Periodic Reporting for period 4 - PAINTBOX (Pancreatic islet dysfunction and type 2 diabetes – beyond the genome)
Periodo di rendicontazione: 2022-04-01 al 2023-04-30
I expect this novel interdisciplinary project to generate groundbreaking information that opens up new horizons for prediction, prevention and treatment of T2D and it will thereby help many patient with the disease and reduce health-related costs for society.
The overall objective is to find new mechanisms that contribute to the development of T2D as well as new biomarkers that predict the diease and potential new therapies.
Unpublished manuscripts
i) Genes with epigenetic alterations in human pancreatic islets impact mitochondrial function, insulin secretion, and type 2 diabetes. Tina Rönn1, Alexander Perfilyev1, Jones K. Ofori1, Anna Wendt2, Petr Volkov3, Sabrina Ruhrmann1, Lena Eliasson2, Karl Bacos1 and Charlotte Ling1 (ms ready to be resubmitted to Nature Communications)
Aim 2. Development of a mathematical platform for analysis of genome-wide human data: Here, we have utilized a Machine Learning approach for performing an integrative analysis of methylation, gene expression, genetic variation and phenotypic information in human pancreatic islets from 110 individuals, with approximately 30% being cases with type 2 diabetes. Charlotte Ling, Tina Rönn and Alexander Perfilyev have been involved in this part of the project.
Unpublished manuscripts
ii) Predicting Type 2 Diabetes via Machine Learning Integration of Multiple OMICs from Human Pancreatic Islets. Tina Rönn, Alexander Perfilyev, Nikolay Oskolkov# and Charlotte Ling# #equal contribution
Aim 4. Epigenetic mechanisms for prediction and treatment of T2D: We have studied blood-based epigenetic biomarkers for prediction of both type 2 diabetes and therapy and studied epigenetics drugs. We published several papers related to these findings, including identifying DNA methylation of specific sites in blood associated with future type 2 diabetes (9), associated with response to metformin (8), and subgroups of type 2 diabetes (13). We also identified methylation sites in cord blood associated with a lifestyle intervention in obese pregnant women and with gestational weight gain (10, 16). We have also identified inhibitors of epigenetic enzymes that impact insulin secretion and may be further developed as novel therapies for type 2 diabetes (2, 7). We have also developed epigenetic editing tools. Charlotte Ling, Tina Rönn, Sabrina Ruhrmann, Josefine Jönsson, Karl Bacos and Alexander Perfilyev have been involved in this part of the project.