POSTERABSTRACTS - ASHG...ent CpG sites covering 96% of RefSeq genes. It provides comprehensive gene...

American Society of Human Genetics 63rd Annual MeetingOctober 22–26, 2013 Boston

POSTER ABSTRACTSThe program and abstract/poster board number next to each listing is followed by a W (Wednesday), or T (Thursday), or F(Friday) to indicate the day on which authors must be present at their poster boards. Posters will remain on the boards for allthree days (Wednesday through Friday).

Abstract/Poster Abstract/PosterBoard Numbers Board Numbers

Session Topic/Title Start # End # Session Topic/Title Start # End #Epigenetics 412 511Genome Structure, Variation and Function 512 694Pharmacogenetics 695 743Complex Traits and Polygenic Disorders 744 1180Psychiatric Genetics, Neurogenetics and

Neurodegeneration 1181 1430Bioinformatics and Genomic Technology 1431 1693Statistical Genetics and Genetic Epidemiology 1694 1942Evolutionary and Population Genetics 1943 2105Cardiovascular Genetics 2106 2260Therapy for Genetic Disorders 2261 2312Metabolic Disorders 2313 2406

Genetics/Genomics Education 2407 2424Ethical, Legal, Social and Policy Issues in

Genetics 2425 2476Genetic Counseling 2477 2500Health Services Research 2501 2521Clinical Genetic Testing 2522 2639Clinical Genetics and Dysmorphology 2640 2816Prenatal, Perinatal and Reproductive Genetics 2817 2884Molecular Basis of Mendelian Disorders 2885 3160Development 3161 3187Cytogenetics 3188 3257Cancer Genetics 3258 3507

Posters should remain on the board for all three days (Wednesday through Friday)

POSTER AUTHOR SCHEDULEThe program and abstract/poster board number next to each listing is followed by a W (Wednesday), T (Thursday), or F (Friday)to indicate the day on which authors must be present at their poster boards. Refer to the schedule below for presentation timesand for the poster mounting/removal schedule. Posters should remain on the boards for all three days.

Wednesday10:00 am–10:30 am Authors place posters on boards10:00 am–6:00 pm Posters open for viewing10:30 am–12:30 pm Poster Session I (W)

10:30 am–11:30 am (odd poster board numbers; author must be present)11:30 am–12:30 pm (even poster board numbers; author must be present)

Thursday10:00 am–4:30 pm Posters open for viewing10:30 am–12:30 pm Poster Session II (T)


Friday10:00 am–2:00 pm Posters open for viewing10:30 am–12:30 pm Poster Session III (F)


2:00 pm–2:30 pm Authors must remove posters2:30 pm Exhibit Hall and Posters closed

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Copyright © 2013 The American Society of Human Genetics. All rights reserved.

Posters: Epigenetics 1

412TQuality Control and Data Normalisation in large Illumina InfiniumHumanMethylation450 Datasets. A. Drong1, B. Lehne2, M. Loh2,3, C.Blancher1, M.-R. Jarvelin2,3,4,5, C.M. Lindgren1, P. Elliott2,4, M.I. McCar-thy1,6, J.S. Kooner7, J.C. Chambers2. 1) Wellcome Trust Centre for HumanGenetics, University of Oxford, Oxford, United Kingdom; 2) Epidemiologyand Biostatistics, Imperial College London, London, United Kingdom; 3)3Institute of Health Sciences, University of Oulu, Oulu, Finland; 4) 4MRC-HPA Centre for Environment and Health, Imperial College London, London,United Kingdom; 5) National Institute of Health and Welfare, Universityof Oulu, Oulu, Finland; 6) Oxford Centre for Diabetes Endocrinology andMetabolism, University of Oxford, Oxford, United Kingdom; 7) National Heartand Lung Institute, Imperial College London, London, United Kingdom.

Objectives: We aimed to develop methodology for epigenome-wide associ-ation studies (EWAS) of DNA methylation. This includes assessments andoptimisation of current approaches for data preprocessing for use on large-scale datasets (N>2,000). Methods: The EpiMigrant DNA methylation dataset was generated using the Illumina HM450 platform and includes baselineDNA samples of non-diabetic South Asians (N=2,687), approximately halfof whom went on to develop diabetes. Of these samples, 36 were measuredin duplicate to constitute the replication subset. We filtered methylationscores by a Bonferroni-corrected detection p-value, cutoff, instead of thedefault value of p 1.5 inter-quartile range). Wethen assessed two different methods for normalisation of methylation scoresacross arrays using the probe- wise correlation between duplicates in thetechnical replication dataset: QN1, quantile normalisation on Beta values,separated by probe type and colour channel into three categories and QN2,quantile normalisation on intensity values, further separated by methylatedor unmethylated targets into six categories. Results:. We find that using theBonferroni-corrected threshold (p=0.8)between the two duplicates. QN1 increases this proportion to 10.6%, whileQN 2 leads to 21.8% of probes reproducing (r>=0.8). The remaining highpercentage of weakly performing probes can be explained by experimentalvariation exceeding inter-individual variation in methylation. These invariantmarkers are also unlikely to give rise to an association signal. Conclusion:We conclude that any analysis of large-scale EWAS data should be basedon probes filtered for a Bonferroni-corrected detection p-value. To furtherincrease data quality, we recommend separate quantile normalisation onintensities of the six different probe categories.

413FIntegrating genotype, methylome, chromatin states and disease statein a cohort of 750 individuals. M.L. Eaton1, G. Srivastava2, A. Kundaje1,L.B. Chibnik2, B.T. Keenan2, J. Ernst3, D. Bennett4, B. Bernstein5, P.DeJager2, M. Kellis1. 1) CSAIL, MIT, Cambridge, MA; 2) NeurosciencesInstitute, Brigham & Women’s Hospital, Boston, MA; 3) UCLA, Los Angeles,CA; 4) Rush University Medical Center, Chicago, IL; 5) MassachusettsGeneral Hospital, Boston, MA.

While the methodological framework for relating genotype to disease hasbeen well established through the development of genome-wide associationstudies, the incorporation of intermediate molecular phenotypes such asDNA methylation and histone modifications into disease studies remainslargely unexplored. Using a cohort of 750 individuals, half of whom werediagnosed with Alzheimer’s Disease (AD), we sought to address the relation-ship between genotype, methylation status, chromatin state, and disease.Our first challenge was to nullify DNA methylation variability not attributableto genotype or AD, as several covariates confound this relationship includinggender, batch and cell type tissue heterogeneity. We used methods includingICA and non-negative least squares to computationally remove this variation.We were then able to discover ~55K CpG probes with detectable genotypeassociations in cis (~12% of the array). These CpGs are preferentiallylocated in enhancers and underrepresented in promoters based on a chro-matin map generated by chromHMM on 7 histone marks of a matchedbrain region, suggesting distinct regulatory architectures. In associating DNAmethylation changes with Alzheimer’s disease, we found a pervasive signalof small effect size, robustly enriched for distal enhancer regions. Moreover,by linking the distal enhancers to the genes they regulate by correlatingchromatin with gene expression, we found robust concentrations of associ-ated CpGs in certain neuron- and signaling-specific gene pathways. Interest-ingly, disease-associated CpGs were enriched for meQTLs of weak effectbut depleted for meQTLs of strong effect even after permutation, arguingfurther for a model of many loci of weak effect contributing overall to adisease onset burden. Overall, our results suggest that global regulatorychanges are associated with complex disease, and suggest a general meth-odology for integration of genetic and epigenetic variation in the context ofhuman disease.

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414TEpigenome-wide DNA methylation study reveals hypermethylated col-lagen genes and suggests a role for TGFβ in osteoarthritis. M.A. Jef-fries1,2, J.A. James2, A.H. Sawalha3. 1) Medicine, University of OklahomaHealth Sciences Center, Oklahoma City, OK; 2) Arthritis & Immunology,OMRF, Oklahoma City, OK; 3) Rheumatology, University of Michigan, AnnArbor, MI.

Background: Osteoarthritis (OA) is the leading cause of chronic disabilityin the U.S., affecting 40% of individuals over the age of 70 and costing $128billion annually in the US alone. Late-stage OA chondrocytes exhibit ahost of gene transcription changes leading to upregulation of enzymes thatcontribute to cartilage breakdown. Herein, we characterize epigenome-wideDNA methylation changes in osteoarthritic compared to healthy cartilagefrom the same joints. Methods: Articular cartilage tissue from 12 OA femoralheads was dissected from affected and normal areas, frozen in liquid nitro-gen, and DNA extracted. Following sodium bisulfite-treatment, DNA methyla-tion was quantified at >485,000 CpG sites across the genome using IlluminaHumanMethylation450 arrays. CpG sites with an absolute methylation differ-ence between OA and normal cartilage (∆β) ≥ 15%, and P

Posters: Epigenetics2

416TDiurnalRhythmsofClockGeneDNAMethylation and theirRelationshipto Rhythms of Clock Gene Expression in the Human Cerebral Cortex.A.S. Lim1, G.P. Srivastava2,3, L. Yu4, A.S. Buchman4, J.A. Schneider4,A.J. Myers5, D.A. Bennett4, P.L. De Jager2,3. 1) Division of Neurology,Sunnybrook Health Sciences Centre, University of Toronto, Toronto,Ontario, Canada; 2) Department of Neurology, Brigham and Women's Hospi-tal, Harvard Medical School, Boston, MA; 3) Program in Medical and Popula-tion Genetics, Broad Institute, Cambridge, MA; 4) Rush Alzheimer's DiseaseCenter, Rush University Medical Center, Chicago, IL; 5) Department ofPsychiatry, University of Miami, Miami, FL.

