Modeling diabetes using gene editing and organoid technologies
The large majority of diabetes are caused by a a very large number of genetic variantsplus environmental factors. In contrast, SNP-associated as well as monogenic diabetes connects thedysfunctional insulin-secreting beta-cells with a single gene variant, thus can be viewed as a simpler“human knockout” condition in understanding. While patients' human islets are scarce resource, induced pluripotent stem cell(iPSC)-derived islets provide a species-, disease- andpatient-specific model that replicates β cell failure seen in patients, to further the understandingof the disease development.
Meetings
- Homozygous and heterozygous insulin mutations cause divergent clinical and iPSC-derived beta-cell phenotypes , Talk @ The 9th Meeting of SGGD, 2024 📍 Exeter, UK
- Discovery of a new treatment for a novel form of rare diabetes caused by an insulin gene mutation using patients , Talks @ The EASD 2023 Annual Meeting, The ISPAD 2023 Annual Meeting, 2023 📍 Hamburg, Germany & Rotterdam, the Netherland
- Bedside-inspired diabetes modeling: learn from monogenic diabetes to understand the pathogenic mechanisms of T1D , Invited Talk @ 19th IDS Congress, 2022 📍 Paris, France
Biomarkers in classifying and predicting diabetes
The classification and prediction of diabetes are essential for early diagnosis and effective management. Bearing the peripherally accessible nature, molecular and physiological biomarkers provide valuable insights into the mechanisms underlying disease heterogeneity and development, including beta-cell dysfunction, immune responses, and metabolic dysregulation. These findings highlight the potential of biomarkers to improve disease classification and enable precision medicine in clinical diabetes care.
Meetings
- Distinct secretion pattern of serum proinsulin in different types of diabetes , Poster @ 17th IDS Congress, 2020 📍 Beijing, China
