Skip to main content

Plasma microRNAs are associated with acute exacerbation in idiopathic pulmonary fibrosis

Abstract

Background

Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) has high short-term mortality with unknown causes. To predict this malignant condition in clinics is challenging. In this study, we aim to demonstrate whether there are miRNAs that differ between AE-IPF and stable IPF, which may be served as reliable biomarker for AE-IPF prediction.

Methods

Human fibrotic-associated miRNAs arrays were designed to detect miRNAs expression in plasma of 3 AE-IPF patients, 3 Stable-IPF (S-IPF) patients and 3 normal controls (NC). Differentially expressed miRNAs between AE-IPF and S-IPF patients were selected for further analyses. The validation studies were carried out in plasma of 12 AE-IPF patients, 45 S-IPF patients and 51 healthy control subjects. Signaling pathways and cellular processes interacted with validated miRNAs were predicted by DIANA-miRPath.

Results

According to the array analysis, 6 miRNAs showed differentiated expression between AE-IPF and S-IPF patients (P < 0.05). In the validation studies, let-7d-5p was decreased in S-IPF and further decreased in AE-IPF, when compared to NC (0.0003 ± 0.0002 vs 0.003 ± 0.002, P < 0.01 and 0.0007 ± 0.0005 vs 0.003 ± 0.002, P < 0.01). While miR-25-3p was obviously decreased in S-IPF (0.0002 ± 0.0001 vs 0.0003 ± 0.0003, P < 0.01) but significantly increased in AE-IP (0.0023 ± 0.002 vs 0.0003 ± 0.0003, P < 0.01). In receiver-operator characteristic (ROC) curve analysis, the areas under the curve (AUCs) of miR-25-3p and let-7d-5p were 0.83 and 0.75, respectively. The sensitivity at fixed specificity of 90% was improved from 50% to 66.7% when the two miRNAs were combined. The functional prediction of miRNAs suggested that the loss of anti-fibrotic capacity and the gain of uncontrolled cell growth may be required in AE-IPF pathogenesis.

Conclusions

In conclusion, miR-25-3p and let-7d-5p in plasma were differentially expressed between AE-IPF and S-IPF. A combination of these two miRNAs may be a potential biomarker for AE-IPF from IPF.

Background

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with steady worsening of symptoms and gas exchange. Most patients die from respiratory failure within 3 years [1–3]. Although the clinical course of IPF is usually gradual, but persistent, decline in lung function, some patients may experience an acute worsening of dyspnea and lung function with an unknown etiology [2], and is typically defined as acute exacerbations (AE) of IPF. AE-IPF may occur at any time during the disease course without an identifiable cause [1]. Approximately 50% of IPF patients died from AE [4] with a poor prognosis and a median survival of less than 3 months [5]. Current treatment strategies have consisted of high-dose corticosteroids, which has no any data from controlled trials to prove their efficacy for the patients of AE-IPF yet [5]. The pathological feature by chest high resolution computed tomography (HRCT) of AE-IPF is a diffuse alveolar damage superimposed on the usual interstitial pneumonia characteristics in IPF [6]. A better understanding of this disease is desirable.

Mature miRNAs are endogenous 18–24 nucleotide non-coding RNA molecules which act as posttranscriptional regulators of gene expression and are stable in circulation. The alterations of miRNAs in plasma or serum have been served as improved and noninvasive biomarkers for numerous pathological conditions, including cancers, autoimmune diseases and tissue injury [7–9]. Over the past years, molecular analysis of lung tissue resected for diagnostic purposes have provided more encouraging results that suggest that IPF lung biopsies have a unique mRNA transcriptome compared with non-fibrotic control biopsy samples [10, 11]. More recently, much effort has been made to define biologically relevant transcriptional differences in IPF patients with distinguishable disease progressions [10, 12]. Several studies have demonstrated that serum miRNAs were differentially expressed in IPF patients with rapidly or slowly progressive groups [13, 14]. However, it is unknown whether differentially expressed miRNAs in the circulation is associated with AE-IPF.

