Report

Teaser, summary, work performed and final results

Periodic Reporting for period 3 - RHAPSODY (Assessing risk and progression of prediabetes and type 2 diabetes to enable disease modification - Sofia ref.: 115881)

Teaser

Diabetes is subdivided into two main forms, Type 1 Diabetes (T1D) and Type 2 Diabetes mellitus (T2D). Of them, T1D is more uniform and accounts for about 10% of all patients, whereas T2D, which accounts for about 80-90% of all patients, is much more heterogeneous, but the...

Summary

Diabetes is subdivided into two main forms, Type 1 Diabetes (T1D) and Type 2 Diabetes mellitus (T2D). Of them, T1D is more uniform and accounts for about 10% of all patients, whereas T2D, which accounts for about 80-90% of all patients, is much more heterogeneous, but the extent of this diversity is not known. RHAPSODY will explore whether diverse sub-forms of T2D are characterized by different rates of progression from pre-diabetes to T2D and by differences in disease progression, e.g. time to insulin. Establishing a better patient stratification already at diagnosis of diabetes will support the design of novel strategies for precision therapy and prevention of diabetes and of more efficient clinical trials.

Work performed

Biomarker candidate selection

We have now obtained lipidomic analysis on a total of 2775 samples belonging to three T2D progression cohorts. Quantitative plasma peptide and protein data have been obtained from 1200 plasma samples. Polar metabolites data have been obtained from >5000 plasma samples from the same cohorts as well as from 268 plasma samples from pancreas surgery patients (partial pancreatectomy patients, PPP) for whom we also have diabetes-related clinical data and islet transcriptomic profiles. We have also obtained miRNAs quantification from 500 blood RNA samples from one diabetes progression cohort. Through various bioinformatic ranking analyses, including literature search, we are in the process of establishing a short list of biomarker candidates for the prediction of T2D progression.

Data federation and systems biology

We have completed the full harmonisation of data annotation from 10 cohorts from 5 different European countries, representing more than 50’000 individuals. Two additional cohorts have been identified and will be integrated in the federated dataset. The newly obtained omics data have been uploaded, they include c-peptide measurements, lipidomics, peptidomics, metabolomics, microRNA and genetics data from 400 SNPs for these cohorts. Analytical tools have been added to the database, including KNN (k nearest neighbour) imputation, Random forest ensemble-learning method, Similarity Network Fusion (SNF). New tutorials have been established to explain how to work with data and perform analyses using the Federated Database. We also established a biomarker prioritization matrix and a web-based prioritization tool to enable (i) to systematically evaluate biomarker candidates with relation to high quality and relevant external data sources and (ii) to place candidate biomarkers in the context of all RHAPSODY data generated and visualise results across multiple experiments.

Predictive biomarkers of glycaemic deterioration

Statistical tools have been implemented through the federated database to perform progression modelling. An online tutorial webinar focussing on the analysis of T2D progression cohorts data through the federated database has been organized. Diabetes progression modelling is now actively ongoing, including a K-means clustering approach. Analysis is being performed on the federated database; this also includes the various omics data obtained. Analysis will continue until BMK candidate lists are finalised, using in part the biomarker prioritization matrix.

Predictive biomarkers of beta cell dysfunction

Preclinical models have been studied to identify the link between plasma lipids, beta-cell dysfunction and gene expression modules, and the liver metabolic pathways that contribute to these plasma lipids biosynthesis. A specific link between plasma triglycerides and liver lipid metabolic pathways and beta-cell insulin secretion has been identified and is being validated by functional studies
Analysis of the clinical data of PPP patients revealed the same five subgroups previously described by Ahlqvist E et al., (Lancet, 2018). The pancreatic islets of these patients have been characterized by RNAseq and correlation between subgroup characteristics and islet gene expression modules is being identified. Aldolase B has now been recognized as a critical gene differentially expressed in T2D islets and negatively correlated with insulin secretion.

Predictive biomarkers of insulin target tissue dysfunction

We strive to identify circulating biomarkers, which are correlated with progression from pre-diabetes to T2D or rapid deterioration of T2D. We aim at identifying the tissues (liver, fat, muscle) and metabolic pathways, which produce plasma lipid biomarkers as these pathways may become new therapeutic targets. We have identified a liver lipid metabolic pathway, different from the above-mentioned one, that is linked to glucose intolerance. This pathway and its role in insulin actio

Final results

RHAPSODY’s ambition is to fully characterize novel biomarkers for pre-diabetes and the prediction of T2D development and deterioration as well as to validate them for clinical use and pharmacological developments. Biomarker identification, replication, and characterization towards the use in clinical and pharmacological applications will be guided by the requirement for their validation by the European Medical Agency and for coherence with cost-benefits assessment.

Website & more info

More info: http://www.imi-rhapsody.eu/.