Literature DB >> 34642840

Understanding the role of corneal biomechanics-associated genetic variants by bioinformatic analyses.

Xiao Sun1, Xiang Gao1, Bo-Kun Mu2, Yan Wang3,4,5.   

Abstract

PURPOSE: To analyze functions of corneal biomechanical properties (CBP)-related variants as corneal resistance factor (CRF) and corneal hysteresis (CH).
METHODS: Related single nucleotide polymorphisms (SNPs) and genes were identified from NHGRI-EBI GWAS catalog, GWASdb v2 and possible data in published studies. HaploReg v4.1 was used to find linkage SNPs. Functional annotations were performed by GWAVA, CADD and RegulomeDB. GTEx Portal database was used to find out expression quantitative trait locus (eQTL) association. Enrichr was used to annotate the function of GWAS gene and the associated signal pathway. STING (v11.0) database was utilized for protein interaction and network construction.
RESULTS: The integration of 302 CH-associated and 420 CRF-associated lead SNPs has produced 531 CBP-associated lead SNPs. A total of 5,324 proxy variants identified using the HaploReg v4.1 and lead SNPs were functionally annotated. Based on the threshold (CADD ≥ 10, GWAVA ≥ 0.4 and RegulomeDB < rank 3), 23 prioritized putative regulatory SNPs were identified. Eight prioritized eQTL variants (rs75203695, rs34861673, rs846766, rs11024102, rs1377416, rs3829492, rs9934438 and rs197912) were found with strong potential of CBP regulation. It was indicated that CBP-associated genes were significantly enriched in extracellular matrix receptor interaction pathway, closely related to the phenotype of corneal dystrophy and keratoconus. COL1A1, SMAD3, BMP4 and RUNX2 occupied the core position in the co-expression network.
CONCLUSIONS: Data integrative analysis can evaluate CBP variations and explore collagen and extracellular matrix pathways in CBP regulation, which is a promising tool to investigate biological process of corneal diseases.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Bioinformatic analysis; Corneal biomechanical properties; GWAS; SNP

Mesh:

Year:  2021        PMID: 34642840     DOI: 10.1007/s10792-021-02081-9

Source DB:  PubMed          Journal:  Int Ophthalmol        ISSN: 0165-5701            Impact factor:   2.031


  4 in total

1.  Keratoconus in vitro and the key players of the TGF-β pathway.

Authors:  Shrestha Priyadarsini; Tina B McKay; Akhee Sarker-Nag; Dimitrios Karamichos
Journal:  Mol Vis       Date:  2015-05-21       Impact factor: 2.367

2.  Functional relevance for central cornea thickness-associated genetic variants by using integrative analyses.

Authors:  Jing Zhang; Dan Wu; Yiqin Dai; Jianjiang Xu
Journal:  BioData Min       Date:  2018-08-15       Impact factor: 2.522

3.  Evaluation of differentially expressed genes identified in keratoconus.

Authors:  Ji-Eun Lee; Boo Sup Oum; Hee Young Choi; Seung Uk Lee; Jong Soo Lee
Journal:  Mol Vis       Date:  2009-11-28       Impact factor: 2.367

4.  Genome-wide meta-analysis of genetic susceptible genes for Type 2 Diabetes.

Authors:  Paul J Hale; Alfredo M López-Yunez; Jake Y Chen
Journal:  BMC Syst Biol       Date:  2012-12-17
  4 in total
  4 in total

1.  Biomechanical Analysis of Arm Manipulation in Tai Chi.

Authors:  Xiaoyan Dong; Xiaofan Hu; Biqing Chen
Journal:  Comput Intell Neurosci       Date:  2022-06-17

2.  Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19.

Authors:  Wenjiang Zheng; Ting Wang; Peng Wu; Qian Yan; Chengxin Liu; Hui Wu; Shaofeng Zhan; Xiaohong Liu; Yong Jiang; Hongfa Zhuang
Journal:  Front Pharmacol       Date:  2021-12-23       Impact factor: 5.810

3.  Comprehensive Transcriptome Analysis of Patients With Keratoconus Highlights the Regulation of Immune Responses and Inflammatory Processes.

Authors:  Xiao Sun; Hao Zhang; Mengyuan Shan; Yi Dong; Lin Zhang; Luxia Chen; Yan Wang
Journal:  Front Genet       Date:  2022-02-25       Impact factor: 4.599

4.  Biomechanical Analysis of Volleyball Players' Spike Swing Based on Deep Learning.

Authors:  Lejun Hu; Kai Zhao; Wei Jiang
Journal:  Comput Intell Neurosci       Date:  2022-08-04
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.