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. 2022 Aug 11:9:955991.
doi: 10.3389/fmolb.2022.955991. eCollection 2022.

Pyroptosis in sepsis: Comprehensive analysis of research hotspots and core genes in 2022

Demeng Xia  1 , Sheng Wang  2 , Renqi Yao  3 , Yuexue Han  4 , Liyu Zheng  3 , Pengyi He  3 , Ying Liu  5 , Lu Yang  6
Affiliations

Pyroptosis in sepsis: Comprehensive analysis of research hotspots and core genes in 2022

Demeng Xia et al. Front Mol Biosci. .

Abstract

Sepsis, a life-threatening disease caused by dysregulated host response to infection, is a major public health problem with a high mortality and morbidity rate. Pyroptosis is a new type of programmed cell death discovered in recent years, which has been proved to play an important role in sepsis. Nevertheless, there is no comprehensive report, which can help researchers get a quick overview and find research hotspots. Thus, we aimed to identify the study status and knowledge structures of pyroptosis in sepsis and summarize the key mechanism of pyroptosis in sepsis. The data were retrieved and downloaded from the WOS database. Software such as VOSviewer was used to analyze these publications. Key genes were picked out by using (https://www.genecards.org) and (http://www.bioinformatics.com). Then, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to performed these key genes. From 2011 to 2021, a total of 299 papers met the search criteria, and the global interest in pyroptosis in sepsis measured by the value of (RRI) has started to increase since 2016. China ranked first in the number of publications, followed by the USA. The journal Frontiers in Immunology published the most relevant articles. Through keyword co-occurrence analysis, the high-frequency subject terms were divided into three clusters like "animal research", "cell research," and "molecular research" clusters. "mir," "aki," "monocyte," and "neutrophil" were the newest keywords that may be the hotspot. In addition, a total of 15 genes were identified as hub genes. TNF, IL-1β, AKT1, CASP1, and STAT3 were highly expressed in lung tissues, thymus tissues, and lymphocytes. KEGG analysis indicated that pyroptosis may play a vital role in sepsis via the NOD, PI3K/AKT, and MAPK/JNK pathways. Through the quantitative analysis of the literature on pyroptosis in sepsis, we revealed the current status and hotspots of research in this field and provided some guidance for further studies.

Keywords: NLRP3 and immune organs; bibliometrics; pyroptosis; sepsis; toll and nod signaling pathways.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Flowchart of literature screening. The detailed process of screening and enrollment.
FIGURE 2
FIGURE 2
Strategy and results of bioinformatic analysis. (A) Flowchart of gene screening. (B) The Venn diagram shows the intersection between pyroptosis and sepsis genes.
FIGURE 3
FIGURE 3
Bibliometrics and bioinformatics analysis flow chart of pyroptosis in sepsis studies.
FIGURE 4
FIGURE 4
The co-occurrence analysis of all keywords in publications of pyroptosis in sepsis. (A) Mapping of the keywords in the area of pyroptosis in sepsis. The words were divided into three clusters in accordance with different colors generated by default: “animal research” (right in green), “cell research” (left in red), and “molecular research” (up in blue). The size of the circle represented the frequency of keywords; (B) The distribution of keywords was presented according to the average time of appearance. The blue color represented early appearance, and the yellow color stood for late appearance. Two keywords were considered co-occurred if they both occurred on the same line in the corpus file. A smaller distance between two keywords indicates relatively higher co-occurrences of the keyword.
FIGURE 5
FIGURE 5
Enrichment analysis of key genes. (A) The enriched GO terms in the component (CC). (B) The enriched GO terms in the molecular function (MF). (C) The enriched GO terms in the biological process (BP). (D) KEGG enrichment analysis.
FIGURE 6
FIGURE 6
The top 15 hub genes. The network of the top 15 hub genes by CytoScope.
FIGURE 7
FIGURE 7
Expression of five hub genes in different tissues. (A) Expression of TNF in different tissues. (B) Expression of IL-1Β in different tissues. (C) Expression of AKT1 in different tissues. (D) Expression of CASP1 in different tissues. (E) Expression of STAT3 in different tissues.
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