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Published in: Molecular Autism 1/2018

Open Access 01-12-2018 | Short report

Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

Authors: 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

Published in: Molecular Autism | Issue 1/2018

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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.
Appendix
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Literature
1.
go back to reference Jedele KB. The overlapping spectrum of Rett and Angelman syndromes: a clinical review. Semin Pediatr Neurol. 2007;14:108–17.CrossRefPubMed Jedele KB. The overlapping spectrum of Rett and Angelman syndromes: a clinical review. Semin Pediatr Neurol. 2007;14:108–17.CrossRefPubMed
2.
go back to reference Mount RH, Charman T, Hastings RP, Reilly S, Cass H. Features of autism in Rett syndrome and severe mental retardation. J Autism Dev Disord. 2003;33:435–42.CrossRefPubMed Mount RH, Charman T, Hastings RP, Reilly S, Cass H. Features of autism in Rett syndrome and severe mental retardation. J Autism Dev Disord. 2003;33:435–42.CrossRefPubMed
4.
go back to reference Amir RE, Van den Veyver IB, Wan M, Tran CQ, Francke U, Zoghbi HY. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat Genet. 1999;23:185–8.CrossRefPubMed Amir RE, Van den Veyver IB, Wan M, Tran CQ, Francke U, Zoghbi HY. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat Genet. 1999;23:185–8.CrossRefPubMed
5.
go back to reference Wan M, Lee SS, Zhang X, Houwink-Manville I, Song HR, Amir RE, et al. Rett syndrome and beyond: recurrent spontaneous and familial MECP2 mutations at CpG hotspots. Am J Hum Genet. 1999;65:1520–9.CrossRefPubMedPubMedCentral Wan M, Lee SS, Zhang X, Houwink-Manville I, Song HR, Amir RE, et al. Rett syndrome and beyond: recurrent spontaneous and familial MECP2 mutations at CpG hotspots. Am J Hum Genet. 1999;65:1520–9.CrossRefPubMedPubMedCentral
6.
go back to reference Sutcliffe JS, Nakao M, Christian S, Orstavik KH, Tommerup N, Ledbetter DH, et al. Deletions of a differentially methylated CpG island at the SNRPN gene define a putative imprinting control region. Nat Genet. 1994;8:52–8.CrossRefPubMed Sutcliffe JS, Nakao M, Christian S, Orstavik KH, Tommerup N, Ledbetter DH, et al. Deletions of a differentially methylated CpG island at the SNRPN gene define a putative imprinting control region. Nat Genet. 1994;8:52–8.CrossRefPubMed
7.
go back to reference Kishino T, Lalande M, Wagstaff J. UBE3A/E6-AP mutations cause Angelman syndrome. Nat Genet. 1997;15:70–3.CrossRefPubMed Kishino T, Lalande M, Wagstaff J. UBE3A/E6-AP mutations cause Angelman syndrome. Nat Genet. 1997;15:70–3.CrossRefPubMed
8.
go back to reference Bell MV, Hirst MC, Nakahori Y, MacKinnon RN, Roche A, Flint TJ, et al. Physical mapping across the fragile X: hypermethylation and clinical expression of the fragile X syndrome. Cell. 1991;64:861–6.CrossRefPubMed Bell MV, Hirst MC, Nakahori Y, MacKinnon RN, Roche A, Flint TJ, et al. Physical mapping across the fragile X: hypermethylation and clinical expression of the fragile X syndrome. Cell. 1991;64:861–6.CrossRefPubMed
9.
go back to reference Vincent A, Heitz D, Petit C, Kretz C, Oberlé I, Mandel JL. Abnormal pattern detected in fragile-X patients by pulsed-field gel electrophoresis. Nature. 1991;349:624–6.CrossRefPubMed Vincent A, Heitz D, Petit C, Kretz C, Oberlé I, Mandel JL. Abnormal pattern detected in fragile-X patients by pulsed-field gel electrophoresis. Nature. 1991;349:624–6.CrossRefPubMed
10.
go back to reference Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron. 2015;87:1215–33.CrossRefPubMedPubMedCentral Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron. 2015;87:1215–33.CrossRefPubMedPubMedCentral
11.