BACKGROUND: The mammalian circadian clock is regulated by a highlyconserved series of ‘clock’ genes participating in a near 24-h transcription-translation negative feedback loop. Recent work in Neurospora has sug-gested that rhythms of DNA methylation in or near clock genes may playa role in regulating the core circadian clock. However, whether such rhythmsare also present in human tissues, and how they relate to clock geneexpression, is uncertain. METHODS: We quantified DNA methylation at 128CpG sites in or near 6 canonical clock genes - PER2, PER3, CRY1, CRY2,ARNTL, and CLOCK - using Illumina Infinium HumanMethylation450microarray data from dorsolateral prefrontal cortex samples from 753deceased individuals in 2 cohort studies of older individuals, the ReligiousOrders Study and the Rush Memory and Aging Project. We quantified tran-script abundance for these genes using Illumina Human HT-12 Expressionmicroarray data from a subset of 490 of these individuals. Transcript abun-dance and methylation level at each CpG site was parameterized as afunction of time of death using cosine curves. RESULTS: Significant dailyrhythms of methylation were seen in 63/128 CpG sites (p


420TIndependent contribution of epigenetic modifications within lipopro-tein metabolism genes to plasma lipid profile variability. S.P. Guay1,2,D. Brisson2,3, B. Lamarche4, D. Gaudet2,3, L. Bouchard1,2. 1) Departmentof Biochemistry, Université de Sherbrooke, Sherbrooke, Qc, Canada; 2)ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, Qc, Canada;3) Department of Medicine, Université de Montréal, Montréal, Qc, Canada;4) Institute of Nutrition and Functional Foods, Université Laval, Québec,Qc, Canada.Background: Inheritance plays a central role in the determination of

plasma levels of lipids by explaining up to 60% of the interindividual variabil-ity. However, the gene polymorphisms identified so far explain less than25% of the heritability of plasma lipid levels. Recent studies suggest thatepigenetic modifications (DNA methylation), a non-traditional hereditary fac-tor, could explain a significant proportion of the missing heritability of complextraits, such as plasma lipid levels. Objective: To assess whether the DNAmethylation of key genes of the lipoprotein metabolism is associated withchanges in fasting plasma lipid levels (high-density lipoprotein cholesterol(HDL C), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG))in patients with familial hypercholesterolemia (FH) carrying the same LDLRmutation (p.W66R). Methods/Results: In the current study, 98 untreatedFH patients (61 men and 37 women) were recruited. Blood DNA methylationlevels were measured at the ABCA1, ABCG1, CETP, LCAT, LDLR, LIPC,LPL, PLTP and SCARB1 gene loci using bisulfite pyrosequencing. PartialPearson’s correlation analysis showed that DNA methylation levels at theABCA1, ABCG1, CETP, LIPC, LPL and PLTP gene loci were significantlyassociated with HDL-C, LDL-C and/or TG levels in a sex-specific mannerin FH (all p


424TDose-dependent effect of in utero smoking on DNAmethylation amongLatino children in a methylome-wide association study. S.S. Oh1, D.Hu1, C.R. Gignoux1, J.M. Galanter1, S. Huntsman1, D. Torgerson1, C. Eng1,L.A. Roth1, A. Davis2, H.J. Farber3, P.C. Avila4, E. Brigino-Buenaventura5,M.A. LeNoir6, K. Meade2, D. Serebrisky7, L.N. Borrell8, W. Rodríguez-Cintrón9, R. Kumar10, J.R. Rodríguez-Santana11, F. Lurmann12, E.Burchard1. 1) UC San Francisco, San Francisco, CA; 2) Children's Hospitaland Research Center Oakland, Oakland, CA; 3) Baylor College of Medicineand Texas Children’s Hospital, Houston, TX; 4) Feinberg School of Medicine,Northwestern University, Chicago, IL; 5) Kaiser Permanente-Vallejo MedicalCenter, Vallejo, CA; 6) Bay Area Pediatrics, Oakland, CA; 7) Jacobi MedicalCenter, Bronx, NY; 8) City University of New York, Bronx, NY; 9) VeteransCaribbean Health System, San Juan, Puerto Rico; 10) The Ann and RobertH. Lurie Children’s Hospital of Chicago, Chicago, IL; 11) Centro de Neumo-logia Pediatrica, San Juan, Puerto Rico; 12) Sonoma Technology, Pet-aluma, CA.

It is known that in utero smoke exposure leads to changes in DNA methyla-tion of specific genomic regions (CpG loci). However, the extent to whichDNA methylation is affected by the amount of exposure is unknown. Wehypothesized that DNA methylation patterns vary by the ‘dose’ of in uterosmoking. To investigate the association of DNA methylation with in uterosmoking, we conducted a methylome-wide association study (MeWAS) on528 Latino children from the GALA II Study, a nation-wide case-controlstudy of Latino children with and without asthma. Methylation status at>480,000 CpG loci was assessed using the Infinium HumanMethylation450BeadChip. We used robust linear regression to test the association betweenCpG methylation and the number of trimesters that children were exposedto in utero smoking, adjusting for sex, age, ethnicity, asthma status, plate,position, and the first 10 principal components of variation within our data set.

The most significant differentially methylated locus in our MeWAS was inthe first exon of FAM83A. For each trimester a mother smoked duringpregnancy, her child had 2% less methylation (p = 4.9E−7; FDR < 0.05).Two additional suggestive loci include ABL2 (1.2% less methylation pertrimester, p = 3.2E−6; FDR < 0.10) and WNT3A (0.5% less methylation pertrimester, p = 4.4E−6; FDR < 0.10). All three genes are involved in pathwaysknown to be disrupted by tobacco smoke exposure. FAM83A is expressedin the lung, and in vitro studies have found it to be upregulated in bronchialepithelial cells following exposure to tobacco smoke. ABL2 functions incytoskeletal rearrangements, and WNT3A is a key regulator of cell fate andpatterning during embryogenesis.

In a MeWAS assessing the dose-response effect of in utero tobaccosmoking, we found that in utero smoking was associated with altered methyl-ation at three biologically relevant loci. Furthermore, we found that thedegree of methylation was dose-dependent. Smoking during pregnancy isparticularly insidious not only for harming the developing fetus but also forits effects manifested in later life. Our findings underscore the importanceof tobacco prevention, control, and cessation efforts.

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425FDNA methylation profiling implicates several genes in type 2 diabetes.M.A. Carless, H. Kulkarni, M.C. Mahaney, H.H.H. Goring, L. Almasy, A.G.Comuzzie, J. Blangero. Department of Genetics, Texas BiomedicalResearch Institute, San Antonio, TX.

Type 2 diabetes (T2D) is a global epidemic, becoming increasingly preva-lent due to a rising incidence of obesity caused primarily by poor diet andlack of physical activity. The incidence of T2D is particularly high in MexicanAmericans and although the disease is known to be genetically regulated,implicated loci explain only a small portion of the genetic liability. Epigeneticregulation, such as DNA methylation, is a novel mechanism that may leadto gene dysfunction and disease development. Using Illumina HumanMethyl-ation450 BeadChips, we performed genome-wide DNA methylation profilingof >450,000 CpG sites in peripheral blood cells from 859 Mexican Americansfrom ~40 large pedigrees. In total, 20% of individuals were diagnosed withT2D and all individuals had fasting glucose measures available. NormalizedDNA methylation data underwent analysis using SOLAR to test for heritabilityof each CpG site, and for association with T2D status and fasting glucose(in non-diabetic samples only). We used the Bonferroni method to correctfor multiple comparisons. Approximately 24% of CpG sites were found tobe significantly heritable (mean h2=0.433, p


427FThe Role of Brain DNA Methylation in the Pathology of Alzheimer'sDisease: Evidence of an Interaction Effect. PL. De Jager1, 2, 3, G. Srivas-tava1, 2, 3, ML. Eaton3, 4, L. Yu5, A. Meissner3, 6, JA. Schneider5, M. Kellis3,4, DA. Bennett5, LB. Chibnik1, 2, 3. 1) Institute for the Neurosciences, Depart-ments of Neurology & Psychiatry, Brigham & Women's Hospital, Boston,MA; 2) Department of Neurology, Harvard Medical School, Boston, MA; 3)Broad Institute of MIT and Harvard, Cambridge, MA; 4) Computer Scienceand Artificial Intelligence Laboratory, MIT, Cambridge, MA; 5) Rush Alzhei-mer's Disease Center, Rush University Medical Center, Chicago, IL; 6)Department of Stem Cell and Regenerative Biology, Harvard Stem CellInstitute, Harvard University, Cambridge, MA.

