Metabolic detoxification (detox)—or biotransformation—is a physiological function that removes toxic substances from our body. Genetic variability and dietary factors may affect the function of detox enzymes, thus impacting the body’s sensitivity to toxic substances of endogenous and exogenous origin. From a genetic perspective, most of the current knowledge relies on observational studies in humans or experimental models in vivo and in vitro, with very limited proof of causality and clinical value. This review provides health practitioners with a list of single nucleotide polymorphisms (SNPs) located within genes involved in Phase I and Phase II detoxification reactions, for which evidence of clinical utility does exist. We have selected these SNPs based on their association with interindividual variability of detox metabolism in response to certain nutrients in the context of human clinical trials. In order to facilitate clinical interpretation and usage of these SNPs, we provide, for each of them, a strength of evidence score based on recent guidelines for genotype-based dietary advice. We also present the association of these SNPs with functional biomarkers of detox metabolism in a pragmatic clinical trial, the LIFEHOUSE study.

With the advent of "-omics" technologies, there has been an explosion of data generation in the field of toxicology, as well as in many others. As new candidate biomarkers of toxicity are being regularly discovered, the next challenge is to validate these observations in a targeted manner. Traditionally, these validation experiments have been conducted using antibody-based technologies such as Western blotting, ELISA, and immunohistochemistry. However, this often produces a significant bottleneck as the time, cost, and development of successful antibodies are often far outpaced by the generation of targets of interest. In response to this, recently there have been several developments in the use of triple quadrupole (QQQ) mass spectrometry (MS) as a platform to provide quantification of proteins by multiple reaction monitoring (MRM). This technology does not require antibodies; it is typically less expensive and quicker to develop, and has the opportunity for more accessible multiplexing. The speed of these experiments combined with their flexibility and ability to multiplex assays makes the technique a valuable strategy to validate biomarker discovery.

A retrospective chart review analyzed the effect of customized nutrition on the incidence of pregnancy-induced hypertension (PIH), gestational diabetes (GDM), and small- and large-for-gestational-age (SGA, LGA) neonates, examining consecutive deliveries between January 1, 2011, and Decem ber 31, 2012, at a low-risk community hospital. The population was divided into 3 groups: (1) study group (SG), (2) private practice (PP), and (3) community healthcare clinic (CHCC). All groups received standard perinatal management, but additionally the study group was analyzed for serum zinc, carnitine, total 25-hydroxy cholecalciferol (25 OH-D), methylene tetrahydrofolate reductase, and catechol-O-methyl transferase polymorphisms in the first trimester prior to intervention, with subsequent second trimester and postpartum assessment of zinc, carnitine, and 25 OH-D after intervention. Intervention consisted of trimesterby-trimester nutrition and lifestyle education, supplementation of L-methyl folate, magnesium, essential fatty acids, and probiotics for all SG patients, with targeted supplementation of zinc, carnitine, and 25 OH-D. Because of small case occurrence rates of individual conditions in the study group, unreportable reductions were found, except GDM (SG vs CHCC, P value .046 with 95.38% confidence interval [CI]), and PIH (SG vs PP, P value .0505 with 94.95% CIl). The aggregated occurrence rate of the four conditions, however, was significantly lower in the study population than in either comparison population (PP P value .0154 with 98.46% CI, and CHCC P value .0265 with 97.35% CI). Customized nutritional intervention appears to have significantly reduced adverse perinatal outcomes. Prospective study within larger, at-risk populations is needed to determine whether customized nutrition improves conditions individually.

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