go back to reference Pinto D, Delaby E, Merico D, Barbosa M, Merikangas A, Klei L, et al. Convergence of genes and cellular pathways dysregulated in autism spectrum disorders. Am J Hum Genet. 2014;94:677–94.CrossRefPubMedPubMedCentral Pinto D, Delaby E, Merico D, Barbosa M, Merikangas A, Klei L, et al. Convergence of genes and cellular pathways dysregulated in autism spectrum disorders. Am J Hum Genet. 2014;94:677–94.CrossRefPubMedPubMedCentral
12.
go back to reference Krumm N, O’Roak BJ, Shendure J, Eichler EE. A de novo convergence of autism genetics and molecular neuroscience. Trends Neurosci. 2014;37:95–105.CrossRefPubMed Krumm N, O’Roak BJ, Shendure J, Eichler EE. A de novo convergence of autism genetics and molecular neuroscience. Trends Neurosci. 2014;37:95–105.CrossRefPubMed
13.
go back to reference Nagarajan RP, Hogart AR, Gwye Y, Martin MR, LaSalle JM. Reduced MeCP2 expression is frequent in autism frontal cortex and correlates with aberrant MECP2 promoter methylation. Epigenetics. 2006;1:e1–11.CrossRefPubMedPubMedCentral Nagarajan RP, Hogart AR, Gwye Y, Martin MR, LaSalle JM. Reduced MeCP2 expression is frequent in autism frontal cortex and correlates with aberrant MECP2 promoter methylation. Epigenetics. 2006;1:e1–11.CrossRefPubMedPubMedCentral
14.
go back to reference Gregory SG, Connelly JJ, Towers AJ, Johnson J, Biscocho D, Markunas CA, et al. Genomic and epigenetic evidence for oxytocin receptor deficiency in autism. BMC Med. 2009;7:62.CrossRefPubMedPubMedCentral Gregory SG, Connelly JJ, Towers AJ, Johnson J, Biscocho D, Markunas CA, et al. Genomic and epigenetic evidence for oxytocin receptor deficiency in autism. BMC Med. 2009;7:62.CrossRefPubMedPubMedCentral
15.
go back to reference James SJ, Shpyleva S, Melnyk S, Pavliv O, Pogribny IP. Elevated 5-hydroxymethylcytosine in the Engrailed-2 (EN-2) promoter is associated with increased gene expression and decreased MeCP2 binding in autism cerebellum. Transl Psychiatry. 2014;4:e460.CrossRefPubMedPubMedCentral James SJ, Shpyleva S, Melnyk S, Pavliv O, Pogribny IP. Elevated 5-hydroxymethylcytosine in the Engrailed-2 (EN-2) promoter is associated with increased gene expression and decreased MeCP2 binding in autism cerebellum. Transl Psychiatry. 2014;4:e460.CrossRefPubMedPubMedCentral
16.
go back to reference James SJ, Shpyleva S, Melnyk S, Pavliv O, Pogribny IP. Complex epigenetic regulation of engrailed-2 (EN-2) homeobox gene in the autism cerebellum. Transl Psychiatry. 2013;3:e232.CrossRefPubMedPubMedCentral James SJ, Shpyleva S, Melnyk S, Pavliv O, Pogribny IP. Complex epigenetic regulation of engrailed-2 (EN-2) homeobox gene in the autism cerebellum. Transl Psychiatry. 2013;3:e232.CrossRefPubMedPubMedCentral
17.
go back to reference Zhu L, Wang X, Li X-L, Towers A, Cao X, Wang P, et al. Epigenetic dysregulation of SHANK3 in brain tissues from individuals with autism spectrum disorders. Hum Mol Genet. 2014;23:1563–78.CrossRefPubMed Zhu L, Wang X, Li X-L, Towers A, Cao X, Wang P, et al. Epigenetic dysregulation of SHANK3 in brain tissues from individuals with autism spectrum disorders. Hum Mol Genet. 2014;23:1563–78.CrossRefPubMed
18.
go back to reference Mor M, Nardone S, Sams DS, Elliott E. Hypomethylation of miR-142 promoter and upregulation of microRNAs that target the oxytocin receptor gene in the autism prefrontal cortex. Mol Autism. 2015;6:46.CrossRefPubMedPubMedCentral Mor M, Nardone S, Sams DS, Elliott E. Hypomethylation of miR-142 promoter and upregulation of microRNAs that target the oxytocin receptor gene in the autism prefrontal cortex. Mol Autism. 2015;6:46.CrossRefPubMedPubMedCentral
19.
