Literature DB >> 26785082

Precision Nutrition 4.0: A Big Data and Ethics Foresight Analysis--Convergence of Agrigenomics, Nutrigenomics, Nutriproteomics, and Nutrimetabolomics.

Vural Özdemir1,2,3, Eugene Kolker3,4,5,6.   

Abstract

Nutrition is central to sustenance of good health, not to mention its role as a cultural object that brings together or draws lines among societies. Undoubtedly, understanding the future paths of nutrition science in the current era of Big Data remains firmly on science, technology, and innovation strategy agendas around the world. Nutrigenomics, the confluence of nutrition science with genomics, brought about a new focus on and legitimacy for "variability science" (i.e., the study of mechanisms of person-to-person and population differences in response to food, and the ways in which food variably impacts the host, for example, nutrient-related disease outcomes). Societal expectations, both public and private, and claims over genomics-guided and individually-tailored precision diets continue to proliferate. While the prospects of nutrition science, and nutrigenomics in particular, are established, there is a need to integrate the efforts in four Big Data domains that are naturally allied--agrigenomics, nutrigenomics, nutriproteomics, and nutrimetabolomics--that address complementary variability questions pertaining to individual differences in response to food-related environmental exposures. The joint use of these four omics knowledge domains, coined as Precision Nutrition 4.0 here, has sadly not been realized to date, but the potentials for such integrated knowledge innovation are enormous. Future personalized nutrition practices would benefit from a seamless planning of life sciences funding, research, and practice agendas from "farm to clinic to supermarket to society," and from "genome to proteome to metabolome." Hence, this innovation foresight analysis explains the already existing potentials waiting to be realized, and suggests ways forward for innovation in both technology and ethics foresight frames on precision nutrition. We propose the creation of a new Precision Nutrition Evidence Barometer for periodic, independent, and ongoing retrieval, screening, and aggregation of the relevant life sciences data. For innovation in Big Data ethics oversight, we suggest "nested governance" wherein the processes of knowledge production are made transparent in the continuum from life sciences and social sciences to humanities, and where each innovation actor reports to another accountability and transparency layer: scientists to ethicists, and ethicists to scholars in the emerging field of ethics-of-ethics. Such nested innovation ecosystems offer safety against innovation blind spots, calibrate visible/invisible power differences in the cultures of science or ethics, and ultimately, reducing the risk of "paper values"--what people say--and "real values"--what innovation actors actually do. We are optimistic that the convergence of nutrigenomics with nutriproteomics, nutrimetabolomics, and agrigenomics can build a robust, sustainable, and trustworthy precision nutrition 4.0 agenda, as articulated in this Big Data and ethics foresight analysis.

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Year:  2016        PMID: 26785082     DOI: 10.1089/omi.2015.0193

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  5 in total

Review 1.  Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome.

Authors:  Juan de Toro-Martín; Benoit J Arsenault; Jean-Pierre Després; Marie-Claude Vohl
Journal:  Nutrients       Date:  2017-08-22       Impact factor: 5.717

Review 2.  Bioactive Nutrients and Nutrigenomics in Age-Related Diseases.

Authors:  Tania Rescigno; Luigina Micolucci; Mario F Tecce; Anna Capasso
Journal:  Molecules       Date:  2017-01-08       Impact factor: 4.411

Review 3.  Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.

Authors:  Akshay Shankar; Krishna Kant Sharma
Journal:  Appl Microbiol Biotechnol       Date:  2022-05-12       Impact factor: 5.560

4.  Differential Proteomics Analysis Unraveled Mechanisms of Arma chinensis Responding to Improved Artificial Diet.

Authors:  Deyu Zou; Thomas A Coudron; Huihui Wu; Lisheng Zhang; Mengqing Wang; Weihong Xu; Jingyang Xu; Liuxiao Song; Xuezhuang Xiao
Journal:  Insects       Date:  2022-07-02       Impact factor: 3.139

5.  Innovation Management? Orienting Sepsis R&D and Technology Transfer Towards Stratified Medicine.

Authors:  Vural Özdemir; Nezih Hekim
Journal:  EBioMedicine       Date:  2016-04-10       Impact factor: 8.143

  5 in total

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