Diet as a source of the non-direct genetic effects in metabolic traits: evidence from a family-based GWAS study

Within-family genome-wide association studies (GWAS) can separate direct genetic effects from non-direct genetic biases introduced by analyses based on unrelated individuals, yet evidence regarding metabolic phenotypes remains sparse. Here, we aim to uncover non-direct genetic effects for metabolic traits and the role of diet in the non-direct genetic mechanism. We conducted family-based GWAS studies on six metabolic traits using data from full siblings (N = 777) and parent-offspring trios (N = 386). We calculated and compared within-family and population-based polygenic score (PGS) associations to identify non-direct genetic effects. Additionally, we assessed the parental indirect genetic effects of diet on offspring's metabolic traits. Within-sibship GWAS analyses were also conducted to evaluate the impact of non-direct genetic effects at the individual variant level. On average, the magnitudes of within-family PGS associations for metabolic traits showed a 35.2% reduction compared to population-based estimates, suggesting the presence of non-direct genetic effects. This discrepancy diminished after accounting for dietary score, indicating that diet is a major source of non-direct genetic effects. Additionally, parental indirect genetic effects of diet were revealed in parent-offspring models. For instance, PGS of parental fat consumption was positively related to the child's blood glucose levels (β: 0.44, 95% CI 0.21-0.67). After excluding non-direct genetic effects, within-sibship GWAS models are more effective at identifying functional genes associated with metabolic traits. Our study showed significant contributions of non-direct genetic effects on metabolic traits and also identified diet as a major source of non-direct genetic effects. These findings underlined the importance of family-based GWAS data in disentangling the genetic effects and gene-environment correlations underlying metabolic traits.

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Journal
Human Genetics
Published
2025-10-13
DOI
https://doi.org/10.1007/s00439-025-02780-8
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Diet as a source of the non-direct genetic effects in metabolic traits: evidence from a family-based GWAS study

Kexin Ding, Yiqun Wu, Han Xiao, Zechen Zhou et al.
Human Genetics
Genetic Associations and Epidemiology
article

Diet as a source of the non-direct genetic effects in metabolic traits: evidence from a family-based GWAS study

Kexin Ding, Yiqun Wu, Han Xiao, Zechen Zhou, Xiaoyi Li, Dafang Chen, Yonghua Hu, Yujia Ma, Tao Wu
article en

Abstract

Within-family genome-wide association studies (GWAS) can separate direct genetic effects from non-direct genetic biases introduced by analyses based on unrelated individuals, yet evidence regarding metabolic phenotypes remains sparse. Here, we aim to uncover non-direct genetic effects for metabolic traits and the role of diet in the non-direct genetic mechanism. We conducted family-based GWAS studies on six metabolic traits using data from full siblings (N = 777) and parent-offspring trios (N = 386). We calculated and compared within-family and population-based polygenic score (PGS) associations to identify non-direct genetic effects. Additionally, we assessed the parental indirect genetic effects of diet on offspring's metabolic traits. Within-sibship GWAS analyses were also conducted to evaluate the impact of non-direct genetic effects at the individual variant level. On average, the magnitudes of within-family PGS associations for metabolic traits showed a 35.2% reduction compared to population-based estimates, suggesting the presence of non-direct genetic effects. This discrepancy diminished after accounting for dietary score, indicating that diet is a major source of non-direct genetic effects. Additionally, parental indirect genetic effects of diet were revealed in parent-offspring models. For instance, PGS of parental fat consumption was positively related to the child's blood glucose levels (β: 0.44, 95% CI 0.21-0.67). After excluding non-direct genetic effects, within-sibship GWAS models are more effective at identifying functional genes associated with metabolic traits. Our study showed significant contributions of non-direct genetic effects on metabolic traits and also identified diet as a major source of non-direct genetic effects. These findings underlined the importance of family-based GWAS data in disentangling the genetic effects and gene-environment correlations underlying metabolic traits.

Human GeneticsVol. 144(11-12)
Peking University (CN), Ministry of Education (RO), Imperial College London (GB)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 69%
Genetic Associations and Epidemiology
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