{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T14:45:28Z","timestamp":1786373128217,"version":"build-2736575974"},"reference-count":75,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","funder":[{"DOI":"10.13039\/100000050","name":"NHLBI","doi-asserted-by":"crossref","award":["X01HL153408, 3R01HL-117626-02S1, HHSN268201800002I, R01HL-120393, U01HL-120393, HHSN268201800001I"],"award-info":[{"award-number":["X01HL153408, 3R01HL-117626-02S1, HHSN268201800002I, R01HL-120393, U01HL-120393, HHSN268201800001I"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01-DK117445 and R01-MD012765"],"award-info":[{"award-number":["R01-DK117445 and R01-MD012765"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["U01-HG011720 and R01-HL146500"],"award-info":[{"award-number":["U01-HG011720 and R01-HL146500"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01-DK124399 and K24-HL155681"],"award-info":[{"award-number":["R01-DK124399 and K24-HL155681"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":["CJASN"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>We identified 69 plasma metabolites associated with sickle cell trait, including markers of eGFR and\/or related to oxidative stress pathways.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Twenty-five percent or 39% of the sickle cell trait-associated metabolites were replicated in the Atherosclerosis Risk in Communities study.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Sickle cell trait\u2013associated metabolites individually or in aggregate were associated with better prediction of incident kidney failure in those with sickle cell trait.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sickle cell trait (SCT) is the heterozygous carrier state for sickle cell disease (SCD) and is common among individuals of African ancestry. Although SCT is a known risk factor for CKD and ESKD, the mechanisms underlying this phenotypic association have not been fully characterized. We used metabolomic profiling to gain insight into the pathobiology of SCT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used a nontargeted metabolomics approach (Metabolon Global Discovery Panel) to measure baseline plasma levels of 851 metabolites in 986 older Black women with SCT (mean age 61\u00b17 years) compared with 998 age- and race-matched controls without SCT from the prospective Women's Health Initiative (WHI) study. Age-adjusted linear regression was used to assess the association between metabolite levels and SCT. Replication was performed in an independent sample of 1070 Black men and women (including 70 with SCT) from the Atherosclerosis Risk in Communities study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In age-adjusted models, 69 metabolites were significantly associated with SCT in WHI after correction for multiple testing. Many of the SCT-associated metabolites are markers of kidney glomerular filtration (eGFR) and\/or related to oxidative stress metabolic pathways are known to be altered in SCD homozygotes. Of the 64 SCT-associated metabolites available for replication, 25 or 39% were replicated in the Atherosclerosis Risk in Communities study. Inclusion of SCT-associated metabolites was associated with significantly better risk prediction of incident ESKD in WHI among SCT individuals compared with a baseline model adjusted for age+eGFR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      We identified and replicated metabolites associated with SCT, many of which are related to eGFR and\/or pathways altered in SCD (\n                      <jats:italic toggle=\"yes\">e.g<\/jats:italic>\n                      ., oxidative stress, membrane remodeling). These results suggest that plasma metabolomic profiling may be useful in ESKD risk stratification for individuals with SCT, meriting validation in larger cohorts.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.2215\/cjn.0000001015","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T17:00:47Z","timestamp":1772211647000},"page":"1135-1148","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Alterations of Plasma Metabolites Associated with Sickle Cell Trait"],"prefix":"10.2215","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3950-3794","authenticated-orcid":false,"given":"Yanwei","family":"Cai","sequence":"first","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4978-5980","authenticated-orcid":false,"given":"Aditya","family":"Surapaneni","sequence":"additional","affiliation":[{"name":"Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1069-2429","authenticated-orcid":false,"given":"Ana Gabriela","family":"Vasconcelos","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9442-8101","authenticated-orcid":false,"given":"Mari","family":"Johnson","sequence":"additional","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8168-4712","authenticated-orcid":false,"given":"Li","family":"Hsu","sequence":"additional","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6350-1107","authenticated-orcid":false,"given":"Wei","family":"Sun","sequence":"additional","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7986-8560","authenticated-orcid":false,"given":"Charles","family":"Kooperberg","sequence":"additional","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4818-1077","authenticated-orcid":false,"given":"Bing","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4141-7123","authenticated-orcid":false,"given":"Wan-Jin","family":"Yeo","sequence":"additional","affiliation":[{"name":"Department of Medicine, New York University Langone School of Medicine, New York, New York"},{"name":"Department of Radiation Oncology, University of California San Francisco, San Francisco, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1735-8044","authenticated-orcid":false,"given":"Paul L.","family":"Auer","sequence":"additional","affiliation":[{"name":"Division of Biostatistics, Data Science Institute, and Cancer Center, Medical College of Wisconsin, Milwaukee, Wisconsin"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4430-6023","authenticated-orcid":false,"given":"Morgan E.","family":"Grams","sequence":"additional","affiliation":[{"name":"Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8346-3662","authenticated-orcid":false,"given":"Nora","family":"Franceschini","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina"},{"name":"Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North 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