Identification of potentially relevant metals for the etiology of autism by using a Bayesian multivariate approach for partially censored values

Abstract

Abstract Heavy metals are known to be able to cross the placental and blood brain barriers to affect critical neurodevelopmental processes in the fetus. We measured metal levels (Al, Cd, Hg, Li, Pb and Zn) in the cord blood of newborns and in the serum of the same children at 5 years of age, and compared between individuals with or without (controls) autism spectrum disorder (ASD) diagnosis. The samples were from a biobank associated with the All Babies in Southeast Sweden (ABIS) registry. We proposed a Bayesian multivariate log-normal model for partially censored values to identify potentially relevant metals for the etiology of ASD. Our results in cord blood suggest prenatal Al levels could be indicative of later ASD incidence, which could also be related to an increased possibility of a high, potentially toxic, exposure to Al and Li during pregnancy. In addition, a larger possibility of a high, potentially beneficial, exposure to Zn could occur during pregnancy in controls. Finally, we found decisive evidence for an average increase of Hg in 5-year-old ASD children compared to only weak evidence for controls. This is concordant with previous research showing an impaired ability for eliminating Hg in the ASD group.