Leader: Antonio Domenico Procopio (INRCA); Other collaborator(s):
We plan to Identify an evidence-based composite profile of circulating biomarkers (cytokines, microRNAs, cell-free DNA and Bacterial DNA, exosomes, metabolities and epigenetic signatures), starting from omic-data. We will combine selected biomarkers with multimorbidity and frailty factors to generate results to be used in pillar #3 and we will apply innovative approaches of data analisis (machine learning) to maximise the chance to identify and validate clinically-relevant circulating composite signatures to stratify geriatric patients according to identified composite profile.
Brief description of the activities and of the intermediate results: We analysed DNA-methylation based epigenetic age and inflammatory markers in peripheral blood leukocytes from Type 2 Diabetic patients and assessed the association of these parameters with all-cause mortality during 17-years follow-up. 50 patients were selected from a data base and included in the final analysis; 27 survived and 23 deceased during the follow-up. DNA methilation was analysed with Infinium Human Methylation EPIC Bead Chip (Illumina). In addition we are currently analysing the cell-free DNA in serum samples of REPORTAGE choort including about 1000 hospithalized elderly patients affected by the most common afge-related diseases.
During the period April-June 2024, the analysis of cfDNA in the samples of the REPORTAGE INRCA case series continued, for a total of 400 samples analyzed. The analysis of the methylome in diabetic patients continued, focusing the analysis on the DNAm-based scores of 3 proteins associated with inflammatory processes, such as CXCL10, CXCL11, enRAGE, C-reactive protein and senescent CD8+ T lymphocytes. The DNAm-based scores of the CXCL10, CXCL11 and enRAGE molecules were lower in patients who died at follow-up, while the DNAm-based scores of the C-reactive protein and senescent CD8+ T cells were higher in deceased patients than in survivors. These results suggest that biological age estimated with epigenetic tools is associated with long-term mortality in type 2 diabetic patients, independently of the most common risk factors. These results have been described in a paper submitted for publication.
In the July-September 2024 period, the analysis of cfDNA on 1100 plasma samples of hospitalized geriatric patients belonging to the REPORTAGE-INRCA case series was concluded. An in-depth statistical analysis has just begun to explore all the possible correlations between the cfDNA data and all the clinical variables present for the patient group.
Our previous work on the analysis of the methylome in diabetic patients (T2DM) was concluded with the publication of the following work: Sabbatinelli J, et al. DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes. Cardiovasc Diabetol. 2024 Jul 13;23(1):250. doi: 10.1186/s12933-024-02351-7. PMID: 39003492; PMCID: PMC11245869.
We have initiated the analysis of telomere length from DNA of patients of REPORTAGE cohort. This analysis aims to assess telomere length as a biomarker of aging and disease risk, integrating these results with the multimorbidity and frailty profile of geriatric patients. Additionally, we are analyzing DNAm-TL (DNA methylation-based telomere length) in a small subgroup of our cohort to explore the relationship between telomere biology and epigenetic modifications. Once the analysis of telomere length of 700 geriatric REPORTAGE patients cohort is completed, we will analyze and integrate these results with the various omic data sets generated throughout this project.
Sabbatinelli J, et al. DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes. Cardiovasc Diabetol. 2024 Jul 13;23(1):250. doi: 10.1186/s12933-024-02351-7. PMID: 39003492; PMCID: PMC11245869.