LC–MS/MS Profiling of Salivary Short-Chain Fatty Acids in Persistent Covid Disease

2020’s Covid-19 pandemic has continued to present a major risk to public health worldwide. Although most efforts have concentrated on the acute phase severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, a considerable number of individuals suffer from continuing symptoms after infection which have become known as persistent Covid disease (PCD). While the etiology of PCD remains, for the most part, misunderstood, there has been some evidence uncovered which suggests that microbiota (especially those located in the upper respiratory tract) might be a factor. A joint study between the Biomedical Research Center of La Rioja (CIBIR, Logroño, Spain) and the Carlos III Health Institute (Madrid, Spain) set out to investigate differences in the composition of the oral microbiota, salivary cytokine, and short-chain fatty acids (SCFAs) concentration, between PCD and healthy controls, with the SCFAs quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A paper based on their research was published in Enfermedades Infecciosas y Microbiología Clínica (English ed).⁽¹⁾

SARS-CoV-2, the causative agent of Covid-19, has caused nearly 778 million confirmed cases and over 7.1 million deaths worldwide. ^(2,3) An enveloped single-stranded RNA virus belonging to the β-coronavirus family, SARS-CoV-2 shares a 79% similarity in its sequence with SARS-CoV-1, the agent responsible for the local epidemic outbreaks that occurred in 2003. ^(3,4) Although most individuals recover fully after acute SARS-CoV-2 infection, there have been instances where a subset of patients experience symptoms which persist for a minimum of three months beyond the patient’s first infection, with no other identifiable cause.⁽⁵⁾

The researchers conducted an age- and sex-matched case-control study, with oral bacterial communities profiled by 16S rDNA gene (V3-V4) amplicon high-throughput sequencing. Salivary IL-6 and TNF-α concentrations were measured; as mentioned previously, SCFA were quantified by LC-MS/MS. Cognitive and fatigue status were assessed with the Montreal Cognitive Assessment (MoCA) and the Modified Fatigue Impact Scale (MFIS). The data that was compiled indicated that oral-microbiota α/β-diversity did not differ between groups; salivary cytokines were likewise similar, and that after Benjamini-Hochberg correction, no SCFA differences were significant (q>0.05). Valeric acid showed the strongest uncorrected signal (p=0.02; r=0.52), but not after adjustment (q=0.23; power ≈0.73). CPD participants had lower MoCA and higher MFIS scores than controls (both p<0.005). ⁽¹⁾

The authors of the study believe that “the modest, non-significant elevation of valeric acid observed in PCD patients may represent a biologically meaningful signal warranting confirmation in larger, longitudinal studies.” ⁽¹⁾

Despite their optimism, the authors admit that their study has several limitations; for example, the small cohort and cross-sectional design, which “may limit the representativeness of the observed microbiota profiles.” In addition,although the case–control study design allows for the establishment of associations, it does not demonstrate a direct causal relationship between the oral microbiota and PCD. Furthermore, microorganisms other than bacteria may play key roles within the oral ecosystem. Finally, there are environmental and lifestyle factors, such as smoking, alcohol consumption, and diet, which also influence microbiota composition; this, in the minds of the research team, highlights the complexity of these interactions as well as the need to consider multiple variables in interpretation. ⁽¹⁾

Despite these constraints, however, the authors believe that the work presented in their paper “provides valuable long-term insight into the oral microbiota of individuals with PCD.” ⁽¹⁾

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References

1. Pérez-Martínez, L.; Romero, L.; Palacios, E. et al. Oral Microbiota in Patients with Long COVID: A Pilot Study. Enferm Infecc Microbiol Clin (Engl Ed) 2026, 44 (2), 503072. DOI: 10.1016/j.eimce.2026.503072
2. N. Zhu, N.; D. Zhang, D.; W. Wang, W. et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med2020, 382, 727-733. DOI:10.1056/NEJMoa2001017
3. WHO COVID-19. Dashboard. https://data.who.int/dashboards/covid19/cases?n=c. (accessed 2025-10-20)
4. Lu, R.; Zhao, X.; Li. J. et al. Genomic Characterisation and Epidemiology of 2019 Novel Coronavirus: Implications for Virus Origins and Receptor Binding. Lancet 2020, 395 (10224), 565-574. DOI: 10.1016/S0140-6736(20)30251-8
5. Weston, S.; Frieman, M. B. COVID-19: Knowns, Unknowns, and Questions. mSphere 2020, 5 (2), e00203-20. DOI: 10.1128/mSphere.00203-20