SysInflam HuDB, a Web Resource for Mining Human Blood Cells Transcriptomic Data Associated with Systemic Inflammatory Responses to Sepsis.

Abstract

Sepsis develops after a dysregulated host inflammatory response to a systemic infection. Identification of sepsis biomarkers has been challenging because of the multifactorial causes of disease susceptibility and progression. Public transcriptomic data are a valuable resource for mechanistic discoveries and cross-studies concordance of heterogeneous diseases. Nonetheless, the approach requires structured methodologies and effective visualization tools for meaningful data interpretation. Currently, no such database exists for sepsis or systemic inflammatory diseases in human. Hence we curated SysInflam HuDB (http://sepsis.gxbsidra.org/dm3/geneBrowser/list), a unique collection of human blood transcriptomic datasets associated with systemic inflammatory responses to sepsis. The transcriptome collection and the associated clinical metadata are integrated onto a user-friendly and Web-based interface that allows the simultaneous exploration, visualization, and interpretation of multiple datasets stemming from different study designs. To date, the collection encompasses 62 datasets and 5719 individual profiles. Concordance of gene expression changes with the associated literature was assessed, and additional analyses are presented to showcase database utility. Combined with custom data visualization at the group and individual levels, SysInflam HuDB facilitates the identification of specific human blood gene signatures in response to infection (e.g., patients with sepsis versus healthy control subjects) and the delineation of major genetic drivers associated with inflammation onset and progression under various conditions.

• Authors: Mohammed Toufiq, Susie Shih Yin Huang, Sabri Boughorbel, Mohamed Alfaki, Darawan Rinchai, Luis R Saraiva, Damien Chaussabel, Mathieu Garand
• Journal: Journal of immunology (Baltimore, Md. : 1950) (J Immunol) Vol. 207 Issue 9 Pg. 2195-2202 (11 01 2021) ISSN: 1550-6606 [Electronic] United States
• PMID: 34663591 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2021 by The American Association of Immunologists, Inc.

Topics

• Blood Cells (physiology)
• Data Mining
• Databases as Topic
• Datasets as Topic
• Gene Expression Profiling
• Humans
• Inflammation (immunology)
• Internet
• Sepsis (immunology)
• Software
• Transcriptome
• User-Computer Interface