Long noncoding RNAs as potential diagnostic biomarkers for diabetes mellitus and complications: A systematic review and meta‐analysis

Abstract

Abstract Aims Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We aimed to synthesize the available data to assess the diagnostic utility of lncRNAs for identification of type 2 diabetes mellitus and its consequences. Materials and Methods We performed a systematic review and meta‐analysis, searching PubMed, Embase, and Web of Science for articles published from September 11, 2015 to December 27, 2022. We evaluated human case–control or cohort studies on differential lncRNA expression in type 2 diabetes mellitus or its associated comorbidities. We excluded studies if they were non‐peer reviewed or published in languages other than English. From 2387 identified studies, we included 17 (4685 participants). Results Analysis of the pooled data showed that lncRNAs had a diagnostic area under the curve (AUC) of 0.84 (95% CI: 0.80–0.87), with a sensitivity of 0.79 (95% CI: 0.74–0.83) and a specificity of 0.75 (95% CI: 0.69–0.80). LncRNAs had an AUC of 0.65 for the diagnosis of prediabetes, with 82% sensitivity and 65% specificity. Conclusions LncRNAs may be promising diagnostic markers for type 2 diabetes mellitus and its complications.

Keywords

• diabetic nephropathy
• diabetic retinopathy
• long noncoding RNA
• meta‐analysis
• type 2 diabetes mellitus