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PRECISION NUTRIGENOMICS VIA MECHANISM-ANCHORED BIG DATA SCIENCE: ANALYTICS FOR SINGLE-SUBJECT EPISTASIS AND PERSONAL GENOME X ENVIRONMENT INTERACTIONS

Yves A. Lussier

Abstract

With the advent of precision health, the view of healthy living is shifting from a population-based to a more individual one. While tailoring nutrition isn’t new, the convergence of Big Data Science and multiple ‘Omics have provided substantial evidence to the fact that one’s response to diet is determined by complex genome x environment interactions and genomic interactions. Indeed, at equal caloric intake, distinct mice strain grow fat while others under specific macronutrient distribution of the diet (standard mouse chow, Western, traditional Japanese, traditional Mediterranean, high-fat, and low carb ketogenic) do not. Simply stated: mammalian diet response is highly personal and involves genetic x sex interactions as well as gene x diet interactions.

While individualizing nutrition according to age, gender, exercise, ancestry, and endocrine/growth patterns isn’t new, precision nutrition seeks to incorporate genome x environment assays. However, conventional genomic studies are conducted using cohort-based statistics that are designed to discover average patterns rather than individual response.

Our group has been developing two novel approaches applicable for individualizing nutrigenomics:

(i) Single-subject epistasis: personal risks of metabolic conditions from genetic synergy and paradoxical antagony discovered using integrative and multi ’omics analyses of coding as well as non-coding polymorphisms. These results present the mitigating risks via environmental response of the metabolome.

(ii) Individualized transcriptome-level stimulation assays paired with single subject analytics. These results democratize the cost of ‘omics, as the summative effect of one’s unique 3.5 billion base-pairs interacting with a well-designed metabolism stimulation assay can be read through a few dozen transcript by affordable RT-PCR.





DOI: http://dx.doi.org/10.14748/ssp.v4i1.3932

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Yves A. Lussier

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