All patients with SAP were admitted within 72 h after onset of symptoms to the Medical or Surgical Intensive Care Units of the Affiliated Zhongshan Hospital of Dalian University and Nanjing General Hospital of Nanjing Military Command from January 2010 to December 2013. Twelve of 30 SAP patients were not complicated with ALI. All patients met the criteria of the Atlanta definition of SAP. Specifically, SAP diagnosis should meet at least one of the following criteria: (1) APACHE II score ≥ 8; (2) Ranson score ≥ 3; (3) organ failure (i.e. transient and persistent); and (4) local complications (i.e. necrosis, abscess or pseudocyst). To ensure inclusion of only eligible patients with a first attack of SAP, patients with recurrent SAP, chronic pancreatitis or pancreatic cancer were excluded. ALI was defined by the American-European Consensus Conference[20].

Patient demographic and clinical characteristics are summarized in Table 1. Six SAP patients were finally excluded for not meeting all inclusion criteria, and 24 patients met the criteria; six of 24 serum samples of patients were randomly selected for miRNA microarray analysis. This study was approved by the Ethics Committee of the Affiliated Zhongshan Hospital of Dalian University and Nanjing General Hospital of Nanjing Military Command. All of the patients gave written informed consent.

Four-milliliter serum specimens from each patient were collected immediately after grouping of patients into SAP without ALI and SAP with ALI. Serum samples were immediately frozen in liquid nitrogen and then stored at -80 °C for later determination. Total RNA was extracted from serum specimens using a mirVana PARIS kit (Ambion, Austin, TX, United States). The quantity and quality of total RNA were determined using an ultraviolet spectrophotometer at 260 and 280 nm.

miRNA microarrays were manufactured by Agilent Technologies (Santa Clara, CA, United States). Total RNA samples (4-8 µg) were 3’-extended with a poly(A) tail using poly(A) polymerase. An oligonucleotide tag was then ligated to the poly(A) tail for later fluorescent dye staining (Atactic Technologies, Houston, TX, United States)[21-23]. Similar methods reported in a previous work were used in this section[24,25]. All raw data were transformed to log² values, and each expression was normalized by having zero mean and unit sample variance. In order to screen significantly differentially expressed miRNAs, we compared expression in serum between the patients with SAP with ALI and those with SAP without ALI.

The relative miRNA expression levels were further normalized using the overall median value for patients with SAP with ALI, which gave each patient a median log ratio of 0 for normalized expression levels. The weighted differences in miRNA expression between patients with SAP with ALI and those with SAP without ALI were calculated using the random variance model t-test, in which fold-change > 1.5 was considered significant. The heatmap analysis and hierarchical cluster analysis of data were performed using Multi-Experiment Viewer (MeV) v4.7.1 from the TM4 software package available as open-source software at http://www.tm4.org[26]. Hierarchical clustering was performed using the Euclidean distance metric with complete linkage option.

qRT-PCR was used to verify miRNA expression identified by microarray analysis. Of 24 serum samples of patients, 18 were assessed by qRT-PCR. The primers for RT-PCR were used to amplify miRNAs, and were designed using Premier 5.0.RNase inhibitor (Toyobo, Osaka, Japan). The reverse primer, M-MLV reverse transcriptase and U6B were purchased from Guangzhou RiboBio Co. Ltd. (China), and U6B was used as internal control. Mixtures of 1 μg total RNA, 50 nmol/L reverse primer, 5 U M-MLV reverse transcriptase (Toyobo), 2 U RNase inhibitor (Toyobo) and 0.5 μmol/L dNTP were incubated for 30 min at 16 °C, 30 min at 42 °C, and 15 min at 70 °C. The reaction mixtures were used as templates for qRT-PCR. PCR product amplification was determined by the level of fluorescence emitted by SYBR Green Realtime PCR Master Mix-Plus (Takara, Dalian, China) and MX3000P qPCR system (Stratagene, Santa Clara, CA, United States). The PCR mixture, containing 1 μL reverse transcriptase product of total RNA, 10 μL SYBR-Green Real-time PCR Master Mix-plus, 2 μL Plus solution, 2 μL each specific forward and reverse primer, and 3 μL diethyl pyrocarbonate water, was prepared in a total final volume of 20 μL. The reaction was performed at 95 °C for 2 min, followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min. Each sample was run in triplicate. Melting curves were used to verify the specificity of each PCR. The procedure for qRT-PCR was described previously[27].

