A Prospective Study of Environmental Exposures and Early Biomarkers in Autism Spectrum Disorder: Design, Protocols, and Preliminary Data from the MARBLES Study

Abstract

Background: Until recently, environmental factors in autism spectrum disorder (ASD) were largely ignored. Over the last decade, altered risks from lifestyle, medical, chemical, and other factors have emerged through various study designs: whole population cohorts linked to diagnostic and/or exposure-related databases, large case–control studies, and smaller cohorts of children at elevated risk for ASD. Objectives: This study aimed to introduce the MARBLES (Markers of Autism Risk in Babies—Learning Early Signs) prospective study and its goals, motivate the enhanced-risk cohort design, describe protocols and main exposures of interest, and present initial descriptive results for the study population. Methods: Families having one or more previous child with ASD were contacted before or during a pregnancy, and once the woman became pregnant, were invited to enroll. Data and biological samples were collected throughout pregnancy, at birth, and until the child’s third birthday. Neurodevelopment was assessed longitudinally. The study began enrolling in 2006 and is ongoing. Results: As of 30 June 2018, 463 pregnant mothers have enrolled. Most mothers ( ) were thirty years of age or over, including 7.9% who are fourty years of age or over. The sample includes 22% Hispanic and another 25% nonHispanic Black, Asian, or multiracial participants; 24% were born outside the United States. Retention is high: 84% of participants whose pregnancies did not end in miscarriage completed the study or are still currently active. Among children evaluated at 36 months of age, 24% met criteria for ASD, and another 25% were assessed as nonASD nontypical development. Conclusion: Few environmental studies of ASD prospectively obtain early-life exposure measurements. The MARBLES study fills this gap with extensive data and specimen collection beginning in pregnancy and has achieved excellent retention in an ethnically diverse study population. The 24% familial recurrence risk is consistent with recent reported risks observed in large samples of siblings of children diagnosed with ASD. https://doi.org/10.1289/EHP535

Cord blood DNA methylome in newborns later diagnosed with autism spectrum disorder reflects early dysregulation of neurodevelopmental and X-linked genes

“…Study inclusion criteria were: the mother or father has at least one biological child with ASD; the mother is at least 18 years old; the mother is pregnant; the mother speaks, reads, and understands English at a sufficient level to complete the protocol, the younger sibling will be taught to speak English; and the mother lives within 2.5 hours of the Davis/Sacramento region at the time of enrollment. As previously described in depth [60], demographic, lifestyle, environmental, diet, and medical information were collected prospectively through telephone-assisted interviews and mailed questionnaires during pregnancy and the postnatal period. Mothers were provided with umbilical cord blood collection kits prior to delivery.…”

A role for gene-environment interactions in Autism Spectrum Disorder is suggested by variants in genes regulating exposure to environmental factors