The DNA methylome captures the transcriptional potential of a cell ortissue. Differential methylation of validated Alzheimer’s disease (AD) locicould influence their effect; however where methylation falls along the dis-ease pathway is unclear. We examine four causal models to assess the roleof methylation on the pathology of AD. We utilized data from two longitudinalcohorts, the Religious Order Study and Rush Memory and Aging Project.DNA methylation profiles were generated in samples of dorsolateral prefron-tal cortex using Illumina HumanMet450K beadset. We analyzed CpG siteswithin 25 kb of 11 validated AD susceptibility genes. The outcomes ofinterest were a measure of neuritic plaque (NP) accumulation and pathologicdiagnosis of AD. First, independent associations between CpGs and out-comes were assessed using linear (NP) and logistic (AD) regression. Thefour hypothesized models are: (1) CpG mediated association, (2) reversecausality, (3) independent associations and (4) SNP by CpG interaction.Both (1) and (2) were assessed using mediation analyses and (4) wasassessed for multiplicative interaction followed by stratified analyses. Cor-rection for multiple testing was done using the Benjamini-Hochberg method.A total of 719 subjects were included in the analyses. Nine CpGs across 5genes (BIN1 (3), CLU (2), MS4A6A (2), ABCA7 (1) and APOE (1)) wereassociated with the outcomes. Together they explain 13.1% of the variabilityof NP and 14.8% of AD. No gene region showed evidence for either model(1) or (2), however APOE showed evidence of (3) with 1 CpG associatedwith the outcomes but not the APOE haplotype. Most interestingly, a stronginteraction effect was seen with the CR1 in 3 CpGs at the 5’ end of thegene, cg10021878 (pinteraction = 4.5E−5, 1.3E−4), cg00175709 (pinteraction =0.003, 0.01) and cg05922028 (pinteraction = 0.004, 0.04) for NP and ADrespectively. Among those with the risk allele rs6656401AT/AA there is aninverse association between methylation and outcome, indicating moremethylation is associated with less NP and decreased odds of AD, whereasthose with rs6656401TT more methylation is associated with more NP andincreased odds of AD. Less significant interactions were also seen in BIN1,ABCA7 and PICALM. These observations suggest that, within known ADsusceptibility genes, methylation is related to pathologic processes associ-ated with AD and may play a role in influencing gene expression fromsusceptibility loci.

428TArray-based assay detects genome-wide 5-methylcytosine and 5-hydroxymethlycytosine in non-human primates and mice. R.S. Alisch1,P. Chopra2, L.A. Papale1, A.T.J. White1, A. Hatch1, P.H. Roseboom1, M.Brown1, S.T. Warren2. 1) Psychiatry, Univ. of Wisconsin School of Medicine- Madison, Madison, WI; 2) Human Genetics, Biochemistry, and Pediatrics,Emory University School of Medicine, Atlanta, GA.

Murine and non-human primates (e.g. rhesus monkeys) represent excel-lent model systems to study human health and disease conditions, especiallyin the brain. However, use of these model systems for genomic profilingstudies is limited because most array-based tools have only been developedto survey the human genome. Here we present the optimization of a widelyused human DNA methylation array, designed to detect 5-methylcytosine(5-mC), and show that non-human data generated using the optimized arrayreproducibly distinguishes tissue types within and between chimpanzee,rhesus, and mouse, with correlations near the human DNA level (R2 > 0.99).While using this assay to conduct a genome-wide methylation analysis ofrhesus placental and fetal tissues reveals 6,102 differentially methylatedloci with pathways analysis significantly overrepresented for developmentalprocesses, restricting the analysis to oncogenes and tumor suppressorsgenes finds 125 differentially methylated loci, suggesting that rhesus placen-tal tissue carries a cancer epigenetic signature. Further optimization of theassay to detect 5-hydroxymethylcytosine (5-hmC) finds highly reproducible5-hmC levels within human, rhesus, and mouse brain tissue that is species-specific with a hierarchical abundance among the three species (human >rhesus >> mouse). Together, these data show that this array-based methyla-tion assay is generalizable to all mammals for the detection of both 5-mCand 5-hmC, greatly improving the utility of mammalian model systems tostudy the role of epigenetics in human health, disease, and evolution.

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429FAirborne Particulate Matter Exposure Modifies the Canonical MAP-Kinase Pathway: FromMethylomic Analysis to Biological Implications.J.J. Carmona1,2,3,4, T. Sofer4,5, L. Cantone6, B. Coull5, A. Maity7, J.Schwartz1,2,3, X. Lin4,5, A. Baccarelli1,2,3,4,8,9. 1) Laboratory of Environmen-tal Epigenetics, Department of Environmental Health, Harvard School ofPublic Health, Boston, MA, USA; 2) Department of Epidemiology, HarvardSchool of Public Health, Boston, MA, USA; 3) Exposure, Epidemiology, &Risk Program, Department of Environmental Health, Harvard School ofPublic Health, Boston, MA, USA; 4) Program in Quantitative Genomics,Harvard School of Public Health, Boston, MA, USA; 5) Department of Biosta-tistics, Harvard School of Public Health, Boston, MA, USA; 6) Departmentof Clinical Sciences and Community Health, Università degli Studi di Milano,Milan, IT; 7) Department of Statistics, North Carolina State University,Raleigh, NC, USA; 8) Dana-Farber/Harvard Cancer Center, Boston, MA,USA; 9) Harvard/Massachusetts General Hospital Center on Genomics,Vulnerable Populations, and Health Disparities, Boston, MA, USA.

Background: Exposure to air particulate matter with an aerodynamic diam-eter < 2.5 m (PM2.5) is known to elevate blood markers of inflammationand increase cardiopulmonary morbidity and mortality. Major componentsof PM2.5 are Black Carbon (BC) due to traffic and sulfate from coal-burningpower plants. DNA methylation is known to be sensitive to environmentaltoxins and to mediate environmental effects on clinical outcomes via regula-tion of gene expression. We hypothesize that exposure to air pollutioncomponents affects DNA methylation in blood leukocytes, in genes frominflammatory pathways. Methods: 141 males from the Normative AgingStudy (NAS), residing in the Boston area, were selected. Leukocyte DNAsamples were hybridized to the RefSeq 385K Promoter tiling array (RocheNimbleGen, Madison, WI) representing the promoter regions of all well-characterized genes in the RefSeq database, as well as all of the UCSC-annotated CpG islands. Sample immunoprecipitation, labeling, hybridizationand data extraction were performed according to standard procedures opti-mized by Roche-NimbleGen. Air pollution components, BC and sulfate, weremeasured with a sensor located on the roof of the Countway Library at theHarvard Longwood Campus. 30-days moving average values of BC andsulfate were calculated for each participant at his clinical visit date. Sulfatemeasures were available for 92 of the individuals. Genes associated withthe MAP-kinase and NFkB signaling pathways were identified using theBIOCARTA website. Forward stepwise Canonical Correlation Analysis wasapplied to identify specific genes in the pathways associated with the expo-sures, and p-values were calculated using a permutation test. Analysis forthe effect of BC on the MAPK pathway was adjusted for age and sulfateexposure, and similarly for other pathways/exposures. Results: The MAPKpathway consists of 84 genes. Our analysis identified 10 genes whosemethylation was associated with BC exposure, adjusted for sulfate and age(p-value 0.01). The association analysis between sulfate and methylationin this pathway suggested 9 genes, but was not statistically significant (p-value 0.086), which is possibly due to low power. There was no evidenceof association between air pollution and methylation in the NFkB pathway.Conclusion: The effects of air pollution may influence inflammatory outcomesvia MAPK gene methylation. These results will be validated in a largersubset of men from the NAS cohort.