The putative target prediction of validated miRNAs by qRT-PCR was performed using three online software programs: PicTar: http://www.pictar.org/; miRanda: http://www.microrna.org/microrna/home.do/; and TargetScan: http://www.targetscan.org. We used PicTar, miRanda and TargetScan together to enhance the credibility of the study. PicTar identified a list of putative targets, searching for almost fully complementary sites between miRNAs and 3’-untranslated region (UTR) mRNAs. The free energy between the binding sites was then calculated and the results were ranked by means of a score obtained using a hidden Markov model (HMM). miRNAs with multiple binding sites were highly scored. The miRanda algorithm searched for target sites on the 3’-UTRs of mRNAs. It considered both the binding energy for the duplex stability and the conservation of the target site among different species. The TargetScan algorithm was based on the identification of fully complementary zones between the miRNA seed (nucleotides 2-8) and 3’-UTR mRNA. Starting from those sites, TargetScan searched for larger interactions, ranking the results in three groups according to the length of the matches. In particular, the presence of an adenine in the first position of the target site was highly scored because of its evolutionary conservation. The prediction followed the rules: (1) perfect match at the seed region (2-8 nucleotides from the 5’ end of miRNA); (2) minimum free energy of the miRNA/target duplex should be smaller than -20 kcal/mol; and (3) total score for miRNA-mRNA pairs should be > 140. GO was performed for analysis of the biological process (BP), cellular component (CC) and molecular function (MF) of miRNA target genes based on the GO database (http://www.geneontology.org/). Fisher’s two-side exact test and χ² test were used to classify the GO categories, and the false discovery rate (FDR) was calculated to correct the P values. We chose only GOs that had a P value < 0.05 and FDR < 0.05.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to identify the enriched pathways of miRNA target genes based on the KEGG database (http://www.genome.jp/kegg/). This analysis provided a better understanding of gene expression information as a complete network. KEGG pathway annotation of the miRNA targets was found using the Database for Annotation, Visualization and Integrated Discovery (DAVID) gene annotation tool (http://david.abcc. ncifcrf.gov/). Fisher’s exact test and the threshold of significance were defined by the P value and FDR. The screening criterion was P < 0.05. To calculate the enrichment ratio and P value for KEGG analysis, we defined N as number of genes annotated by pathway chip and M as number of differentially expressed genes annotated by pathway in predicted miRNA targets. We recorded the intersecting genes belonging to GO and the pathway at the same time. According to the attributes of the intersecting target genes and miRNAs, the miRNA gene network, representing the critical miRNAs and their targets, was established in accordance with the miRNA degree. The key miRNA and gene in the network had the largest extent. The most important biological metabolic pathway and signal transduction pathway could be determined using pathway enrichment.

Statistical analyses were performed using GraphPad Prism 6.0 software (San Diego, CA, United States). Fisher’s exact test and t-test were used to assess differences in clinical features between the participants in the two groups. A value of P < 0.05 was considered statistically significant.

We investigated 287 miRNAs based on microarray data analysis. The miRNAs with fold-changes > 1.5 or < 1/2 and P < 0.05 were selected for further study. Twelve miRNAs met these criteria and were differentially expressed in patients with SAP with ALI, and in those with SAP without ALI. The 12 miRNAs are summarized in Figure 1.

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Figure 1 Circulating miRNA expression in patients with SAP with ALI and those with SAP without ALI. A and B: Differentially expressed miRNAs (P < 0.05) were analyzed by hierarchical clustering of the log² values of miRNA microarray signals. Red: Up-regulation; Green: Down-regulation; Black: No change. The legend on the right displays the miRNA represented in the corresponding row. The bar code on the top represents the color scale of the log² values. The heatmap shows 12 significantly expressed circulating miRNAs in patients with SAP with ALI and SAP without ALI using miRNA array data; C: Information and expression of 12 circulating miRNAs. ALI: Acute lung injury; miRNA: microRNA; SAP: Severe acute pancreatitis.

In order to validate the microarray results, qRT-PCR was performed for the identified 12 miRNAs (P < 0.05). We found that five miRNAs (hsa-miR-22-3p, hsa-miR-1260b, hsa-miR-762, hsa-miR-23b and hsa-miR-23a) were significantly up-regulated and seven (hsa-miR-550a*, hsa-miR-324-5p, hsa-miR-484, hsa-miR-331-3p, hsa-miR-140-3p, hsa-miR-342-3p and hsa-miR-150) were down-regulated in patients with SAP with ALI and in those with SAP without ALI (Figure 2).

