Tooth biomarkers to characterize the temporal dynamics of the fetal and early-life exposome.

BACKGROUND: Teeth have unique histology that make this biomatrix a time-capsule for retrospective exposure analysis of fetal and early life. However, most analytic methods require pulverizing the whole tooth, which eliminates exposure timing information. Further, the range of chemicals and endogenous exposures that can be measured in teeth has yet to be fully characterized. METHODS: We performed untargeted metabolomics on micro-dissected layers from naturally shed deciduous teeth. Using four liquid-chromatography high-resolution mass spectrometry analytical modes, we profiled small molecules (<1000 Da) from prenatal and postnatal tooth fractions. In addition, we employed linear regression on the tooth fraction pairs from 31 children to identify metabolites that discriminate between prenatal and postnatal exposures. RESULTS: Of over 10,000 features measured in teeth dentin, 390 unique compounds were annotated from 62 chemical classes. The class with the largest number of compounds was carboxylic acids and their derivatives (36%). Of the annotated exogenous metabolites (phthalates, parabens, perfluoroalkyl compounds, and cotinine) and endogenous metabolites (fatty acids, steroids, carnitines, amino acids, and others), 91 are linked to 256 health conditions through published literature. Differential analysis revealed 267 metabolites significantly different between the prenatal and the postnatal tooth fractions (adj. p-value < 0.05, Bonferroni correction), and 21 metabolites exclusive to the prenatal fraction. CONCLUSIONS: The prenatal and early postnatal exposome revealed from dental biomarkers represents a broad range of endogenous and exogenous metabolites for a comprehensive characterization in environmental health research. Most importantly, this technology provides a direct window into fetal exposures that is not possible by maternal biomarkers. Indeed, we identified several metabolites exclusively in the prenatal fraction, suggesting unique fetal exposures that are markedly different to postnatal exposures. Expansion of databases that include tooth matrix metabolites will strengthen biological interpretation and shed light on exposures during gestation and early life that may be causally linked with later health conditions.

Developmental Trajectories of Infants With Multiplex Family Risk for Autism: A Baby Siblings Research Consortium Study.

Importance: Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with different genetic etiologies. Prospective examination of familial-risk infants informs understanding of developmental trajectories preceding ASD diagnosis, potentially improving early detection. Objective: To compare outcomes and trajectories associated with varying familial risk for ASD across the first 3 years of life. Design, Setting, and Participants: This longitudinal, prospective cohort study used data from 11 sites in the Baby Siblings Research Consortium database. Data were collected between 2003 and 2015. Infants who were younger siblings of children with ASD were followed up for 3 years. Analyses were conducted in April 2018. Of the initial 1008 infants from the database, 573 were removed owing to missing necessary data, diagnostic discrepancies, or only having 1 older sibling. Exposures: Number of siblings with ASD. Main Outcomes and Measures: Outcomes included ASD symptoms, cognitive abilities, and adaptive skills. Diagnosis (ASD or no ASD) was given at 36-month outcome. The no-ASD group was classified as atypical (developmental delays and/or social-communication concerns) or typical for some analyses. Generalized linear mixed models examined developmental trajectories by ASD outcome and familial-risk group. Results: In the 435 analyzed participants (age range at outcome, 32-43 months; 246 male [57%]), 355 (82%) were from single-incidence families (1 sibling with ASD and ≥1 sibling without ASD) and 80 (18%) were from multiplex families (≥2 siblings with ASD). There were no significant group differences in major demographics. Children from multiplex families were more likely than those from single-incidence families to be classified as having ASD (29 of 80 [36%] vs 57 of 355 [16%]; 95% CI, 9%-31%; P < .001) and less likely as typical (26 of 80 [33%] vs 201 of 355 [57%]; 95% CI, -36% to -13%; P < .001), with similar rates of atypical classifications (25 of 80 [31%] vs 97 of 355 [27%]; 95% CI, -7% to 15%; P = .49). There were no differences in ASD symptoms between multiplex and single-incidence groups after controlling for ASD outcome (95% CI, -0.02 to 0.20; P = .18). During infancy, differences in cognitive and adaptive abilities were observed based on ASD outcome in the single-incidence group only. At 36 months, the multiplex/no-ASD group had lower cognitive abilities than the single-incidence/no-ASD group (95% CI, -11.89 to -2.20; P = .02), and the multiplex group had lower adaptive abilities than individuals in the single-incidence group after controlling for ASD outcome (95% CI, -9.01 to -1.48; P = .02). Conclusions and Relevance: Infants with a multiplex family history of ASD should be monitored early and often and referred for early intervention at the first sign of concern. Direct examination of genetic contributions to neurodevelopmental phenotypes in infants with familial risk for ASD is needed.