Background: Previous research on the role of maternal diet in relation to autism has focused on examining individual nutrient associations. Few studies have examined associations with multiple nutrients using mixtures approaches, which may better reflect true exposure scenarios.

Objective: To examine associations of nutrient mixtures with children's autism diagnosis and traits scores within a large, diverse population.

Methods: Participants were drawn from the US Environmental influences on Child Health Outcomes (ECHO) consortium. Maternal prenatal diet was reported via validated food frequency questionnaires. Children's autism-related traits were measured using the Social Responsiveness Scale (SRS) and autism diagnoses were from parent report of physician diagnosis. Bayesian kernel machine regression (BKMR) was used to examine the overall mixture effect and interactions between a set of 5 primary nutrients (folate, vitamin D, omega 3 and omega 6 fatty acids, and iron), adjusted for potential confounders, in relationship to child outcomes. Secondary analyses were conducted in a subset of cohorts with an expanded set of 14 nutrients. Traditional linear and logistic regression models were also run for comparison of results to mixture models.

Results: 2,614 participants drawn from 7 ECHO cohorts were included in primary analysis. Mixture analyses suggested that increasing the overall 5-nutrient mixture was associated with lower SRS scores. Individual U-shaped associations and bivariate interactions between folate and omega 3 fatty acids were suggested. In the subset included in the secondary analyses of the 14-nutrient mixture, a modest inverse trend remained, but individual nutrient associations were altered, with vitamin D demonstrating higher relative importance than other nutrients. Strong associations with autism diagnosis were not observed.

Conclusion: In this large sample, we found evidence for combined nutrient effects with broader autism-related traits. Because results for individual nutrients were sensitive to mixture components, replication of combined associations between nutrients and autism-related outcomes is needed.

Keywords: Neurodevelopment; epidemiology; nutrients; statistical mixtures methods.

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