Marc K. Hellerstein M.D., Ph.D.

Dr. Hellerstein is Professor of Human Nutrition at the University of California, Berkeley, where he occupies an Endowed Chair (Dr. Robert C. and Veronica Atkins Chair). He is also Professor of Endocrinology, Metabolism and Nutrition in the Department of Medicine at the University of California at San Francisco, where he ran the diabetes clinic at SF General Hospital for 25 years. Dr. Hellerstein’s medical training was at Yale Medical School and he completed a PhD at the Massachusetts Institute of Technology, in addition to medical training in Internal Medicine and Endocrinology and Metabolism.

Dr. Hellerstein's major research interest has been the measurement in vivo of metabolic fluxes through pathways critical to health and disease, as biomarkers for understanding metabolic control and its disorders, including applications in drug development and clinical diagnostics. This research has resulted in over 300 publications, 80 issued patents and participation on several editorial boards, including Science Translational Medicine. Dr. Hellerstein co-founded a medical diagnostics and drug development biotech company, KineMed, Inc., in 2001.

By combining powerful mass spectrometric technology with insights into the mathematical footprint of metabolic flux in complex networks, his group has quantified in humans many metabolic processes that could not previously be studied. Methodologic advances from the Hellerstein lab include Mass Isotopomer Distribution Analysis (MIDA), the “equation for polymerization biosynthesis”; heavy water labeling for protein synthesis, including Dynamic Proteomics for measuring flux rates of proteins across the proteome; cell proliferation and turnover rates by metabolic labeling of newly replicated DNA with heavy water or glucose; non-invasive probes of intracellular intermediary metabolic fluxes, or “virtual biopsies”, including hepatic fibrogenesis, muscle protein synthesis and brain myelination rates; and muscle mass from a spot urine sample.

This work directly addresses the major challenge of the next generation of biomedical research: translating our advanced understanding of molecular components (reductionist knowledge) into the ability to control and predict functional outcomes in vivo (integrated understanding), including humans. His work continues to look for ways that dynamic systems measurements can have a fundamental impact on basic biology and human health.