“…Table S1: Individual chemicals potentially relevant for ASD studied for interactions with genes involved in detoxification and regulation of barriers permeability, using the Comparative Toxicogenomics Database. ) 0 (0) n/a n/a n/a 2 (0.021) AKR1B15 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) AKR1C1 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) ALDH1A3 1 (0.041) 8.48 0.000717 0.09 (0.01-0.62) 0 (0) n/a n/a n/a 46 (0.477) ALDH3A1 2 (0.082) 0.74 0.184213 3.95 (0.56-28.04) 0 (0) n/a n/a n/a 2 (0.021) ALOX5 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) ANKRD33 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) ARSA 2 (0.082) 0.30 0.267282 2.63 (0.44-15.76) 0 (0) n/a n/a n/a 3 (0.031) ARSJ 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) BCHE 1 (0.041) 2.56x10-30 1 0.79 (0.09-6.76) 0 (0) n/a n/a n/a 5 (0.052) CBR3 7 (0.286) 1.87 0.171303 2.13 (0.85-5.34) 0 (0) n/a n/a n/a 13 (0.135) CBS 2 (0.082) 0.085 0.350127 1.97 (0.36-10.78) 0 (0) n/a n/a n/a 4 (0.041) CES2 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) CHAT 3 (0.123) 4.43 0.028043 11.85 (1.23-113.95) 0 (0) n/a n/a n/a 1 (0.01) CHST10 2 (0.082) 0.74 0.184213 3.95 (0.56-28.04) 0 (0) n/a n/a n/a 2 (0.021) CRYZ 2 (0.082) 1.65 0.106128 7.9 (0.72-87.11) 0 (0) n/a n/a n/a 1 (0.01) CYP11B1 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) CYP24A1 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) CYP27B1 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) CYP2C18 2 (0.082) 0.049 0.74907 0.66 (0.15-2.94) 0 (0) n/a n/a n/a 12 (0.124) CYP2C19 2 (0.082) 0.12 0.749765 0.61 (0.14-2.69) 0 (0) n/a n/a n/a 13 (0.135) CYP2W1 1 (0.041) 3.75x10-25 1 0.99 (0.11-8.83) 0 (0) n/a n/a n/a 4 (0.041) CYP46A1 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) CYP7B1 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) DCXR 2 (0.082) 0.085 0.350127 1.97 (0.36-10.78) 0 (0) n/a n/a n/a 4 (0.041) DRD4 1 (0.041) 4.44x10-26 1 0.66 (0.08-5.46) 0 (0) n/a n/a n/a 6 (0.062) EPHX4 1 (0.041) 4.44x10-26 1 0.66 (0.08-5.46) 0 (0) n/a n/a n/a 6 (0.062) FBN2 2 (0.082) 0.74 0.184213 3.95 (0.56-28.04) 0 (0) n/a n/a n/a 2 (0.021) FCGR2B 5 (0.204) 2.22 0.136027 2.82 (0.89-8.9) 0 (0) n/a n/a n/a 7 (0.073) GPR32 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) GPX5 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) GPX6 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) GSTO1 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) GSTO2 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) GSTP1 2 (0.082) 0.74 0.184213 3.95 (0.56-28.04) 0 (0) n/a n/a n/a 2 (0.021) IGF2 1 (0.041) 6.58x10-25 1 1.32 (0.14-12.65) 0 (0) n/a n/a n/a 3 (0.031) IYD 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) JAM3 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) KIF17 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) LRP1 1 (0.041) 1.17 0.221204 0.26 (0.03-1.99) 0 (0) n/a n/a n/a 15 (0.155) MAPK8IP2 2 (0.082) 0.74 0.184213 3.95 (0.56-28.04) 0 (0) n/a n/a n/a 2 (0.021) NOTCH1 6 (0.245) 6.05 0.0139 4.74 (1.45-15.55) 0 (0) n/a n/a n/a 5 (0.052) PAOX 4 (0.164) 6.49 0.004026 0.27 (0.1-0.75) 0 (0) n/a n/a n/a 58 (0.601) PARD6G 1 (0.041) 2.39x10-27 0.492306 1.97 (0.18-21.77) 0 (0) n/a n/a n/a 2 (0.021) PHLDA2 1 (0.041) 0.028 0.36358 3.95 (0.25-63.11) 0 (0) n/a n/a n/a 1 (0.01) PSG8 25 3 (0.123) 0.32 0.398461 1.97 (0.49-7.9) 0 (0) n/a n/a n/a 6 (0.062) SLC12A7…”

“…Given that no treatment exists for the pathology, the identification of relevant modifiable exposures can contribute to the development of preventive strategies for health management policies in ASD. early exposures and ASD risk, studies either adopt prospective or retrospective designs, resorting to one of four different strategies to measure the exposures: 1) collection of biological samples (blood (22), urine (23) and naturally-shed deciduous teeth (24)) from the pregnant women and/or their offspring to quantify multiple analytes; 2) application of questionnaires answered by the mothers of the children to evaluate self-reported exposures (25,26); 3) geo-referencing studies for the mapping of sources of environmental toxins (e.g. landfill sites (27) and agricultural fields (28)) or understanding of air-quality patterns (29,30); 4) analysis of medical and prescription records to evaluate medications and supplements intake (31).Multiple associations between environmental exposures and ASD have been reported and, while some, such as vaccination and thimerosal exposure, have been contradicted (32), others warrant further investigation.…”

A meta-analysis of two high-risk prospective cohort studies reveals autism-specific transcriptional changes to chromatin, autoimmune, and environmental response genes in umbilical cord blood

“…As described in more detail elsewhere [21], demographic, diet, lifestyle, environmental, and medical information were prospectively collected through telephone-assisted interviews and mailed questionnaires throughout pregnancy and the postnatal period. Mothers were provided with sampling kits for cord blood collection prior to delivery.…”

“…While several studies have previously examined child blood gene expression differences in ASD [8,[14][15][16][17][18][19][20], this is the first study to take advantage of cord blood samples collected from two prospective studies (Markers of Autism Risk in Babies--Learning Early Signs (MARBLES) and the Early Autism Risk Longitudinal Investigation (EARLI)) in order to assess the perinatal transcriptional changes that precede ASD diagnosis in high-risk children [21,22]. The subjects in this study are all siblings of children with ASD and thus have a 13-fold increased risk for ASD compared to the general population [23].…”