In this retrospective study, we initially compared the human fibrosis-related miRNAs between S-IPF and AE-IPF. Moreover, through a validation study in an expanded cohort, we determined the predictive role of the miRNAs in distinguishing between S-IPF and AE-IPF.

Methods

Study population

The diagnosis of IPF was recommended by the American Thoracic Society and the European Respiratory Society (ATS\ERS)[15] and was previously described [16].

The diagnosis of AE-IPF was made according to the proposed diagnostic criteria that mainly focus on a previous or concurrent diagnosis of IPF with a worsening of its clinical manifestations over 30 days or less, and the absence of infection or another identifiable etiology such as left heart failure, or pulmonary embolism [17].

A total of 63 IPF patients were admitted to Drum Tower Hospital from January 1, 2013 to June 30, 2014. Among them, 15 patients were diagnosed as AE-IPF and died within 1 month after the diagnosis. And 48 IPF patients with the stable radiographic findings and without a worsening of their clinical manifestations over a period of 30 days were defined as S-IPF. These S-IPF patients had no acute exacerbation during the follow-up period of 1–2.5 years after enrollment. In addition, 54 unrelated age-matched healthy individuals were enrolled without current or prior history of lung diseases in this study at the Center of Physical Examination of Drum Tower Hospital.

This study was approved by the Ethical Committee of the Affiliated Drum Tower Hospital of Nanjing University Medical School.

Imaging studies

Chest HRCT was performed using various CT scanners with the patients in suspended inspiration. The criteria for inclusion of IPF in the study described previously [16]. Chest HRCT for AE-IPF generally demonstrated bilateral ground-glass abnormality with or without areas of consolidation, superimposed on the UIP pattern described previously [2]. Two radiologists, without knowledge of any of the clinical, functional, and radiographic findings, independently reviewed the HRCT of all patients.

Plasma miRNAs preparation

Blood samples were obtained once the patients were diagnosed as S-IPF or AE-IPF. About 5 ml venous blood samples were collected in EDTA-containing tubes. Blood samples were centrifuged within 1 h in two steps. Firstly, all samples were centrifuged at 800 g for 10 min at 4 °C, and the supernatants were collected into new RNase-free tubes for a second centrifugation at 12,000 g for 10 min at 4 °C. The supernatants were then stored for RNA extraction.

Plasma total RNA including miRNAs were extracted with miRNeasy Serum/Plasma Kit (Qiagen) from 400ul plasma samples according to the manufacturer’s instructions. 100pmol/L synthesized cel-miR-39 was added into plasma as an internal calibrator to monitor extraction efficiency. The concentration and purity of the total RNA were measured by Nanodrop 2000.

miRNAs array procedure

96-well miRNA expression profiles were used for 3 AE-IPF, 3 Stable-IPF(S-IPF) and 3 normal controls (NC). The array was designed according to miScript miRNA PCR Array (MIHS-117Z, Qiagen) including 84 human fibrosis-associated miRNAs, an external reference cel-miR-39 and an internal reference U6. First, reverse transcription (RT) of the total RNA samples was performed with TaqMan miRNA Multiplex Reverse Transcription Kit (Applied Biosystems) according to its protocol. Next, quantitative real time PCR was performed according to the protocol of TaqMan Universal PCR master mix (Applied Biosystems) on Step One plus PCR system (Applied Biosystems).

Quantitative RT-PCR (qRT-PCR) for plasma miRNAs validation

Total miRNAs were extracted from 400 μl plasma of additional 12 AE-IPF patients, 45 S-IPF patients, as well as 51 healthy controls with PARIS Kit (Ambion), mixed with 100pmol/L synthesized cel-miR-39 as an internal calibrator to monitor extraction efficiency, and were dissolved in 50 μl elution buffer. Total miRNAs were reverse transcribed into a final volume of 30 μL cDNA with specific primers (Roche) using Prime Script RT-PCR Kit (Takara) according to the instructions. Finally, quantitative PCR was performed with UPL probe kit (Roche) using Step One plus PCR system (Applied Biosystems). The reaction conditions were: 95 °C for 10 min, and 40 cycles of 95 °C for 15 s followed by 60 °C for 1 min. Each sample was detected three times.