430TEpigenomic fetal programming: identifying genomic sites differentiallymethylated after exposure to maternal gestational diabetes andresponsive to its treatment. A.A. Houde1,2, S.M. Ruchat1,2, C. Allard3, P.Perron2,3, J.P. Baillargeon3, J. St-Pierre2,4, D. Gaudet2,5, D. Brisson2, M.F.Hivert3,6,7, L. Bouchard1,2. 1) Department of Biochemistry, Université deSherbrooke, Sherbrooke, QC, Canada; 2) ECOGENE-21 and Lipid Clinic,Chicoutimi Hospital, Saguenay, QC, Canada; 3) Department of Medicine,Université de Sherbrooke, Sherbrooke, QC, Canada; 4) Department of Pedi-atrics, Chicoutimi Hospital, Saguenay, QC, Canada; 5) Department of Medi-cine, Université de Montréal, Montréal, QC, Canada; 6) Department of Popu-lation Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; 7) Mas-sachusetts General Hospital, Boston, MA.Background: In utero exposition to gestational diabetes mellitus (GDM)

is associated with increased lifelong susceptibility to obesity and metabolicdisorders for the offspring. Recent evidences showed that epigenetic modifi-cations may be involved in the metabolic health programming of the newbornexposed to GDM. Nevertheless, whether the treatment of GDM women (dietor diet+insulin) has an impact on DNA methylation levels has not beenestablished.Hypothesis:DNA methylation at specific gene locus in placentaand cord blood is affected by exposure to GDM and its treatment. Methods:Placenta and cord blood samples were obtained from 43 women: 14 withnormoglycemia (NGT) and 29 with GDM treated with diet (n=16, GDM-D)or diet+insulin (n=13, GDM-I). GDM was diagnosed between weeks 24-28of pregnancy according to WHO criteria. DNA methylation was assessedat >485 000 CpG sites using the Infinitum HumanMethylation450 BeadArray.DNA methylation differences between the 3 groups were determined usingANCOVAs (adjustment for infant sex, gestational age, maternal BMI at 1sttrimester of pregnancy and history of GDM (Padj)) and significance of pairwisecomparisons was verified with Tukey’s test. Results: Women were on aver-age 29 years old. GDM-I women were slightly overweight at 1st trimester(BMI=27.1 kg/m2) in comparison to GDM-D and NGT (23.9 and 24.6 kg/m2) (P=0.05). In placenta exposed to GDM, lower levels of methylation wereobserved at TOX2 (P=6.8×10−7; Padj=1.2×10−6) and DPP6 (P=8.8×10−6;Padj=1.9×10−5) compared to NGT-exposed placenta. At PLB1 locus, lowermethylation levels were observed in placenta from GDM-D women (77.5%in NGT vs 73.6% in GDM-D; ANCOVA Padj=9.6×10−6), whereas levels fromGDM-I (78.2%) were similar to those from women with NGT. Similarly, incord blood, we observed that CpG sites near GNASAS (Padj=8.5×10−5)and MYH7B (Padj=4.5×10−5) were differentially methylated in offspring fromGDM-D mothers and were similar in NGT and GDM-I groups suggestingthat insulin treatment offsets the impact of GDM exposure at these loci. Incord blood, methylation levels at STC2 were lower in offspring from motherwith GDM, treated either with diet or insulin (Padj=4.0×10−5). Conclusion:Our results suggest that exposure to GDM or its treatment may influenceDNA methylation at specific locus in the placenta and cord blood. The choiceof clinical management of GDM may therefore have long lasting effect onthe offspring’s epigenome and metabolic health.


431FConvergence of genetic, epigenetic and environmental factors onCpG-SNPs associated with human disorders: implications for transcrip-tional regulation in human brain. D.R. Sarkisyan, I. Bazov, M.M.H. Taqi,H. Watanabe, O. Kononenko, V. Tashbulatov, T. Yakovleva, G. Bakalkin.Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.

Interaction between the genome, epigenome and environment is criticalfor the development of complex disorders. Expression of the genome maybe influenced by the environment by shaping epigenetic mechanisms. AtCpG-SNP sites, the genetic factors such as SNPs converge with environ-mentally-influenced epigenetic marks such as CpG dinucleotides, sites forcytosine methylation. The average occurrence rate of SNPs at a CpG siteis 10-fold higher than the overall SNP occurrence rate, thus CpG-SNPs areoverrepresented in the human genome (Xie et al., 2009). CpG dinucleotidesare 7-fold more abundant at SNP sites than expected (Tomso and Bell,2003). Correlation analysis identified allele specific methylation (ASM) on30% heterozygous SNPs, and found that up to 88% of ASM regions aredependent on the presence of CpG-SNPs (Kerkel et al., 2008; Shoemakeret al., 2010). Some CpG-SNPs may be associated with a disease, andalterations of their methylation under environmental influences may be acritical factor affecting gene expression and contributing to disease vulnera-bility. Such CpG-SNPs may be located within DNAse I hypersensitivity sites(DHSs) and targeted by generic and sequence-specific regulatory factors(RF). The CpG-SNP hypothesis received support in recent studies by usand others (John et al., 2011; Kaminsky et al., 2011; Martin-Trujillo et al.,2011; Reynard et al., 2011; Taqi et al., 2011; Ursini et al., 2011). We addressthis hypothesis by comparing abundance of CpG-SNPs and non-CpG SNPsat DHSs and binding places for 161 RFs in a panel of 91 cell lines (ENCODEreleases 1-3). We compared SNPs associated with alcohol dependence,behavioral disorders, neurodegenerative disorders, and the rest of SNPsimplicated by NHGRI GWAS Catalog. As a model gene we analyzed methyl-ation of CpG-SNPs in prodynorphin (PDYN), coding for opioid dynorphinpeptides. Three PDYN CpG-SNPs were significantly associated with alcoholdependence and differentially methylated in human brain. In the brain ofalcoholics, methylation of the C allele of SNP rs2235749 (3’-UTR; C>T; Cis non-risk variant) was increased (P


433FAn Integrated epigenomic-transcriptomic-genetic analysis of schizo-phrenia brain identifies novel molecular pathways to disease. J. Mill1,2,R. Pidsley2, J. Viana1, A. Jeffries2, C.Wong2, C. Troakes2, L. Schalkwyk2. 1)Exeter University, Exeter, Devon, United Kingdom; 2) Institute of Psychiatry,King's College London, London, United Kingdom.

Schizophrenia (SZ) is a common psychiatric disorder characterized by thepresence of psychotic symptoms and altered cognition. Although SZ is highlyheritable, the molecular etiology of the disease is largely unknown. In additionto genetic and structural genomic variation, recent evidence supports a rolefor altered epigenomic and transcriptomic processes in disease pathogene-sis. Frontal cortex and cerebellum tissue was obtained from 23 schizophreniapatients and 24 healthy controls. Genome-wide DNA methylation, expres-sion and SNP profiling were performed using the Illumina Infinium HumanMethylation450, HumanHT-12v4 Expression, HumanOmniExpress Bead-Chips respectively. Integrated multi-level analyses provide evidence of SZ-associated DNA methylation and gene expression changes at biologicallyrelevant loci, including GABBR1, RASA3, C8A, NRN1, BNIP3, GAD1 andSERPINA3. Furthermore we identify cis-eQTLs and cis-mQTLs at SZ candi-date genes nominated from published GWAS analyses, an increased burdenof CNVs in patients with SZ, and a rare NRXN1 deletion in an SZ patientthat is associated with altered DNA methylation. Together these resultsprovide important insights into the biological mechanisms underlying SZand highlight the value of taking an integrated ‘-omics’ approach to com-plex disease.

434TWhole Genome Bisulfite Sequencing of Cell Free DNA and its CellularContributors Links Placenta Hypomethylated Domains to GeneDeserts. T. Jensen1, S. Kim1, C. Chin1, Z. Zhu1, T. Lu1, C. Deciu1, D. vanden Boom2, M. Ehrich2. 1) Research and Development, Sequenom Centerfor Molecular Medicine, San Diego, CA; 2) Research and Development,Sequenom, San Diego, CA.

Circulating cell free (ccf) DNA is useful for non-invasive diagnostic testingin prenatal health and oncology. In both cases, the nucleic acid of interestis the minority species and thus needs to be differentiated from the highlyabundant ccf DNA background. DNA methylation can serve as a methodfor distinguishing these; however, this depends on an in depth knowledgeof the DNA composition. Whole genome bisulfite sequencing (WGBS) wasperformed on a set of unmatched samples including ccf DNA from 8 non-pregnant (NP) female donors, genomic DNA from 7 buffy coat and 5 placentasamples, and ccf DNA from 7 pregnant females to gain a comprehensiveunderstanding of the ccf DNA methylome in pregnant plasma. We firstcreated a methylome map of ccf DNA from non-pregnant donors at singlebase resolution. Consistent with previous work in differentiated cell types,almost all cytosine methylation in NP ccf DNA samples occurred in the CpGcontext. We also found CpG cytosines within longer fragments were morelikely to be methylated, linking DNA methylation and fragment size in ccfDNA. Next, we performed a series of pairwise comparative analyses toidentify differentially methylated regions (DMRs). Comparison of the meth-ylomes of placenta and NP ccf DNA enabled the detection of greater than50000 DMRs, the majority resulting from placenta hypomethylation. Wefound that >90% of these DMRs were located outside of CpG islands andwere often associated with distinct histone tail modifications. Further investi-gation of the identified DMRs revealed the presence of large domains exhibit-ing consistent hypomethylation in placenta samples relative to NP ccf DNAacross millions of consecutive bases. We found these domains to occurprimarily in CpG poor gene deserts. DMRs identified when comparing pla-centa to NP ccf DNA were recapitulated when comparing pregnant ccf DNAto NP ccf DNA, confirming the ability to detect differential methylation in ccfDNA mixtures. Overall, these data enabled the generation of methylomemaps for each sample type at single base resolution, identified a link betweenlocal DNA methylation and ccf DNA fragment length, provided comprehen-sive lists of DMRs between sample groups, and uncovered the presenceof megabase-size placenta hypomethylated domains. Furthermore, weanticipate these results to provide a foundation to which future studiesbased upon discriminatory DNA methylation for non-invasive testing canbe compared.