go back to reference Ladd-Acosta C, Hansen KD, Briem E, Fallin MD, Kaufmann WE, Feinberg AP. Common DNA methylation alterations in multiple brain regions in autism. Mol Psychiatry. 2014;19:862–71.CrossRefPubMed Ladd-Acosta C, Hansen KD, Briem E, Fallin MD, Kaufmann WE, Feinberg AP. Common DNA methylation alterations in multiple brain regions in autism. Mol Psychiatry. 2014;19:862–71.CrossRefPubMed
20.
go back to reference Nardone S, Sams DS, Reuveni E, Getselter D, Oron O, Karpuj M, et al. DNA methylation analysis of the autistic brain reveals multiple dysregulated biological pathways. Transl Psychiatry. 2014;4:e433.CrossRefPubMedPubMedCentral Nardone S, Sams DS, Reuveni E, Getselter D, Oron O, Karpuj M, et al. DNA methylation analysis of the autistic brain reveals multiple dysregulated biological pathways. Transl Psychiatry. 2014;4:e433.CrossRefPubMedPubMedCentral
22.
go back to reference Shulha HP, Cheung I, Whittle C, Wang J, Virgil D, Lin CL, et al. Epigenetic signatures of autism: trimethylated H3K4 landscapes in prefrontal neurons. Arch Gen Psychiatry. 2012;69:314–24.CrossRefPubMed Shulha HP, Cheung I, Whittle C, Wang J, Virgil D, Lin CL, et al. Epigenetic signatures of autism: trimethylated H3K4 landscapes in prefrontal neurons. Arch Gen Psychiatry. 2012;69:314–24.CrossRefPubMed
23.
go back to reference Sun W, Poschmann J, Cruz-Herrera Del Rosario R, Parikshak NN, Hajan HS, Kumar V, et al. Histone acetylome-wide association study of autism spectrum disorder. Cell 2016;167:1385–1397.e11. Sun W, Poschmann J, Cruz-Herrera Del Rosario R, Parikshak NN, Hajan HS, Kumar V, et al. Histone acetylome-wide association study of autism spectrum disorder. Cell 2016;167:1385–1397.e11.
24.
go back to reference Wong CCY, Meaburn EL, Ronald A, Price TS, Jeffries AR, Schalkwyk LC, et al. Methylomic analysis of monozygotic twins discordant for autism spectrum disorder and related behavioural traits. Mol Psychiatry. 2014;19:495–503.CrossRefPubMed Wong CCY, Meaburn EL, Ronald A, Price TS, Jeffries AR, Schalkwyk LC, et al. Methylomic analysis of monozygotic twins discordant for autism spectrum disorder and related behavioural traits. Mol Psychiatry. 2014;19:495–503.CrossRefPubMed
25.
go back to reference Nguyen A, Rauch TA, Pfeifer GP, Hu VW. Global methylation profiling of lymphoblastoid cell lines reveals epigenetic contributions to autism spectrum disorders and a novel autism candidate gene, RORA, whose protein product is reduced in autistic brain. FASEB J Off Publ Fed Am Soc Exp Biol. 2010;24:3036–51. Nguyen A, Rauch TA, Pfeifer GP, Hu VW. Global methylation profiling of lymphoblastoid cell lines reveals epigenetic contributions to autism spectrum disorders and a novel autism candidate gene, RORA, whose protein product is reduced in autistic brain. FASEB J Off Publ Fed Am Soc Exp Biol. 2010;24:3036–51.
26.
go back to reference Berko ER, Suzuki M, Beren F, Lemetre C, Alaimo CM, Calder RB, et al. Mosaic epigenetic dysregulation of ectodermal cells in autism spectrum disorder. PLoS Genet. 2014;10:e1004402.CrossRefPubMedPubMedCentral Berko ER, Suzuki M, Beren F, Lemetre C, Alaimo CM, Calder RB, et al. Mosaic epigenetic dysregulation of ectodermal cells in autism spectrum disorder. PLoS Genet. 2014;10:e1004402.CrossRefPubMedPubMedCentral
27.
