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Mayamba Nlandu Y, Tannor EK, Bamikefa TA, Rissassi Makulo JR. Kidney damage associated with COVID-19: from the acute to the chronic phase. Ren Fail 2024; 46:2316885. [PMID: 38561236 PMCID: PMC10986440 DOI: 10.1080/0886022x.2024.2316885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/05/2024] [Accepted: 02/05/2024] [Indexed: 04/04/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) infection is well established as a systemic disease including kidney damage. The entry point into the renal cell remains the angiotensin-converting enzyme 2 (ACE-2) receptor and the spectrum of renal lesions is broad, with a clear predominance of structural and functional tubular lesions. The most common form of glomerular injury is collapsing glomerulopathy (CG), which is strongly associated with apolipoprotein L1(APOL-1) risk variants. These acute lesions, which are secondary to the direct or indirect effects of SARS-CoV-2, can progress to chronicity and are specific to long COVID-19 in the absence of any other cause. Residual inflammation associated with SARS-CoV-2 infection, in addition to acute kidney injury (AKI) as a transitional state with or without severe histological lesions, may be responsible for greater kidney function decline in mild-to-moderate COVID-19. This review discusses the evidence for renal histological markers of chronicity in COVID-19 patients and triggers of low-grade inflammation that may explain the decline in kidney function in the post-COVID-19 period.
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Affiliation(s)
- Yannick Mayamba Nlandu
- Nephrology Unit, Kinshasa University Hospital, Kinshasa, Democratic Republic of the Congo
| | - Elliot Koranteng Tannor
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
- Directorate of Medicine, Komfo Anokye Teaching Hospital, Kumasi, Ghana
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Li C, Zhang C, Chen J, Chen Y, Ying Z, Hu Y, Song H, Fu P, Zeng X. The Time-Varying Impact of COVID-19 on the Acute Kidney Disorders: A Historical Matched Cohort Study and Mendelian Randomization Analysis. HEALTH DATA SCIENCE 2024; 4:0159. [PMID: 39011273 PMCID: PMC11246837 DOI: 10.34133/hds.0159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 06/04/2024] [Indexed: 07/17/2024]
Abstract
Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a "short-term" causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.
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Affiliation(s)
- Chunyang Li
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
| | - Chao Zhang
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
| | - Jie Chen
- Department of Core Laboratory, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yilong Chen
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
| | - Zhiye Ying
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
| | - Yao Hu
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
| | - Huan Song
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Ping Fu
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Xiaoxi Zeng
- Division of Nephrology, West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610065, China
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