J Clin Invest 106(2): 171-176

Cellular mechanisms of insulin resistance

Howard Hughes Medical Institute, Departments of Internal Medicine and Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, Connecticut, USA

Address correspondence to: Gerald I. Shulman, Howard Hughes Medical Institute, Yale University School of Medicine, 254C Boyer Center for Molecular Medicine, 295 Congress Avenue, New Haven, Connecticut 06510, USA. Phone: (203) 785-5447; Fax: (203) 737-4059; E-mail: ude.elay@namluhs.dlareg.

It is estimated that by the year 2020 there will be approximately 250 million people affected by type 2 diabetes mellitus worldwide (1). Although the primary factors causing this disease are unknown, it is clear that insulin resistance plays a major role in its development. Evidence for this comes from (a) the presence of insulin resistance 10–20 years before the onset of the disease (2, 3); (b) cross-sectional studies demonstrating that insulin resistance is a consistent finding in patients with type 2 diabetes (3–6); and (c) prospective studies demonstrating that insulin resistance is the best predictor of whether or not an individual will later become diabetic (2, 3). Here, I focus on some recent advances in our understanding of human insulin resistance that have been made using nuclear magnetic resonance spectroscopy (NMR). This technique takes advantage of the spin properties of the nuclei of certain isotopes, such as ^H,^{C, and}^{P, which endow the isotopes with a magnetic component that can be used to measure the concentration of intracellular metabolites noninvasively and to assess biochemical differences between normal and diabetic subjects. Drawing on NMR studies from my laboratory and others, I first consider the control of glucose phosphorylation and transport in regulating muscle responses to insulin. I then turn to the effects of fatty acids on insulin responses, showing that commonly accepted models that attempt to explain the association of insulin resistance and obesity are incompatible with recent findings. Finally, I propose an alternative model that appears to fit these and other available data.}

Acknowledgments

Space limitations preclude this from being a comprehensive review, and this unfortunately limits appropriate recognition of many of my colleagues worldwide who have contributed immeasurably to the development of this field. However, I specifically wish to thank Kitt Petersen, Gary Cline, and Douglas Rothman for their scientific contributions, advice, and editorial assistance, and Dennis McGarry for many stimulating discussions. The studies summarized in this review were supported in part by grants from the NIH (R01 DK-49230, R01 DK-40936, and P30 DK-45735). G.I. Shulman is an investigator of the Howard Hughes Medical Institute.

Acknowledgments

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