Maternal dietary patterns, supplements intake and autism spectrum disorders

Li, Yamin; Shen, Yidong; Li, Yong-Jiang; Xun, Guanglei; Liu, Huaqing; Wu, Renrong; Xia, Kun; Zhao, Jingping; Ou, Jianjun

doi:10.1097/md.0000000000013902

Cited by 30 publications

(73 citation statements)

References 37 publications

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“…We also observed a relation with nutritive supplements and reproductive hormones. Increased and decreased risk of ASD has been previously reported for medications from these groups [32,33]. Maternal metabolic conditions and disruptions in the endocrine system have been associated with ASD-risk [32,33], and contributed to case classification.…”

Section: Discussionmentioning

confidence: 97%

“…Increased and decreased risk of ASD has been previously reported for medications from these groups [32,33]. Maternal metabolic conditions and disruptions in the endocrine system have been associated with ASD-risk [32,33], and contributed to case classification. Taken together, the agreement between our most useful features with previous studies analyzing ASD patients increases the confidence in our combined approach.…”

Section: Discussionmentioning

confidence: 97%

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Identification of newborns at risk for autism using electronic medical records and machine learning

et al. 2020

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Background. Current approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, and most ASD patients are not identified until after the age of 4. This is despite substantial evidence suggesting that early diagnosis and intervention improves developmental course and outcome. The aim of the current study was to test the ability of machine learning (ML) models applied to electronic medical records (EMRs) to predict ASD early in life, in a general population sample. Methods. We used EMR data from a single Israeli Health Maintenance Organization, including EMR information for parents of 1,397 ASD children (ICD-9/10) and 94,741 non-ASD children born between January 1st, 1997 and December 31st, 2008. Routinely available parental sociodemographic information, parental medical histories, and prescribed medications data were used to generate features to train various ML algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross-validation by computing the area under the receiver operating characteristic curve (AUC; C-statistic), sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value [PPV]). Results. All ML models tested had similar performance. The average performance across all models had C-statistic of 0.709, sensitivity of 29.93%, specificity of 98.18%, accuracy of 95.62%, false positive rate of 1.81%, and PPV of 43.35% for predicting ASD in this dataset. Conclusions. We conclude that ML algorithms combined with EMR capture early life ASD risk as well as reveal previously unknown features to be associated with ASD-risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 97%

Identification of newborns at risk for autism using electronic medical records and machine learning

et al. 2020

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“…Of the cohort studies, 3 relied on prospectively selfreported FA supplement use, including 2 analyses in the DNBC [Strom et al, 2018;Virk et al, 2016], and 1 in the SYC cohort [DeVilbiss et al, 2017]. Of the case control studies, one relied on retrospectively self-reported information [Y. M. Li et al, 2018], and one on national registry data [Sharman Moser et al, 2019]. Lastly, two studies assessed offspring autistic traits and maternal folate concentration using biomarkers from blood samples collected during pregnancy from the HOME cohort [Braun Results across the rapidly growing number of folate/FA supplementation studies therefore suggest that, while protective associations have been replicated, there is also a fair degree of conflicting information.…”

Section: Fa/folatementioning

confidence: 99%

“…We identified three studies evaluating associations between combined dietary factors or dietary patterns and ASD [L. Gao, Cui, et al, 2016;House et al, 2018;Y. M. Li et al, 2018].…”

Section: Dietary Patterns/habitsmentioning

confidence: 99%

Maternal Dietary Factors and the Risk of Autism Spectrum Disorders: A Systematic Review of Existing Evidence

et al. 2020

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Prenatal maternal diet is a critical factor in offspring neurodevelopment. Emerging evidence suggests that prenatal diet may also play a role in the etiology autism spectrum disorder (ASD). This review summarizes studies published in English that examined prenatal nutrients or maternal diet in association with ASD from PubMed as of July 2020. Thiry-six studies from nine countries were included in this systematic review; these focused on multivitamin (n = 5), prenatal vitamin (n = 3), folic acid (FA; n = 14), Vitamin D (n = 11), polyunsaturated fatty acid or fish/supplement intake (n = 7), iron (n = 3), Vitamin B12 (n = 1), calcium (n = 1), magnesium (n = 1), and broad maternal dietary habits (n = 3). Overall, higher or moderate intake of prenatal/multivitamin, FA, and Vitamin D was associated with reductions in odds of ASD, though results have not been uniform and there is a need to clarify differences in findings based on biomarkers versus reported intake. Evidence was inconclusive or insufficient for other nutrients. Differences in the timing and measurement of these dietary factors, as well as potential residual confounding, may contribute to existing discrepancies. Key areas for future research to better understand the role of maternal diet in ASD include the need to address potential critical windows, examine the combined effect of multiple nutrients, and consider interactions with genetic or environmental factors.

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“…In individuals with a genetic predisposition, a range of environmental factors have been proposed to increase ASD risk [7,12]. Among them are variations in maternal metabolism at pregnancy [13,14]. Beside maternal metabolism, adverse health conditions during early pregnancy such as viral infections, inflammation, and immune activation are considered as risk factors for psychiatric disorders in the offspring [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Maternal blood folate status during early pregnancy and occurrence of autism spectrum disorder in offspring: a study of 62 serum biomarkers

et al. 2020

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Background: Autism spectrum disorder (ASD) evolves from an interplay between genetic and environmental factors during prenatal development. Since identifying maternal biomarkers associated with ASD risk in offspring during early pregnancy might result in new strategies for intervention, we investigated maternal metabolic biomarkers in relation to occurrence of ASD in offspring using both univariate logistic regression and multivariate network analysis. Methods: Serum samples from 100 women with an offspring diagnosed with ASD and 100 matched control women with typically developing offspring were collected at week 14 of pregnancy. Concentrations of 62 metabolic biomarkers were determined, including amino acids, vitamins (A, B, D, E, and K), and biomarkers related to folate (vitamin B 9 ) metabolism, lifestyle factors, as well as C-reactive protein (CRP), the kynurenine-tryptophan ratio (KTR), and neopterin as markers of inflammation and immune activation. Results: We found weak evidence for a positive association between higher maternal serum concentrations of folate and increased occurrence of ASD (OR per 1 SD increase: 1.70, 95% CI 1.22-2.37, FDR adjusted P = 0.07). Multivariate network analysis confirmed expected internal biochemical relations between the biomarkers. Neither inflammation markers nor vitamin D 3 levels, all hypothesized to be involved in ASD etiology, displayed associations with ASD occurrence in the offspring. Conclusions: Our findings suggest that high maternal serum folate status during early pregnancy may be associated with the occurrence of ASD in offspring. No inference about physiological mechanisms behind this observation can be made at the present time because blood folate levels may have complex relations with nutritional intake, the cellular folate status and status of other B-vitamins. Therefore, further investigations, which may clarify the potential role and mechanisms of maternal blood folate status in ASD risk and the interplay with other potential risk factors, in larger materials are warranted.

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Maternal dietary patterns, supplements intake and autism spectrum disorders

Cited by 30 publications

References 37 publications

Identification of newborns at risk for autism using electronic medical records and machine learning

Identification of newborns at risk for autism using electronic medical records and machine learning

Maternal Dietary Factors and the Risk of Autism Spectrum Disorders: A Systematic Review of Existing Evidence

Maternal blood folate status during early pregnancy and occurrence of autism spectrum disorder in offspring: a study of 62 serum biomarkers

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