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.

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.

1000 patients affected by malnutrition due to deficiency or excess, associated with at least one of the pathological conditions(small for gestational age; metabolic syndrome; type 1 diabetes mellitus; neurological diseases; psychiatric; chronic infectious diseases; oncological pathologies; gastrointestinal diseases; cardiovascular diseases; kidney disease; lung pathologies) aged 0-85 years (50% male) and 1000 sex- and age- matched healthy controls not affected by any pathology and/or malnutrition due to deficiency or excess.