448 - Blood-based Transcriptomic Profiling as Predictive Biomarkers for Retinopathy of Prematurity in Premature Infants

Nitin Chouthai, Wayne State University School of Medicine, Detroit, MI, United States

Background: Severe Retinopathy of prematurity (S-ROP) poses substantial therapeutic challenges, highlighting the need for early non-invasive biomarkers.

Objective: This study investigates the potential of peripheral blood mononuclear cells (PBMCs) transcriptome as a source of novel biomarkers for ROP.

Design/Methods: Patient populations divided into 3 categories: Group 1 includes No ROP (ST 0 or no ROP), Group 2 includes mild to moderate ROP (Zone III, Zone II, ST 1 ROP, Zone II, ST 2 without plus dx or stage 3 ROP, and Group 3: Severe ROP (need of laser surgery). This is a pilot study and a convenience sample size of 8 neonates with no ROP, 6 neonates with mild to moderate ROP (M-ROP), and 7 neonates with severe ROP (S-ROP) that necessitated laser surgery. Inclusion criteria was newborns born
Results: Clinical variables were not statistically significantly different across the three groups. Transcriptomic analysis of PBMCs from premature infants with severe S-ROP revealed differential expression of known and novel genes. A total of 789 genes exhibited differential expression with a p-value < 0.05. We observed 572 genes were down regulated and 217 were up regulated with an absolute log2 fold change. Gene Ontology (GO) and KEGG pathway analyses identified enriched gene sets related to oxygen transport, immune response, developmental, oxidative stress, and nutrient sensing. We did not find any significant changes between mild-ROP and No ROP group. We identified 179 dysregulated genes with 56 up regulated and 123 down regulated in S-ROP as compared to mild-ROP. Dysregulated genes in S-ROP were associated with matrix metalloproteins, immune response, and hemoglobin metabolism. We identified a distinct gene signature that is consistently dysregulated in S-ROP compared to M-ROP and control groups. This signature includes 19 up regulated genes, and 109 down regulated genes.

Conclusion(s): These findings could facilitate the development of predictive biomarkers for early ROP diagnosis and treatment. Further research is warranted to elucidate the underlying mechanisms and validate the clinical utility of these biomarkers.

Table 1: Description of Clinical Variables
Table1.pdfThe p Values represent One Way ANOVA analyses for continuous variables and Chi square test for categorical variables

Figure1: Differentially expressed gene in Severe ROP compared to No ROP.
Figure1igure1.pdfFigure 1: Volcano plot: Red represents upregulated genes, blue represents downregulated genes, and gray represents non-differentially expressed genes (S-ROP n=7, No ROP n=8).