Paola Pirillo (Presenter)
UNIVERSITY OF PADOVA
Bio: I am currently a postdoctoral fellow in the Department of Women’s and Children’s Health of the University of Padova. My research is focused on the analysis of metabolic profiles of biological samples (urine, plasma, EBC, amniotic fluid) for the study of different pediatric conditions. I involve in the collection and preparation of the samples, in the building of the sequences for the analysis, and in the conduction of the analysis in HRMS coupled with UPLC. In particular, I deal with data extraction with different software (MarkerLynx, R, Progenesis) and with data processing by multivariate and univariate statistical analysis (SIMCA, R). I involve in the compounds identification by the investigation of spectra and by the research of the metabolites on the specific database, and I participate in the interpretation of putative biomarkers in biological pathways. Besides metabolomic research, I conducted target analysis by LC-MS/MS on some metabolites like ADMA; vitamin D and bile acids, and, during the period like a visiting scholar at UC Davis University, I had the opportunity to extract and analyze oxylipins in plasma samples. As to the diagnostic analysis for rare diseases conducted in our laboratory, I also learned how to analyze and quantify acylcarnitines and amino acids in blood spot and plasma samples, and bile acids in urine .
Authorship: Paola Pirillo(1), Alfonso Galderisi(1), Vittoria Moret(1), Matteo Stocchero(3), Antonina Gucciardi(2), Mauro Naturale(1), Eugenio Baraldi(1), Giuseppe Giordano(1),
(1)Department of Women’s and Children’s Health, University of Padova, Italy; (2)Città della Speranza Institute of Pediatric Research (IRP), Padova, Italy; (3)S-IN Soluzioni Informatiche, Vicenza, Italy
| Short Abstract Type 1 diabetes (T1D) is a crucial pathology, that influences the life of patients, since from the childhood. In our work, we studied the T1D in infancy, through the metabolomic approach for a whole assessment of biologic profile of T1D children in insulin therapy and in good glycemic control (mean HbA1c % < 8), and of healthy children comparable for age, sex and puberty. Applying the high-definition mass spectrometry to the urine samples, we were able, after processing data with specific statistical multivariate and univariate analysis, to clearly separate the peers in two groups and to reveal important alteration in different metabolic pathways in diabetic subjects, even if they are not far from the onset of the diseases, like adults, and they are all in good glycemic control. |
Long Abstract
Type 1 diabetes mellitus (T1D), characterized by defects in insulin secretion or action, is one of the most common chronic diseases in childhood [1], that influences the entire life of the patient. Despite the good glycemic control that is possible to obtain with insulin replacement, T1D is still associated with an excess of mortality in adulthood population [2], in particular for cardiovascular events, suggesting that several metabolic disorders persist in T1D patients in insulin treatment. The aim of our study is to investigate, on the basis of the untargeted analysis, not "a priori" hypothesis driven, if and which different metabolic alterations already present in T1D childhood population, not far from diabetes onset.
The analysis was conducted on the urine specimens through high-definition mass spectrometry (HDMS). The samples were collected from 56 children of the pediatric population (Padova University-Hospital) with the diagnosis of type 1 diabetes and in insulin replacement therapy and from 32 healthy volunteers comparable for age, sex and puberty.
The urine samples were diluted 1:5 ratio (v:v) in 0.1% Formic acid solution. The diluted samples were analyzed through a Q-ToF mass spectrometer coupled with the UPLC for the chromatographic separation in reverse phase column. The acquisition operated in ESI + and in ESI - ions, in scan and in MSE mode. The urine Quality Controls (QC) and the Standards Sample were injected to assess the reliability of the analytical process. The data obtained, after filtering and normalizing, were processed with multivariate (PCA, PLS-DA) and univariate statistical analysis (ROC curves, t-test) to obtain the models describing the distribution and variance of the samples on the basis of the metabolomic profiles of each enrolled subjects.
Thanks to the validation of the models (Monte Carlo stability selection) we were able to build robust models that clearly separate T1D children from healthy peers, and to extract a panel of variables discriminating between the two groups. The accurate mass (m/z) obtained from HDMS allowed to compare the variables with the compounds listed in the online database (METLIN, HMDB), and to evaluate the putative biomarkers on the basis of the accurate mass, retention times and fragmentation spectra, and to identify the compounds where the standards were available. The metabolites extracted showed that several pathways (in particular steroids hormones, small peptides, fatty acids, and compounds from gut microflora) are already altered in a T1D pediatric cohort, even if the age of the onset is not far from the samples collection and all enrolled children are in good glycemic control. (mean HbA1c % < 8).
References & Acknowledgements:
[1] EURODIAB ACE Study Group, Variation and trends in incidence of childhood diabetes in Europe. Lancet2000,355,873-876
[2] Lind, M., et al., Glycemic control and excess mortality in type 1 diabetes. N Engl J Med, 2014. 371(21): p. 1972-82.
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