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Liem DA, Murali S, Sigdel D, Shi Y, Wang X, Shen J, Choi H, Caufield JH, Wang W, Ping P, Han J. Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease. Am J Physiol Heart Circ Physiol 2018; 315:H910-H924. [PMID: 29775406 DOI: 10.1152/ajpheart.00175.2018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely, ischemic heart disease, cardiomyopathies, cerebrovascular accident, congenital heart disease, arrhythmias, and valve disease, anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the 6 groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-Aware Semantic Online Analytical Processing was applied to semantically rank the association of proteins to each CVD and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein was visualized as a six-dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins, whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all 6 CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely, insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters predominantly associated with a targeted CVD; analyses of these proteins revealed unexpected insights underlying the key ECM-related molecular pathogenesis of each CVD, including virus assembly and release in arrhythmias. NEW & NOTEWORTHY The present study is the first application of a text-mining algorithm to characterize the relationships of 709 extracellular matrix-related proteins with 6 categories of cardiovascular disease described in 1,099,254 abstracts. Our analysis informed unexpected extracellular matrix functions, pathways, and molecular relationships implicated in the six cardiovascular diseases.
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Affiliation(s)
- David A Liem
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California
| | - Sanjana Murali
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California
| | - Dibakar Sigdel
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California
| | - Yu Shi
- NIH BD2K Program Centers of Excellence for Big Data Computing-KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign , Champaign, Illinois
| | - Xuan Wang
- NIH BD2K Program Centers of Excellence for Big Data Computing-KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign , Champaign, Illinois
| | - Jiaming Shen
- NIH BD2K Program Centers of Excellence for Big Data Computing-KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign , Champaign, Illinois
| | - Howard Choi
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California
| | - John H Caufield
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California
| | - Wei Wang
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Heart Big Data to Knowledge Center, Department of Computer Science, Scalable Analytics Institute, Henry Samueli School of Engineering and Applied Science, University of California , Los Angeles, California
| | - Peipei Ping
- NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Departments of Physiology, Medicine/Cardiology, and Bioinformatics, David Geffen School of Medicine, University of California , Los Angeles, California.,NIH BD2K Program Centers of Excellence for Big Data Computing-Heart BD2K Center, Heart Big Data to Knowledge Center, Department of Computer Science, Scalable Analytics Institute, Henry Samueli School of Engineering and Applied Science, University of California , Los Angeles, California
| | - JiaWei Han
- NIH BD2K Program Centers of Excellence for Big Data Computing-KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign , Champaign, Illinois
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Krivega M, Geens M, Van de Velde H. CAR expression in human embryos and hESC illustrates its role in pluripotency and tight junctions. Reproduction 2014; 148:531-44. [PMID: 25118298 DOI: 10.1530/rep-14-0253] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Coxsackie virus and adenovirus receptor, CXADR (CAR), is present during embryogenesis and is involved in tissue regeneration, cancer and intercellular adhesion. We investigated the expression of CAR in human preimplantation embryos and embryonic stem cells (hESC) to identify its role in early embryogenesis and differentiation. CAR protein was ubiquitously present during preimplantation development. It was localised in the nucleus of uncommitted cells, from the cleavage stage up to the precursor epiblast, and corresponded with the presence of soluble CXADR3/7 splice variant. CAR was displayed on the membrane, involving in the formation of tight junction at compaction and blastocyst stages in both outer and inner cells, and CAR corresponded with the full-length CAR-containing transmembrane domain. In trophectodermal cells of hatched blastocysts, CAR was reduced in the membrane and concentrated in the nucleus, which correlated with the switch in RNA expression to the CXADR4/7 and CXADR2/7 splice variants. The cells in the outer layer of hESC colonies contained CAR on the membrane and all the cells of the colony had CAR in the nucleus, corresponding with the transmembrane CXADR and CXADR4/7. Upon differentiation of hESC into cells representing the three germ layers and trophoblast lineage, the expression of CXADR was downregulated. We concluded that CXADR is differentially expressed during human preimplantation development. We described various CAR expressions: i) soluble CXADR marking undifferentiated blastomeres; ii) transmembrane CAR related with epithelial-like cell types, such as the trophectoderm (TE) and the outer layer of hESC colonies; and iii) soluble CAR present in TE nuclei after hatching. The functions of these distinct forms remain to be elucidated.
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Affiliation(s)
- M Krivega
- Research Group Reproduction and GeneticsFaculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, BelgiumCentre for Reproductive Medicine (CRG)UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium
| | - M Geens
- Research Group Reproduction and GeneticsFaculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, BelgiumCentre for Reproductive Medicine (CRG)UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium
| | - H Van de Velde
- Research Group Reproduction and GeneticsFaculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, BelgiumCentre for Reproductive Medicine (CRG)UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium Research Group Reproduction and GeneticsFaculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, BelgiumCentre for Reproductive Medicine (CRG)UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium
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