Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19
Abstract Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:298 |
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| Enthalten in: |
Molecular genetics and genomics - 298(2023), 4 vom: 14. Apr., Seite 823-836 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Jin, Xin [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
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| Anmerkungen: |
© The Author(s) 2023 |
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| doi: |
10.1007/s00438-023-02014-4 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR051688468 |
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| 520 | |a Abstract Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19. | ||
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| 700 | 1 | |a Wang, Yanqun |4 aut | |
| 700 | 1 | |a Xu, Jinjin |4 aut | |
| 700 | 1 | |a Li, Yimin |4 aut | |
| 700 | 1 | |a Cheng, Fanjun |4 aut | |
| 700 | 1 | |a Luo, Yuxue |4 aut | |
| 700 | 1 | |a Zhou, Haibo |4 aut | |
| 700 | 1 | |a Lin, Shanwen |4 aut | |
| 700 | 1 | |a Xiao, Fei |4 aut | |
| 700 | 1 | |a Zhang, Lu |4 aut | |
| 700 | 1 | |a Lin, Yu |4 aut | |
| 700 | 1 | |a Zhang, Zhaoyong |4 aut | |
| 700 | 1 | |a Jin, Yan |4 aut | |
| 700 | 1 | |a Zheng, Fang |4 aut | |
| 700 | 1 | |a Chen, Wei |4 aut | |
| 700 | 1 | |a Zhu, Airu |4 aut | |
| 700 | 1 | |a Tao, Ye |4 aut | |
| 700 | 1 | |a Zhao, Jingxian |4 aut | |
| 700 | 1 | |a Kuo, Tingyou |4 aut | |
| 700 | 1 | |a Li, Yuming |4 aut | |
| 700 | 1 | |a Li, Lingguo |4 aut | |
| 700 | 1 | |a Wen, Liyan |4 aut | |
| 700 | 1 | |a Ou, Rijing |4 aut | |
| 700 | 1 | |a Li, Fang |4 aut | |
| 700 | 1 | |a Lin, Long |4 aut | |
| 700 | 1 | |a Zhang, Yanjun |4 aut | |
| 700 | 1 | |a Sun, Jing |4 aut | |
| 700 | 1 | |a Yuan, Hao |4 aut | |
| 700 | 1 | |a Zhuang, Zhen |4 aut | |
| 700 | 1 | |a Sun, Haixi |4 aut | |
| 700 | 1 | |a Chen, Zhao |4 aut | |
| 700 | 1 | |a Li, Jie |4 aut | |
| 700 | 1 | |a Zhuo, Jianfen |4 aut | |
| 700 | 1 | |a Chen, Dongsheng |4 aut | |
| 700 | 1 | |a Zhang, Shengnan |4 aut | |
| 700 | 1 | |a Sun, Yuzhe |4 aut | |
| 700 | 1 | |a Wei, Peilan |4 aut | |
| 700 | 1 | |a Yuan, Jinwei |4 aut | |
| 700 | 1 | |a Xu, Tian |4 aut | |
| 700 | 1 | |a Yang, Huanming |4 aut | |
| 700 | 1 | |a Wang, Jian |4 aut | |
| 700 | 1 | |a Xu, Xun |4 aut | |
| 700 | 1 | |a Zhong, Nanshan |4 aut | |
| 700 | 1 | |a Xu, Yonghao |4 aut | |
| 700 | 1 | |a Sun, Kun |4 aut | |
| 700 | 1 | |a Zhao, Jincun |4 aut | |
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