Case-control meta-analysis of blood DNA methylation and autism spectrum disorder
Abstract Background Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2018-06-01
|
| Series: | Molecular Autism |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13229-018-0224-6 |
| _version_ | 1818522312306065408 |
|---|---|
| author | Shan V. Andrews Brooke Sheppard Gayle C. Windham Laura A. Schieve Diana E. Schendel Lisa A. Croen Pankaj Chopra Reid S. Alisch Craig J. Newschaffer Stephen T. Warren Andrew P. Feinberg M. Daniele Fallin Christine Ladd-Acosta |
| author_facet | Shan V. Andrews Brooke Sheppard Gayle C. Windham Laura A. Schieve Diana E. Schendel Lisa A. Croen Pankaj Chopra Reid S. Alisch Craig J. Newschaffer Stephen T. Warren Andrew P. Feinberg M. Daniele Fallin Christine Ladd-Acosta |
| author_sort | Shan V. Andrews |
| collection | DOAJ |
| description | Abstract Background Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies. Methods DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample. Findings In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10− 7. Seven CpGs showed differences at p < 1 × 10− 5 and 48 at 1 × 10− 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds. Conclusions No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD. |
| first_indexed | 2024-12-11T05:31:36Z |
| format | Article |
| id | doaj.art-b59941b0d8a9406dae4c1ce6a87647b3 |
| institution | Directory Open Access Journal |
| issn | 2040-2392 |
| language | English |
| last_indexed | 2024-12-11T05:31:36Z |
| publishDate | 2018-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Molecular Autism |
| spelling | doaj.art-b59941b0d8a9406dae4c1ce6a87647b32022-12-22T01:19:25ZengBMCMolecular Autism2040-23922018-06-019111110.1186/s13229-018-0224-6Case-control meta-analysis of blood DNA methylation and autism spectrum disorderShan V. Andrews0Brooke Sheppard1Gayle C. Windham2Laura A. Schieve3Diana E. Schendel4Lisa A. Croen5Pankaj Chopra6Reid S. Alisch7Craig J. Newschaffer8Stephen T. Warren9Andrew P. Feinberg10M. Daniele Fallin11Christine Ladd-Acosta12Department of Epidemiology, Johns Hopkins Bloomberg School of Public HealthDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public HealthCalifornia Department of Public HealthNational Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and PreventionDeparment of Public Health, Section of Epidemiology, Aarhus UniversityKaiser Permanente Division of ResearchDepartment of Human Genetics, Emory University School of MedicineDepartment of Psychiatry, University of Wisconsin-MadisonDepartment of Epidemiology and Biostatistics, Drexel University School of Public HealthDepartment of Human Genetics, Emory University School of MedicineCenter for Epigenetics, Johns Hopkins School of MedicineWendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public HealthDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public HealthAbstract Background Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies. Methods DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample. Findings In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10− 7. Seven CpGs showed differences at p < 1 × 10− 5 and 48 at 1 × 10− 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds. Conclusions No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.http://link.springer.com/article/10.1186/s13229-018-0224-6DNA methylationEpigenomeAutism spectrum disordersPeripheral bloodStudy to Explore Early DevelopmentSimons Simplex Collection |
| spellingShingle | Shan V. Andrews Brooke Sheppard Gayle C. Windham Laura A. Schieve Diana E. Schendel Lisa A. Croen Pankaj Chopra Reid S. Alisch Craig J. Newschaffer Stephen T. Warren Andrew P. Feinberg M. Daniele Fallin Christine Ladd-Acosta Case-control meta-analysis of blood DNA methylation and autism spectrum disorder Molecular Autism DNA methylation Epigenome Autism spectrum disorders Peripheral blood Study to Explore Early Development Simons Simplex Collection |
| title | Case-control meta-analysis of blood DNA methylation and autism spectrum disorder |
| title_full | Case-control meta-analysis of blood DNA methylation and autism spectrum disorder |
| title_fullStr | Case-control meta-analysis of blood DNA methylation and autism spectrum disorder |
| title_full_unstemmed | Case-control meta-analysis of blood DNA methylation and autism spectrum disorder |
| title_short | Case-control meta-analysis of blood DNA methylation and autism spectrum disorder |
| title_sort | case control meta analysis of blood dna methylation and autism spectrum disorder |
| topic | DNA methylation Epigenome Autism spectrum disorders Peripheral blood Study to Explore Early Development Simons Simplex Collection |
| url | http://link.springer.com/article/10.1186/s13229-018-0224-6 |
| work_keys_str_mv | AT shanvandrews casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT brookesheppard casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT gaylecwindham casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT lauraaschieve casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT dianaeschendel casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT lisaacroen casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT pankajchopra casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT reidsalisch casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT craigjnewschaffer casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT stephentwarren casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT andrewpfeinberg casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT mdanielefallin casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder AT christineladdacosta casecontrolmetaanalysisofblooddnamethylationandautismspectrumdisorder |