Background
Publicly available genomics datasets have been growing drastically during the past decades. Although most of these datasets were initially generated to answer a pre-defined scientific question, their re-purposing became useful when new challenges such as COVID-19 arise. While the establishment and use of experimental models of COVID-19 are in progress, the potential hypotheses for mechanisms of onset and progression of COVID-19 can be generated by using in silico analysis of known COVID-19 conditions and SARS-CoV-2 targets.
Methods
Selecting condition: COVID-19 infection leads to acute respiratory distress syndrome (ARDS) and acute kidney injury (AKI). There is increasing data demonstrating mechanistic links between AKI and ARDS.
Selecting targets: SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) and transmembrane protease, serine 2 (TMPRSS2) for cell entry. We hypothesized that modeling AKI and ARDS would lead to changes in kidney and lung ACE2 and TMPRSS2. We therefore evaluated expression of ACE2 and TMPRSS2 as well as other novel molecular players of AKI and AKI-lung cross-talk in publicly available microarray datasets GSE6730 and GSE60088, which represented gene expression of lungs and kidneys in mouse models that resembled lung-kidney injury seen during SARS-CoV-2 infection.
Results
Expression of COVID-19 related genes ACE2 and TMPRSS2 was downregulated in lungs at early stages of injury. At a later stage, the expression of ACE2 decreased further, while expression of TMPRSS2 recovered. In kidneys, both genes were downregulated by AKI, but not by distant lung injury. We also identified 53 kidney genes upregulated by pneumonia and mechanical ventilation (PMV); and 254 lung genes upregulated by AKI, 9 genes of which were common to both organs. 3 of 9 genes were previously linked to kidney-lung cross-talk: Lcn2 (Fold Change (FC)Lung(L) =18.6, FCKidney(K) =6.32), Socs3 (FCL =10.5, FCK =10.4), Inhbb (FCL =6.20, FCK =6.17). This finding validates the current approach and reveals new 6 candidates, including Maff (FCL =7.21, FCK =5.98).
Conclusions
Using our in-silico approach, we identified changes in COVID-19 related genes ACE2 and TMPRSS2 in traditional mouse models of AKI and lung cross-talk. We also found changes in the new candidate genes, which could be involved in the combined kidney-lung injury during COVID-19