ReviewTanaffos2025
COVID-19: A Systematic Review of Metabolomics Data and Predicting Potential Biomarkers Based on Pathway Analysis.
Review in Tanaffos, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic is a worldwide disaster in medicine, public health, and the economy. Many details of COVID-19 are currently unknown. This study aims to offer dysregulated metabolic profiles as potential biomarkers for SARS-CoV-2 infection by analyzing identified COVID-19 metabolites. We searched PubMed, Web of Science, EMBASE, and Scopus for metabolomics studies on COVID-19 patients. Studies investigating COVID-19 metabolite changes and utilizing mass spectrometry-based techniques are included. Two reviewers separately retrieved pertinent data for each selected publication. Differences of opinion among the reviewers were settled via conversation, and a final judgment was obtained. The online MetaboAnalyst 3.0 was used to conduct the pathway analysis of COVID-19. This study comprised 31 investigations with QUADOMICS quality evaluation. We isolated modified metabolites that have been found in at least three other investigations. The metabolomics data in response to SARS-CoV-2 alter at the metabolite expression level, leading to dysregulation of major metabolic pathways, including carbohydrates, amino acids, and lipids associated with COVID-19. The pathway analysis of metabolic reprogramming across different biological samples demonstrated a significant role in amino acid metabolism, including phenylalanine, tyrosine, and tryptophan production, in the severity of COVID-19. This review showed dysregulated metabolic profiling for identifying individuals with high severity of COVID-19. These results provide an understanding of metabolic pathways and how dysregulated metabolic profiling reflects the severity of COVID-19 in the general population. The high frequency of changed metabolites might be used as COVID-19 biomarkers for early detection, and significant metabolic routes could reveal new information about pathogenesis and lead to potential treatment targets.
Indexed as
Identifiers
42027972PMC13101934What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.