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ICP-MS/MS-Based Ionomics: A Validated Methodology to Investigate the Biological Variability of the Human Ionome
journal contribution
posted on 2017-04-06, 00:00 authored by Tobias Konz, Eugenia Migliavacca, Loïc Dayon, Gene Bowman, Aikaterini Oikonomidi, Julius Popp, Serge RezziWe
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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Keywords
bone remodellingserum samplesvalidation procedureindividualmetabolomic data mining approachzinc ratioValidated Methodologycomponent analysisgender-specific compartmentalizationionome profilesquadrupole mass spectrometryHuman Ionomecalibration curvesmicronutrient statusmeasurement uncertainty29 elementsmethodologyICP-MSBiological Variabilityiron concentration
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