Environmental influences measured by epigenetic clock and vulnerability components at birth impact clinical ASD heterogeneity

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dc.contributor.authorNeri de Souza Reis V.
dc.contributor.authorTahira A.C.
dc.contributor.authorGastaldi V.D.
dc.contributor.authorMari P.
dc.contributor.authorPortolese J.
dc.contributor.authorDos Santos A.C.F.
dc.contributor.authorLisboa B.
dc.contributor.authorMari J.
dc.contributor.authorCaetano S.C.
dc.contributor.authorBrunoni D.
dc.contributor.authorBordini D.
dc.contributor.authorde Paula C.S.
dc.contributor.authorVencio R.Z.N.
dc.contributor.authorQuackenbush J.
dc.contributor.authorBrentani H.
dc.date.accessioned2024-03-12T19:19:17Z
dc.date.available2024-03-12T19:19:17Z
dc.date.issued2021
dc.description.abstract© 2021 by the authors. Licensee MDPI, Basel, Switzerland.Although Autism Spectrum Disorders (ASD) is recognized as being heavily influenced by genetic factors, the role of epigenetic and environmental factors is still being established. This study aimed to identify ASD vulnerability components based on familial history and intrauterine environmental stress exposure, explore possible vulnerability subgroups, access DNA methylation age acceleration (AA) as a proxy of stress exposure during life, and evaluate the association of ASD vulnerability components and AA to phenotypic severity measures. Principal Component Analysis (PCA) was used to search the vulnerability components from 67 mothers of autistic children. We found that PC1 had a higher correlation with psychosocial stress (maternal stress, maternal education, and social class), and PC2 had a higher correlation with biological factors (psychiatric family history and gestational complications). Comparing the methylome between above and below PC1 average subgroups we found 11,879 statistically significant differentially methylated probes (DMPs, p < 0.05). DMPs CpG sites were enriched in variably methylated regions (VMRs), most showing environmental and genetic influences. Hypermethylated probes presented higher rates in different regulatory regions associated with functional SNPs, indicating that the subgroups may have different affected regulatory regions and their liability to disease explained by common variations. Vulnerability components score moderated by epigenetic clock AA was associated with Vineland Total score (p = 0.0036, adjR2 = 0.31), suggesting risk factors with stress burden can influence ASD phenotype.
dc.description.issuenumber9
dc.description.volume12
dc.identifier.doi10.3390/genes12091433
dc.identifier.issn2073-4425
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/34594
dc.relation.ispartofGenes
dc.rightsAcesso Aberto
dc.subject.otherlanguageASD
dc.subject.otherlanguageExome
dc.subject.otherlanguageMethylation
dc.subject.otherlanguagePsychiatry
dc.subject.otherlanguageRisk factors
dc.subject.otherlanguageVulnerability components
dc.titleEnvironmental influences measured by epigenetic clock and vulnerability components at birth impact clinical ASD heterogeneity
dc.typeArtigo
local.scopus.citations4
local.scopus.eid2-s2.0-85115662398
local.scopus.subjectAdolescent
local.scopus.subjectAdult
local.scopus.subjectAge Factors
local.scopus.subjectAutism Spectrum Disorder
local.scopus.subjectBrazil
local.scopus.subjectChild
local.scopus.subjectChild, Preschool
local.scopus.subjectCircadian Clocks
local.scopus.subjectDisease Susceptibility
local.scopus.subjectDNA Methylation
local.scopus.subjectEnvironment
local.scopus.subjectEpigenesis, Genetic
local.scopus.subjectFemale
local.scopus.subjectGene-Environment Interaction
local.scopus.subjectGenetic Heterogeneity
local.scopus.subjectHumans
local.scopus.subjectInfant
local.scopus.subjectInfant, Newborn
local.scopus.subjectMale
local.scopus.subjectMiddle Aged
local.scopus.subjectParturition
local.scopus.subjectPregnancy
local.scopus.subjectRisk Factors
local.scopus.subjectVulnerable Populations
local.scopus.subjectYoung Adult
local.scopus.updated2024-12-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115662398&origin=inward
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