go back to reference Schendel DE, Diguiseppi C, Croen LA, Fallin MD, Reed PL, Schieve LA, et al. The Study to Explore Early Development (SEED): a multisite epidemiologic study of autism by the Centers for Autism and Developmental Disabilities Research and Epidemiology (CADDRE) network. J Autism Dev Disord. 2012;42:2121–40.CrossRefPubMedPubMedCentral Schendel DE, Diguiseppi C, Croen LA, Fallin MD, Reed PL, Schieve LA, et al. The Study to Explore Early Development (SEED): a multisite epidemiologic study of autism by the Centers for Autism and Developmental Disabilities Research and Epidemiology (CADDRE) network. J Autism Dev Disord. 2012;42:2121–40.CrossRefPubMedPubMedCentral
28.
go back to reference Wiggins LD, Levy SE, Daniels J, Schieve L, Croen LA, DiGuiseppi C, et al. Autism spectrum disorder symptoms among children enrolled in the Study to Explore Early Development (SEED). J Autism Dev Disord. 2015;45:3183–94.CrossRefPubMedPubMedCentral Wiggins LD, Levy SE, Daniels J, Schieve L, Croen LA, DiGuiseppi C, et al. Autism spectrum disorder symptoms among children enrolled in the Study to Explore Early Development (SEED). J Autism Dev Disord. 2015;45:3183–94.CrossRefPubMedPubMedCentral
29.
go back to reference Rutter M, Bailey A, Lord C. The social communication questionnaire: manual. Western Psychological Services. West Psychol Serv. 2003; Rutter M, Bailey A, Lord C. The social communication questionnaire: manual. Western Psychological Services. West Psychol Serv. 2003;
30.
go back to reference Mullen EM. Mullen Scales of Early Learning. Am Guid Serv Inc. 1995; Mullen EM. Mullen Scales of Early Learning. Am Guid Serv Inc. 1995;
31.
go back to reference Lord C, Risi S, Lambrecht L, Cook EH, Leventhal BL, DiLavore PC, et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30:205–23.CrossRefPubMed Lord C, Risi S, Lambrecht L, Cook EH, Leventhal BL, DiLavore PC, et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30:205–23.CrossRefPubMed
32.
go back to reference Gotham K, Risi S, Pickles A, Lord C. The Autism Diagnostic Observation Schedule: revised algorithms for improved diagnostic validity. J Autism Dev Disord. 2007;37:613–27.CrossRefPubMed Gotham K, Risi S, Pickles A, Lord C. The Autism Diagnostic Observation Schedule: revised algorithms for improved diagnostic validity. J Autism Dev Disord. 2007;37:613–27.CrossRefPubMed
33.
go back to reference Lord C, Rutter M, DeLavore P, Risi S. Autism Diagnostic Observation Schedule-WPS (ADOS-WPS). West Psychol Serv. 1999; Lord C, Rutter M, DeLavore P, Risi S. Autism Diagnostic Observation Schedule-WPS (ADOS-WPS). West Psychol Serv. 1999;
34.
go back to reference Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994;24:659–85.CrossRefPubMed Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994;24:659–85.CrossRefPubMed
35.
go back to reference Rutter M, Le Couteur A, Lord C. ADI-R: Autism diagnostic interview-revised: manual. Western Psychological Services. West Psychol Serv. 2003; Rutter M, Le Couteur A, Lord C. ADI-R: Autism diagnostic interview-revised: manual. Western Psychological Services. West Psychol Serv. 2003;
36.
go back to reference Wiggins LD, Piazza V, Robins DL. Comparison of a broad-based screen versus disorder-specific screen in detecting young children with an autism spectrum disorder. Autism Int J Res Pract. 2014;18:76–84.CrossRef Wiggins LD, Piazza V, Robins DL. Comparison of a broad-based screen versus disorder-specific screen in detecting young children with an autism spectrum disorder. Autism Int J Res Pract. 2014;18:76–84.CrossRef
37.
go back to reference Fischbach GD, Lord C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron. 2010;68:192–5.CrossRefPubMed Fischbach GD, Lord C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron. 2010;68:192–5.CrossRefPubMed
38.
go back to reference Gotham K, Pickles A, Lord C. Standardizing ADOS scores for a measure of severity in autism spectrum disorders. J Autism Dev Disord. 2009;39:693–705.CrossRefPubMed Gotham K, Pickles A, Lord C. Standardizing ADOS scores for a measure of severity in autism spectrum disorders. J Autism Dev Disord. 2009;39:693–705.CrossRefPubMed
39.
go back to reference Fortin J-P, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, et al. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 2014;15(12):503. Fortin J-P, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, et al. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 2014;15(12):503.
