The menstrual cycle is an essential life rhythm governed by interacting levels of progesterone, estradiol, follicular stimulating, and luteinizing hormones. To study metabolic changes, biofluids were collected at four timepoints in the menstrual cycle from 34 healthy, premenopausal women. Serum hormones, urinary luteinizing hormone and self-reported menstrual cycle timing were used for a 5-phase cycle classification. Plasma and urine were analyzed using LC-MS and GC-MS for metabolomics and lipidomics; serum for clinical chemistries; and plasma for B vitamins using HPLC-FLD. Of 397 metabolites and micronutrients tested, 208 were significantly (p < 0.05) changed and 71 reached the FDR 0.20 threshold showing rhythmicity in neurotransmitter precursors, glutathione metabolism, the urea cycle, 4-pyridoxic acid, and 25-OH vitamin D. In total, 39 amino acids and derivatives and 18 lipid species decreased (FDR < 0.20) in the luteal phase, possibly indicative of an anabolic state during the progesterone peak and recovery during menstruation and the follicular phase. The reduced metabolite levels observed may represent a time of vulnerability to hormone related health issues such as PMS and PMDD, in the setting of a healthy, rhythmic state. These results provide a foundation for further research on cyclic differences in nutrient-related metabolites and may form the basis of novel nutrition strategies for women.

Ferritin, an iron storage protein, is a sensitive clinical biomarker for iron metabolic disorders. It is mainly accumulated in the liver hepatocytes and is present in human plasma at trace levels (picomolar or nanograms per milliliter). Therefore, highly sensitive analytical methods are required to perform ferritin quantification in plasma with high precision and accuracy. For this purpose, we present a mass spectrometry-based analytical strategy (inductively coupled plasma-mass spectrometry, ICP-MS) combined with antibody labeling in a sandwich assay format for ferritin determination. The developed methodology involves two ferritin monoclonal antibodies, one of them biotinylated and the other one labeled with a ruthenium chelate [Ru(bpy)3](2+). The complex formed in solution between ferritin and the two antibodies is then captured using streptavidin-coated magnetic microparticles and directly introduced into ICP-MS for Ru monitoring. Since the Ru complex also allows one to obtain electrogenerated chemiluminescence (ECL), the combination of both sets of data (ICP-MS and ECL) will permit the establishment of the ferritin:Ru stoichiometry. This serves as a basis for further quantification studies using flow injection analysis with isotopically enriched (99)Ru as a carrier with ICP-MS detection. Such strategy permits absolute ferritin determination at a picomolar level with good precision (below 5%) and accuracy (85-109% recovery in the existing ferritin reference material, NIBSC code 94/572). Furthermore, the development of a new strategy to address ferritin:iron-ferritin ratios by ICP-MS opens the door also to address the potential of such ratios as a new clinical biomarker for Fe metabolic disorders.

We here describe the development, validation and application of a quantitative methodology for the simultaneous determination of 29 elements in human serum using state-of-the-art inductively coupled plasma triple quadrupole mass spectrometry (ICP-MS/MS). This new methodology offers high-throughput elemental profiling using simple dilution of minimal quantity of serum samples. We report the outcomes of the validation procedure including limits of detection/quantification, linearity of calibration curves, precision, recovery and measurement uncertainty. ICP-MS/MS-based ionomics was used to analyze human serum of 120 older adults. Following a metabolomic data mining approach, the generated ionome profiles were subjected to principal component analysis revealing gender and age-specific differences. The ionome of female individuals was marked by higher levels of calcium, phosphorus, copper and copper to zinc ratio, while iron concentration was lower with respect to male subjects. Age was associated with lower concentrations of zinc. These findings were complemented with additional readouts to interpret micronutrient status including ceruloplasmin, ferritin and inorganic phosphate. Our data supports a gender-specific compartmentalization of the ionome that may reflect different bone remodelling in female individuals. Our ICP-MS/MS methodology enriches the panel of validated "Omics" approaches to study molecular relationships between the exposome and the ionome in relation with nutrition and health.

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Hepcidin-25 is a peptide-hormone that has been proposed as the key biomarker for the diagnosis and monitoring of iron disorders. Structurally, hepcidin-25 is a S-rich peptide (with 8 cysteines and 1 methionine) that contains a metal binding motif in the N-terminus. That domain binds preferably Cu(II) ion forming a stable complex. Such selective binding can be used as mean to determine hepcidin-25 in biological fluids by highly sensitive Cu measurement. Thus, we use liquid chromatography coupled to inductively coupled plasma mass spectrometry (LC-ICP-MS) to perform hepcidin-25 determination via Cu detection. For this purpose, the incubation conditions were optimized to address the complex formation and stability by electrospray-MS (ESI-q-TOF). It was found that Cu:hepcidin-25 complex is stable under physiological conditions and shows an equimolar stoichiometry (1:1). The collisional induced dissociation (CID) experiments confirmed the specific binding of Cu to the N-terminal motif. For Cu quantification, two isotope dilution strategies have been developed. The first one, including postcolumn addition of a (65)Cu spike and the second, by synthesizing the labeled (65)Cu:hepcidin-25 complex as tracer (species-specific). Both methods have been optimized and critically compared in real samples. The determination of hepcidin-25 in different serum samples from healthy individuals based on Cu monitoring showed a mean value of 21.6 ng mL(-1) which is in good agreement to previously published data.