Metformin, an FDA approved first-line drug for the treatment of type 2 diabetes, has known beneficial effects on glucose metabolism. Evidence from animal models and in vitro studies suggest that in addition to its effects on glucose metabolism, metformin may influence metabolic and cellular processes associated with the development of age-related conditions, such as inflammation, oxidative damage, diminished autophagy, cell senescence and apoptosis. As such, metformin is of particular interest in clinical translational research in aging since it may influence fundamental aging factors that underlie multiple age-related conditions. The investigators therefore propose a pilot study to examine the effect of metformin treatment on the biology of aging in humans. Namely, whether treatment with metformin will restore the gene expression profile of older adults with impaired glucose tolerance (IGT) to that of young healthy subjects.

Aging in humans is a well-established primary risk factor for many disabling diseases and conditions, among them diabetes, cardiovascular disease, Alzheimer's disease and cancer. In fact, the risk of death from these causes is dramatically accelerated (100-1000 fold) between the ages of 35 and 85 years. For this reason, there is a need for the development of new interventions to improve and maintain health into old age - to improve "healthspan".

Several mechanisms have been shown to delay the aging process, resulting in improved healthspan in animal models, including mammals. These include caloric restriction, alteration in GH/IGF1 pathways, as well as use of several drugs such as resveratrol (SIRT1 activator) and rapamycin (mTOR inhibitor). At Einstein, the investigators have been working to discover pathways associated with exceptional longevity. The investigators propose the study of drugs already in common clinical use (and FDA approved) for a possible alternative purpose -healthy aging. The investigators goal is to identify additional mechanisms involved in aging, the delay of aging and the prevention of age-related diseases. In this proposal, the investigators explore the possibility of a commonly used drug, metformin, to reverse relevant aspects of the physiology and biology of aging.

Metformin is an FDA approved drug in common use in the US since the 1990s. It is the first-line drug of choice for prevention and treatment of type 2 diabetes (T2DM). The effect of metformin on aging has been extensively studied, and has been associated with longevity in many rodent models. Metformin also extends the lifespan of nematodes, suggesting an evolutionarily conserved mechanism. A recent high impact study demonstrated that metformin reduces oxidative stress and inflammation and extends both lifespan and health span in a mouse model .

If indeed metformin is an "anti-aging" drug, its administration should be associated with less age-related disease in general, rather than the decreased incidence of a single age-related disease. This notion led investigators to further study whether anti-aging effects can be demonstrated in the type 2 diabetes population. Notably, in the United Kingdom Prospective Diabetes Study (UKPDS) metformin, compared with other anti-diabetes drugs, demonstrated a decreased risk of cardiovascular disease. This has been suggested in other studies and meta-analyses and remains an active area of research.

In addition, numerous epidemiologic studies have shown an association of metformin use with a decreased risk of cancer, as well as decreased cancer mortality. There is also evidence from studies performed both in-vitro and in-vivo of metformin's role in attenuating tumorigenesis. The mechanisms proposed relate to its effects on reducing insulin levels, improved insulin action, decreased IGF-1 signaling (central to mammalian longevity), as well as activation of AMP-kinase. In fact, metformin's potential protective effect against cancer has been gaining much attention, with over 100 ongoing studies registered on the Clinical Trials.gov website.

To characterize pathways associated with increased lifespan and healthspan, the investigators plan to compile a repository of muscle and adipose biopsy samples obtained from young healthy subjects and older adults before and after treatment with potential anti-aging drugs. RNA-Seq analysis will be used to identify a unique biological "fingerprint" for aging in these tissues by comparing changes in gene expression in older adults post-drug therapy to the profiles of young healthy subjects. This overall approach is supported by a grant from the Glenn Foundation for the Study of the Biology of Human Aging.

The investigators believe that if metformin changes the biology of aging in tissues to a younger profile, it supports the notion that this drug may have more widespread use - as an "anti-aging" drug.

Inclusion Criteria:

1. Men and women;
2. age >60 years with IGT based on 75g OGTT (fasting plasma glucose < 126 mg/dl, 2-hr glucose between 140 - 199 mg/dl);
3. this definition of IGT will include individuals with combined impaired fasting glucose (IFG) and IGT.

The investigators chose these inclusion criteria in order to study subjects who have evidence of impaired glucose regulation, but are not yet diabetic.

Exclusion Criteria:

1. Serious chronic or acute illness: cancer, clinically significant congestive heart failure, COPD, inflammatory conditions, serum creatinine > 1.4 mg/dl (female) or > 1.5 mg/dl (male), active liver disease, history of metabolic acidosis, poorly controlled hypertension, epilepsy, recent (within 3 months) CVD event (MI, PTCA, CABG, stroke); history of bariatric or other gastric surgery, cigarette smoking, binge alcohol use (>7 drinks in 24 hrs).
2. Treatment with drugs known to influence glucose metabolism (other diabetes medications, systemic glucocorticoids, pharmacologic doses of niacin)
3. Hypersensitivity to metformin or any component of the formulation

Adverse event data were collected during the study period of 14 weeks.

Limitations:

Crossover design may lead to a carryover effect that was not detected due to small sample size.

The sample size was small and certain genes that were differentially expressed may not have been detected.