Abstract: TH-PO1163
Metabolomics Profile of Hemodialysis Patients during the COVID-19 Putative Incubation Period
Session Information
- COVID-19
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Coronavirus (COVID-19)
- 000 Coronavirus (COVID-19)
Authors
- Ferreira Dias, Gabriela, Renal Research Institute, New York, New York, United States
- Fan, Chenxi, University of California Santa Barbara, Santa Barbara, California, United States
- Han, Maggie, Renal Research Institute, New York, New York, United States
- Wang, Xin, Renal Research Institute, New York, New York, United States
- Wang, Xiaoling, Renal Research Institute, New York, New York, United States
- Zhang, Hanjie, Renal Research Institute, New York, New York, United States
- Grobe, Nadja, Renal Research Institute, New York, New York, United States
- Guo, Wensheng, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Kotanko, Peter, Renal Research Institute, New York, New York, United States
- Wang, Yuedong, University of California Santa Barbara, Santa Barbara, California, United States
Group or Team Name
- Renal Research Institute's Laboratory Research.
Background
Hemodialysis (HD) patients are at high risk of developing serious complications from COVID-19. To the best of our knowledge, metabolic alterations occurring before COVID-19 diagnosis in the HD population have not been studied. Using untargeted metabolomics, we aimed to (a) identify early alterations in the metabolome of HD patients within the putative incubation period (PIP, defined for the purpose of this research as two weeks before COVID-19 diagnosis) and (b) evaluate their longitudinal metabolic profiles.
Methods
We analyzed routinely collected serum samples from HD patients from 60 days before and 60 days after a positive SARS-CoV-2 RT-PCR. Metabolites were extracted using cold methanol and subjected to reverse phase liquid chromatography/mass spectrometry (LC/MS). Metabolite identification was achieved with library matching (mass, retention time and MS/MS fragmentation spectra). A linear mixed-effects model was fitted to evaluate the change in metabolic feature levels from baseline phase (days -60 to -15) to the PIP (days -14 to 0). False Discovery Rate (FDR) adjusted p-value cutoff was 0.05.
Results
We analyzed 201 serum samples from a cohort of 30 HD patients (59.2 ± 13.3 years, 57% male). Untargeted analysis of these samples revealed 422 metabolic features, 15 of which showed alterations between baseline and the PIP (Fig.1a). Notably, α-guanidinoglutaric acid and sialic acid levels increased between baseline and PIP. (Fig.1b).
Conclusion
The metabolomics profile of HD patients is altered in the PIP of COVID-19. These molecular fingerprints - as well as α-guanidinoglutaric acid and sialic acid as potential biomarkers - could contribute to the development of predictive models for early COVID-19 detection in HD patients.
Funding
- NIDDK Support