MTHFR allele and one-carbon metabolic profile predict severity of COVID-19
While the public health burden of SARS-CoV-2 infection has lessened due to natural and vaccine-acquired immunity, emergence of less virulent variants, and antiviral medications, COVID-19 continues to take a significant toll. There are thousands of new hospitalizations and hundreds of deaths per week in the United States, many of whom develop long COVID. Early identification of individuals at high risk of severe COVID-19 is key for monitoring and supporting respiratory status and improving outcomes. Therefore, precision tools for early detection of patients at high risk of severe disease can reduce morbidity and mortality.
Here, we report an untargeted, longitudinal plasma metabolomics study of COVID-19 patients. One-carbon metabolism, a pathway previously shown as critical for viral propagation and disease progression, and a potential target for COVID-19 treatment, scored strongly as differentially abundant in patients with severe COVID-19.
Targeted metabolite profiling revealed that one arm of the one-carbon metabolism pathway, the methionine cycle, is a major driver of the metabolic profile associated with disease severity. Further, genomic data from the profiled patients revealed a genetic contributor to methionine metabolism and identified the C677T allele of the MTHFR gene as a preexisting contributor to disease trajectory—patients that show aberrant one-carbon metabolite levels and that are homozygous for the MTHFR C677T, have higher incidence of severe COVID.
Our results raise the possibility that MTHFR variant status may inform precision COVID-19 treatment strategies.
SIGNIFICANCE
Given long COVIDs health burden, identifying at-risk groups and tailoring prevention strategies is vital to reduce long-term morbidity. Leveraging a large longitudinal U.S. adult cohort, we integrated genomics with targeted and untargeted metabolomics, to identify disruption of one-carbon metabolism as a risk factor for long COVID. Focusing on methionine metabolism, we found that combining MTHFR genetic polymorphism data with plasma methionine cycle biomarkers predicts COVID-19 severity and long COVID risk, offering an accessible molecular axis for potential early clinical risk assessment.
Web | DOI | PDF | Proceedings of the National Academy of Sciences | Open Access
Petrova, Boryana; Syphurs, Caitlin; Culhane, Andrew J; Chen, Jing; Chen, Ernie; Cotsapas, Chris; Esserman, Denise; Montgomery, Ruth R; Kleinstein, Steven H; Smolen, Kinga K; Mendez, Kevin; null, null; Lasky-Su, Jessica; Steen, Hanno; Levy, Ofer; Diray-Arce, Joann; Kanarek, Naama
While the public health burden of SARS-CoV-2 infection has lessened due to natural and vaccine-acquired immunity, emergence of less virulent variants, and antiviral medications, COVID-19 continues to take a significant toll. There are thousands of new hospitalizations and hundreds of deaths per week in the United States, many of whom develop long COVID. Early identification of individuals at high risk of severe COVID-19 is key for monitoring and supporting respiratory status and improving outcomes. Therefore, precision tools for early detection of patients at high risk of severe disease can reduce morbidity and mortality.
Here, we report an untargeted, longitudinal plasma metabolomics study of COVID-19 patients. One-carbon metabolism, a pathway previously shown as critical for viral propagation and disease progression, and a potential target for COVID-19 treatment, scored strongly as differentially abundant in patients with severe COVID-19.
Targeted metabolite profiling revealed that one arm of the one-carbon metabolism pathway, the methionine cycle, is a major driver of the metabolic profile associated with disease severity. Further, genomic data from the profiled patients revealed a genetic contributor to methionine metabolism and identified the C677T allele of the MTHFR gene as a preexisting contributor to disease trajectory—patients that show aberrant one-carbon metabolite levels and that are homozygous for the MTHFR C677T, have higher incidence of severe COVID.
Our results raise the possibility that MTHFR variant status may inform precision COVID-19 treatment strategies.
SIGNIFICANCE
Given long COVIDs health burden, identifying at-risk groups and tailoring prevention strategies is vital to reduce long-term morbidity. Leveraging a large longitudinal U.S. adult cohort, we integrated genomics with targeted and untargeted metabolomics, to identify disruption of one-carbon metabolism as a risk factor for long COVID. Focusing on methionine metabolism, we found that combining MTHFR genetic polymorphism data with plasma methionine cycle biomarkers predicts COVID-19 severity and long COVID risk, offering an accessible molecular axis for potential early clinical risk assessment.
Web | DOI | PDF | Proceedings of the National Academy of Sciences | Open Access