Aspirin-associated iron loss as an anticancer mechanism

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.

Iron Status and Associated Factors among Canadian Women: Results from the Canadian Health Measures Survey

BACKGROUND

Iron deficiency and overload may negatively impact women's health. There has been limited assessment of iron status and its associated factors among Canadian women.

OBJECTIVES

This study investigated associations of various sociodemographic, lifestyle, medication, and dietary factors with body iron stores among pre- and postmenopausal women in Canada.

METHODS

Analyses were conducted using cross-sectional, nationally representative survey and biomarker data from women aged 20-79 y (n = 6362) in the Canadian Health Measures Survey (2009-2017). Body iron stores were assessed by measuring serum concentrations of ferritin (SF). Information on potential correlates was collected during an in-home interview. Multivariable linear regression analyses were performed to evaluate associations with SF concentration, and logistic regression was used to estimate associations with iron deficiency (SF <15 μg/L) or elevated iron stores (SF >150 μg/L).

RESULTS

Geometric mean SF concentrations were significantly higher in postmenopausal than in premenopausal women (73.2 versus 33.8 μg/L; P < 0.001). The prevalence of iron deficiency among pre- and postmenopausal women was 16.0% and 4.0%, respectively, whereas that of elevated iron stores was 2.7% and 21.0%, respectively. After simultaneous adjustment for multiple factors, including high-sensitivity CRP (inflammation marker), we found that age, East/Southeast Asian (versus White) race/ethnicity, alcohol, and red meat consumption were positively associated with SF concentration among pre- and postmenopausal women. In addition, aspirin use and dairy consumption were inversely associated with SF concentration among postmenopausal women only. Similar patterns were observed for associations with elevated iron stores among postmenopausal women, whereas higher grain consumption was associated with an increased prevalence of iron deficiency among premenopausal women.

CONCLUSIONS

Sociodemographic, lifestyle, medication, and dietary factors are correlated with iron status determined by SF concentration among Canadian women. The findings may have implications for intervention strategies aimed at optimizing body iron stores in pre- and postmenopausal women.

Iron: an underrated factor in aging

Iron is an essential element for virtually all living organisms, but its reactivity also makes it potentially harmful. Iron accumulates with aging, and is associated with many age-related diseases; it also shortens the lifespans of several model organisms. Blocking iron absorption through drugs or natural products extends lifespan. Many life-extending interventions, such as rapamycin, calorie restriction, and old plasma dilution can be explained by the effects they have on iron absorption, excretion, and metabolism. Control of body iron stores so that they remain in a low normal range may be an important, lifespan- and healthspan-extending intervention.

A prospective cohort examination of haematological parameters in relation to cancer death and incidence: the Busselton Health Study

BACKGROUND

Cancer risk is associated with serum iron levels. The aim of this study was to evaluate whether haematological parameters reflect serum iron levels and may also be associated with cancer risk.

METHODS

We studied 1564 men and 1769 women who were enrolled in the Busselton Health Study, Western Australia. Haematological parameters evaluated included haemoglobin (Hb), mean cell volume (MCV), mean cell haemoglobin (MCH) and mean cell haemoglobin concentration (MCHC) and red cell distribution width (RCDW). Statistical analyses included t-tests for quantitative variables, chi-square tests for categorical variables and Cox proportional hazards regression modelling for cancer incidence and death.

RESULTS

There was marginal evidence of an association between MCV (as a continuous variable) and non-skin cancer incidence in women (HR 1.15, 95% CI 1.013, 1.302; p = 0.030) but the hazard ratio was attenuated to non-significance after adjustment for serum ferritin (SF), iron and transferrin saturation (TS) (HR 1.11, 95% CI 0.972, 1.264; p = 0.126). There was strong evidence of an association between MCHC and prostate cancer incidence in men; the estimated hazard ratio for an increase of one SD (0.5) in MCHC was 1.27 (95% CI 1.064, 1.507; p = 0.008). These results remained significant after further adjustment for SF and iron; the estimated hazard ratio for an increase of one SD (0.5) in MCHC was 1.25 (p = 0.014, 95% CI 1.05 to 1.48).

CONCLUSIONS

The MCHC and MCV were associated with cancer incidence in a Western Australian population, although only MCHC remained associated with prostate cancer after adjusting with serum iron and TS (circulating iron) and SF (storage iron). Haematological parameters are thus of limited utility in population profiling for future cancer risk.

Involvement of endogenous salicylic acid in iron-deficiency responses in Arabidopsis

Several phytohormones have been demonstrated to be involved in iron (Fe) homeostasis. We took advantage of a salicylic acid (SA) biosynthesis defective mutant phytoalexin deficient 4 (pad4: T-DNA Salk_089936) to explore the possible effects of endogenous SA on the morphological and physiological responses to Fe deprivation. The morphological and physiological analysis was carried out between Col-0 and the pad4 mutant. Under an Fe-deficiency treatment, Col-0 showed more severe leaf chlorosis and root growth inhibition compared with the pad4 mutant. The soluble Fe concentrations were significantly higher in pad4 than in Col-0 under the Fe-deficiency treatment. Fe deficiency significantly induced SA accumulation in Col-0 and the loss-of-function of PAD4 blocked this process. The requirement of endogenous SA accumulation for Fe-deficiency responses was confirmed using a series of SA biosynthetic mutants and transgenic lines. Furthermore, a comparative RNA sequencing analysis of the whole seedling transcriptomes between Col-0 and the pad4 mutant was also performed. Based on the transcriptome data, the expression levels of many auxin- and ethylene-response genes were altered in pad4 compared with Col-0. Fe deficiency increases SA contents which elevates auxin and ethylene signalling, thereby activating Fe translocation via the bHLH38/39-mediated transcriptional regulation of downstream Fe genes.