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Nutrients. 2018 Feb 26;10(3). pii: E266. doi: 10.3390/nu10030266.

Impact of Genetic Variants on the Individual Potential for Body Fat Loss.

Author information

1
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. scha@ncsu.edu.
2
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. kangx342@gmail.com.
3
Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon 16419, Gyeonggi-do, Korea. kangx342@gmail.com.
4
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. noonolee@gmail.com.
5
Software R&D Center, Samsung Electronics, Hwaseong 18448, Gyeonggi-do, Korea. jk.neo.kim@samsung.com.
6
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. wonniey@gmail.com.
7
Department of Food and Nutrition, Dongduk Women's University, Seoul 02748, Korea. yjyang@dongduk.ac.kr.
8
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. woongyang.park@samsung.com.
9
Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon 16419, Gyeonggi-do, Korea. woongyang.park@samsung.com.
10
Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea. jinho.jk.kim@samsung.com.

Abstract

The past decade has witnessed the discovery of obesity-related genetic variants and their functions through genome-wide association studies. Combinations of risk alleles can influence obesity phenotypes with different degrees of effectiveness across various individuals by interacting with environmental factors. We examined the interaction between genetic variation and changes in dietary habits or exercise that influences body fat loss from a large Korean cohort (n = 8840). Out of 673 obesity-related SNPs, a total of 100 SNPs (37 for carbohydrate intake; 19 for fat intake; 44 for total calories intake; 25 for exercise onset) identified to have gene-environment interaction effect in generalized linear model were used to calculate genetic risk scores (GRS). Based on the GRS distribution, we divided the population into four levels, namely, "very insensitive", "insensitive", "sensitive", and "very sensitive" for each of the four categories, "carbohydrate intake", "fat intake", "total calories intake", and "exercise". Overall, the mean body fat loss became larger when the sensitivity level was increased. In conclusion, genetic variants influence the effectiveness of dietary regimes for body fat loss. Based on our findings, we suggest a platform for personalized body fat management by providing the most suitable and effective nutrition or activity plan specific to an individual.

KEYWORDS:

BMI; GWAS; body fat; diet; exercise; genetic risk score; health; obesity

PMID:
29495392
PMCID:
PMC5872684
DOI:
10.3390/nu10030266
[Indexed for MEDLINE]
Free PMC Article

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