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Figure 2 Differential expression of 12 circulating miRNAs were validated by quantitative reverse transcription-polymerase chain reaction. A: Validation of up-regulated expressed miRNAs. Hsa-miR-22-3p, hsa-miR-1260b, hsa-miR-762, hsa-miR-23b and hsa-miR-23a in patients with SAP with ALI were significantly up-regulated compared to patients with SAP without ALI; B: Validation of down-regulated expressed miRNAs. hsa-miR-550a*, hsa-miR-324-5p, hsa-miR-484, hsa-miR-331-3p, hsa-miR-140-3p, hsa-miR-342-3p and hsa-miR-150 were down-regulated in patients with SAP with ALI in comparison with patients with SAP without ALI. ^aP < 0.05, ^bP < 0.01. ALI: Acute lung injury; miRNA: microRNA; SAP: Severe acute pancreatitis.

Eighty-five putative target genes of the 12 validated miRNAs were found in patients with SAP with ALI and those with SAP without ALI by TargetScan, miRanda and PicTar database.

GO analysis showed annotation of the genes from three ontologies: BP, MF and CC. GO enrichment analysis of 12 validated miRNAs indicated that 4817 GOs were regulated by the down-regulated miRNAs, whereas 5088 GOs were regulated by the up-regulated miRNAs. In BP terms, they were enriched in signal transduction and metabolic processes. In CC terms, they focused on cytoplasm, cell membranes and plasma membranes, and were enriched in protein binding and in receptor activity terms in MF (Figure 3).

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Figure 3 Gene ontology analysis of genes. In BP terms, they were enriched in signal transduction and metabolic processes. In CC terms, they focused on cytoplasm, cell membranes and plasma membranes, and were enriched in protein binding and receptor activity terms in MF. In each ontology, the first at least 10 enriched terms are listed. BP: Biological process; CC: Cellular component; MF: Molecular function.

KEGG pathway analysis showed that the target genes of up-regulated miRNAs were involved in glutathione metabolism, Wnt signaling pathway, cytokine-cytokine receptor interaction, complement and coagulation cascades, methionine metabolism, apoptosis, cytosolic DNA-sensing pathway, Notch signaling pathway, chemokine signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. Target genes of down-regulated miRNAs were related to the insulin signaling pathway, transforming growth factor (TGF)-β signaling pathway, T-cell receptor signaling pathway, amino sugar and nucleotide sugar metabolism, and starch and sucrose metabolism. As an example, the Wnt signaling pathway involved in up-regulated miRNAs and regulation of Rab GTPase activity by down-regulated miRNAs is shown in Figure 4A and B.

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Figure 4 Wnt receptor signaling pathway and regulation of Rab GTPase activity involved in miRNA expression. A: Up-regulated miRNAs (has-miR-762, has-miR-1260b, has-miR-22-3p and has-miR-23b-3p) take part in regulation of the Wnt receptor signaling pathway. B: All down-regulated miRNAs (hsa-miR-550a*, hsa-miR-324-5p, hsa-miR-484, hsa-miR-331-3p, hsa-miR-140-3p, hsa-miR-342-3p and hsa-miR-150) were involved in regulating Rab GTPase activity. miRNA: microRNA.

Severe acute pancreatitis (SAP) is a potentially fatal disease characterized by wide clinical variation. Acute lung injury (ALI) is a common and serious complication of SAP. At present, the early diagnosis of SAP with ALI is still difficult. So, it is important to choose several biomarkers that may be used jointly to improve the diagnostic rate and establish the mechanism of SAP with ALI.

Some biochemical parameters have been used for diagnosis of ALI, but there are no definitive diagnostic markers and few research studies in this area. We identify circulating biomarkers for prediction of SAP with ALI.

The authors identify 12 significantly expressed circulating miRNA in SAP with ALI patients. The information on these miRNAs shed light on potential pathological mechanisms underlying SAP associated with ALI and open new doors for the development of circulating biomarkers for SAP associated with ALI.

This observational study contributes to finding relevant biomarkers for prediction of SAP with ALI.

ALI is defined as a syndrome of inflammation and increased permeability that is associated with a constellation of clinical, radiologic and physiologic abnormalities that cannot be explained by, but may coexist with, left atrial or pulmonary capillary hypertension.

SAP associated with ALI is a critical situation in clinic; therefore, it is important to find relevant biomarkers for detecting SAP associated with ALI in patients. In the present study, the authors demonstrated that 12 circulating microRNAs are associated with SAP patients with ALI. In conclusion, this observational study is novel, interesting and has potential clinical application.