435FDNAMethylation at CPT1A is Associated with Triglyceride Levels, BMIand WHR. D.M. Absher1, M.R. Irvin2, S. Aslibekyan2, J. Sha2, L.L. Waite1,D. Zhi3, K. Stanton Thibeault1, J. Ordovas4, D.K. Arnett2. 1) HudsonAlphaInstitute for Biotechnology, Huntsville, AL; 2) Department of Epidemiology,University of Alabama, Birmingham, Birmingham, AL; 3) Department ofBiostatistics, University of Alabama, Birmingham, Birmingham, AL; 4)Department of Epidemiology, Atherothrombosis and Imaging, Centro Nacio-nal de Investigaciones Cardiovasculares, Madrid, Spain.

Epigenetic variation is thought to be a contributor to complex traits, andis likely to account for some of the missing heritability for phenotypes thathave been incompletely explained by genetic variants. As the epigenomeis dynamic and environmentally responsive, epigenetic modulators of dietarytraits and responses are likely to be critically important to the developmentof cardiovascular disease and type-2 diabetes. We have undertaken anepigenetic analysis of GOLDN (Genetics of Lipid Lowering Drugs and DietNetwork) study participants to identify DNA methylation patterns that contrib-ute to lipid metabolic traits and related phenotypes. Using the Illumina Meth-ylation450 array to measure DNA methylation at ~470,000 CpGs in CD4+T-cells from 995 individuals in 183 families, we fit mixed effects regressionmodels to identify CpGs where DNA methylation levels were strongly associ-ated with baseline triglyceride levels (TG), body mass index (BMI), andwaist-hip-ratio (WHR). We identified a CpG in the CPT1A (carnitine palmi-toyltransferase 1A) gene that was significantly associated with all three traits(p=6.9e−28 for TG, p=2.8e−11 for BMI, and p=4.7e−11 for WHR), with~2.4% of baseline TG variance explained by methylation at this locus. Giventhat CPT1A is an important regulator of fatty acid metabolism, we hypothe-sized that the impact of methylation on BMI and WHR would be mediatedthrough its effects on TG. Regression models using TG as a covariate ledto a reduced, but not eliminated, significance for BMI (p=6.8e−06) and WHR(p=2.3e−04), suggesting that CPT1A methylation has some effects on BMIand WHR that are independent of baseline TG. In addition to CPT1A, wealso identified 7 other CpGs that achieved genome-wide significance withBMI exclusively, including CpGs near the CD38, AHRR and PGHDH genes.Furthermore, 1 additional CpG near RPS6KA2 was significantly associatedwith WHR.

436TDNA Methylation Profiling is Robust in Different Tissue Types andReveals Distinct Patterns Across Rheumatoid Arthritis Samples andPhenotypes. L.F. Barcellos1, X. Shao1, E. Elboudwarej1, A. Baker1, E.Sinclair3, L.A. Criswell2. 1) Div Epidemiology-SPH, Univ California, Berkeley,Berkeley, CA; 2) Div Rheumatology, Dept Medicine, Univ California, SanFrancisco, CA; 3) The UCSF-GIVI CFAR Immunology Core, Univ California,San Francisco, CA.

Rheumatoid arthritis (RA) is a chronic inflammatory disease with potentialto cause substantial disability, primarily due to the erosive and deformingprocess in joints. RA etiology is complex with contributions from geneticand non-genetic factors. Epigenetic changes such as altered patterns ofDNA methylation (DNAm), are also present in RA. Our goal was twofold:(1) to establish a protocol for performing DNAm profiling of specific immunecell populations isolated from large numbers of samples that is cost andlabor efficient, and both accurate and reproducible; (2) to characterize DNAmprofiles in RA cases and controls across multiple cell types to identify similari-ties and differences relevant to disease status, phenotypes and pathogene-sis. We generated genome-wide DNAm profiles using Illumina HumanMeth-ylation450 BeadChips (n~22,000 genes, 459704 sites, post QC) in PBMCs,CD14+ monocytes, CD19+ B cells, and CD4+ memory and naïve T cellsin 90 individuals (60 female cases and 30 controls) from the UCSF RACohort. We investigated the impact of sample storage conditions on: cellcount, purity, DNA yields, quality and stability of DNAm profiles. The fiveoutcomes were compared between cells isolated from PBMCs, stained andsorted by FACS on the same day of blood collection, and cells isolated fromPBMCs, stained and stored overnight in buffer at 4°C and sorted the secondday following collection; all from the same individual. Results show overnightstorage did not impact the above outcomes. Background subtraction andbeta-mixture quantile normalization was applied to all case and control data.Mean DNAm levels were highly correlated between all cell types in bothcases and controls; however, CD4+ memory T cells differed more fromCD14+ monocytes (r


437FGene networks for social cognition in Williams syndrome. L. Dai1, R.Weiss2, J.R. Korenberg1. 1) Center for Integrated Neuroscience and HumanBehavior, Brain Institute, Department of Pediatrics, Univ. of Utah, Salt LakeCity, UT; 2) Human Genetics, Univ. of Utah, Salt Lake City, UT.

Williams syndrome (WS), a neurodevelopmental disorder with hypersocialbehavior, results from a deletion of ~ 28 genes on 7q11.23, that ultimatelydisturbs the neural circuitry involving oxytocin and vasopressin. Althoughcognitive deficits and social-emotional features are ultimately due to thedeleted genes, the critical downstream pathways are unknown. Previousstudies used rare WS genetic events, partial deletions seen in


441FEpigenetic dysregulation of ectodermal cells in autism spectrumdisor-der. E.R. Berko1, M. Suzuki1, F. Beren2, C. Lemetre1, C. Alaimo3, R.B.Calder1, K. Ballaban-GIl4, B. Gounder2, K. Kampf2, J. Kirschen1, S.B. Maq-bool1, Z. Momin1, D.M. Reynolds1, N. Russo3,5, L. Shulman6, E. Stasiek1,J. Tozour1, M. Valicenti-McDermott6, S. Wang7, B.S. Abrahams1,8, J. Hargi-tai1, D. Inbar9, Z. Zhang1, J.D. Buxbaum10, S. Molholm3, J.J. Foxe3, R.W.Marion6, A. Auton1, J.M. Greally1. 1) Center for Epigenomics and Depart-ment of Genetics (Division of Computational Genetics), Albert Einstein Col-lege of Medicine, Bronx, NY, 10461, USA; 2) Stern College for Women,Yeshiva University, New York, NY 10016, USA; 3) The Sheryl and DanielR. Tishman Cognitive Neurophysiology Laboratory, Children’s Evaluationand Rehabilitation Center, and Departments of Pediatrics and Neuroscience,Albert Einstein College of Medicine, Bronx, NY 10461, USA; 4) Departmentof Neurology, Children’s Hospital at Montefiore, Bronx, NY 10467, USA; 5)Department of Psychology, The College of Arts and Sciences, SyracuseUniversity, Syracuse, NY 13244, USA; 6) Children’s Evaluation and Rehabili-tation Center, Department of Pediatrics, Albert Einstein College of Medicine.Bronx, NY 10461, USA; 7) Information Technology Services, New YorkUniversity, New York, NY 10003, USA; 8) Department of Neuroscience,Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, NY10461, USA; 9) Child Development and Rehabilitation Institute, SchneiderChildren’s Medical Center, Petach Tikvah, Israel; 10) Seaver Autism Centerfor Research and Treatment, Departments of Psychiatry, Neuroscience, andGenetics and Genomic Sciences, and the Friedman Brain Institute, MountSinai School of Medicine, New York, NY 10023, USA.

In this study we investigated the role of the epigenome, a possible mediatorof environmental effects during development, in the pathogenesis of AutismSpectrum Disorders (ASDs). ASDs encompass a heterogeneous group ofdiseases characterized by impairments in communication and social interac-tion, and repetitive stereotyped behaviors. The prevalence of ASDs hasincreased dramatically, with current epidemiologic estimates citing a diagno-sis in 1 out of every 90 individuals. Rates of ASD rise with parental age,with fathers older than 40 and mothers older than 35 each possessinggreater independent risk of having a child with an ASD. Recent studies havehelped further elucidate the genetic basis of ASDs, investigating the role ofcopy number, common, and rare variation in the disease. However, thesefindings explain only a fraction of ASD etiology.

