Junjie Hu,1,* Zufen Zheng,2,* Dakang Liang,1 Yongjin Zhang,2 Jiejing Chen,1 Cuiyi Zhou,1 Chuming You,3 Qiong Liu3 

1Department of General Pediatrics, Sihui People’s Hospital, Sihui, 526200, People’s Republic of China; 2Department of Neonatal Pediatrics, Sihui People’s Hospital, Sihui, 526200, People’s Republic of China; 3Department of Neonatal Pediatrics, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, 510310, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Qiong Liu, Department of Neonatal Pediatrics, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Compound No. 466, Xingangzhong Road, Haizhu District, Guangzhou, 510310, People’s Republic of China, Tel +86 020-89168888, Email qiongliu154@163.com Chuming You, Department of Neonatal Pediatrics, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Compound No. 466, Xingangzhong Road, Haizhu District, Guangzhou, 510310, People’s Republic of China, Tel +86 020-89168888, Email youkuiqq7362@163.com

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, obesity, metabolic syndrome, miR-27a-3p, diagnostic