40.
go back to reference Triche TJ, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-level processing of Illumina Infinium DNA Methylation BeadArrays. Nucleic Acids Res. 2013;41:e90.CrossRefPubMedPubMedCentral Triche TJ, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-level processing of Illumina Infinium DNA Methylation BeadArrays. Nucleic Acids Res. 2013;41:e90.CrossRefPubMedPubMedCentral
41.
go back to reference Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinforma Oxf Engl. 2014;30:1363–9.CrossRef Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinforma Oxf Engl. 2014;30:1363–9.CrossRef
42.
go back to reference Chen Y, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics. 2013;8:203–9.CrossRefPubMedPubMedCentral Chen Y, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics. 2013;8:203–9.CrossRefPubMedPubMedCentral
43.
go back to reference Alisch RS, Barwick BG, Chopra P, Myrick LK, Satten GA, Conneely KN, et al. Age-associated DNA methylation in pediatric populations. Genome Res. 2012;22:623–32.CrossRefPubMedPubMedCentral Alisch RS, Barwick BG, Chopra P, Myrick LK, Satten GA, Conneely KN, et al. Age-associated DNA methylation in pediatric populations. Genome Res. 2012;22:623–32.CrossRefPubMedPubMedCentral
44.
go back to reference Reinius LE, Acevedo N, Joerink M, Pershagen G, Dahlén S-E, Greco D, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS One. 2012;7:e41361.CrossRefPubMedPubMedCentral Reinius LE, Acevedo N, Joerink M, Pershagen G, Dahlén S-E, Greco D, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS One. 2012;7:e41361.CrossRefPubMedPubMedCentral
45.
go back to reference Delaneau O, Zagury J-F, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods. 2013;10:5–6.CrossRefPubMed Delaneau O, Zagury J-F, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods. 2013;10:5–6.CrossRefPubMed
46.
go back to reference Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955–9.CrossRefPubMedPubMedCentral Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955–9.CrossRefPubMedPubMedCentral
47.
go back to reference Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.CrossRefPubMed Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.CrossRefPubMed
48.
go back to reference Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, et al. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010;11:587.CrossRefPubMedPubMedCentral Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, et al. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010;11:587.CrossRefPubMedPubMedCentral
50.
go back to reference Author VJCP to R by TL (versions 3 13 and 4 4) and BR (version 4 13) N that maintainers are not available to give advice on using a package they did not. gee: Generalized Estimation Equation Solver. 2015. https://CRAN.R-project.org/package=gee. Accessed 19 Jun 2018. Author VJCP to R by TL (versions 3 13 and 4 4) and BR (version 4 13) N that maintainers are not available to give advice on using a package they did not. gee: Generalized Estimation Equation Solver. 2015. https://​CRAN.​R-project.​org/​package=​gee. Accessed 19 Jun 2018.
51.
go back to reference Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet. 2007;3:1724–35.CrossRefPubMed Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet. 2007;3:1724–35.CrossRefPubMed
52.
go back to reference McGregor K, Bernatsky S, Colmegna I, Hudson M, Pastinen T, Labbe A, et al. An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies. Genome Biol. 2016;17:84.CrossRefPubMedPubMedCentral McGregor K, Bernatsky S, Colmegna I, Hudson M, Pastinen T, Labbe A, et al. An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies. Genome Biol. 2016;17:84.CrossRefPubMedPubMedCentral
54.
go back to reference Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinforma Oxf Engl. 2010;26:2190–1.CrossRef Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinforma Oxf Engl. 2010;26:2190–1.CrossRef
55.
go back to reference Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Ser B Methodol. 1995;57:289–300. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.
56.
go back to reference Tsai P-C, Bell JT. Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation. Int J Epidemiol. 2015; Tsai P-C, Bell JT. Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation. Int J Epidemiol. 2015;
57.
go back to reference Andrews SV, Ellis SE, Bakulski KM, Sheppard B, Croen LA, Hertz-Picciotto I, et al. Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder. Nat Commun. 2017;8:1011.CrossRefPubMedPubMedCentral Andrews SV, Ellis SE, Bakulski KM, Sheppard B, Croen LA, Hertz-Picciotto I, et al. Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder. Nat Commun. 2017;8:1011.CrossRefPubMedPubMedCentral
58.
