Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 11, 7

Maternal Blood Folate Status During Early Pregnancy and Occurrence of Autism Spectrum Disorder in Offspring: A Study of 62 Serum Biomarkers


Maternal Blood Folate Status During Early Pregnancy and Occurrence of Autism Spectrum Disorder in Offspring: A Study of 62 Serum Biomarkers

Olga Egorova et al. Mol Autism.


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 B9) 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 D3 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.

Keywords: Autism; Folate; Inflammation; One-carbon metabolism; Pregnancy; Vitamin A; Vitamin B; Vitamin D.

Conflict of interest statement

Competing interestsSven Bölte declares no conflict of interest related to this article. Bölte discloses that he has in the last 5 years acted as an author, consultant, or lecturer for Shire, Medice, Roche, Eli Lilly, Prima Psychiatry, GLGroup, System Analytic, Kompetento, Expo Medica, and Prophase. He receives royalties for text books and diagnostic tools from Huber/Hogrefe, Kohlhammer and UTB. Erik Domellöf is supported by a grant from the Knut and Alice Wallenberg Foundation (KAW 2015.0192). There are no other financial disclosures or conflicts of interest.


Fig. 1
Fig. 1
Study design
Fig. 2
Fig. 2
Spearman’s correlations between analyzed serum biomarkers with a hierarchical cluster analysis based on the correlations
Fig. 3
Fig. 3
Odds ratios (ORs) for ASD risk by 1 standard deviation (SD) increase in biomarkers levels. ORs were calculated using logistic regression adjusted for mother’s age at sampling, year of sampling, sex of child, and serum cotinine and mTHF levels. Vitamin D3 was further adjusted for month of sampling (light/dark months). Median serum concentration levels in cases and controls are presented in nmol/L for biomarker kynurenic acid; 25-hydroxy vitamin D3; xanthurenic acid; trigonelline; cystathionine; 4-pyridoxic acid; quinolinic acid; pyridoxal; neopterin; nicotinic acid; para-amino benzoylglutamate; acetamidobenzoglutamate; hmTHF; mTHF;and in mg/l for CRP and all remaining biomarkers
Fig. 4
Fig. 4
a Bayesian network of serum biomarkers and background information variables estimated by a Hill-climbing algorithm and averaged over 1000 bootstrap samples. A line between two variables indicates an association independent of all other variables in the network. Line thickness corresponds to association strength measured as proportion of times an association was present in 1000 bootstrap sample networks (a thicker line indicates a stronger association). Node size corresponds to the number of connections. The network was estimated using discrete data (with biomarkers divided into low/high groups, with cut-off defined by the median biomarker concentrations in the controls). b Association strengths to ASD risk for each biomarker measured as proportion of times an association was present in 1000 bootstrap sample networks

Similar articles

See all similar articles


    1. Diagnostic and Statistical Manual of Mental Disorders . Association AP, editor. Washington, DC, USA: American Psychiatric Association; 1994.
    1. Lyall K, Croen L, Daniels J, Fallin MD, Ladd-Acosta C, Lee BK, et al. The changing epidemiology of autism spectrum disorders. Annu Rev Public Health. 2017;38:81–102. - PMC - PubMed
    1. Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, et al. Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 Sites, United States, 2014. Morbidity and mortality weekly report Surveillance summaries (Washington, DC : 2002). 2018;67(6):1-23. - PMC - PubMed
    1. Elsabbagh M, Divan G, Koh YJ, Kim YS, Kauchali S, Marcin C, et al. Global prevalence of autism and other pervasive developmental disorders. Autism Res. 2012;5(3):160–179. - PMC - PubMed
    1. Rutter M. Incidence of autism spectrum disorders: changes over time and their meaning. Acta Paediatr. 2005;94(1):2–15. - PubMed

LinkOut - more resources