Manuscript Title: A 4-miRNAs Serum Panel for Obstructive Sleep Apnea Syndrome Screening

Abstract

Background: Obstructive sleep apnea syndrome (OSAS) is a common chronic sleep disorder. OSAS is closely related to cardiovascular disease, metabolic disorders, cancer risk, and sudden death. This association has special significance in young people. Although it is known that OSAS has a great impact on physical health, it is estimated that 70-80% of patients with moderate-to-severe OSAS remain undiagnosed. Therefore, a new method for early diagnosis of the disease, the therapeutic effect of OSAS and prevention of complications to important.

Methods: A total of 110 patients with moderate-to-severe OSAS diagnosed in the Sleep Disorders Diagnosis and Treatment Center of Peking University Shenzhen Hospital were selected. After excluding other diseases, 59 patients were finally selected as the OSAS group. In addition, 60 healthy people were selected as the control group. Serum RNA was then extracted. Eight RNA samples were randomly selected from the two groups for high-throughput miRNA sequencing. The 10 miRNAs with the greatest differences were selected as preselected markers from the results. Then, qRT-PCR was performed on the remaining RNA samples of the two groups to extract and verify the 10 miRNAs, and statistical analysis was performed between groups.

Results: A diagnostic panel was constructed by a stepwise logistic regression model combined with the expression data of miRNAs in the validation phase. A four-miRNA panel was identified to better predict OSAS, and the model was calculated using the following formula: Logit (P)= 0.77-1.65 × miR-486-5p - 4.56 × miR-148a-3p + 1.79 × miR-744-5p + 1.13 × let-7d-3p. The AUC for the four-miRNA panel was 0.955 (95% CI: 0.899 to 0.985; sensitivity = 91.38%, specificity = 91.38%). Gene Ontology (GO) annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis was included in bioinformatic analysis.

Conclusion: A 4-miRNAs panel as a diagnostic biomarker for OSAS screening is feasible.

Keywords: bioinformatics; biomarkers; diagnosis; microRNA; obstructive sleep apnea syndrome.

Figure 1

The flowchart of the study design.

Figure 2

The expression profile of miRNAs by miRNA sequencing in the screening stage. (A) the volcanic map of the expression profile of miRNAs. (B) the heatmap of the expression profile of miRNAs with the serums of 8 OSASH patients and 8 controls. Different color indicates the fold-change of the relative expression level, whereas blue means down-regulated, and red means upregulated. Ten candidate miRNAs were selected based on the differential expression (2-fold change and p-value < 0.01).

Figure 3

Expression levels of the 10 candidate miRNAs in the validation stage. Expression levels of miR-486-5p (A), miR-215-5p (B), miR-148a-3p (C), miR-191-5p (D), miR-182-5p(E), miR-150-5p (F), miR-744-5p (G), miR-223-3p (H), let-7d-3p (I), and miR-361-3p (J) in the validation stage. The serum of 59 OSASH patients and 60 controls were used in the stage. *Represents P < 0.05, **Represents P < 0.01, ***Represents P < 0.001.

Figure 4

The receiver operating characteristic (ROC) curve analyses of 10 candidate miRNAs in validation stage. The AUCs were 0.745 for miR-486-5p (A), 0.645 for miR-215-5p (B), 0.804 for miR-148a-3p (C), 0.513 for miR-191-5p (D), 0.565 for miR-182-5p (E), 0.5 for miR-150-5p (F), 0.729 for miR-744-5p (G), 0.525 for miR-223-3p (H), 0.742 for let-7d-3p (I), and 0.646 for miR-361-3p (J).

Figure 5

The receiver operating characteristic (ROC) curve analyses for the miRNA panels. The AUC for the four-miRNA panel (miR-486-5p, miR-148a-3p, miR-744-5p, let-7d-3p, and miR-361-3p) was 0.955 (95% CI: 0.899 to 0.985; sensitivity = 91.38%, specificity = 91.38%).

Figure 6

GO functional annotation and KEGG pathway enrichment analysis of the target genes of miR-486-5p, miR-148a-3p, miR-744-5p and let-7d-3p. (A) Biological process (BP) analysis; (B) cellular component (CC) analysis; (C) molecular function (MF) analysis; (D) KEGG pathway enrichment analysis.