SERUM LncRNA SNHG16: A Biomarker for Diagnosing Childhood Obesity and Predicting Its Progression to Metabolic Syndrome

Abstract

Purpose: Obesity is a major risk factor for metabolic syndrome (MS) in children. This study explores the expression and clinical significance of long non-coding RNA SNHG16 (SNHG16) in childhood obesity and its complications with MS (obesity-MS).

Patients and methods: Healthy controls and obese children (categorized as those with simple obesity or obesity-MS) were enrolled. Serum SNHG16 and miR-27a-3p levels were quantified by RT-qPCR. ROC curves evaluated SNHG16's diagnostic value for obesity. Logistic regression analysis identified potential risk factors for the development of obesity-MS. DLR assay and RIP assay confirmed the interaction between SNHG16 and miR-27a-3p. Bioinformatics was used to predict downstream genes of miR-27a-3p and, then GO and KEGG enrichment analysis identified the functions and signaling pathways of these genes.

Results: Serum SNHG16 levels were distinctly upregulated in obese children, especially those with obesity-MS. In contrast, miR-27a-3p expression showed the opposite trend. Additionally, SNHG16 was positively correlated with BMI in obese children. Serum SNHG16 exhibited 81.18% sensitivity and 76.47% specificity in distinguishing controls from obese individuals. Furthermore, serum SNHG16, BMI, HOMA-IR, and TG are potential risk factors for MS in obese children. Mechanistically, SNHG16 directly targets miR-27a-3p, and miR-27a-3p targets 65 genes primarily enriched in insulin response and the MAPK, Ras, and mTOR signaling pathways.

Conclusion: Elevated serum SNHG16 levels may serve as diagnostic biomarkers for obese children and predict obesity-MS. SNHG16 may also contribute to the progression of obesity and MS by targeting miR-27a-3p.

Keywords: SNHG16; diagnostic; metabolic syndrome; miR-27a-3p; obesity.

Figure 1

SNHG16 expression in the serum of obese children and its diagnostic significance. (A) RT-qPCR was performed to examine the serum expression of SNHG16 in healthy and obese children. (B) Pearson coefficient analysis of the correlation between BMI and serum SNHG16 levels in healthy and obese children. (C) ROC curves were used to analyze the diagnostic significance of SNHG16 in obese children. **** P < 0.0001 vs Controls.

Figure 2

SNHG16 levels predict metabolic syndrome in obese children. (A) The expression of SNHG16 in children with simple obesity and those with obesity-MS. (B) Predictive significance of SNHG16 in obese children with MS using ROC curves. **** P < 0.0001 vs simple obesity group.

Figure 3

miR-27a-3p was the direct target miRNA of SNHG16. (A) The putative binding sequences are presented. DLR assay (B) and RIP assay (C) were conducted to examine the target relationship between SNHG16 and miR-27a-3p. (D) The expression of serum miR-27a-3p in the subjects. Pearson coefficient was conducted to examine the correlation between miR-27a-3p and SNHG16 in children with simple obesity (E) and obesity with MS (F). ** P < 0.01, *** P < 0.001, **** P < 0.0001 vs miR NC or controls.

Figure 4

GO enrichment and KEGG enrichment of overlapping target of miR-27a-3p. (A) Venn diagram presents target mRNAs from five databases predicting miR-27a-3p. (B) The PPI network was established by the overlapping targets. (C) Top 10 hub genes with higher degrees screened from a PPI network. (D) The top 20 enriched BP, MF, and CC terms for the overlapping targets were analyzed by the GO enrichment. (E) Sankey dot pathway enrichment of the top 10 KEGG pathway enrichment for the targets.