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Examining Prenatal Dietary Factors in Association with Child Autism-Related Traits Using a Bayesian Mixture Approach:
Kristen Lyall1, Juliette Rando1, Siwen Wang2
1AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States.
Insights
Prenatal nutrient intake and diet composition may influence autism traits. Some vegetables were linked to lower autism scores, but results varied by cohort and specific food groups.
Area of Science:
- Nutritional epidemiology
- Autism spectrum disorder research
- Maternal and child health
Background:
- Prior research suggests a link between maternal nutrient intake during pregnancy and autism risk.
- Understanding these associations is crucial for early intervention and prevention strategies.
Purpose of the Study:
- To investigate the combined effects of prenatal nutrient and food intake on autism-related traits.
- To explore potential differences in these associations based on family history of autism.
Main Methods:
- Utilized data from the Early Autism Risks Longitudinal Investigation and Nurses' Health Study II cohorts.
- Employed Bayesian kernel machine regression to analyze associations between nutrient mixtures (PUFAs, iron, zinc, vitamin D, folate, methyl donors) and food groups with child Social Responsiveness Scale (SRS) scores.
- Collected dietary information via food frequency questionnaires and assessed autism traits using the SRS.
Main Results:
- No significant overall mixture effects of nutrients or foods on SRS scores were found in adjusted analyses in the first cohort.
- A potential trend of decreasing SRS scores with increased nutrient mixture was observed in the Nurses' Health Study II.
- Specific findings included associations between n-6 polyunsaturated fatty acids (PUFAs) and lower SRS scores, and varied associations with vegetable intake across cohorts.
Conclusions:
- Findings highlight the complexity of prenatal diet-autism associations, emphasizing the need for a combined effects approach.
- The study suggests potential differences in nutrient-autism associations related to family history, indicating a need for future research on gene-environment interactions.
Background:
Prior work has suggested relationships between prenatal intake of certain nutrients and autism.
Objectives:
We examined a broad set of prenatal nutrients and foods using a Bayesian modeling approach.
Methods:
Participants were drawn from the Early Autism Risks Longitudinal Investigation (n = 127), a cohort following women with a child with autism through a subsequent pregnancy. Participants were also drawn from the Nurses' Health Study II (NHSII, n = 713), a cohort of United States female nurses, for comparison analyses. In both studies, information on prospectively reported prenatal diet was drawn from food frequency questionnaires, and child autism-related traits were measured by the Social Responsiveness Scale (SRS). Bayesian kernel machine regression was used to examine the combined effects of several nutrients with neurodevelopmental relevance, including polyunsaturated fatty acids (PUFAs), iron, zinc, vitamin D, folate, and other methyl donors, and separately, key food sources of these, in association with child SRS scores in crude and adjusted models.
Results:
In adjusted analyses, the overall mixture effects of nutrients in Early Autism Risks Longitudinal Investigation and foods in both cohorts on SRS scores were not observed, though there was some suggestion of decreasing SRS scores with increasing overall nutrient mixture in NHSII. No associations were observed with folate within the context of this mixture, but holding other nutrients fixed, n-6 PUFAs were associated with lower SRS scores in NHSII. In both cohorts, lower SRS scores were observed with higher intake of some groupings of vegetables, though for differing types of vegetables across cohorts, and some vegetable groups were associated with higher SRS scores in NHSII.
Conclusions:
Our work extends prior research and suggests the need to further consider prenatal dietary factors from a combined effects perspective. In addition, findings here point to potential differences in nutrient associations based on a family history of autism, which suggests the need to consider gene interactions in future work.
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