Bioinformatic Analysis of Genes and MicroRNAs Associated With Atrioventricular Septal Defect in Down Syndrome Patients

Abstract

SummaryDown syndrome (DS) is a common chromosome 21 abnormality disease, leading to various health problems, especially atrioventricular septal defect (AVSD). Genes and microRNAs (miRNAs) associated with AVSD in DS patients still need in-depth study.Gene expression data (GSE34457) of 22 DS patients without congenital heart disease and 7 DS patients with AVSD were downloaded from Gene Expression Omnibus. After screening differentially expressed genes (DEGs) based on limma package in R (criteria: P < 0.05 and |log 2 fold change (FC)| > 0.5), pathway and functional enrichment analyses were performed using the online software DAVID (criterion: P < 0.05). The protein-protein interaction (PPI) networks of DEGs were constructed based on the online server STRING (criterion: combined score > 0.4). Next, miRNAs that targeted DEGs were predicted based on Webgestalt (criteria: P < 0.05 and target DEGs ≥ 2), and miRNA-DEG regulatory networks were visualized through Cytoscape.A total of 179 DEGs were identified. Next, 5 functions and 1 pathway were enriched by up-regulated DEGs, while 4 functions were enriched by down-regulated DEGs. Furthermore, miRNA-DEG regulatory networks were constructed. IL1B was the hub-gene of PPI networks, and AUTS2 and KIAA2022 were predicted to be targeted by miR-518a, miR518e, miR-518f, miR-528a, and miR-96.IL1B, IL12RB2, AUTS2, and KIAA2022 might participate in AVSD in DS patients, and AUTS2 and KIAA2022 might be targeted by miR-518a, miR-518e, miR-518f, miR-528a, and miR-96. The identified genes and miRNAs might provide a theoretical basis for understanding AVSD in DS patients. (Int Heart J 2016; 57: 490-495)

Identification of Common Differentially Expressed Genes and Potential Therapeutic Targets in Ulcerative Colitis and Rheumatoid Arthritis

“…STRING (version 11.0) 7 , is a freely accessible database, that collects, scores, and integrates data, is used to predict functional relationships between proteins (Szklarczyk et al, 2019). A PPI network of the DEGs with combined score >0.4 in STRING was considered as a functional link, and was constructed using the Cytoscape software (version 3.7.2) 8 (Smoot et al, 2011;Wang et al, 2016aWang et al, , 2018Li et al, 2017;Zhao et al, 2019). Subsequently, we used the MCODE plugin to identify densely connected modules from the PPI network with the criteria of K-core = 2, degree cutoff = 2, max depth = 100, and node score cutoff = 0.2 (Bandettini et al, 2012).…”

<p>The Population Prevalence, Associations of Congenital Heart Defect and Mortality Risk for Down’s Syndrome in South Korea Based on National Health Insurance Service (NHIS) Data</p>

“…26 The genes outside chromosome 21, CRELD1 has been found to participate in AVSD development in DS patients. 27,28 Recent studies attempted to investigate the basic biological association of cardiac anomalies with DS through overexpression of chromosome 21 microRNAs (miRNAs). 29 However, the mechanism of CHD development in DS is not clearly understood.…”

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection

“…In 2015, two studies [ 13 , 14 ] confirmed that genes NKX2-5 , GATA4 , and CREL1 participate in the pathogenesis of AVSD in DS. In 2016, another study [ 15 ] focusing on all types of genetic contribution on AVSD in DS showed that not only the genetic variants but also other regulatory variants (e.g., altered microRNA expression) may participate in such pathogenesis. As a specific form of genetic variants, copy number variants (CNVs) have been widely identified in DS according to many recent publications.…”