MiRNAs target prediction and pathway analysis

DIANA miRPath v.2.0 was used to predict target genes by one or more miRNAs into known KEGG pathways [18]. The graphical output of the program provides an overview of the parts of the pathway modulated by validated miRNAs. The statistical significance value associated with the identified signaling pathways and biological process was calculated by the program.

Statistical analysis

For the miRNA array and validation data analyses, the raw expression levels were determined by the cycle number at a predetermined threshold cycle (CT) <35. The fold-change for each miRNA from the control group to each patient group was calculated as 2-∆∆CT with miR-16 as a reference miRNA. Relative Concentrations of miRNAs in AE-IPF, S-IPF and control plasma samples were calculated as 2-∆CT and compared by the T- test. Receiver-operator characteristic (ROC) curve was generated under the nonparametric distribution assumption for expression levels of plasma miRNAs of AE-IPF and S-IPF patients by plotting sensitivity% vs (100%-specificity %). Areas under the curves (AUCs) were calculated. The biomarkers were considered to be useful when the value of AUCs were >0.7. Logistic regression was used in the combined markers analysis. All statistical analysis was performed with either SPSS17.0 or GraphPad Prism5.0 Software. 95% confidence intervals were used to quantify uncertainty, and P values < 0.05 were considered to be statistically significant.

Results

Patient characteristics

Characteristics of patients and controls including age, gender, results of lung function tests were detailed in Table 1.

Table 1 Characteristics of study subjects

Identification of pulmonary fibrosis progress-related miRNAs in plasma

We initially profiled the expression of 84 fibrosis-related miRNAs in the plasma of 3 AE-IPF patients, 3 S-IPF patients and 3 healthy controls by the fibrosis-specific miRNAs arrays. With setting a threshold of CT < 35, a total of 34 miRNAs were further analyzed. As shown in the heat map (Fig. 1), the levels of the majority of miRNAs detected in this study were decreased in both AE-IPF and S-IPF patients, when compared to that of the controls. Among them, miR-132-3p and let-7d-5p were further decreased in AE-IPF patients when compared to that of S-IPF patients (p < 0.05). To identify the miRNAs that were deferentially expressed miRNAs between AE-IPF and S-IPF patients, we further compared the expressions of the miRNAs in these two fibrotic groups to the control group. We found that miR-31-5p and miR-338-5p were up-regulated in S-IPF patients (p < 0.05), but down-regulated in AE-IPF patients (p < 0.05), while miR-25-3p and miR-92-3p were up-regulated in AE-IPF group, but down-regulated in S-IPF group. All the above miRNAs were selected for further validation.

Fig. 1
figure 1

Heatmap of the expressions of miRNAs in plasma of AE-IPF, S-IPF and healthy control. Data were shown in 2-ΔΔCT. Red indicates miRNAs induced and green indicates miRNAs repressed. AE1, AE2, AE3 represent AE-IPF samples. S1, S2, S3 represent S-IPF samples. C1, C2, C3 represent control samples. * means p < 0.05

Validation of differentially expressed miRNAs between AE-IPF and S-IPF

Concentrations of the 6 miRNAs were detected in additional 12 AE-IPF and 45 S-IPF patients, as well as 51 healthy controls by using RT-qPCR. We found that 4 of them, miR-132-3p, miR-338-5p, miR-92-3p and miR-31-5p, were not differentially expressed between AE-IPF and S-IPF groups (data not shown). As been shown in Fig. 2 and Table 2, the level of let-7d-5p was significantly decreased in AE-IPF patients, when compared to those of S-IPF patients (p < 0.05) and controls (p < 0.01). Interestingly, in the same comparison, miR-25-3p was found to be significantly decreased in S-IPF group (p < 0.01), but increased greatly in AE-IPF group (p < 0.01).

