Interaction between a mixture of heavy metals (lead, mercury, arsenic, cadmium, manganese, aluminum) and GSTP1, GSTT1, and GSTM1 in relation to autism spectrum disorder. (November 2020)

• Record Type: Journal Article
• Authors: Rahbar, Mohammad H.; Samms-Vaughan, Maureen; Lee, MinJae; Zhang, Jing; Hessabi, Manouchehr; Bressler, Jan; Bach, MacKinsey A.; Grove, Megan L.; Shakespeare-Pellington, Sydonnie; Beecher, Compton; McLaughlin, Wayne; Loveland, Katherine A.
• Is Part Of: Research in autism spectrum disorders. Volume 79(2020)
• Publication Date: 2020-11
• Subjects: Autism Spectrum Disorder -- Glutathione S-transferase (GST) genes (GSTP1 GSTT1 and GSTM1) -- Mixture analysis -- Generalized weighted quantile sum regression (gWQS) -- Heavy metals -- Jamaica; Autism spectrum disorders -- Periodicals; 616.85882005
• DOI: 10.1016/j.rasd.2020.101681
• Languages: English
• ISSNs: 1750-9467

Abstract

Highlights: Humans are exposed to mixtures of metals and other environmental chemicals. We used mixture analysis to assess relative contribution of six metals in ASD. We found a possible effect modification of GSTP1 with Mn, Pb, and Hg in ASD. Our finding of interaction of GSTP1 with Mn in ASD has been reported previously. Possible effect modification of GSTP1 with Pb, and Hg in ASD requires replication. Abstract: Background: Exposure to many environmental chemicals, including metals, often does not occur in isolation, hence requires assessment of the associations between exposure to mixtures of chemicals and human health. Objectives: To investigate associations of a metal mixture of lead (Pb), mercury (Hg), arsenic (As), cadmium (Cd), manganese (Mn), and aluminum (Al) in children with autism spectrum disorder (ASD), additively or interactively with each of three glutathione S-transferase (GST) genes ( GSTP1, GSTT1, and GSTM1 ). Method: Using data from 266 case-control pairs of Jamaican children (2–8 years old), we fitted negative and positive generalized weighted quantile sum (gWQS) regression models to assess the aforementioned associations. Results: Based on additive and interactive negative gWQS models adjusted for maternal age, parental education, child's parish, and seafood consumption, we found inverse associations of the overall mixture score with ASD [MOR (95 % CI) = 0.70 (0.49, 0.99); P < 0.05) and [MOR (95 % CI) = 0.46 (0.25, 0.84); P = 0.01], respectively. In an unadjusted negative gWQS model, we found a marginally significant interaction between GSTP1 and a mixture of three metals (Pb, Hg, and Mn) ( P = 0.07) while the association was no longer significant after adjustment for the same covariates ( P = 0.24). Conclusions: Differences in diet between ASD and control groups may play a role in the inverse associations we found. The possible interactive association between Mn and GSTP1 in ASD based on gWQS is consistent with our previous reports. However, possible interaction of GSTP1 with Pb and Hg in ASD requires further investigation and replication.