) and IPF (B) cohorts. A flow diagram of study enrollment divides patients into groups according to clinical diagnosis, the history of medicine, comorbidities, and the history of smoking. IPAF, interstitial pneumonia with autoimmune features; IPF, idiopathic pulmonary fibrosis.
of IPAF are presented in Table 2. In addition to KL-6, SP-A increased significantly, other three investigational biomarkers showed no obvious abnormalities (all within the normal range).
According to the stratification of IPAF's severity, AUCs for the five investigational biomarkers ranged from 0.379 to 0.710; and these combinatorial biomarkers were 0.583 and 0.867, respectively (Table 3). In Stability AUC versus Improvement AUC, the AUCs ranged from 0.537 to 0.710 with a combined AUC of 0.583; in Stability AUC versus Exacerbation AUC, the AUCs ranged from 0.379 to 0.600 with a combined AUC of 0.867 ( Figure 4).
Interestingly, the correlation between MMPs and LDH showed a good effect based on previous studies; thus in our study, we performed a relevant analysis in order to explore the potential efficiency and found that MMP-2 and MMP-9 lead the above relevance whatever in all patients with IPAF or each stratification of IPAF's severity ( Figure 5).

| Combinatorial signature
A combination of clinical risk factors and MMPs is strongly associated with all IPAF severity. Importantly the addition of the five investigational biomarkers SP-A, KL-6, LDH, CRP, and tIgE significantly increased the AUC to 0.756 for comparison of Stability AUC-Exacerbation AUC in the IPAF cohort (p < 0.05 for the difference between the curves) (Table 3, Figure 4).

| Pulmonary function tests (PFTs) and Blood cell test
Whether comparison between IPAF and IPF or simply a contrast among the three stratifications of IPAF's severity (p < 0.05), apart from DLCO, which identified 36 patients with moderate interstitial lung diseases, the remaining PFTs including FVC and FEV1 showed no obvious clinical significance in two cohorts ( Figure 6). No abnormality was found in the selected cytokines in the blood cell test in the IPAF and IPF cohorts.  The high incidence of Exacerbation-IPAF and adverse clinical outcomes in Table 2  In brief, we found that MMP-12 had a significant association with Improvement-IPAF, while MMP-13 predicted a specific association with Exacerbation-IPAF, yet more evidence in this finding has yet to be confirmed. MMP-13 is a crucial interstitial collagenase, important in bone remodeling and liver injury. However, the correlation between MMP-13 and Exacerbation-IPAF remains unclear.
This study found that the serum MMP-13 level in patients with Fortunately, periostin is very much in line with current research, as IPAF is also a common typing in ILD. Given the strong diagnostic efficacy of IPF, we will try to measure the potential F I G U R E 6 Analysis of the difference of various indicators at onset in IPAF and IPF cohorts. IPAF, interstitial pneumonia with autoimmune features; IPF, idiopathic pulmonary fibrosis.
efficacy of periostin in patients with IPAF for the next step. We hold a belief that any query about the limitations of this realm would be clarified in future studies.

| CON CLUS ION
Overall, this study set out to gain a better understanding of clinical risk factors, MMPs associated with combinatorial biomarkers composed of SP-A, KL-6, LDH, CRP, tIgE, to some extent, identify the existence of Improvement and Exacerbation in the IPAF cohort.
Unfortunately, further studies on the IPF cohort could not be com-

CO N FLI C T O F I NTE R E S T
The authors declare no conflict of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
Data are contained within the article or supplementary material.

CO N S E NT TO PA RTI CI PATE
Human serum samples were used in accordance with the legislation in China and the wishes of donors, their legal guardians, or next of kin, where applicable, who had offered written informed consent to use the serum samples for future unspecified research purposes.