Fig. 2
figure 2

Concentration of miR-25-3p and let-7d-5p in plasma of AE-IPF, S-IPF and healthy controls. The dash presents the mean value. NC, healthy controls. * means p < 0.05. ** means p < 0.01

Table 2 Diagnostic sensitivities of measurements of single markers for predicting AE-IPF at predefined specificities

ROC analysis

To evaluate the effectiveness of the two miRNAs for predicting AE-IPF patients among IPF patients, ROC curves were constructed by comparing plasma measurements of let-7d-5p and miR-25-3p in the AE-IPF patients with that in the S-IPF patients. The diagnostic accuracy of the two miRNAs for AE-IPF prediction was calculated (Fig. 3 and Table 2). The AUCs of miR-25-3p and let-7d-5p were 0.831 and 0.752, respectively. The two candidate markers were then subject to logistic regression analysis to optimize the diagnostic utility. The sensitivity at fixed specificity of 90% was improved from 50 to 66.7%.

Fig. 3
figure 3

ROC curve analyses of plasma miR-25-3p and let-7d-5p as single markers and combined markers for predicting AE-IPF from IPF. a ROC curve of miR-25-3p as a single biomarker for predicting AE-IPF from IPF. b ROC curve of let-7d-5p as a single biomarker for predicting AE-IPF from IPF. c ROC curve of combination of miR-25-3P and let-7d-5pas a biomarker for predicting AE-IPF from IPF

Signaling pathways prediction

DIANA-mirPath analysis was applied to predict the biologic targets and pathways as well as cellular processes that miR-25-3p and let-7d-5p affected. We found that the two miRNAs shared no common direct targets at transcriptional levels. We then investigated the cellular processes interacted with miR-25-3p and let-7d-5p. We found the intersections between the two miRNAs in cell cycle related processes in an opposite way, while let-7d-5p showed the suppressive effects on these processes, miR-25-3p promoted (Table 3). Targets of miR-25-3p involved in TP53, BCL2L11 and CDKN1C, etc. The expressions of these genes were predicted to be down-regulated by miR-25-3p in AE-IPF, which suggested a proliferative potential of cells. On the other hand, the targets of let-7d-5p included TGFBR1 and CDK6. The expressions of these genes were predicted to be up-regulated in AE-IPF, which also suggested the probability of cells growth.

Table 3 The intersected biologic pathways of miR-25-3p and let-7d-5p predicted by KEGG pathways analysis

Discussion

During the last decade, several studies have explored biomarkers for the prediction of rapid progressive IPF [13, 14, 19–21]. Still, AE-IPF is a less characterized condition with unidentified causes and no tools for the prediction. Current study offers an opportunity to appreciate circulating miRNAs detection as a newer standardized tool for prediction of AE-IPF.

In line with previous studies [13, 14], we found that let-7d-5p expression was decreased in the plasma of S-IPF and further decreased in AE-IPF. We were also able to show that miR-25-3p was down-regulated in S-IPF, but significantly up-regulated in AE-IPF, a new observation that indicates that S-IPF and AE-IPF are indeed separable molecularly. As a single biomarker, the AUC of miR-25-3p or let-7d-5p was 0.831 or 0.752 respectively, and the sensitivity of the combination of the two at fixed specificity of 90% was significantly improved, arguing a beneficial potential with the combination of the two miRNAs in AE-IPF determination, although the AUC value of the current combination of the miRNAs isolated in our study is still relatively low. Further studies involve a larger AE-IPF cohort and a larger panel of testing miRNAs are desirable in order to obtain an improved AUC value. Since men and women are represented in the IPF population in different proportions, we compared the levels of miR-25-3p and let-7d-5p in the plasma of female and male patients in our study in both fibrotic groups, and observed no significant differences (data not shown).

The various functional studies on the two miRNAs, miR-25-3p and let-7d-5p, should not be neglected. First, a reduction of let-7d in epithelial cells causes epithelial-mesenchymal transition and over-expression of let-7d in fibroblasts can reduce their mesenchymal properties [22, 23], suggesting that the effect of let-7d is pro-fibrotic, a process occurring in both S-IPF and AE-IPF, but significantly enhanced in latter. On the other hand, miR-25 has been found to be increased in various cancers and may act as an onco-miRNA [24–28]. The specific large increase of miR-25-3p in AE-IPF, but reduced in S-IPF, suggested that the disease may have gained a pro-growth condition. Our findings have etiological implications that acute exacerbation in IPF may be due to the collapse of anti-fibrosis mechanisms and the gain of tumorigenic molecular tendency locally or systemically. Whether the two processes are parallel or mutually interacted is not known. More importantly, whether AE-IPF may obtain a neoplastic disease-like alteration is extremely provoking, but needs cellular and pathological evidence.

