AUTHOR=Yang Weiling , Xu Hong , Xu Chenhao , Cao Keyi , Pan Yinan , Gu Renjie , Zhu Qi , Xiao Jing 

TITLE=Research progress on the mechanistic impact of single-nucleotide polymorphisms and dietary pattern interactions on overweight and obesity in Chinese adults: a narrative review

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1603038

DOI=10.3389/fnut.2025.1603038

ISSN=2296-861X

ABSTRACT=Obesity is a major global public health challenge caused by a complex interplay of genetic predisposition, environmental factors (notably dietary transitions), and their interactions. In 2025, China's National Health Commission (NHC) launched the “Year of Weight Management” initiative during its key policy-setting sessions, generating substantial public and scientific attention. Despite extensive research on obesity, a comprehensive analysis integrating gene–diet interactions with sex differences specifically in Chinese adults remains lacking. This review synthesizes recent advances in understanding obesity-related gene polymorphisms, dietary influences, and gene–diet interactions in Chinese adults, with particular emphasis on multigene synergistic effects. Our analysis demonstrates that such genetic synergism shows potential for predicting obesity intervention outcomes, while gene–diet interactions substantially contribute to obesity heterogeneity. Furthermore, maintaining a balanced dietary structure is particularly crucial for specific genotypes, with sex differences exerting distinct moderating effects. By transcending conventional single-factor analytical frameworks and incorporating population-specific genetic and dietary backgrounds, this study proposes that future research should prioritize developing a three-dimensional gene–diet–metabolic phenotype model (an integrative framework considering genotype, dietary intake, and dynamic metabolic outcomes) to identify critical windows and mechanisms of metabolic dysregulation. This approach holds substantial promise for informing personalized precision strategies for obesity prevention and control.