grant

Developmental methylomics of autism spectrum disorder

Organization VIRGINIA COMMONWEALTH UNIVERSITYLocation RICHMOND, UNITED STATESPosted 1 Apr 2021Deadline 31 Jan 2027
NIHUS FederalResearch GrantFY2025ASDActive Follow-upAffectAgeAlgorithmsAssayAutismAutistic DisorderAutopsyBindingBioassayBioconductorBiological AssayBirthBloodBlood Reticuloendothelial SystemBlood SampleBlood specimenBrainBrain DiseasesBrain DisordersBrain Nervous SystemCase-Base StudiesCase-Comparison StudiesCase-Compeer StudiesCase-Referent StudiesCase-Referrent StudiesCase/Control StudiesCausalityCo(beta)-cyano-7''-(2-methyl)adeninylcobamideDNA IntegrationDNA MethylationDNA Methylation RegulationDNA SequenceDNA analysisDataDevelopmentDiagnosisEarly DiagnosisEarly Infantile AutismEarly InterventionEncephalonEncephalon DiseasesEnvironmentEnvironmental FactorEnvironmental Risk FactorEpidemiologic analysisEpigeneticEpigenetic ChangeEpigenetic MechanismEpigenetic ProcessEquationEtiologyGWA studyGWASGender BiasGenesGeneticGenetic predisposing factorGenomicsGenotypeGoalsHuman GenomeIndividualInfantile AutismIntracranial CNS DisordersIntracranial Central Nervous System DisordersInvestigationKanner's SyndromeMachine LearningMediatingMethylationModelingMolecular InteractionNeonatalNeurodevelopmental DisorderNeurological Development DisorderParticipantParturitionPhenotypePopulationPredicting RiskProcessProtocolProtocols documentationPsychiatryRNA SeqRNA sequencingRNAseqRiskRisk FactorsRoleSEQ-ANSamplingSequence AnalysesSequence AnalysisSex BiasSiteStatistical Data AnalysesStatistical Data AnalysisStatistical Data InterpretationTimeUniversitiesVariantVariationVirginiaWhole BloodX Chromosomeactive followupadult youthagesanalyze DNAautism spectral disorderautism spectrum disorderautistic spectrum disorderbiobankbiorepositorybirthing individualbirthing patientbirthing peoplecase-controlled studiescausationcell typechromatin modificationdevelopmentaldisease causationdisease riskdisorder riskearly detectionenvironmental riskepidemiologic evaluationepigeneticallyexome sequencingexome-seqexperiencefactor Afollow upfollow-upfollowed upfollowupforecasting riskgenetic informationgenetic risk factorgenome scalegenome wide associationgenome wide association scangenome wide association studygenome-widegenomewidegenomewide association scangenomewide association studyhigh dimensional datahuman whole genomeimprovedin uteroindividual who gives birthinherited factormachine based learningmethylation biomarkermethylation markermethylomemethylomicsmultidimensional datamultidimensional datasetsnecropsyneurodevelopmental diseasenovelpatient who gives birthpeople giving birthpeople who birthpeople who give birthphenotypic datapopulation basedpostmortempredict riskpredict riskspredicted riskpredicted riskspredicting riskspredictive riskpredicts riskprenatalrisk predictionrisk predictionssample collectionscreeningscreeningssocial rolespecimen collectionstatistical analysistranscriptome sequencingtranscriptomic sequencingunbornwhole genome association analysiswhole genome association studyyoung adultyoung adult ageyoung adulthood
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Full Description

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects ~1% of the population.
Progress has been made in elucidating the genetics of ASD through large-scale genome-wide association

studies (GWAS) and whole-exome sequencing (WES) studies that have identified several loci associated with

ASD. However, a substantial fraction of ASD status cannot be explained by genetic sequence variation. There

are multiple reasons to expect that DNA methylation (DNAm) may account for part of this unexplained

variation. First, part of the ASD-related genes identified via DNA sequence variation include genes involved in

chromatin modification and DNAm. Second, ASD likely originates during prenatal development, a period of

dynamically regulated changes in DNAm in the brain. As this remodeling may result in epimutations that can

dysregulate brain function, disruption of the DNAm regulation in utero represents a plausible ASD risk

mechanism. Third, ASD is associated with several neonatal and other environmental risk factors. Because

DNAm can be modified by environmental factors, it may mediate the effect of these risk factors on ASD.

The overall aims of this project is to enhance our understanding of DNAm in ASD etiology, and use DNAm

marks at for early detection of individuals at risk for ASD. For this purpose we will generate methylome-wide

data using samples from ASD cases age 18-25 years and matched controls from an existing Swedish case-

control study called Population-based Autism Genetics and Environment Study. In addition, we will use stored

neonatal blood samples to generate a second methylation profile for these same individuals at birth. Thus, we

will have methylome-wide data from blood for two time-points from all participants, accompanied by

longitudinal phenotype information spanning birth to current date obtained from the Swedish registers.

We will use a sequencing-based approach to assay the DNAm status of nearly all 28 million common CpG

sites in the human genome and will perform a battery of novel statistical analyses including methylome-wide

association studies (MWAS) of whole blood and individual cell-types in blood; analyses integrating DNAm

information with neonatal risk factors and already existing GWAS and WES data; and studies exploring the role

of DNAm in the ASD sex-bias. Significant findings will be replicated in four existing and independent blood

sample collections, and studied in the newly generated methylation/expression data from ASD brain samples.

Finally, we propose to use neonatal DNAm markers to create multi-marker methylation risk scores (MRSs) for

predicting ASD risk.

Grant Number: 5R01MH124981-05
NIH Institute/Center: NIH

Principal Investigator: Karolina Aberg

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