ESPN 51th Annual Meeting

ESPN 2018


 
SERUM AND URINE METABOLOMICS ANALYSIS IN INFANTS WITH URETEROPELVIC JUNCTION OBSTRUCTION
ANTIGONI PAVLAKI 1 NIKOLETA PRINTZA 1 OLGA BEGOU 2 EVANGELIA FARMAKI 1 JOHN DOTIS 1 STELLA STABOULI 1 HELEN GIKA 3 ANNA TAPARKOU 1 CHRYSA GKOGKA 1 NIKOLAOS RAIKOS 3 GEORGE THEODORIDIS 2 FOTIOS PAPACHRISTOU 1

1- PEDIATRIC NEPHROLOGY UNIT, FIRST DEPARTMENT OF PEDIATRICS, HIPPOKRATION HOSPITAL, ARISTOTLE UNIVERSITY OF THESSALONIKI
2- LABORATORY OF ANALYTICAL CHEMISTRY, DEPARTMENT OF CHEMISTRY, ARISTOTLE UNIVERSITY OF THESSALONIKI
3- LABORATORY OF FORENSIC MEDICINE AND TOXICOLOGY, SCHOOL OF MEDICINE, ARISTOTLE UNIVERSITY OF THESSALONIKI
 
Introduction:

The most common cause of chronic kidney disease in children is congenital anomalies of the urinary tract and particularly obstructive nephropathies. Despite the fact that ureteropelvic junction obstruction (UPJO) is the most prevalent obstructive nephropathy fundamental questions regarding its assessment and treatment remain unanswered. Aim of the present study was to clarify whether the serum or urine metabolic profile of children with UPJO differs from that of healthy children, and if through metabolic analysis new biomarkers can emerge that will allow early diagnosis of renal dysfunction in these children. Furthermore, the potential of the metabolomic profile to separate surgical from non-surgical cases was studied.  

Material and methods:

Serum and urine samples were collected from 23 obstructive UPJO patients preoperatively, 22 patients with mild stenosis treated conservatively and 19 healthy infants as controls. The median age of the participants in all three groups was 2 months and all had normal creatinine values. Samples were subjected to targeted metabolomic analysis by Hydrophilic Interaction Liquid Chromatography coupled to mass spectrometry (HILIC-MS/MS).

Results:

Analysis of the serum metabolic profile of the patients through multifactorial statistical models revealed a clear separation of the samples with a statistically significant difference between all three groups. Analysis of the urinary metabolic profile clearly separated the surgical cases from controls but not from those conservatively treated.

Conclusions:

Serum metabolic analysis enabled the discrimination of patients who required surgery from those treated conservatively as well as from healthy controls. In addition, the urinary metabolic profile clearly distinguished surgical cases from controls. Analyzing a larger number of samples, using potentially multi-omics could more accurately identify biomarkers-metabolites with utility in clinical practice.