An Expanded Examination of Neonatal Cytokines and Chemokines As Predictors of Autism Risk: The Early Markers for Autism (EMA) Study

Background: Previous work by our group identified cytokines and chemokines (CyChs) in neonatal bloodspots as potential biomarkers for evaluating autism risk. Obtaining an early biomarker is crucial to preventative medicine in autism spectrum disorder (ASD), allowing for earlier identification and earlier intervention, potentially leading to improved outcomes.

Objectives: Utilizing a more sensitive and expansive immunoassay, we aimed to expand upon our earlier findings in the characterization of newborn bloodspot profiles of CyChs in a larger sample population of children with autism spectrum disorders (ASD), children with developmental delay (DD) without ASD, and children considered to be typically developing. 

Methods: Data are from the Early Markers for Autism (EMA) study, a population-based nested case control study that utilizes archived maternal mid-pregnancy and neonatal blood specimens from mother-baby pairs. Birth records were linked to the California Department of Developmental Services (DDS) client databases to identify children with ASD (N=370) and children with DD without ASD (N=140). General population controls (GP, N=378) were randomly selected from the remaining birth records, matched to ASD cases on child month and year of birth and gender. Final diagnostic status, based on DSM-IV-TR criteria, was determined by expert clinical review of abstracted diagnostic and clinical information in DDS client records. Newborn bloodspots were eluted and assayed for 42 different CyChs using a multiplex platform. CyChs that had significant non-detects or that remained non-normally distributed after natural log transformation were broken into quartiles. Comparisons of CyChs concentrations between groups were carried out on a cytokine by cytokine basis using a multivariate logistic regression models, adjusting for birth type (cesarean vs vaginal), gestational days at birth, age at time of newborn bloodspot collection, infant gender, birth weight, and birth season, as well as parental (maternal and paternal) age, education, race, and plate number to control for plate to plate variation. Normally distributed CyChs were subjected to a linear regression model incorporating the aforementioned covariates. The corresponding residuals from each CyCh were used in partial least squares discriminant analysis (PLS-DA), a multivariate approach to derive combinations of CyChs that would discriminate between cases and controls. 

Results: Children with ASD had significantly increased neonatal levels of IL-4, IL-6, IL-8, IFN-g, and Eotaxin-1 compared to GP controls. In addition, children with ASD had significantly decreased levels of Eotaxin-1 and increased IL-12p70 levels relative to DD children. We observed no significant differences in CyChs levels between the DD and GP groups. After adjusting for multiple comparisons by FDR, all associations were no longer statistically significant. Furthermore, the PLS-DA multivariate approach did not identify any combinations of CyChs that discriminated between study groups. 

Conclusions: Elevated levels of some cytokines and chemokines measured in newborn bloodspots indicated a higher level of immune activation at birth in children who were subsequently diagnosed with ASD. However, this expanded sample set was not sufficient to determine if the CyCh analytes noted herein will constitute reliable biomarkers of ASD risk, and thus should be repeated in future studies.