We tested an homogeneous ectodermal cell type from individuals withASD compared with typically developing (TD) controls born to mothers of≥35 years, using a quantitative genome-wide DNA methylation assay. Weshow that DNA methylation patterns are dysregulated in individuals withASD, performing a stringent analysis that accounted for confounding effectsdue to subject age, sex and ancestral haplotype, while also excluding mosaicaneuploidy and copy number variability in these subjects. Of note, the lociwith altered DNA methylation were found at genes expressed in the brain,genes encoding protein products significantly enriched for interactions withthose produced by known ASD-causing genes, representing a perturbationby epigenomic dysregulation of the same networks compromised by DNAmutational mechanisms.

The results indicate the presence of a mosaic subpopulation of epigenet-ically-dysregulated, ectodermally-derived cells in subjects with ASD. Theepigenetic dysregulation observed in these ASD subjects born to oldermothers may be associated with aging parental gametes, environmentalinfluences during embryogenesis or could reflect mutations of the chromatinregulatory genes increasingly implicated in ASD. The results indicate thatepigenetic dysregulatory mechanisms may complement and interact withDNA mutations in the pathogenesis of the disorder.


442TEpigenetic and ecogenetic silencing of the FMRgene unrelated to CGGTNR expansion. J. Kapalanga1,3,4,5,6, Y. Said3,7, D. Wong2,3, A. Gandy2,3,M. Moyo5,6, N. Nkiru4, A. Singh3. 1) Dept Pediatrics, Genetics, SchulichSchool of Medicine, Western University/Grey Bruce Health Services, OwenSound, ON, Canada; 2) Paediatrics, Dalhousie University, Halifax, NS Can-ada; 3) Summerside Medical Center, Summerside, PEI Canada; 4) GreyBruce Health Services, Owen Sound, ON, Canada; 5) Cambridge MemorialHospital, Cambridge, ON, Canada; 6) Pediatrics, McMaster University, Ham-ilton, ON, Canada; 7) Allergy and Pediatric Pulmonology King Fahad Special-ist Hospital, Dammam,Saudi Arabia.

Expansions and hypermethylation of a CGG trinucleotide repeat (TNR) atthe 5’untranslated region of the FMR1 gene results in transcriptional silenc-ing of the gene. These molecular events have been established as theunderlying cause of over 95% of patients with the Fragile-X syndrome (FXS).The commonest features of the FXS phenotype include intellectual disability,hyperactivity, impulsivity, a peculiar jovial speech, autistic features, macro-cephaly, macrotia, and macroorchidism. In a behavioral and developmentalpediatric practice it is common to see patients with the FXS phenotype butwithout molecular demonstration of the CGG TNR expansion in the abnormalrange. In this study pediatric patients were ascertained through multicentergeneral, behavioral and developmental pediatrics clinics over a 10 yearperiod. Patients were identified after presenting with a constellation of atleast four common FXS phenotypic features including, intellectual disability,hyperactivity, autistic features, and distinctive craniofacial features. Duringthe 10 year period 798 patients with the FXS phenotype, were tested forFXS by currently established molecular methods. Chromosomal studieswere also done in all 798 patients. All patients were found to have CGGrepeat size of 5 - 45 in their FMR1 gene and chromosomal studies werenormal. Point mutations are rare (


443FMultiple methylation errors at imprinting control regions in patientswith S-adenosylhomocysteine hydrolase (AHCY) deficiency. U.Zechner1, A. Fitzner1, J. Knežević2, M. Polović2, N. El Hajj3, E. Schneider3,R. Belužić 2, S.H. Mudd4, T. Haaf3, O. Vugrek2. 1) Institute of HumanGenetics, University Medical Center of the Johannes Gutenberg UniversityMainz, Mainz, Germany; 2) Division of Molecular Medicine, Institute RuerBošković, Zagreb, Croatia; 3) Institute of Human Genetics, University ofWürzburg, Germany; 4) Laboratory of Molecular Biology, National Instituteof Mental Health, Bethesda, MD.

S-adenosylhomocysteine hydrolase (AHCY) deficiency is a novel humandisease, which was first discovered in Croatia in 2004. Main characteristicsare psychomotor delay and severe myopathy (hypotonia, absent tendonreflexes and delayed myelination) from birth, associated with hypermethioni-naemia, elevated serum creatine kinase levels and increased genome-wideDNA methylation. The prime function of AHCY is the efficient removal ofS-adenosylhomocysteine (SAH), the by-product of transmethylation reac-tions. As SAH is one of the most potent methyltransferase (MT) inhibitors,its rapid removal is crucial to avoid product inhibition of MTs. Thus, AHCYplays a critical role in regulation of biological methylation processes. Weset out to more specifically characterize DNA methylation changes in bloodDNA samples of seven AHCY-deficient patients as well as HepG2 andHEK293 cell lines after shRNA-mediated knockdown of the AHCY gene bydetermining the DNA methylation levels at differentially methylated regions(DMRs) of seven imprinted genes (MEST, NESPAS, SNRPN, LIT1, H19,GTL2 and PEG3) as well as Alu and LINE-1 repetitive elements. Analysisof the imprinted gene DMRs revealed abnormal methylation levels withmoderate to strong hypermethylation at several DMRs in three of the sevenpatients and rather normal differential methylation patterns in the other fourpatients. The knockdown cell lines also exhibited methylation changes todifferent degrees at the analyzed DMRs. Methylation analysis of Alu andLINE-1 repetitive elements demonstrated no methylation abnormalities.Microarray-based experiments to analyze the complete DNA methylome ofAHCY-deficient patients in comparison to normal individuals are in progress.The finding of hypermethylation in the patients' DNA samples is oppositeto what is expected considering the inhibitory effect of SAH on MTs. As anexplanation for this finding, it can be speculated that only some MTs areinhibited and, thus, leave excess substrate for other specific DNA MTs notsensitive to increased SAH levels and functioning properly. Our preliminarydata indicate that AHCY deficiency may represent a good model diseasefor studying the biological consequences of multiple methylation errors inepigenetic research. Thus, findings from this study may make an importantcontribution to develop standard and high-throughput tools for the diagnosisof AHCY deficiency and other diseases associated with aberrant epige-netic modifications.

444TDNA differential methylation is observed at BRCA1 promoter but notin 8q24.21 in cleft lip and palate. L. Alvizi, G.S. Kobayashi, C.B.F. Silva,D.Y. Sunaga,D.F. Bueno,M.R.S. Passos-Bueno.Genetics and EvolutionaryBiology, University of São Paulo, São Paulo, Sao Paulo, Brazil.

Purpose: DNA methylation is known to be a heritable regulatory mecha-nism in gene expression and influenced by both genetic and environmentalfactors. It is also known that impairment in gene methylation status maylead to gene expression dysregulation and thus disease. In this context,cleft lip and palate (CL/P) is a congenital craniofacial malformation withhigh incidence (1:700 live births) strongly determined by the genetic andenvironmental interplay in which epigenetic factors such as DNA methylationare very plausible factors in the malformation etiology. Aiming to investigateDNA methylation at specific sites to CL/P, we investigated whether BRCA1, previously associated to CL/P (Kobayashi and Alvizi et al, 2013 PloS ONE),and 8q24.21 CL/P risk region were differentially methylated in CL/P samplesin comparison to control samples. Methods: Bisulfite sequencing analysisfor BRCA1 promoter was performed in a DNA sample set obtained fromdental pulp stem cells (DPSC) of 18 CL/P and 12 controls and for 8q24region in a DNA sample set from white blood cells DNA of 34 CL/P and 44controls. A total of 300 clones for BRCA1 promoter and 780 clones for8q24.21 were sequenced and analysis was performed using BISMA (Bisul-fite Methylation Analysis - BPCD online tool). BRCA1 expression was alsoassessed by qRT-PCR in the DPSC sample. Results/Conclusions: TotalBRCA1 promoter methylation was significantly higher (+1,4%) in the DPSCCL/P sample. Besides, BRCA1 promoter CpGs 1, 2 and 11 were the mosthipermethylated in the CL/P sample (17.8%, 30.2% and 23.1%, respec-tively). As expected, BRCA1 expression was significantly reduced in compar-ison to controls (p=0.001). No evidence of differential methylation at the8q24.21 cleft lip risk locus was found in the white blood cells DNA sampleof CLP patients as compared to controls. Our results suggest that downregu-lation of BRCA1 in CL/P samples may be driven by increased BRCA1promoter methylation and the causative factors in this hypermethylationshould be next investigated. BRCA1 expression rescue by promoter demeth-ylation is being conducted in DPSC CL/P samples. FAPESP/CNPq-MCT.


