Stability During Processing and Storage
The stability of the nutrient or bioactive during processing and storage is another
aspect to consider when selecting and/or evaluating nutritional biomarkers. For
example, carotenoids are light sensitive, and as such, blood sampling and pro-
cessing should be conducted in a darkened room and phlebotomy tubes should be
covered with foil or amber covers to minimize light exposure. Alternately, stability
of ascorbic acid concentrations in blood is highly dependent on collection and
processing conditions including room temperature and humidity. Current recom-
mendations include collection in heparin tubes, immediate centrifugation, and
plasma acidification prior to storage at−80 °C (Karlsen et al. 2007 ). Importantly,
some nutrients and diet-derived compounds will denature over time even if stored at
the proper temperature. Examples of bioactives that show low tolerance to
long-term frozen storage are the anthocyanins (de Ancos et al. 2000 ). On the other
hand, phospholipid fatty acids have been shown to be stable for up to 10 years at
−80 °C (Matthan et al. 2010 ). Storage temperature also influences the stability of
nutrient measures over time. In a study evaluating storage temperature and folate
measurement, samples stored at−20 °C were deemed unreliable for measurement,
while those stored at−80 °C were stable over 12 months; B12 concentrations were
stable at both storage temperatures (Jansen et al. 2012 ). Standardized laboratory
procedures and methods for a wide range of nutrients are available through the
Centers for Disease Control and Prevention.
Advancements in Dietary Biomarkers
In recent years, expanded emphasis on the need for more reliable, valid, and
sophisticated biomarkers in nutrition research has led to innovative approaches and
methodological advances. Certainly, the re-emphasis on isotopes for quantification
of exposure—afield that was productive in relation to earlier work defining nutrient
requirements—has gained popularity. But even beyond stable isotope labeling, the
area of metabolomics has advanced our understanding of nutrient/dietary exposures
(Swann and Claus 2014 ). Metabolomics, which involves the measurement of all
metabolite concentrations, has been applied to assess disease risk in relation to a
comprehensive array of metabolites, whereas metabonomics is more specifictoa
systems biology approach that aims to assess metabolic response to biological,
environmental (diet), and genetic exposures (Nicholson and Lindon 2008 ).
Metabolomics requires the use of more sophisticated instrumentation such as
nuclear magnetic resonance (NMR) as well as higher level statistical modeling to
achieve greater precision in relation to food intake and true biological exposure and
bioactivity relative to disease risk. The end product of such biomarker approaches is
a metabolic phenotype that can be assigned at the individual or population sample
level to evaluate health risks and outcomes. Further, this metabolic phenotype can
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