TY - JOUR
T1 - Metabolites Associated With Uremic Symptoms in Patients With CKD
T2 - Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study
AU - CRIC Study Investigators
AU - Wulczyn, Kendra E.
AU - Shafi, Tariq
AU - Anderson, Amanda
AU - Rincon-Choles, Hernan
AU - Clish, Clary B.
AU - Denburg, Michelle
AU - Feldman, Harold I.
AU - He, Jiang
AU - Hsu, Chi yuan
AU - Kelly, Tanika
AU - Kimmel, Paul L.
AU - Mehta, Rupal
AU - Nelson, Robert G.
AU - Ramachandran, Vasan
AU - Ricardo, Ana
AU - Shah, Vallabh O.
AU - Srivastava, Anand
AU - Xie, Dawei
AU - Rhee, Eugene P.
AU - Kalim, Sahir
AU - Dember, Laura M.
AU - Landis, J. Richard
AU - Townsend, Raymond R.
AU - Appel, Lawrence
AU - Fink, Jeffrey
AU - Rahman, Mahboob
AU - Horwitz, Edward J.
AU - Taliercio, Jonathan J.
AU - Rao, Panduranga
AU - Sondheimer, James H.
AU - Lash, James P.
AU - Chen, Jing
AU - Go, Alan S.
AU - Parsa, Afshin
AU - Rankin, Tracy
N1 - Publisher Copyright:
© 2024 National Kidney Foundation, Inc.
PY - 2024/7
Y1 - 2024/7
N2 - Rationale & Objective: The toxins that contribute to uremic symptoms in patients with chronic kidney disease (CKD) are unknown. We sought to apply complementary statistical modeling approaches to data from untargeted plasma metabolomic profiling to identify solutes associated with uremic symptoms in patients with CKD. Study Design: Cross-sectional. Setting & Participants: 1,761 Chronic Renal Insufficiency Cohort (CRIC) participants with CKD not treated with dialysis. Predictors: Measurement of 448 known plasma metabolites. Outcomes: The uremic symptoms of fatigue, anorexia, pruritus, nausea, paresthesia, and pain were assessed by single items on the Kidney Disease Quality of Life-36 instrument. Analytical Approach: Multivariable adjusted linear regression, least absolute shrinkage and selection operator linear regression, and random forest models were used to identify metabolites associated with symptom severity. After adjustment for multiple comparisons, metabolites selected in at least 2 of the 3 modeling approaches were deemed “overall significant.” Results: Participant mean estimated glomerular filtration rate was 43 mL/min/1.73 m2, with 44% self-identifying as female and 41% as non-Hispanic Black. The prevalence of uremic symptoms ranged from 22% to 55%. We identified 17 metabolites for which a higher level was associated with greater severity of at least one uremic symptom and 9 metabolites inversely associated with uremic symptom severity. Many of these metabolites exhibited at least a moderate correlation with estimated glomerular filtration rate (Pearson's r ≥ 0.5), and some were also associated with the risk of developing kidney failure or death in multivariable adjusted Cox regression models. Limitations: Lack of a second independent cohort for external validation of our findings. Conclusions: Metabolomic profiling was used to identify multiple solutes associated with uremic symptoms in adults with CKD, but future validation and mechanistic studies are needed. Plain-Language Summary: Individuals living with chronic kidney disease (CKD) often experience symptoms related to CKD, traditionally called uremic symptoms. It is likely that CKD results in alterations in the levels of numerous circulating substances that, in turn, cause uremic symptoms; however, the identity of these solutes is not known. In this study, we used metabolomic profiling in patients with CKD to gain insights into the pathophysiology of uremic symptoms. We identified 26 metabolites whose levels were significantly associated with at least one of the symptoms of fatigue, anorexia, itchiness, nausea, paresthesia, and pain. The results of this study lay the groundwork for future research into the biological causes of symptoms in patients with CKD.
AB - Rationale & Objective: The toxins that contribute to uremic symptoms in patients with chronic kidney disease (CKD) are unknown. We sought to apply complementary statistical modeling approaches to data from untargeted plasma metabolomic profiling to identify solutes associated with uremic symptoms in patients with CKD. Study Design: Cross-sectional. Setting & Participants: 1,761 Chronic Renal Insufficiency Cohort (CRIC) participants with CKD not treated with dialysis. Predictors: Measurement of 448 known plasma metabolites. Outcomes: The uremic symptoms of fatigue, anorexia, pruritus, nausea, paresthesia, and pain were assessed by single items on the Kidney Disease Quality of Life-36 instrument. Analytical Approach: Multivariable adjusted linear regression, least absolute shrinkage and selection operator linear regression, and random forest models were used to identify metabolites associated with symptom severity. After adjustment for multiple comparisons, metabolites selected in at least 2 of the 3 modeling approaches were deemed “overall significant.” Results: Participant mean estimated glomerular filtration rate was 43 mL/min/1.73 m2, with 44% self-identifying as female and 41% as non-Hispanic Black. The prevalence of uremic symptoms ranged from 22% to 55%. We identified 17 metabolites for which a higher level was associated with greater severity of at least one uremic symptom and 9 metabolites inversely associated with uremic symptom severity. Many of these metabolites exhibited at least a moderate correlation with estimated glomerular filtration rate (Pearson's r ≥ 0.5), and some were also associated with the risk of developing kidney failure or death in multivariable adjusted Cox regression models. Limitations: Lack of a second independent cohort for external validation of our findings. Conclusions: Metabolomic profiling was used to identify multiple solutes associated with uremic symptoms in adults with CKD, but future validation and mechanistic studies are needed. Plain-Language Summary: Individuals living with chronic kidney disease (CKD) often experience symptoms related to CKD, traditionally called uremic symptoms. It is likely that CKD results in alterations in the levels of numerous circulating substances that, in turn, cause uremic symptoms; however, the identity of these solutes is not known. In this study, we used metabolomic profiling in patients with CKD to gain insights into the pathophysiology of uremic symptoms. We identified 26 metabolites whose levels were significantly associated with at least one of the symptoms of fatigue, anorexia, itchiness, nausea, paresthesia, and pain. The results of this study lay the groundwork for future research into the biological causes of symptoms in patients with CKD.
KW - Chronic Renal Insufficiency Cohort (CRIC)
KW - Chronic kidney disease
KW - machine learning
KW - metabolomics
KW - multivariable model
KW - uremic symptoms
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U2 - 10.1053/j.ajkd.2023.11.013
DO - 10.1053/j.ajkd.2023.11.013
M3 - Article
C2 - 38266973
AN - SCOPUS:85188437639
SN - 0272-6386
VL - 84
SP - 49-61.e1
JO - American Journal of Kidney Diseases
JF - American Journal of Kidney Diseases
IS - 1
ER -