445FWidespread changes in DNA methylation at CpG island shores anddistal regulatory regions in response to a bacterial infection. L.B. Bar-reiro1,2, A. Pacis2,3, L. Tailleaux4, V. Yotova2, J.C. Grenier2, R. Pique-Regi6,K.D. Hansen7, Y. Gilad5. 1) Department of Paediatrics, Faculty of Medicine,University of Montréal, Montréal, Canada; 2) Ste-Justine Hospital ResearchCentre, Montreal, Canada; 3) Department of Bioinformatics, Faculty of Medi-cine, University of Montréal, Montréal, Canada; 4) Unité de GénétiqueMyco-bactérienne, Pasteur Institute, Paris, France; 5) Department of HumanGenetics, University of Chicago, Chicago, USA; 6) Department of MolecularMedicine and Genetics, Wayne State University, Detroit, USA; 7) Depart-ment of Biostatistics, Johns Hopkins Bloomberg School of Public Health,Baltimore, USA.

DNA methylation is an essential epigenetic modification for gene regula-tion, development, and disease processes. Recent studies have reported thedynamic nature of DNA methylation in response to different environmentalconditions in mammalian cells. To better understand the role of DNA methyl-ation in immune responses to infection, we collected single-base pair resolu-tion methylation profiles of dendritic cells (DCs) before and after infectionwith Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis(TB). We identified 1695 differentially methylated regions (DMRs) genome-wide that span 300 hundred base pairs on average. Our findings show thatchanges in methylation do not occur in CpG islands and promoters butrather in low CpG-density regions, namely in CpG shores and distal regula-tory regions. By using DNAse hypersensitivity sites (DHS) data we showthat DMRs are enriched among DHS, which are strong predictors of openchromatin and active regulatory regions. We also observed a significantoverlap of DMRs with enhancer regions as well as regions bound by tran-scription factors of key importance in immune responses, such as NF-κB.Finally, we show that DMRs are enriched within close proximity of genesthat were differentially expressed genes after MTB infection. Specifically,we show that 25% of the genes that change expression after infectionalso have a DMR in close proximity. Genes close to DMRs that are hypo-methylated after MTB infection tend to be up-regulated upon infection,whereas genes close to hyper-methylated DMRs tend to decrease theirexpression levels. These findings suggest a mechanistic link betweenchanges in DNA methylation and changes in gene expression after MTBinfection. Importantly, our results suggest that methylation levels might bemore dynamic than previously thought, particularly in response to an infec-tious agent.

446TAcceleration of age-associated methylation patterns in peripheralblood of HIV-1-infected adults.R.M. Baxter1, T.M. Rickabaugh2, M. Sehl2,J.S. Sinsheimer1, O. Martinez-Masa3, S. Horvath1, E. Vilain1, B.D. Jami-son2. 1) Human Genetics, UCLA, Los Angeles, CA; 2) Medicine, divisionof Hem./Onc., UCLA, Los Angeles, CA; 3) Medicine, divsion of OB & GYN,UCLA, Los Angeles, CA.

Young HIV-1-infected adults, even when successfully treated with anti-retroviral therapy, are prone to diseases more commonly associated witholder uninfected adults. In addition, HIV-1-infection has been shown to haveadditive, detrimental effects, with aging on both cell number and telomerelength within peripheral lymphocytes suggesting that HIV-1-infection accel-erates aging in these cells by at least 10 years. However, it remains unknownwhether aging and HIV-1-infection exert these effects through similar, ordisparate, mechanisms. As we had previously identified methylation patternsassociated with aging in uninfected adults, we tested whether HIV-1-infectionwould induce methylation changes associated with aging. Utilizing Infiniummethylation arrays, we evaluated methylation levels at more than 450,000CpG sites in DNA isolated from peripheral blood mononuclear cells (PBMC)obtained from the Multicenter AIDS Cohort Study (MACS), a longitudinalstudy of HIV-1 infection. Samples were from young (20–24 years) and olderadults (48–56 years). Each group consisted of 12 HIV-1-infected individualsand 12 age-matched uninfected controls. We examined the relationshipbetween differential methylation across age and HIV-1 infection and foundthat CpG sites with a positive age correlation were often also hypermethyl-ated in HIV-1 infected individuals. A smaller number of sites correlated withdecreased methylation in both aging and HIV-1-infeciton. Weighted geneco-methylation network analysis (WGCNA) identified 11 modules in the databased on methylation levels. CpG sites within module 7 were significantlycorrelated with both age and HIV-1 status. Using this module we demon-strated that HIV-1 infection accelerated age-related methylation by about13 years. Examination of the genes related to the CpGs in this moduleshowed enrichment for polycomb group targets, genes such as SOX1,SOX8, PENK, MYOD1, and NPTX2 that are known to be involved in cellrenewal and aging. These data demonstrate that HIV-1 infection is associ-ated with methylation patterns that are similar to those associated with agingin the general population. The acceleration of aging due to HIV-1 infectionby 13 years fits well with other studies on the effects of HIV-1 in the immunesystem. Taken together these data suggest that HIV-1-infection does accel-erate some aspects of aging and that general aging and HIV-1 related agingwork through at least some common mechanisms.


447FMethylation QTLs often show opposite allelic directions when compar-ing different tissues. M.J. Bonder1, S. Kasela2,3, K. Kirotar3, M. Kals2, M.Ivanov4, A. Metspalu2,3, M. Ingelman-Sundberg4, C. Wijmenga1, A. Zherna-kova1, L. Milani2, L. Franke1. 1) Genetics, University Medical Center Gron-ingen, Groningen, Groningen, Netherlands; 2) Estonian Genome Center,University of Tartu, Tartu, Estonia; 3) Institute of Molecular and Cell Biology,University of Tartu, Tartu, Estonia; 4) Section of Pharmacogenetics, Depart-ment of Physiology and Pharmacology, Karolinska Institutet, Stockholm,Sweden.Introduction It is clear that many disease-associated genetic variants

affect gene expression (eQTL mapping). However, this effect is often tissuespecific. We recently observed that within the same individuals eQTLs canshow opposite allelic directions when comparing different tissues (Fu etal, PLoS Genetics 2012, Fairfax et al, Nature Genetics 2012). Here weinvestigated whether the same phenomena can be observed when investi-gating the effects of genetic variants on methylation (meQTL mapping)Material and Methods We collected genotype, expression and methyla-

tion data from 94 Swedish liver samples. This was combined with a setof 84 Dutch individuals for whom we collected genotype, expression andmethylation from liver, saturated adipose tissue, visceral adipose tissue andmuscle. We performed eQTL and mQTL mapping in each of these tissues.Results In the liver data we identified 2,920 significant meQTL probes

and 443 significant eQTL probes after stringent multiple testing correction(estimated false discovery rate = 0). When investigating the other threetissues, we found that around 80% of the meQTLs and around 50% of theeQTLs that were identified in the non-liver datasets were also present inliver. We then assessed whether these overlapping QTL signals had consis-tent allelic directions. For the eQTLs we did not identify probes which showedan opposite effects in liver as compared to the other tissues. However, weobserved 14 unique methylation probes, which gave significant oppositeallelic effects in liver as compared to the three other tissue types. As wedid not observe any opposite allelic effects when comparing the meQTLsdetected in the individual Swedish and Dutch liver samples, we believe the14 probes with opposite allelic effects reflect true positive results.Conclusion In this study we found that around 80% of the meQTLs are

shared between different tissues, but we also identified a few meQTLs thatshowed completely opposite allelic effects when comparing different tissues.We thus conclude that careful selection of the tissue of interest is crucialwhen it comes to interpretation of both methylation and expression QTLresults.

448TPredicting Prostate Cancer Progression through Gene Network Analy-sis of Methylation Data. L. Briollais, K. Kron, B. Bapat, H. Ozcelik. SamuelLunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, M5T1L9, Canada.

Promoter and 5' end methylation regulation of tumour suppressor genesis a common feature of many cancers. Such occurrences often lead to thesilencing of these key genes and thus they may contribute to the develop-ment of cancer, including prostate cancer. In order to identify methylationchanges in prostate cancer progression, we performed a genome-wideanalysis of DNA methylation using Agilent human CpG island arrays avail-able on 20 patients (10 with Gleason score 6 and 10 with Gleason score8). Our first set of analyses identified a large number of potential epigeneticbiomarkers of prostate cancer progression, including various genes belong-ing to the Homeobox family. The second set of analyses aimed at construct-ing a gene network around the Homeobox genes and use this informationas a predictive tool for prostate cancer progression. The different modelsfound in the second stage of our analysis showed an excellent predictiveability and these models were further validated in an independent data setof methylation data as well as in a gene expression data set. We finallydiscuss various statistical approaches for gene network analysis includinggraphical models. Our conclusion is that gene network analysis can providea very sensible and comprehensive framework for understanding the geneticbasis of complex human diseases and for identifying individuals the moresusceptible to disease progression.


