{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T22:49:54Z","timestamp":1792363794015,"version":"4.4.0"},"reference-count":73,"publisher":"National Academy of Sciences","issue":"51","license":[{"start":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T00:00:00Z","timestamp":1766016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100015691","name":"HHS | NIH | NIAID | Division of Microbiology and Infectious Diseases","doi-asserted-by":"publisher","award":["AI118608"],"award-info":[{"award-number":["AI118608"]}],"id":[{"id":"10.13039\/100015691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"HHS | NIH | National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["AI089992"],"award-info":[{"award-number":["AI089992"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2025,12,23]]},"abstract":"<jats:p>\n                    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\n                    <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                    gene as a preexisting contributor to disease trajectory\u2014patients that show aberrant one-carbon metabolite levels and that are homozygous for the\n                    <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                    C677T, have higher incidence of severe COVID. Our results raise the possibility that\n                    <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                    variant status may inform precision COVID-19 treatment strategies.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2509118122","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T16:04:20Z","timestamp":1766073860000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":7,"title":["MTHFR allele and one-carbon metabolic profile predict severity of COVID-19"],"prefix":"10.1073","volume":"122","author":[{"given":"Boryana","family":"Petrova","sequence":"first","affiliation":[{"name":"Department of Pathology, Boston Children\u2019s Hospital","place":["Boston"]},{"name":"Harvard Medical School","place":["Boston"]},{"name":"Core Facilities, Medical University of Vienna","place":["Vienna, Austria"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5066-3985","authenticated-orcid":false,"given":"Caitlin","family":"Syphurs","sequence":"additional","affiliation":[{"name":"Precision Vaccines Program, Boston Children\u2019s Hospital","place":["Boston"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew J.","family":"Culhane","sequence":"additional","affiliation":[{"name":"Department of Pathology, Boston Children\u2019s Hospital","place":["Boston"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5900-7460","authenticated-orcid":false,"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Precision Vaccines Program, Boston Children\u2019s Hospital","place":["Boston"]},{"name":"Research Computing, Department of Information Technology, Boston Children\u2019s 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Public Health","place":["New Haven"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8661-4454","authenticated-orcid":false,"given":"Ruth R.","family":"Montgomery","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Yale School of Medicine","place":["New Haven"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4957-1544","authenticated-orcid":false,"given":"Steven H.","family":"Kleinstein","sequence":"additional","affiliation":[{"name":"Department of Pathology, Yale School of Medicine","place":["New Haven"]},{"name":"Program in Computational Biology and Biomedical Informatics, Yale University","place":["New Haven"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kinga K.","family":"Smolen","sequence":"additional","affiliation":[{"name":"Harvard Medical School","place":["Boston"]},{"name":"Precision Vaccines Program, Boston Children\u2019s Hospital","place":["Boston"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8832-2607","authenticated-orcid":false,"given":"Kevin","family":"Mendez","sequence":"additional","affiliation":[{"name":"Harvard Medical School","place":["Boston"]},{"name":"Channing Institute of Medicine, Brigham and Women\u2019s Hospital","place":["Boston"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"IMPACC Network","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Lasky-Su","sequence":"additional","affiliation":[{"name":"Harvard Medical School","place":["Boston"]},{"name":"Channing Institute of Medicine, Brigham and Women\u2019s 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Harvard","place":["Cambridge"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2183-4269","authenticated-orcid":false,"given":"Joann","family":"Diray-Arce","sequence":"additional","affiliation":[{"name":"Harvard Medical School","place":["Boston"]},{"name":"Precision Vaccines Program, Boston Children\u2019s Hospital","place":["Boston"]},{"name":"Broad Institute of MIT and Harvard","place":["Cambridge"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2068-3908","authenticated-orcid":false,"given":"Naama","family":"Kanarek","sequence":"additional","affiliation":[{"name":"Department of Pathology, Boston Children\u2019s Hospital","place":["Boston"]},{"name":"Harvard Medical School","place":["Boston"]},{"name":"Broad Institute of MIT and 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Wang , Trajectories of functional limitations, health-related quality of life and societal costs in individuals with long COVID: A population-based longitudinal cohort study. BMJ Open 14, e088538 (2024).","journal-title":"BMJ Open"},{"key":"e_1_3_4_2_2","unstructured":"U.S. Centers For Disease Control and Prevention (CDC) Preliminary estimates of COVID-19 burden for 2024-2025. https:\/\/www.cdc.gov\/covid\/php\/surveillance\/burden-estimates.html. 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Peters J. A. Overton R. Vita K. Westendorf Data from \u201cSDY1760: Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) A Prospective Cohort Study to Assess Longitudinal Immune Responses in Hospitalized Patients with COVID-19.\u201d ImmPort. https:\/\/www.immport.org\/shared\/study\/SDY1760\/studyFiles. Deposited 26 July 2022."},{"key":"e_1_3_4_72_2","unstructured":"S. Kleinstein Data from \u201cImmunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays.\u201d dbGaP. https:\/\/www.ncbi.nlm.nih.gov\/projects\/gap\/cgi-bin\/study.cgi?study_id=phs002686.v3.p2. Deposited 12 March 2025."},{"key":"e_1_3_4_73_2","unstructured":"S. Kleinstein IMPACC Public Code. Bitbucket. https:\/\/bitbucket.org\/kleinstein\/impacc-public-code\/src\/master\/targeted_metabolomics_manuscript\/. 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