A metabolomics approach identified toxins associated with uremic symptoms in advanced chronic kidney disease.


Journal

Kidney international
ISSN: 1523-1755
Titre abrégé: Kidney Int
Pays: United States
ID NLM: 0323470

Informations de publication

Date de publication:
02 2022
Historique:
received: 08 03 2021
revised: 27 09 2021
accepted: 01 10 2021
pubmed: 30 11 2021
medline: 12 3 2022
entrez: 29 11 2021
Statut: ppublish

Résumé

Uremic symptoms are common in patients with advanced chronic kidney disease, but the toxins that cause these symptoms are unknown. To evaluate this, we performed a cross-sectional study of the 12 month post-randomization follow-up visit of Modification of Diet in Renal Disease (MDRD) participants reporting uremic symptoms who also had available stored serum. We quantified 1,163 metabolites by liquid chromatography-tandem mass spectrometry. For each uremic symptom, we calculated a score as the severity multiplied by the number of days the symptom was experienced. We analyzed the associations of the individual symptom scores with metabolites using linear models with empirical Bayesian inference, adjusted for multiple comparisons. Among 695 participants, the mean measured glomerular filtration rate (mGFR) was 28 mL/min/1.73 m

Identifiants

pubmed: 34843755
pii: S0085-2538(21)01076-0
doi: 10.1016/j.kint.2021.10.035
pmc: PMC8792216
mid: NIHMS1766195
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

369-378

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL132372
Pays : United States
Organisme : NINR NIH HHS
ID : R01 NR017399
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK085689
Pays : United States

Informations de copyright

Copyright © 2021 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

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Auteurs

Jiun-Ruey Hu (JR)

Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

Leslie Myint (L)

Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, Minnesota, USA.

Andrew S Levey (AS)

Division of Nephrology, Tufts Medical Center, Boston, Massachusetts, USA.

Josef Coresh (J)

Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

Lesley A Inker (LA)

Division of Nephrology, Tufts Medical Center, Boston, Massachusetts, USA.

Morgan E Grams (ME)

Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Division of Nephrology, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA.

Eliseo Guallar (E)

Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

Kasper D Hansen (KD)

Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

Eugene P Rhee (EP)

Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts, USA.

Tariq Shafi (T)

Division of Nephrology, University of Mississippi Medical Center, Jackson, Mississippi, USA. Electronic address: tshafi@umc.edu.

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