Interestingly, two genes, ATP11A and OBFC1 found to be associated with IPF susceptibility in a GWAS study [29] were predicted as targets of miR-25-3p. It will be highly interesting to study the association between the two genes and miR-25-3P in IPF pathogenesis. Moreover, it is known that the shortening of telomere length is a risk factor for the survival of IPF [16, 30]. Whether one could make a link between the shortening of telomere length and the ill-expression of miRNAs in IPF progression remains to be determined.

In addition to the patients enrolled from a single medical center with a relatively small size in our study, one weakness of this investigation is that the current study was based on a scheme of one-time-point detection of the miRNAs without longitudinal measurements due to the clinical limitations, which may mask the relationship between the dynamic expressions of the miRNAs and the disease progression. Since the variability of the clinical courses of IPF are widely ranged and might be heterogeneous [31], the identification of the predictors that are capable of distinguishing the clinical courses of IPF would be a great challenge. Nevertheless, our study may have provided a clue to position miRNAs as the candidates of AE-IPF predicators.

Conclusions

In this study, we reported that the human fibrosis-related miRNAs, miR-25-3p and let-7d-5p, were differentially expressed between S-IPF and AE-IPF. The combination of these two miRNAs was significant in predicting an acute exacerbation of IPF. The result indicates that both loss of tissue anti-fibrotic capacity and gaining of uncontrolled cell growth may be required in AE-IPF pathogenesis.

Abbreviations

AE-IPF:

Acute exacerbation of idiopathic puhlmonary fibrosis

AUCs:

Areas under the curves

IPF:

Idiopathic pulmonary fibrosis

miRNAs:

microRNAs

NC:

Normal controls

ROC:

Receiver-operator characteristic

S-IPF:

Stable in idiopathic pulmonary fibrosis

References

  1. Kim DS, Collard HR, King TJ. Classification and natural history of the idiopathic interstitial pneumonias. Proc Am Thorac Soc. 2006;3:285–92.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Collard HR, Moore BB, Flaherty KR, Brown KK, Kaner RJ, King TJ, Lasky JA, Loyd JE, Noth I, Olman MA, et al. Acute exacerbations of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2007;176:636–43.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hyzy R, Huang S, Myers J, Flaherty K, Martinez F. Acute exacerbation of idiopathic pulmonary fibrosis. Chest. 2007;132:1652–8.

    Article  PubMed  Google Scholar 

  4. Natsuizaka M, Chiba H, Kuronuma K, Otsuka M, Kudo K, Mori M, Bando M, Sugiyama Y, Takahashi H. Epidemiologic survey of Japanese patients with idiopathic pulmonary fibrosis and investigation of ethnic differences. Am J Respir Crit Care Med. 2014;190:773–9.

    Article  PubMed  Google Scholar 

  5. Song JW, Hong SB, Lim CM, Koh Y, Kim DS. Acute exacerbation of idiopathic pulmonary fibrosis: incidence, risk factors and outcome. Eur Respir J. 2011;37:356–63.

    Article  CAS  PubMed  Google Scholar 

  6. Parambil JG, Myers JL, Ryu JH. Histopathologic features and outcome of patients with acute exacerbation of idiopathic pulmonary fibrosis undergoing surgical lung biopsy. Chest. 2005;128:3310–5.

    Article  PubMed  Google Scholar 

  7. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’Briant KC, Allen A, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A. 2008;105:10513–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tijsen AJ, Pinto YM, Creemers EE. Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases. Am J Physiol Heart Circ Physiol. 2012;303:H1085–95.

    Article  CAS  PubMed  Google Scholar 

  9. Laterza OF, Lim L, Garrett-Engele PW, Vlasakova K, Muniappa N, Tanaka WK, Johnson JM, Sina JF, Fare TL, Sistare FD, et al. Plasma MicroRNAs as sensitive and specific biomarkers of tissue injury. Clin Chem. 2009;55:1977–83.

