Genomics, Diabetes and Endocrinology
Intro: Diabetes results from a collision between a genetic predisposition and an affluent environment, and we need a more systematic approach to learn how this confrontation leads to the disease. Also, the current classification of diabetes into two main forms is imprecise and poor in predicting disease outcome. A refined diabetes classification could provide a powerful tool to implement individualized care from diagnosis in the same way as a genetic diagnosis of monogenic forms of diabetes guides clinicians to optimal treatment.
Goals: Dissect the genetic and metabolic complexity of diabetes and provide a refined diabetes classification that can pave the way for precision medicine in diabetes and development of a decision tool (road map) for the diabetic patients.
Impact: Understanding the genetic and metabolic complexity of diabetes could help in identifying novel drug targets. A new classification of diabetes may pave the way for early intensified treatment and thereby possibly prevent late diabetic complications ascribed to the “metabolic memory”. It may also help the pharma industry to better stratify patients for drug trials and thereby reduce cost for development of new drugs.
- The first comprehensive transcriptomic maps of human pancreatic islets (Taneera et al 2012, Fadista et al 2014)
- Identification of a rare variant in the SLC30A8 gene (encoding for Zink transporter T8) protecting from diabetes and thereby a potential new target for antidiabetic therapy (Flannick 2014).
- Translational studies on the role of genetic variants in the MTRN1B gene in determining response to melatonbin treatment (Tuomi 2016).
- Demonstration that glucose can induce expression of pro-inflammatory genes in kidney and thereby predispose to kidney disease by influencing epigenetic mechanisms ,i.e. histone marks (DeMarinis 2016)
- Demonstration that some genes do not exert the same effect when inherited from the mother as inherited from the father, so called Parent-of-Origin effects (Prasad 2016).
- A novel fine-tuned classification of diabetes with prognostic value representing an important step towards precision medicine in diabetes (Ahlqvist 2018).