Published online Jan 6, 2025. doi: 10.12998/wjcc.v13.i1.93632
Revised: September 22, 2024
Accepted: October 23, 2024
Published online: January 6, 2025
Processing time: 249 Days and 14.8 Hours
The study by Cao et al aimed to identify early second-trimester biomarkers that could predict gestational diabetes mellitus (GDM) development using advanced proteomic techniques, such as Isobaric tags for relative and absolute quantitation isobaric tags for relative and absolute quantitation and liquid chromatography-mass spectrometry liquid chromatography-mass spectrometry. Their analysis revealed 47 differentially expressed proteins in the GDM group, with retinol-binding protein 4 and angiopoietin-like 8 showing significantly elevated serum levels compared to controls. Although these findings are promising, the study is limited by its small sample size (n = 4 per group) and lacks essential details on the reproducibility and reliability of the protein quantification methods used. Furthermore, the absence of experimental validation weakens the interpretation of the protein-protein interaction network identified through bioinformatics analysis. The study's focus on second-trimester biomarkers raises concerns about whether this is a sufficiently early period to implement preventive interventions for GDM. Predicting GDM risk during the first trimester or pre-conceptional period may offer more clinical relevance. Despite its limitations, the study presents valuable insights into potential GDM biomarkers, but larger, well-validated studies are needed to establish their predictive utility and generalizability.
Core Tip: The letter highlights certain limitations of the study by Cao et al, which explored early second-trimester biomarkers, retinol-binding protein 4 and angiopoietin-like 8, for predicting gestational diabetes mellitus (GDM). While valuable, identifying GDM in the early second trimester may not provide sufficient time for pregnant mothers to adopt major lifestyle interventions. Early first-trimester prediction or pre-conceptional identification would be more clinically significant. While the study uses advanced proteomic techniques, including isobaric tags for relative and absolute quantitation and liquid chromatography-mass spectrometry, to identify differentially expressed proteins, it is constrained by a small sample size and methodological gaps. Specifically, the reliability of protein quantification and high-abundance protein removal is unclear, and the lack of experimental validation limits the functional interpretation of identified protein interactions.