    Article  CAS  PubMed  Google Scholar 

  10. Selman M, Pardo A, Barrera L, Estrada A, Watson SR, Wilson K, Aziz N, Kaminski N, Zlotnik A. Gene expression profiles distinguish idiopathic pulmonary fibrosis from hypersensitivity pneumonitis. Am J Respir Crit Care Med. 2006;173:188–98.

    Article  CAS  PubMed  Google Scholar 

  11. Yang IV, Burch LH, Steele MP, Savov JD, Hollingsworth JW, McElvania-Tekippe E, Berman KG, Speer MC, Sporn TA, Brown KK, et al. Gene expression profiling of familial and sporadic interstitial pneumonia. Am J Respir Crit Care Med. 2007;175:45–54.

    Article  CAS  PubMed  Google Scholar 

  12. Boon K, Bailey NW, Yang J, Steel MP, Groshong S, Kervitsky D, Brown KK, Schwarz MI, Schwartz DA. Molecular phenotypes distinguish patients with relatively stable from progressive idiopathic pulmonary fibrosis (IPF). PLoS One. 2009;4:e5134.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Oak SR, Murray L, Herath A, Sleeman M, Anderson I, Joshi AD, Coelho AL, Flaherty KR, Toews GB, Knight D, et al. A micro RNA processing defect in rapidly progressing idiopathic pulmonary fibrosis. PLoS One. 2011;6:e21253.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Yang G, Yang L, Wang W, Wang J, Wang J, Xu Z. Discovery and validation of extracellular/circulating microRNAs during idiopathic pulmonary fibrosis disease progression. Gene. 2015;562:138–44.

    Article  CAS  PubMed  Google Scholar 

  15. American Thoracic Society. Idiopathic pulmonary fibrosis: diagnosis and treatment. International consensus statement. American Thoracic Society (ATS), and the European Respiratory Society (ERS). Am J Respir Crit Care Med. 2000;161:646–64.

    Article  Google Scholar 

  16. Dai J, Cai H, Zhuang Y, Wu Y, Min H, Li J, Shi Y, Gao Q, Yi L. Telomerase gene mutations and telomere length shortening in patients with idiopathic pulmonary fibrosis in a Chinese population. Respirology. 2015;20:122–8.

    Article  PubMed  Google Scholar 

  17. Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, Colby TV, Cordier JF, Flaherty KR, Lasky JA, et al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med. 2011;183:788–824.

    Article  PubMed  Google Scholar 

  18. I. S. Vlachos NKTV. DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways. Nucleic Acids Res. 2012;40:W498-504.

  19. Matsuzawa Y, Kawashima T, Kuwabara R, Hayakawa S, Irie T, Yoshida T, Rikitake H, Wakabayashi T, Okada N, Kawashima K, et al. Change in serum marker of oxidative stress in the progression of idiopathic pulmonary fibrosis. Pulm Pharmacol Ther. 2015;32:1–6.

    Article  CAS  PubMed  Google Scholar 

  20. Kakugawa T, Yokota S, Ishimatsu Y, Hayashi T, Nakashima S, Hara S, Sakamoto N, Kubota H, Mine M, Matsuoka Y, et al. Serum heat shock protein 47 levels are elevated in acute exacerbation of idiopathic pulmonary fibrosis. Cell Stress Chaperones. 2013;18:581–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Asano S, Takemura T, Katoh K, Taneda M, Kitagawa M. Epithelial regeneration after diffuse alveolar damage in relation to underlying disease and DAD stage: an autopsy study. J Med Dent Sci. 2011;58:113–21.