go back to reference Breton CV, Marsit CJ, Faustman E, Nadeau K, Goodrich JM, Dolinoy DC, et al. Small-magnitude effect sizes in epigenetic end points are important in children’s environmental health studies: the children’s environmental health and disease prevention research center’s epigenetics working group. Environ Health Perspect. 2017;125:511–26.CrossRefPubMedPubMedCentral Breton CV, Marsit CJ, Faustman E, Nadeau K, Goodrich JM, Dolinoy DC, et al. Small-magnitude effect sizes in epigenetic end points are important in children’s environmental health studies: the children’s environmental health and disease prevention research center’s epigenetics working group. Environ Health Perspect. 2017;125:511–26.CrossRefPubMedPubMedCentral
59.
go back to reference Hannon E, Lunnon K, Schalkwyk L, Mill J. Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes. Epigenetics. 2015;10:1024–32.CrossRefPubMedPubMedCentral Hannon E, Lunnon K, Schalkwyk L, Mill J. Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes. Epigenetics. 2015;10:1024–32.CrossRefPubMedPubMedCentral
60.
go back to reference Davies MN, Volta M, Pidsley R, Lunnon K, Dixit A, Lovestone S, et al. Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol. 2012;13:R43.CrossRefPubMedPubMedCentral Davies MN, Volta M, Pidsley R, Lunnon K, Dixit A, Lovestone S, et al. Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol. 2012;13:R43.CrossRefPubMedPubMedCentral
61.
go back to reference Bakulski KM, Halladay A, Hu VW, Mill J, Fallin MD. Epigenetic research in neuropsychiatric disorders: the “tissue issue”. Curr Behav Neurosci Rep. 2016;3:264–74.CrossRefPubMedPubMedCentral Bakulski KM, Halladay A, Hu VW, Mill J, Fallin MD. Epigenetic research in neuropsychiatric disorders: the “tissue issue”. Curr Behav Neurosci Rep. 2016;3:264–74.CrossRefPubMedPubMedCentral
62.
go back to reference Montano C, Taub MA, Jaffe A, Briem E, Feinberg JI, Trygvadottir R, et al. Association of DNA methylation differences with schizophrenia in an epigenome-wide association study. JAMA Psychiatry. 2016;73:506–14.CrossRefPubMed Montano C, Taub MA, Jaffe A, Briem E, Feinberg JI, Trygvadottir R, et al. Association of DNA methylation differences with schizophrenia in an epigenome-wide association study. JAMA Psychiatry. 2016;73:506–14.CrossRefPubMed
63.
go back to reference Edgar RD, Jones MJ, Meaney MJ, Turecki G, Kobor MS. BECon: a tool for interpreting DNA methylation findings from blood in the context of brain. Transl Psychiatry. 2017;7:e1187.CrossRefPubMedPubMedCentral Edgar RD, Jones MJ, Meaney MJ, Turecki G, Kobor MS. BECon: a tool for interpreting DNA methylation findings from blood in the context of brain. Transl Psychiatry. 2017;7:e1187.CrossRefPubMedPubMedCentral
64.
go back to reference Hannon E, Schendel D, Ladd-Acosta C, Grove J, iPSYCH-Broad ASD Group, Hansen CS, et al. Elevated polygenic burden for autism is associated with differential DNA methylation at birth. Genome Med. 2018;10:19.CrossRefPubMedPubMedCentral Hannon E, Schendel D, Ladd-Acosta C, Grove J, iPSYCH-Broad ASD Group, Hansen CS, et al. Elevated polygenic burden for autism is associated with differential DNA methylation at birth. Genome Med. 2018;10:19.CrossRefPubMedPubMedCentral
65.
go back to reference Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8:21.CrossRef Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8:21.CrossRef
66.
go back to reference Johnson SB, Whitney G, McAuliffe M, Wang H, McCreedy E, Rozenblit L, et al. Using global unique identifiers to link autism collections. J Am Med Inform Assoc JAMIA. 2010;17:689–95.CrossRefPubMed Johnson SB, Whitney G, McAuliffe M, Wang H, McCreedy E, Rozenblit L, et al. Using global unique identifiers to link autism collections. J Am Med Inform Assoc JAMIA. 2010;17:689–95.CrossRefPubMed
Metadata
Title
Case-control meta-analysis of blood DNA methylation and autism spectrum disorder
Authors
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
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Molecular Autism / Issue 1/2018
Electronic ISSN: 2040-2392
DOI
https://doi.org/10.1186/s13229-018-0224-6

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