Prenatal Metabolic Syndrome and Autism Spectrum Disorder: The Moderating Influence of Familial History

Poster Presentation
Saturday, May 4, 2019: 11:30 AM-1:30 PM
Room: 710 (Palais des congres de Montreal)
C. A. Palmer1, A. V. Bakian1, M. S. Esplin2, E. Clark3, A. Fraser4, H. Coon1, S. R. Dager5 and D. A. Bilder1, (1)Psychiatry, University of Utah, Salt Lake City, UT, (2)Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, (3)University of Utah, Salt Lake City, UT, (4)Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, (5)University of Washington, Seattle, WA
Background: Established prenatal risk factors for autism spectrum disorder (ASD) include maternal conditions characterized by inflammation and/or steroid dysregulation, such as gestational/pre-existing hypertension, preeclampsia, and gestational/pre-existing diabetes. In combination, these risk factors are referred to as prenatal metabolic syndrome (PNMS). Both ASD and PNMS are known to have familial predispositions that are attributable, in part, to heritability.

Objectives: 1) To confirm increased ASD risk associated with PNMS exposure, and 2) investigate the interaction and moderating effects of ASD and PNMS familial predispositions on the association between PNMS exposure and ASD.

Methods: Index offspring of First and Second Trimester Evaluation of Risk (FASTER) study participants (N=6441) were linked to their birth certificate and genealogical records in the Utah Population Database. ASD case status was determined through linkage with research and population-ascertained ASD cohorts, including the Utah Registry of Autism and Developmental Disabilities. PNMS status was determined from birth certificates. Familial predisposition of PNMS and ASD was treated as a dichotomous variable based on the presence of at least one first through third degree relative with PNMS or ASD. A log-linear model assuming a Poisson distribution with robust error variances was fit to calculate ASD relative risk associated with PNMS exposure. The model was adjusted using inverse probability of treatment weights (IPTW). Two additional IPTW models were fit that included 1) PNMS familial predisposition and a PNMS exposure*PNMS familial predisposition interaction to test for effect moderation and interaction and 2) ASD familial predisposition and a PNMS exposure*ASD familial predisposition interaction.

Results: 168 offspring were identified with ASD resulting in a prevalence of 2.6% within the FASTER cohort. PNMS exposure (Overall 11%, n=684) was more frequent in offspring with versus without ASD (19%, n=32 vs. 10%, n=652, respectively; p=0.003). ASD relative risk (RR) associated with PNMS exposure was 1.72 (95% CI: 1.1-2.7, p=0.02). Familial predisposition of PNMS moderated ASD risk associated with PNMS exposure (RR=2.07, 95% CI: 1.22-3.51, p=0.007 in children having a familial PNMS predisposition vs RR=1.49, 95% CI: 0.66-3.33, p=0.33 in children without familial PNMS predisposition); however, no interaction existed between familial PNMS predisposition and PNMS exposure (p = 0.5). In contrast, a similar increased risk of ASD from PNMS exposure was identified in both children having familial risk for ASD (RR=2.20, 95% CI: 1.00-4.82; p=0.05) and those without familial ASD risk (RR=1.72, 95% CI: 1.04-2.84; p=0.03) suggesting no effect modification or interaction (p=0.6).

Conclusions: ASD risk increased by 72% in children exposed to PNMS and over 100% in children exposed to PNMS who shared a familial risk of PNMS. In contrast, while ASD risk was heightened in all children exposed to PNMS, a family history of ASD had an independent but not moderating or interactive effect on ASD risk. Whether PNMS impacts ASD’s causal pathway or shares common etiologic factors with ASD, this association appears moderated by familial risk of PNMS, yet independent of familial risk of ASD. Study findings justify further investigation into the nature of this relationship as identifying shared preclinical precursors could establish prevention strategies for ASD.