Dr. Anat Yaskolka Meir

Dr. Anat Yaskolka Meir
Dr. Anat Yaskolka Meir
Zuckerman-CHE Israeli Woman Postdoctoral Scholars
2021-2022 Cohort
Department of Epidemiology

Anat Yaskolka Meir’s research has been conducted in the framework of large international research groups. The data for her Master’s in Public Health from Ben-Gurion University of the Negev came from a large randomized controlled trial examining the effect of lifestyle intervention on intermuscular adipose tissue and thigh muscle.

For her PhD, Dr. Yaskolka Meir expanded her research field from nutrition and epidemiology to clinical epigenetics. One large trial whose data she used compared how different dietary lifestyle intervention strategies (low-fat diet vs. Mediterranean low-carbohydrate diet) affected major fat deposits. One measurement was DNA methylation, assessed through blood samples taken at the beginning and the end of the intervention. Dr. Yaskolka Meir concluded that weight loss following the lifestyle intervention was associated with specific blood DNA methylation. The DNA methylation levels were also used to calculate a score called methylation age (mAge), which might serve as a biological marker for health. The other large trial examined how incremental amounts of a compound called polyphenols affect liver fat. The high-polyphenol Mediterranean diet, rich in green plant-based proteins and low in red and processed meat, might be an effective clinical tool for treating fatty liver.

Dr. Yaskolka Meir’s current research, in the Program in Genetic Epidemiology and Statistical Genetics in the Department of Epidemiology at Harvard T.H. Chan School of Public Health, focuses on human genetic variation, including DNA methylation and the calculated mAge score. For the mAge project, she uses several statistical models to assess immediate and long-term mAge associations with lifestyle interventions and clinical outcomes. She hopes that mAge as a biomarker could serve as an objective indicator for health status and risk of premature morbidity from cardiometabolic diseases. It could potentially predict individual responsiveness to weight loss interventions and help develop more successful personalized preventive and treatment strategies.