    PubMed  Google Scholar 

  22. Pandit KV, Corcoran D, Yousef H, Yarlagadda M, Tzouvelekis A, Gibson KF, Konishi K, Yousem SA, Singh M, Handley D, et al. Inhibition and role of let-7d in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2010;182:220–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Huleihel L, Ben-Yehudah A, Milosevic J, Yu G, Pandit K, Sakamoto K, Yousef H, LeJeune M, Coon TA, Redinger CJ, et al. Let-7d microRNA affects mesenchymal phenotypic properties of lung fibroblasts. Am J Physiol Lung Cell Mol Physiol. 2014;306:L534–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Li LM, Hu ZB, Zhou ZX, Chen X, Liu FY, Zhang JF, Shen HB, Zhang CY, Zen K. Serum microRNA profiles serve as novel biomarkers for HBV infection and diagnosis of HBV-positive hepatocarcinoma. Cancer Res. 2010;70:9798–807.

    Article  CAS  PubMed  Google Scholar 

  25. Zhao H, Wang Y, Yang L, Jiang R, Li W. MiR-25 promotes gastric cancer cells growth and motility by targeting RECK. Mol Cell Biochem. 2014;385:207–13.

    Article  CAS  PubMed  Google Scholar 

  26. Wang X, Meng X, Li H, Liu W, Shen S, Gao Z. MicroRNA-25 expression level is an independent prognostic factor in epithelial ovarian cancer. Clin Transl Oncol. 2014;16:954–8.

    Article  CAS  PubMed  Google Scholar 

  27. Razumilava N, Bronk SF, Smoot RL, Fingas CD, Werneburg NW, Roberts LR, Mott JL. miR-25 targets TNF-related apoptosis inducing ligand (TRAIL) death receptor-4 and promotes apoptosis resistance in cholangiocarcinoma. Hepatology. 2012;55:465–75.

    Article  CAS  PubMed  Google Scholar 

  28. Li BS, Zuo QF, Zhao YL, Xiao B, Zhuang Y, Mao XH, Wu C, Yang SM, Zeng H, Zou QM, et al. MicroRNA-25 promotes gastric cancer migration, invasion and proliferation by directly targeting transducer of ERBB2, 1 and correlates with poor survival. Oncogene. 2015;34:2556–65.

    Article  CAS  PubMed  Google Scholar 

  29. Fingerlin TE, Murphy E, Zhang W, Peljto AL, Brown KK, Steele MP, Loyd JE, Cosgrove GP, Lynch D, Groshong S, et al. Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis. Nat Genet. 2013;45:613–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Alder JK, Chen JJ, Lancaster L, Danoff S, Su SC, Cogan JD, Vulto I, Xie M, Qi X, Tuder RM, et al. Short telomeres are a risk factor for idiopathic pulmonary fibrosis. Proc Natl Acad Sci U S A. 2008;105:13051–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Moore BB, Fry C, Zhou Y, Murray S, Han MK, Martinez FJ, Flaherty KR. Inflammatory leukocyte phenotypes correlate with disease progression in idiopathic pulmonary fibrosis. Front Med. 2014;1:1–12.

Download references

Acknowledgements

We would like to thank all the participants in the studies.

Funding

The study was supported by the National Natural Science Foundation of China (81470253, 81570058, and 81570775), the Fundamental Research Funds for the Central Universities (021414340286), and the Medical Technology Project of Nanjing (YKK14063).

Availability of data materials

The datasets supporting the conclusions of this article are included within the article. Raw data files are available upon request.

Authors’ contributions

HYM initially designed the study, carried out array analysis and RT-qPCR examinations, data analysis and drafted the manuscript. SSF performed samples extraction, the RT-qPCR examinations, and helped to data analysis. SYS contributed to array analysis and prepared the manuscript. YZ, HL and HRC helped to collect samples, HRCT examinations and lung function tests. YZW contributed to samples extraction and helped to draft the manuscript. LY helped to data analysis and functional prediction. JHD managed collection of samples and the clinical data, participated in study design. QG supervised, coordinated, and revised the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study was approved by the Ethical Committee of the Affiliated Drum Tower Hospital of Nanjing University Medical School (No. 2013081). All participants agreed to participate in this study at the time of blood samples collection.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jinghong Dai or Qian Gao.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Min, H., Fan, S., Song, S. et al. Plasma microRNAs are associated with acute exacerbation in idiopathic pulmonary fibrosis. Diagn Pathol 11, 135 (2016). https://doi.org/10.1186/s13000-016-0583-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13000-016-0583-2

Keywords