Associations between Kidney Disease Progression and Metabolomic Profiling in Stable Kidney Transplant Recipients—A 3 Year Follow-Up Prospective Study

<b>Background:</b> kidney transplant recipients are exposed to multiple pathogenic pathways that may alter short and long-term allograft survival. Metabolomic profiling is useful for detecting potential biomarkers of kidney disease with a predictive capacity. This field is still under development in kidney transplantation and metabolome analysis is faced with analytical challenges. We performed a cross-sectional study including stable kidney transplant patients and aimed to search for relevant associations between baseline plasmatic and urinary metabolites and relevant outcomes over a follow-up period of 3 years. <b>Methods:</b> we performed a cross-sectional study including 72 stable kidney transplant patients with stored plasmatic and urinary samples at the baseline evaluation which were there analyzed by nuclear magnetic resonance in order to quantify and describe metabolites. We performed a 3-year follow-up and searched for relevant associations between renal failure outcomes and baseline metabolites. Between-group comparisons were made after classification by observed estimated glomerular filtration rate slope during the follow-up: positive slope and negative slope. <b>Results</b>: The mean estimated GFR (glomerular filtration rate) was higher at baseline in the patients who exhibited a negative slope during the follow-up (63.4 mL/min/1.73 m<sup>2</sup> vs. 55.8 mL/min/1.73 m<sup>2</sup>, <i>p</i> = 0,019). After log transformation and division by urinary creatinine, urinary dimethylamine (3.63 vs. 3.16, <i>p</i> = 0.027), hippuric acid (7.33 vs. 6.29, <i>p</i> = 0.041), and acetone (1.88 vs. 1, <i>p</i> = 0.023) exhibited higher concentrations in patients with a negative GFR slope when compared to patients with a positive GFR slope. By computing a linear regression, a significant low-strength regression equation between the log 2 transformed plasmatic level of glycine and the estimated glomerular filtration rate was found (<i>F</i> (1,70) = 5.15, <i>p</i> = 0.026), with an <i>R</i><sup>2</sup> of 0.069. Several metabolites were correlated positively with hand grip strength (plasmatic tyrosine with r = 0.336 and <i>p</i> = 0.005 and plasmatic leucine with r = 0.371 and <i>p</i> = 0.002). Other urinary metabolites were found to be correlated negatively with hand grip strength (dimethylamine with r = -0.250 and <i>p</i> = 0.04, citric acid with r = -0.296 and <i>p</i> = 0.014, formic acid with r = -0.349 and <i>p</i> = 0.004, and glycine with r = -0.306 and <i>p</i> = 0.01). <b>Conclusions</b>: some metabolites had different concentrations compared to kidney transplant patients with negative and positive slopes, and significant correlations were found between hand grip strength and urinary and plasmatic metabolites.

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Journal
Journal of Clinical Medicine
Published
2024-10-08
DOI
https://doi.org/10.3390/jcm13195983
Primary Topic
Metabolism and Genetic Disorders
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article
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article

Associations between Kidney Disease Progression and Metabolomic Profiling in Stable Kidney Transplant Recipients—A 3 Year Follow-Up Prospective Study

Lucian Sirițeanu, Alina Nicolescu, Adrian Covic, T. Andrian et al.
Journal of Clinical Medicine
Metabolism and Genetic Disorders
article

Associations between Kidney Disease Progression and Metabolomic Profiling in Stable Kidney Transplant Recipients—A 3 Year Follow-Up Prospective Study

Lucian Sirițeanu, Alina Nicolescu, Adrian Covic, T. Andrian, Călin Deleanu, Luminița Voroneanu, Andreea Covic
article en

Abstract

<b>Background:</b> kidney transplant recipients are exposed to multiple pathogenic pathways that may alter short and long-term allograft survival. Metabolomic profiling is useful for detecting potential biomarkers of kidney disease with a predictive capacity. This field is still under development in kidney transplantation and metabolome analysis is faced with analytical challenges. We performed a cross-sectional study including stable kidney transplant patients and aimed to search for relevant associations between baseline plasmatic and urinary metabolites and relevant outcomes over a follow-up period of 3 years. <b>Methods:</b> we performed a cross-sectional study including 72 stable kidney transplant patients with stored plasmatic and urinary samples at the baseline evaluation which were there analyzed by nuclear magnetic resonance in order to quantify and describe metabolites. We performed a 3-year follow-up and searched for relevant associations between renal failure outcomes and baseline metabolites. Between-group comparisons were made after classification by observed estimated glomerular filtration rate slope during the follow-up: positive slope and negative slope. <b>Results</b>: The mean estimated GFR (glomerular filtration rate) was higher at baseline in the patients who exhibited a negative slope during the follow-up (63.4 mL/min/1.73 m<sup>2</sup> vs. 55.8 mL/min/1.73 m<sup>2</sup>, <i>p</i> = 0,019). After log transformation and division by urinary creatinine, urinary dimethylamine (3.63 vs. 3.16, <i>p</i> = 0.027), hippuric acid (7.33 vs. 6.29, <i>p</i> = 0.041), and acetone (1.88 vs. 1, <i>p</i> = 0.023) exhibited higher concentrations in patients with a negative GFR slope when compared to patients with a positive GFR slope. By computing a linear regression, a significant low-strength regression equation between the log 2 transformed plasmatic level of glycine and the estimated glomerular filtration rate was found (<i>F</i> (1,70) = 5.15, <i>p</i> = 0.026), with an <i>R</i><sup>2</sup> of 0.069. Several metabolites were correlated positively with hand grip strength (plasmatic tyrosine with r = 0.336 and <i>p</i> = 0.005 and plasmatic leucine with r = 0.371 and <i>p</i> = 0.002). Other urinary metabolites were found to be correlated negatively with hand grip strength (dimethylamine with r = -0.250 and <i>p</i> = 0.04, citric acid with r = -0.296 and <i>p</i> = 0.014, formic acid with r = -0.349 and <i>p</i> = 0.004, and glycine with r = -0.306 and <i>p</i> = 0.01). <b>Conclusions</b>: some metabolites had different concentrations compared to kidney transplant patients with negative and positive slopes, and significant correlations were found between hand grip strength and urinary and plasmatic metabolites.

Journal of Clinical MedicineVol. 13(19)
Grigore T. Popa University of Medicine and Pharmacy (RO), Spitalul Clinic Dr. C. I. Parhon (RO)
Good health and well-being
Openalex Percentile: Top 74%
Metabolism and Genetic Disorders
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