Biomarkers per la diagnosi precose di patologie cardiovascolari e per la valutazione di efficacia antiossidante di nuovi nutraceutici in soggetti affetti da sindrome metabolica (Biomarkers-Angelica)

The project focuses on the development and application of new bioanalytical methodologies (high resolution mass spectrometry) to identify and characterize, in patients who share the common last pathway of the cardiovascular damage, through the activation of the oxidative/carbonyl stress, new unequivocal, sensitive and reliable biomarkers for the early diagnosis of CVD: oxidatively-modified peptides and proteins.



Our experimental approach involves the search of suitable biomarkers (in particular by identification and characterization of the covalent modifications of plasma albumin and erythrocyte haemoglobin) in subjects with metabolic syndrome, a cluster of the most dangerous CVD risk factors: diabetes and prediabetes, abdominal obesity, hyperlipidemia, hypertension.



Albumin and haemoglobin have been selected as target proteins due to their well known susceptibility to oxidation/carbonylation, on the basis of our in vitro and ex vivo studies recently published. These studies allowed to demonstrate that both proteins are highly susceptible to oxidation/carbonylation-induced covalent and non-covalent modifications. Such modifications may represent new specific and early biomarker of systemic oxidative/carbonylic stress, highly predictive for cardiovascular risk in subjects with metabolic syndrome.



Once validated, the identified biomarker/s will be employed to evaluate the antioxidant efficacy of new functional foods (nutrition bars rich in plant-derived antioxidants) in human volunteers with metabolic syndrome.



This is a field of remarkable interest and in continuous evolution, that foresees meaningful technological relapses both within the diagnostic area and in the studies of effectiveness of new bioactive molecules.







The project implies the reach of the following goals:

1. Recruitment of healthy older adults (< 50 yr) amd older adults metabolic syndrome (> 50 yr) controls) (Human Nutrition Research Center on Aging HNRCA; Tufts University, Boston) and evaluation of the main plasma and urinary biochemical parameters (total cholesterol, HDL, LDL, VLDL, glucose, insulin, adiponectin, hsCRP, HbAlc, creatinine.


2. Evaluation of a series of already validated oxidative stress parameters in both the groups of volunteers: Total Antioxidant Performance (Tap assay), DNA damage and repair (COMET assay), fat-soluble and water-soluble antioxidants (HNRCA)


3. Identification and characterization, through a proteomic approach (immunochemistry and high-resolution mass spectrometry) of the post-synthesis modifications and the oxidation/adduction sites on albumin and haemoglobin in human volunteers with metabolic syndrome (DSFPP)


4. Development of new high-resolution mass spectrometric techniques for the quantitative determination of the modified protein(s) in the biological matrix, to be used as unequivocal biomarker(s) of oxidative damage (DSFPP)


5. Chronic treatment of the human volunteeers (healthy and with metabolic syndrome recruited in 1) with nutrition bars containing
   Angelica keinskei
   as a plant-derived source of antioxidants, with the final aim to increase the human antioxidant defences (HNRCA)


6. Evaluation of the treatment efficacy: determination of the biochemical plasma/urine parameters and of the oxidative stress parameters described under point 1) and 2) (HNRCA)


7. Application of the quantitative mass spectrometric approach described under point 4) to the human volunteers chronically treated with the nutrition bars, in order to demonstrate the antioxidant efficacy of the new functional food (DSFPP)


8. Bioavailability profile of the active components of the functional food in the treated subjects: identification in plasma of a marker of gastro-intestinal absorption and development of a quantiative method by LC-MS/MS (liquid chromatography-tandem mass spectrometry) for determination of plasma levels (DSFPP).


9. Statistical analysis of the data: relationship efficacy parameters – new biomarkers (HNRCA + DSFPP).