Session/Event: Precision Nutrition in the Age of 'Omics' (Oral 29)

(OR29-06-22) A Bioinformatic Rational Gene Targeting Approach to Treating Pathologies With Healthy Diet

On Demand

Presenting Author(s)

Dana R. Crawford, PhD

Associate Professor
Albany Medical College
Albany, New York, United States

Disclosure: Disclosure(s): No relevant financial relationship(s) with ineligible companies to disclose.

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Co-Author(s)

TB

Tamia Brefo

Rensselaer Polytechnic Institute
JC

Jeffrey Chai

Rensselaer Polytechnic Institute
JC

Jessica Coco

Rensselaer Polytechnic Institute
JC

Jessica Colley

Rensselaer Polytechnic Institute
JE

John Erickson

Rensselaer Polytechnic Institute
MF

Morgan Ford

Rensselaer Polytechnic Institute
SR

Shanthni Ravindrababu

Rensselaer Polytechnic Institute
NR

Natasha Rosa

Rensselaer Polytechnic Institute
VS

Veda Sripada

Albany Medical College
DX

Dorothy Xu

Rensselaer Polytechnic Institute
KB

Kristin Bennett

Rensselaer Polytechnic Institute

Objectives: We hypothesize that identification of healthy whole foods that modulate disease-causing gene expression back toward the normal is a low-cost, healthy, and readily-translatable alternative and/or complementary approach to costly and sometimes toxic pharmaceutical drugs. Our objectives are (1) to identify human studies assessing gene expression after healthy whole food ingestion, and (2) use this data to develop an online app for patients, community and healthcare providers as a dietary guide for a wide range of diseases and conditions.

Methods: We used the keywords “human”, “gene expression” and separately, 42 different dietary agents with reported health benefits to search GEO, PubMed, Google Scholar, Clinical trials, Cochrane library, and EMBL-EBI for studies. For app development, The R-Shiny platform was utilized to construct a public web app (“Eat4Genes”) featuring: a drop-down disease or condition selector; risk genes; user menus; dietary studies; ranking; and study links. To identify key risk genes, the above databases, Big Pharma targets, and NCBI’s “Genes and Disease” were reviewed.

Results: 42 human whole food (or extract) studies were identified. Despite varying conditions (e.g., 4 hours to 8 week diets), the number of whole genome modulated genes were reasonable consistent (1061 +/- 227 SEM). Human gene expression studies were only found for 13 of 34 searched whole foods, underscoring the need for more as compared with much less useful but much more prevalent dietary supplement, cell culture and rodent studies. We identified 96 key risk genes for a wide range of pathologies (e.g., HMGCR for Hypercholesterolemia) for our app. Successful app construction was achieved with the above features, and included the ability to select specific diseases/conditions followed by their key risk genes, identification of dietary agents that express and modulate these genes, and the studies supporting these findings with numerous links. A usability survey was also carried out (N=17).

Conclusions: Our dietary rational gene targeting approach offers an innovative, low-cost, healthy, personalized, and readily translatable strategy to improve health and reduce treatment costs. Construction of our new Eat4Genes app now extends its promise to practice in the form of an interactive online dietary guide.

Funding Sources: NIH, the Wildermuth Foundation, and IDEA at RPI