Table 1. Summary of observational studies investigating genetic interactions associated with obesity

No. Study design Studies Genetic approach Outcome (s) Data source (s) Sample size (n) Conclusions
1 Cross-Sectional study Lee et al. (2021) PRS1) BMI2) KARE3)CAVAS4)HEXA5) 8,4449,30017,350 PRS and aPRS were significantly associated with BMI and obesity, but no significant interaction was observed with total calorie or macronutrient intake.
2 Cross-sectional & Longitudinal study Yoon & Cho (2023) PRS Obesity Metabolic traits KARECAVASHEXA 13,504(longitudinal study 5,400) The developed PRS effectively predicted obesity and related metabolic diseases. Longitudinal analysis showed that a higher PRS was associated with an increased incidence of dyslipidemia and hypo-HDL cholesterolemia.
3 Cross-sectional Lee et al. (2010) FTOrs9939609 BMI KARE 8,842 Common FTO variants were associated with BMI and overweight in adults. A significant interaction was observed between rs9939609 and physical activity, whereas no association with dietary fat intake was found in adults.
4 Case-control Doo & Kim (2011) ESR1rs1884051 BMI KARE 3,039 The ESR1 rs1884051 polymorphism was significantly associated with obesity-related variables in men. This association was modified by total energy and plant protein intake; specifically, the minor T allele was associated with lower BMI in the high plant protein intake group.
5 Cross-sectional study Jin et al. (2013) SPRY1rs923982 %BF6)%AbF7)BMIWHR8) KARE 3,013 SPRY1 gene polymorphisms and the TGCC haplotype were significantly associated with increased body fat percentage, abdominal fat, and osteoporosis risk in Korean women.
6 Case-control Doo et al. (2015) APOBrs1469513 BMI obesity KoGES 6,470 The association between the APOB rs1469513 polymorphism and obesity was significantly modified by dietary fat intake; specifically, high fat intake increased obesity risk in minor G allele carriers.
7 Cross-sectional Kim et al. (2016) NPYrs16149 BMIWC9)VAT10) KARE 1,468 Common NPY polymorphisms were not directly associated with obesity but showed significant interactions with psychosocial stress on BMI, waist circumference, and visceral adipose tissue (VAT).
8 Cross-sectional Choi (2021) CD36rs1527479 Dietary intake KARE 6,619 The CD36 polymorphism was associated with cruciferous vegetable intake in obese males; those with the risk genotype consumed significantly less vegetables, while no association was found with fat intake.
9 Cross-sectional Goh & Choi (2022) FTOrs1121980 BMIDietary intake KARE 6,262 The FTO rs1121980 variation was associated with a preference for high-fat foods (e.g., coffee creamer, snacks), and these preferences varied by sex and BMI.
10 Longitudinal Lee et al. (2024) PDGFCrs4691380TREHrs2276064 Longitudinal BMI change KARE 3,074 Identified specific genetic variants (e.g., PDGFC, TREH) significantly associated with long-term BMI changes and obesity risk in Korean adults.
11 Cross-sectional Kwon et al. (2022) CAB39rs6722579CPQrs59465035 Abdominal obesity KoGES 50,808 Specific genetic variants interacted with nutrient intake to influence obesity risk; CAB39 variant increased abdominal obesity risk with high fat intake, while CPQ variant decreased risk with high vitamin C intake.
PRS, polygenic risk score;
BMI, body mass index;
KARE, Korean Association Resource;
CAVAS, Cardiovascular and Metabolic Diseases Etiology Research Center;
HEXA, Health Examinees Study;
%BF, percentage of body fat;
%AbF, percentage of abdominal fat;
WHR, waist-to-hip ratio;
WC, waist circumference;
VAT, visceral adipose tissue.