Wetenschappelijk onderzoeker/Docent (UHD)

Dr. L.M. (Leen) ‘t Hart

Specialismen:
Moleculaire Epidemiologie van type 2 Diabetes
Even voorstellen
I was trained in biotechnology (1991), and started my academic career at Leiden University working on a project regarding plant genetics. In 1993 I joined the group of Prof JA Maassen at Leiden University Medical Center (LUMC) working on genetic aspects of diabetes and especially mitochondrial diabetes. In 2002 I obtained my PhD on a thesis titled “Genetic analysis of type 2 diabetes, insulin resistance and insulin secretion” with Profs JA Maassen (LUMC) en RJ Heine (VUmc) as promotors. Currently I am appointed as associate professor at the department of Cell and Chemical Biology working on molecular epidemiology of type 2 diabetes. I am also affiliated with the Biomedical Data Sciences department and the department of Epidemiology and Data Science at the Amsterdam UMC.
Besides my research activities I am also involved in teaching and coordinator of one of the first year courses for medical students at the LUMC (G1CM).
Wetenschappelijk onderzoek
I am the lead scientist of the diabetes ‘omics’ research for the Hoorn studies and the Hoorn Diabetes Care System cohort. My group has performed extensive research in the field of (pharmaco-)genetics of type 2 diabetes. Furthermore, I have a strong interest in functional studies to further elucidate functional mechanisms behind the observed associations.

Using data from these cohorts we for instance showed that several gene variants impact on response to diabetes drugs. In addition my team has identified several proteins and metabolites in blood that predict incident type 2 diabetes or diabetes progression. During the last few years we expanded our research into other omics, exploring the potential of genomics, metabolomics, proteomics and transcriptomics in stratification of patients according their risk for rapid progression of diabetes and development of diabetic complications using a combination of traditional statistical methods and modern techniques such as machine learning.
Our worked is embedded within the LUMC Medical Genomics and Lifecourse themes for innovation.

Publicaties