Toenail and serum levels as biomarkers of iron status in pre- and postmenopausal women: correlations and stability over eight-year follow-up.

Iron status is often assessed in epidemiologic studies, and toenails offer a convenient alternative to serum because of ease of collection, transport, and storage, and the potential to reflect a longer exposure window. Very few studies have examined the correlation between serum and toenail levels for trace metals. Our aim was to compare iron measures using serum and toenails on both a cross-sectional and longitudinal basis. Using a subset of the US-wide prospective Sister Study cohort, we compared toenail iron measures to serum concentrations for iron, ferritin and percent transferrin saturation. Among 146 women who donated both blood and toenails at baseline, a subsample (59%, n = 86) provided specimens about 8 years later. Cross-sectional analyses included nonparametric Spearman's rank correlations between toenail and serum biomarker levels. We assessed within-woman maintenance of rank across time for the toenail and serum measures and fit mixed effects models to measure change across time in relation to change in menopause status. Spearman correlations at baseline (follow-up) were 0.08 (0.09) for serum iron, 0.08 (0.07) for transferrin saturation, and - 0.09 (- 0.17) for ferritin. The within-woman Spearman correlation for toenail iron between the two time points was higher (0.47, 95% CI 0.30, 0.64) than for serum iron (0.30, 95% CI 0.09, 0.51) and transferrin saturation (0.34, 95% CI 0.15, 0.54), but lower than that for ferritin (0.58, 95% CI 0.43, 0.73). Serum ferritin increased over time while nail iron decreased over time for women who experienced menopause during the 8-years interval. Based on cross-sectional and repeated assessments, our evidence does not support an association between serum biomarkers and toenail iron levels. Toenail iron concentrations did appear to be moderately stable over time but cannot be taken as a proxy for serum iron biomarkers and they may reflect physiologically distinct fates for iron.

Development and validation of a prediction model for iron status in a large U.S. cohort of women.

Serum iron levels can be important contributors to health outcomes, but it is not often feasible to rely on blood-based measures for a large epidemiologic study. Predictive models that use questionnaire-based factors such as diet, supplement use, recency of blood donation, and medical conditions could potentially provide a noninvasive alternative for studying health effects associated with iron status. We hypothesized that a model based on questionnaire data could predict blood-based measures of iron status biomarkers. Using iron (mcg/dL), ferritin (mcg/dL), and transferrin saturation (%) based on blood collected at study entry, in a subsample from the U.S.-wide Sister Study (n = 3171), we developed and validated a prediction model for iron with multivariable linear regression models. Model performance based on these cross-sectional data was weak, with R2 less than 0.10 for serum iron and transferrin saturation, but better for ferritin, with an R2 of 0.13 in premenopausal women and 0.19 in postmenopausal women. When menopause was included in the predictive model for the sample, the R2 was 0.31 for ferritin. Internal validation of the estimates indicated some optimism present in the observed prediction model, implying there would be worse performance when applied to new samples from the same population. Serum iron status is hard to assess based only on questionnaire data. Reducing measurement error in both the exposure and outcome may improve the prediction model performance, but environmental heterogeneity, temporal variation, and genetic heterogeneity in absorption and storage may contribute substantially to iron status.

Association Between Serum Iron Biomarkers and Breast Cancer.

BACKGROUND: Iron is both essential to life and potentially toxic at higher levels. Epidemiologic studies of iron and breast cancer are sparse, with substantial heterogeneity found in a recent meta-analysis. Evidence based on a comprehensive set of iron biomarkers and a large sample size could help clarify relationships between iron body stores and breast cancer risk. METHODS: A case-cohort sample of 6,008 women, including 3,011 incident cases, has been followed for a median of 7.9 years. We estimated breast cancer HRs with Cox models, including age as the primary time scale and including in turn iron, ferritin, percent transferrin saturation, and their first principal component (PC) both as categorical (quartiles) and continuous measures. RESULTS: Adjusted HRs for the highest versus lowest quartiles of iron, ferritin, and transferrin saturation (95% confidence interval) were 1.06 (0.90-1.25), 1.03 (0.87-1.23), and 0.94 (0.80-1.12), respectively, and 1.06 (0.90-1.25) for the first principal component (PC). Associations were similar when follow-up time was restricted to ≤4 or >2 years. Post hoc analyses suggested low iron stores were associated with reduced breast cancer risk, in both pre- and postmenopause and the obese. CONCLUSIONS: A study with one of the largest sample sizes to date and with all three measures of circulating iron, ferritin, and transferrin saturation does not support a strong association between elevated iron stores and breast cancer risk. Further investigation of low iron may be warranted. IMPACT: These results do not support a strong association between iron overload and breast cancer incidence.