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.