In Silico analysis unveils rs2109069 of DPP9 as a potential catalyst for COVID-19 severity and risk of inflammatory symptoms

Our in silico findings reveal that severe COVID-19 inflammatory responses and inflammatory lung diseases share the same genetic risk loci, helping to elucidate the underlying physiological mechanisms of severe COVID-19 inflammation. Additionally, the individual differences in immune sensitivity may contribute to the varying multi-organ inflammatory effects among patients. The rs2109069 of DPP9 could be a genetic marker to predict the risk of specific COVID-19 symptoms and severity.

Authors

Institutions

Publication Details

Journal
Experimental and Molecular Pathology
Published
2024-11-29
DOI
https://doi.org/10.1016/j.yexmp.2024.104946
Citations
2
Primary Topic
Dermatological and COVID-19 studies
Type
article
Field-Weighted Citation Impact
1.07

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In Silico analysis unveils rs2109069 of DPP9 as a potential catalyst for COVID-19 severity and risk of inflammatory symptoms

Yung‐Jen Chuang, Zih‐Yin Lai, Chi‐Ying Lee
2 citations
Experimental and Molecular Pathology
Dermatological and COVID-19 studies
1.07
article

In Silico analysis unveils rs2109069 of DPP9 as a potential catalyst for COVID-19 severity and risk of inflammatory symptoms

Yung‐Jen Chuang, Zih‐Yin Lai, Chi‐Ying Lee
article en
2 citations

Abstract

Our in silico findings reveal that severe COVID-19 inflammatory responses and inflammatory lung diseases share the same genetic risk loci, helping to elucidate the underlying physiological mechanisms of severe COVID-19 inflammation. Additionally, the individual differences in immune sensitivity may contribute to the varying multi-organ inflammatory effects among patients. The rs2109069 of DPP9 could be a genetic marker to predict the risk of specific COVID-19 symptoms and severity.

Experimental and Molecular PathologyVol. 140
National Tsing Hua University (TW)
Taiwan Semiconductor Manufacturing Company, Ministry of Science and Technology, Taiwan
Openalex Percentile: Top 19%
Dermatological and COVID-19 studies
1.07
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.