MicroRNA expression profiles as biomarkers of minor salivary gland inflammation and dysfunction in Sjögren's syndrome

Abstract

Objective: MicroRNA reflect physiologic and pathologic processes and may be used as biomarkers of concurrent pathophysiologic events in complex settings such as autoimmune diseases. We generated microRNA microarray profiles from the minor salivary glands of control subjects without Sjögren's syndrome (SS) and patients with SS who had low-grade or high-grade inflammation and impaired or normal saliva production, to identify microRNA patterns specific to salivary gland inflammation or dysfunction.

Methods: MicroRNA expression profiles were generated by Agilent microRNA arrays. We developed a novel method for data normalization by identifying housekeeping microRNA. MicroRNA profiles were compared by unsupervised mathematical methods to test how well they distinguish between control subjects and various subsets of patients with SS. Several bioinformatics methods were used to predict the messenger RNA targets of the differentially expressed microRNA.

Results: MicroRNA expression patterns accurately distinguished salivary glands from control subjects and patients with SS who had low-degree or high-degree inflammation. Using real-time quantitative polymerase chain reaction, we validated 2 microRNA as markers of inflammation in an independent cohort. Comparing microRNA from patients with preserved or low salivary flow identified a set of differentially expressed microRNA, most of which were up-regulated in the group with decreased salivary gland function, suggesting that the targets of microRNA may have a protective effect on epithelial cells. The predicted biologic targets of microRNA associated with inflammation or salivary gland dysfunction identified both overlapping and distinct biologic pathways and processes.

Conclusion: Distinct microRNA expression patterns are associated with salivary gland inflammation and dysfunction in patients with SS, and microRNA represent a novel group of potential biomarkers.

Trial registration: ClinicalTrials.gov NCT00001196 NCT00001852.

Figure 1

Minor salivary gland classes used for the microRNA microarray expression analysis. Each of the subgroups comprised biopsy specimens obtained from Sjögren's syndrome (SS) patients with high salivary flow and those with low salivary flow.

Figure 2

Data normalization and analysis. A, Housekeeping microRNA used to normalize data (see Patients and Methods). B, Distribution of Pearson's correlation coefficients for expression of all pairs of microRNA over all microarrays before and after normalization to the housekeeping microRNA. Only microRNA that were scored as present using Agilent Feature Extraction software on all microarrays were included in the calculations. Data are presented as box plots, where the boxes represent the 25th to 75th percentiles, the lines within the boxes represent the median, and the lines outside the boxes represent the 10th and 90th percentiles. Circles indicate outliers.

Figure 3

A, Principal components analysis (PCA) of all 24 hybridized samples. The samples are plotted along their first 3 principal components; 3 orientations of the PCA plot are shown. Non-Sjögren's syndrome (SS) minor salivary glands (MSGs) are shown in brown, MSGs with low focus scores are shown in blue, and MSGs with high focus scores are shown in red. The plots were exported from Gene-Spring. B, Hierarchical clustering of the microRNA arrays. There is a clear separation of control (C) samples from SS samples as well as a separation between SS samples with high focus scores (HF) and those with low focus scores (LF), with only 1 sample with a high focus score (HF-1) clustering with the samples with low focus scores. The dendro-gram was exported from BRB-ArrayTools. * = samples with high salivary flow.

Figure 4

Correlation between relative expression of selected microRNA and minor salivary gland focus scores (FS). From the normalized data set, we identified a pair of microRNA with distinct and opposite expression patterns in control samples, Sjögren's syndrome (SS) samples with low focus scores, and SS samples with high focus scores (the expression of miR-768-3p increases, whereas the expression of miR-574 decreases with increasing focus scores). We validated the expression patterns of these 2 microRNA by real-time quantitative polymerase chain reaction (PCR) in an independent set of samples (n = 15) with various focus scores, determining the relative expression of these 2 microRNA by calculating the difference for their respective C_t values from the same TaqMan real-time quantitative PCR. A 1-unit difference in the C_t value between the 2 microRNA represents a 2-fold difference between the 2 microRNA. There was a statistically significant difference in the C_t values between samples with low focus scores (FS 0–2), those with medium focus scores (FS 5–7), and those with high focus scores (FS 12) (P = 0.0003 by one-way analysis of variance). Values are the mean ± SEM.