Please use this identifier to cite or link to this item: https://doi.org/10.3390/jcm9092920
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dc.titleA Pilot Study on MicroRNA Profile in Tear Fluid to Predict Response to Anti-VEGF Treatments for Diabetic Macular Edema
dc.contributor.authorChan, Hwei Wuen
dc.contributor.authorYang, Binxia
dc.contributor.authorWong, Wendy
dc.contributor.authorBlakeley, Paul
dc.contributor.authorSeah, Ivan
dc.contributor.authorTan, Queenie Shu Woon
dc.contributor.authorWang, Haofei
dc.contributor.authorBhargava, Mayuri
dc.contributor.authorLin, Hazel Anne
dc.contributor.authorChai, Charmaine HC
dc.contributor.authorMangunkusumo, Erlangga Ariadarma
dc.contributor.authorThet, Naing
dc.contributor.authorYuen, Yew Sen
dc.contributor.authorSethi, Raman
dc.contributor.authorWang, Si
dc.contributor.authorHunziker, Walter
dc.contributor.authorLingam, Gopal
dc.contributor.authorSu, Xinyi
dc.date.accessioned2021-11-12T06:48:03Z
dc.date.available2021-11-12T06:48:03Z
dc.date.issued2020-09-01
dc.identifier.citationChan, Hwei Wuen, Yang, Binxia, Wong, Wendy, Blakeley, Paul, Seah, Ivan, Tan, Queenie Shu Woon, Wang, Haofei, Bhargava, Mayuri, Lin, Hazel Anne, Chai, Charmaine HC, Mangunkusumo, Erlangga Ariadarma, Thet, Naing, Yuen, Yew Sen, Sethi, Raman, Wang, Si, Hunziker, Walter, Lingam, Gopal, Su, Xinyi (2020-09-01). A Pilot Study on MicroRNA Profile in Tear Fluid to Predict Response to Anti-VEGF Treatments for Diabetic Macular Edema. JOURNAL OF CLINICAL MEDICINE 9 (9). ScholarBank@NUS Repository. https://doi.org/10.3390/jcm9092920
dc.identifier.issn20770383
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/206062
dc.description.abstract(1) Background: Intravitreal anti-vascular endothelial growth factor (anti-VEGF) is an established treatment for center-involving diabetic macular edema (ci-DME). However, the clinical response is heterogeneous. This study investigated miRNAs as a biomarker to predict treatment response to anti-VEGF in DME. (2) Methods: Tear fluid, aqueous, and blood were collected from patients with treatment-naïve DME for miRNA expression profiling with quantitative polymerase chain reaction. Differentially expressed miRNAs between good and poor responders were identified from tear fluid. Bioinformatics analysis with the miEAA tool, miRTarBase Annotations, Gene Ontology categories, KEGG, and miRWalk pathways identified interactions between enriched miRNAs and biological pathways. (3) Results: Of 24 participants, 28 eyes received bevacizumab (15 eyes) or aflibercept (13 eyes). Tear fluid had the most detectable miRNA species (N = 315), followed by serum (N = 309), then aqueous humor (N = 134). MiRNAs that correlated with change in macular thickness were miR-214-3p, miR-320d, and hsa-miR-874-3p in good responders; and miR-98-5p, miR-196b-5p, and miR-454-3p in poor responders. VEGF-related pathways and the angiogenin-PRI complex were enriched in good responders, while transforming growth factor-β and insulin-like growth factor pathways were enriched in poor responders. (4) Conclusions: We reported a panel of novel miRNAs that provide insight into biological pathways in DME. Validation in larger independent cohorts is needed to determine the predictive performance of these miRNA candidate biomarkers.
dc.language.isoen
dc.publisherMDPI
dc.sourceElements
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectMedicine, General & Internal
dc.subjectGeneral & Internal Medicine
dc.subjectanti-vascular endothelial growth factor
dc.subjectaflibercept
dc.subjectbevacizumab
dc.subjectbiomarker
dc.subjectdiabetic macular edema
dc.subjectmicroRNA
dc.subjectEXPRESSION PROFILES
dc.subjectRISK-FACTORS
dc.subjectANGIOGENIN
dc.subjectSERUM
dc.subjectRETINOPATHY
dc.subjectHUMOR
dc.subjectIDENTIFICATION
dc.subjectRANIBIZUMAB
dc.subjectPREVALENCE
dc.subjectBIOMARKERS
dc.typeArticle
dc.date.updated2021-11-11T20:01:57Z
dc.contributor.departmentOPHTHALMOLOGY
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.description.doi10.3390/jcm9092920
dc.description.sourcetitleJOURNAL OF CLINICAL MEDICINE
dc.description.volume9
dc.description.issue9
dc.published.statePublished
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