DOI: 10.5061/dryad.bcc2fqzj1
title: miRNAs in primary open-angle glaucoma and ocular hypertension

description: Glaucoma is a chronic neurodegenerative disease, which is the leading
 cause of irreversible blindness worldwide. As a response to high
 intraocular pressure, the clinical and molecular glaucoma biomarkers
 indicate the biological state of the visual system. Classical and
 uncovering novel biomarkers of glaucoma development and progression,
 follow-up, and monitoring the response to treatment are key objectives to
 improve vision outcomes. While the glaucoma imaging field has successfully
 validated biomarkers of disease progression, there is still a considerable
 need for developing new biomarkers of early glaucoma, that is, at the
 preclinical and initial glaucoma stages. Outstanding clinical trials and
 animal-model study designs, innovative technology, and analytical
 approaches in bioinformatics are essential tools to successfully uncover
 novel glaucoma biomarkers with a high potential for translation into
 clinical practice. To better understand the clinical and
 biochemical–molecular–genetic glaucoma pathogenesis, we conducted an
 analytical, observational, and case-comparative/control study in 358
 primary open-angle glaucoma (POAG) patients and 226 comparative-control
 individuals to collect tears, aqueous humor, and blood to process for
 identifying POAG biomarkers by exploring several biological pathways, such
 as inflammation, neurotransmitter/neurotrophin alteration, oxidative
 stress, gene expression, miRNAs fingerprint and its biological targets,
 and vascular endothelial dysfunction. We are incredibly enthusiastic about
 gathering as much information as possible on POAG biomarkers to learn how
 this information can be used to better steer the diagnosis and therapy of
 glaucoma to prevent blindness in the predictable future.
description: On the day of processing,
 samples were defrosted and prepared for RNA extraction using the miRNeasy
 Mini Kit (QIAGEN Inc., Hilden, Germany). Briefly, purification is based on
 spin column chromatography using a proprietary resin as the separation
 matrix. Small RNAs are separated from other cellular components such as
 proteins without the use of phenol or chloroform. The quality and quantity
 of total RNA obtained from tears was assessed using a Bioanalyzer 2100
 (Agilent® Technologies, Inc., Santa Clara, CA, USA), and the RNA 6000 Nano
 Kit (Agilent® Technologies, Inc.). RNA libraries were prepared using
 NEBNext® Multiplex Small RNA Library Prep Set for Illumina® (#E7300 y
 #7580; New England BioLabs®, Inc., Ipswich, MA, USA), according to the
 manufacturer’s protocol https://international.neb.com/protocols /2018/03/27/protocol-for-use-with-nebnext-small-rna-library-prep-set-for-illumina-e7300-e7580-e7560-e7330. According to the guidelines for low RNA concentration samples, the adapters and RT primers were diluted 1:2 with nuclease-free water and 15 cycles were used for the amplification by PCR. The indexed libraries were purified using the QIAquick® PCR Purification Kit (#28104, QIAGEN®, Hilden, Germany). Library quality control was assessed using a 4200 TapeStation (Agilent® Technologies, Inc.) and High Sensitivity D1000 Kit (Agilent® Technologies, Inc.). The miRNA fraction of each library (120–200 bp) was collected using the Pippin Prep System (Sage Science, Inc., Beverly, MA, USA) following the manufacturer’s guidelines and using 3% agarose dye-free gel cassettes with internal standards (Marker P) (Sage Science # CDP3010). miRNAs were quantified using a 4200 TapeStation (Agilent® Technologies, Inc.) and High Sensitivity D1000 Kit (Agilent® Technologies, Inc.) prior to normalization and pooling. Sequencing was performed on a NextSeq 500 System (Illumina, Inc., San Diego, CA, USA) with a Mid-Output flow cell for 150-cycle reads obtaining about 3.5 million reads per sample. FASTQ file quality was assessed using FASTQC tool (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Adapters and low liability reads were removed. At this point, non-coding RNAs previously described in the ENSEMBL database were selected and characterized. Statistical analyses were performed using Limma and edgeR packages deposited in Bioconductor (www.bioconductor.org). A predictive analysis based on receiver operating characteristic (ROC) curves was performed to select those miRNAs showing an area under the curve (AUC) greater than 0.75. Subsequently, an analysis of the main components (PCA) was performed.