Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10-5), BMI (p=0.01), and blood carotenoid levels (p=1x10-5)-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

IGF-I shares structural homology and in vitro metabolic activity with insulin. Laboratory models suggest that IGF-I and its binding proteins IGFBP-1 and IGFBP-2 have potentially beneficial effects on diabetes risk, whereas IGFBP-3 may have adverse effects. We therefore conducted a prospective nested case-control investigation of incident diabetes (n = 742 case subjects matched 1:1 to control subjects) and its associations with IGF-axis protein levels in the Nurses’ Health Study, a cohort of middle-aged women. The median time to diabetes was 9 years. Statistical analyses were adjusted for multiple risk factors, including insulin and C-reactive protein. Diabetes risk was fivefold lower among women with baseline IGFBP-2 levels in the top versus bottom quintile (odds ratio [OR]_q5–q1 = 0.17 [95% CI 0.08–0.35]; P trend < 0.0001) and was also negatively associated with IGFBP-1 levels (OR_q5–q1 = 0.37 [0.18–0.73]; P trend = 0.0009). IGFBP-3 was positively associated with diabetes (OR_q5–q1 = 2.05 [1.20–3.51]; P trend = 0.002). Diabetes was not associated with total IGF-I levels, but free IGF-I and diabetes had a significant association that varied (P interaction = 0.003) by insulin levels above the median (OR_q5–q1 = 0.48 [0.26–0.90]; P trend = 0.0001) versus below the median (OR_q5–q1 = 2.52 [1.05–6.06]; P trend < 0.05). Thus, this prospective study found strong associations of incident diabetes with baseline levels of three IGFBPs and free IGF-I, consistent with hypotheses that the IGF axis might influence diabetes risk.

Adiposity is an established risk factor for postmenopausal breast cancer. Recent data suggest that high insulin levels in overweight women may play a major role in this relationship, due to insulin's mitogenic/antiapoptotic activity. However, whether overweight women who are metabolically healthy (i.e., normal insulin sensitivity) have elevated risk of breast cancer is unknown. We investigated whether overweight women with normal insulin sensitivity [i.e., homeostasis model assessment of insulin resistance (HOMA-IR) index, or fasting insulin level, within the lowest quartile (q1)] have increased breast cancer risk. Subjects were incident breast cancer cases (N = 497) and a subcohort (N = 2,830) of Women's Health Initiative (WHI) participants with available fasting insulin and glucose levels. In multivariate Cox models, metabolically healthy overweight women, defined using HOMA-IR, were not at elevated risk of breast cancer compared with metabolically healthy normal weight women [HR_HOMA-IR, 0.96; 95% confidence interval (CI), 0.64–1.42]. In contrast, the risk among women with high (q3-4) HOMA-IRs was elevated whether they were overweight (HR_HOMA-IR, 1.76; 95% CI, 1.19-2.60) or normal weight (HR_HOMA-IR, 1.80; 95% CI, 0.88–3.70). Similarly, using fasting insulin to define metabolic health, metabolically unhealthy women (insulin q3-4) were at higher risk of breast cancer regardless of whether they were normal weight (HR_insulin, 2.06; 95% CI, 1.01–4.22) or overweight (HR_insulin, 2.01; 95% CI, 1.35–2.99), whereas metabolically healthy overweight women did not have significantly increased risk of breast cancer (HR_insulin, 0.96; 95% CI, 0.64–1.42) relative to metabolically healthy normal weight women. Metabolic health (e.g., HOMA-IR or fasting insulin) may be more biologically relevant and more useful for breast cancer risk stratification than adiposity per se. Cancer Res; 75(2); 270–4. ©2014 AACR.