Gene and Genetic Expression and its Contribution to Nutritional Assessment

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Nutrition and diet has become a focal point in the prevention of disease. The tools doctors have at their disposal have done a fair job, but what if there could be a better and more individualized way of making recommendations regarding nutrition for disease prevention? The nutritional assessment tools doctors have been using lack an individualized look at a patient’s genes and genetic expressions. Nutrition in a perfect world would be tailored to an individual’s unique needs and requirements since genetics vary from person to person. A new way of looking at nutrition and disease prevention is through the use of Nutritional Genomics. Nutritional Genomics offers patients and doctors an in depth look at genes and genetic expressions, taking into account the smallest of aspects regarding a patient’s health. With the assistance of this analysis, doctors have an opportunity to help patients who don’t fall under the umbrella of the average individual find the nutrition and disease prevention they’ve been looking for.

In the United States, the use of Dietary Guidelines is the source of information regarding nutrition and helps in the development of the Federal governments food polices and other important information regarding health, nutrition, and disease prevention.1 Traditional ways of analyzing a patient’s health come from plans such as Dietary Guidelines, which aims to give advice and guide our way of planning, managing, and executing health.1 The issue with this way of thinking comes down to the fact that these plans are based off average individuals making all of society seem uniform, when in reality there is much diversity in age, sex, race, genetics, gene expressions, and disease predisposition. Instead of relying on the government to fulfill its duty of guiding proper health and nutrition, the use of Nutritional Genomics can be implemented to give patients a more individualized approach to their health.

Nutritional Genomics can look at an individual’s unique genes and assess what type of disease the individual may be predisposed to. When analyzing the genetics, a key maker is Single-Nucleotide Polymorphisms (SNP’s) which helps make each person unique in their own genetic way. Looking at SNP’s allows doctors to focus on 30 genes that could play a role in a patient having a disease or getting a disease and how their diet and nutrition could be correlated. By looking this deep, it allows us to give the patient exactly what they need and slow if not prevent any complications in their future health. Getting doctors and health professionals to think Nutritional Genomics is a difficult task though. Analyzing an entire genome is costly and that could be a deciding factor when choosing how to make nutritional and disease prevention recommendations. What will help drive cost down and get doctors to choose this as a standard will be further testing and positive results.

The use of Nutritional Genomics in formulating diet and nutrition recommendations for patients has the potential to be a significant breakthrough. Utilizing this method provides the patient with a more thorough guide to their health and nutritional needs and helps doctors be more precise in their recommendations. The primary obstacle for Nutritional Genomics to get past is the cost to benefit ratio. Until we can get the cost of genetic analysis to come down, it will remain difficult to implement this as a new standard of thinking in nutrition among health professionals. Further research and trials must continue to reproduce positive results in an attempt to swing momentum in favor of Nutritional Genomics as part of our diet and nutritional planning. Nutritional Genomics plans will allow us to move in a more modern direction of thinking in regards to an individual’s nutrition and leave behind the classic all-encompassing ways that have been limiting us for years.

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Gene and Genetic Expression and its contribution to nutritional assessment. (2019, Feb 20). Retrieved December 11, 2024 , from
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