## 4 Discussion  
In 2010, it was proposed to use dogs for the detection of certain urological tumors and, during the 2020 pandemic, dogs were used to detect individuals infected with the COVID-19 virus. This suggested that the volatile compounds present in urine could be used as possible biomarkers of COVID-19 [19; 39]. Changes in the composition of urine could be due to the metabolic alterations caused by SARS-CoV-2 infection [5; 8]. Electronic noses could also be used to detect these volatile compounds in urine, but first, it is necessary to identify the biomarkers associated with the disease, as has been done in the detection of certain types of tumors [24; 37; 40]. Electronic noses also need to identify scent profiles to be effective, which would significantly limit their use in the case of COVID-19. In the present study, we have found a number of volatile compounds present in urine that could be considered biomarkers of COVID-19, using PLS-LDA models fit for discriminating individuals according to their status. The samples presented with an error rate of 0% and a sensitivity and specificity of 100% in all analyzed cases. We performed three different treatments for the urine samples. Initially, a certain amount of NaCl was added to increase ionic strength and promote the formation of volatile compounds [25]. With the same objective, we freeze-dried the samples for the second treatment [26]. The third sample treatment consisted of sulfuric acid addition, as protonation of the molecules favors the formation of volatile compounds by decreasing the solubility of the protonated compounds [25]. In the first treatment, although the signal intensity was not very high, several compounds were identified (ID 2 according to the MSI), such as those listed in Table 2. The more intense signals in the urine of COVID-19 patients corresponded to 2\({}^{\prime}\)-hydroxy-4\({}^{\prime}\),5\({}^{\prime}\)-dimethylacetophenone, 2,4-bis(1,1-dimethylethyl) phenol, and benzothiazole, which are aromatic compounds. In plants, compounds such as 2,4-bis(1,1-dimethylethyl) phenol appear in response to infections and are induced by arachidonic acid, playing an antioxidant role [41], but its role in human metabolism has not been identified. In healthy individuals, the signals corresponding to decahydro-4,4,8,9,10-pentamethylhahntalene, toluene, and p-xylene were more intense. Some of these compounds, such as toluene, seem to have an exogenous origin, while others result from secondary metabolism [42; 43; 44], making it difficult to identify the metabolic pathways or precursors that generate them. We can assume that the differences between illness (COVID-19) and health generate distinct profiles in the spectra of volatile compounds, highlighting the metabolic alterations caused by COVID-19 [34; 45; 46]. For lyophilized samples, the spectra provided a greater number of volatile compounds and also allowed a good classification of the urine from COVID-19 patients using the PLS-LDA algorithm (Figure 4). When integrating the regions of the peaks, the SPA algorithm classifies these regions based on the \(p\)-value (Figure 5), allowing us to identify a series of potential biomarkers that are elevated in COVID-19 patients, such as caprolactam and benzaldehyde, 2,4,5-trimethyl, a biomarker in bladder cancer [47] or anxiety in mice [48]. In healthy individuals, we identified 2,3-butanediol; cyclopentanone, 3-methyl;