Malnutrition
Conditions
Brief summary
The latest data from the World Health Organization (WHO) shows that malnutrition in all its forms affects over 2.5 billion people globally. This condition is constantly increasing and affects the entire population, from childhood to the elderly. Malnutrition in all its forms negatively impacts the quality of life of patients affected and increases the risk of morbidity and mortality, as well as healthcare costs. Considering the complexity and multifactorial nature of malnutrition, the integration of multi-omics data obtained from analyzes with high-throughput technologies such as epigenomics, metagenomics, metabolomics, could benefit the prediction and evaluation of prognosis and/or response to specific treatments; this could pave the way for personalized precision medicine interventions for patients suffering from malnutrition. The SAM study aims to characterize malnutrition through the identification of specific biomarkers of the condition with the aim of developing innovative prevention and treatment programs.
Interventions
OTHERData and samples collection
Collection of clinical, anamnestic and lifestyle data; collection of faecal, blood and saliva samples
Sponsors
Federico II University
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
0 Years to 85 Years
Healthy volunteers
No
Inclusion criteria
* Caucasian ethnicity; * both sexes; * age between 0 and 85 years; * affected by malnutrition due to deficiency or excess in association with other patology and sex- and age-matched healthy controls not affected by malnutrition due to deficiency or excess and any pathology * Written informed consent
Exclusion criteria
* Non-Caucasian ethnicity; * Age \> 85 years.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Characterization of malnutrition through the identification of specific biomarkers of the condition. | 36 months | Data and samples analyses |
| Untargeted microRNA expression profile in blood samples | 36 months | TruSeq Small RNA Sample Preparation Kit (Illumina) |
| Plasmatic extracellular vesicles | 36 months | A transmission electron microscope will be used to analyze the morphology of extracellular vesicles and the total protein concentration of the extracellular vesicles will be measured with a Bradford assay and the quantitation of specific membrane proteins and specific intracellular proteins (Heat-Shock Proteins/HSP) will be carried out by ELISA. |
| Metagenomic analysis of fecal samples | 36 months | Shotgun analysis |
| Metabolomicanalysis of fecal samples | 36 months | Gas chromatography-mass spectrometry |
| Untargeted microRNA expression profile in saliva samples | 36 months | TruSeq Small RNA Sample Preparation Kit (Illumina) |
| Salivary extracellular vesicles | 36 months | A transmission electron microscope will be used to analyze the morphology of extracellular vesicles and the total protein concentration of the extracellular vesicles will be measured with a Bradford assay and the quantitation of specific membrane proteins and specific intracellular proteins (Heat-Shock Proteins/HSP) will be carried out by ELISA. |
| Metagenomic analysis of salivary samples | 36 months | Shotgun analysis |
Countries
Italy
Outcome results
None listed