449FA pilot study testing DNA methylation profiles in Samoan obese andlean young adult males. O.D. Buhule1, N.L. Hawley5, M. Medvedovic3,R.L. Minster2, G. Sun3, H. Cheng4, S. Viali6, R. Deka3, D.E. Weeks1,2,S.T. McGarvey7. 1) Department of Biostatistics, Graduate School of PublicHealth, University of Pittsburgh, Pittsburgh, PA, USA; 2) Department ofHuman Genetics, Graduate School of Public Health, University of Pittsburgh,Pittsburgh, PA, USA; 3) Department of Environmental Health, University ofCincinnati, Cincinnati, Ohio 45367, USA; 4) Department of EnvironmentalHealth, University of Cincinnati College of Medicine, Cincinnati, OH, USA;5) Weight Control and Diabetes Research Center, The Miriam Hospital,Providence, RI, USA & The Alpert Medical School, Brown University, Provi-dence, RI, USA; 6) Medical Specialist Clinic and National Health Services,Government of Samoa, Apia, Samoa; 7) International Health Institute andDepartment of Epidemiology, Brown University School of Public Health,Providence, RI 02912, USA.

Background and Objective: Methylation levels, which influence geneexpression, can be influenced by environment and life style. Obesity, as aproduct of both nutritional environment and life style, could be related tomethylation levels. Here we present preliminary findings from a pilot studyexamining DNA methylation patterns across the genome in young obeseand lean male Samoans to identify epigenetic loci associated with obesity.Methods: DNA was extracted from whole peripheral blood from 46 obese(BMI >=32 & Abdominal Circumference >=92.5cm) and 46 lean (BMI


450TDNA Methylation Alterations in CHARGE Patients with HeterozygousCHD7Mutations.D.T. Butcher1, D. Grafodatskaya1, D.W.X.Wei1,W. Rear-don2, B. Gilbert-Dussardier3, A. Verloes4, F. Bilan5, B. Papsin6,7, R. Badilla-Porras8, R. Mendoza-Londono8, R. Weksberg1,8,9. 1) Genetics & GenomeBiology, Sickkids Research Institute, Toronto, Ontario, Canada; 2) NationalCentre for Medical Genetics, Our Lady's Children's Hospital, Dublin, Ireland;3) Service de Génétique, Centre de Référence Anomalies du Développe-ment de l'Ouest, CHU Poitiers, France; 4) AP-HP, Groupe Hospitalier Pitié-Salpêtrière, UF de Génétique Clinique, Paris, France; 5) Institut de Physiolo-gie et Biologie Cellulaires, Centre National de la Recherche ScientifiqueUnité Mixte de Recherche, Université de Poitiers, CHU Poitiers, France;6) Otolaryngology, The Hospital for Sick Children, Toronto, Canada; 7)Department of Otolaryngology, The University of Toronto, Toronto, Canada;8) Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto,Canada; 9) Department of Paediatrics, The University of Toronto,Toronto, Canada.

CHARGE syndrome (CHARGE) is a rare autosomal dominant geneticdisorder, with an incidence of 1 in 8500–10000 births. Clinical diagnosis forCHARGE is based on non-random associations of the following congenitalabnormalities: Coloboma of the eye, Heart defects, Atresia of the choanae,Retarded growth and development, Genital abnormalities, Ear abnormali-ties/deafness/vestibular disorder. In the majority of cases, CHARGE is theresult of haploinsufficiency due to a nonsense, missense, or deletion inthe gene encoding Chromodomain Helicase DNA-binding protein (CHD7).Targeted mutational studies in Drosophila (kismet) and mouse (Chd7) havefound phenotypes similar to those found in human. In Drosophila reducedexpression of kismet/CHD7 results in deficits in axonal pruning, guidanceand extension as well as defects in memory and motor function. Normalmammalian growth and development depend on the correct epigenetic pro-gramming of the genome. Epigenetic patterns evolve across developmentutilizing mechanisms such as DNA methylation and covalent modificationsof histone proteins. In Drosophila, kismet the ortholog of human CHD7 hasbeen demonstrated to regulate the repressive histone H3 methylation markof lysine 27. In human cell lines, CHD7 has been shown to bind to chromatinregions that are active as demonstrated by histone H3 lysine 4 methylationand DNAse1 hypersensitivity of these binding sites. CHD7 also interactswith RNA polymerase II, forming complexes that alter chromatin structureto facilitate access for transcriptional machinery. These epigenetic modifica-tions of histone H3 are tightly linked to DNA methylation patterns. We hypoth-esized that specific DNA methylation alterations occur as a result of theheterozygous CHD7 mutations and could reveal critical downstream targetsassociated with CHARGE clinical features. We have analyzed cases withCHD7 mutations comparing their methylation alterations to age and sex-matched controls using the Illumina Inifinium Methylation450 BeadChiparray. Data were analyzed using the IMA package in R and Genome Studiosoftware from Illumina. We identified both gain and loss of methylation ingenes that play a role in growth and neurodevelopment. The identificationof these epigenetic modifications could lead to an improved understandingof the pathophysiology of CHARGE and the type of chromatin regions towhich CHD proteins are recruited.

451FContribution of DNA methylation to gene expression varies by tissueand age. C. Chen1,2, C. Zhang1,2, L. Cheng1,2, J. Badner4, E. Gershon4,J. Sweeney5, J. Reilly6, J. Bishop1,3, C. Liu1,2. 1) Psychiatry, University ofIllinois at Chicago, Chicago, IL; 2) Institute of Human Genetics, Universityof Illinois at Chicago, Chicago, IL; 3) Department of Pharmacy, University ofIllinois at Chicago, Chicago, IL; 4) Department of Psychiatry and BehavioralNeuroscience, The University of Chicago, Chicago, IL; 5) Department ofPsychiatry, University of Texas Southwestern, Medical Cetner, Dallas, TX;6) Psychiatry, Northwestern University, Chicago, IL.

DNA methylation, as an epigenetic mark on CpG dinucleotides, was con-sidered to simply block the binding of transcription factors in promoter regionand repress gene expression. However, recent studies showed that DNAmethylation functions vary with genomic context and tissues. We systemati-cally evaluated correlations between expression of individual genes andDNA methylation at cis-regions in brain cerebellum (CB), prefrontal cortex(PFC), and blood and lymphatic endothelial cells (LEC). We found that lessthan 5% of the genes were significantly correlated with DNA methylationlevel within one specific tissue. Many other genes have their expressioncorrelated with methylation by tissue types or across life span while theirexpressions have little variation within one tissue of limited age range.Positive correlations were observed in all tests. CpG sites from correlatedpairs were more dynamic and tissue-specific in CpG-poor regions. Genesinvolved in age-dependent methylation regulation were enriched with braindevelopment functions. CpG sites in promoter CpG Island (CGI) were morelikely to be consistently unmethylated, and corresponding regulated geneswere enriched for acetylation functions. These diverse correlations sug-gested complexity of the roles of DNA methylation in regulating gene expres-sion. DNA methylation of most CpG sites may have been used to definespatiotemporal gene expression patterns, i.e., tissue and age variations,while much fewer CpG sites mediate variations of gene expression withintissue in human population for individual differences.


452TEffective adjustment of differential cell populations in epigenome-wideassociation studies. J. Chen1, J. Huang2, L. Liang1,2, X. Lin1. 1) Depart-ment of Biostatistics, Harvard School of Public Health, Boston, MA; 2)Department of Epidemiology, Harvard School of Public Health, Boston, MA.

Epigenome-wide association studies, which investigate an associationbetween epigenetic variation and phenotypic variation, have attractedincreasing attention recently, especially given the availability of the InfiniumHumanMethylation450 BeadChip. Blood samples are routinely collected formeasuring DNA methylation. However, blood is a mixture of different celltypes, each with a unique methylation pattern. Differential cell populationsbetween case and control samples can potentially confound the associationsof interest. Several approaches have been proposed to estimate cell propor-tions and include them as covariates in a regression model. The effective-ness of this strategy depends on the quality and completeness of a referencepanel of purified cell types, which are not always available. We propose toadjust for the confounding of cell mixtures using PCA (Principle ComponentAnalysis), SVA (Surrogate Variable Analysis) and ISVA (Independent Surro-gate Variable Analysis). Our proposed method is easily to be carried outand does not require a reference panel. By including the estimated principlecomponents (PCs) or surrogate variables (SVs) in regression models, thesemethods correct the inflation of QQ-plots under the null due to cell mixtureconfounding and improve power when true signal presents. We demonstrateby simulation that the proposed methods can capture the cell proportionsas low as 3% in presence of batch effects and population stratification, andISVA is more efficient in capturing the proportions of rare cell types, whileall methods perform similarly for dominant cell types. We further show thatPCA but not SVA/ISVA breaks down when a large number of true signalsare mixed with false signals due to confounding. We apply the methods toseveral 450K methylation data sets and find that the first few PC/SVs aresufficient to capture the proportions of dominant cell types - neutrophil andlymphocyte, while rare cell types such as eosinophil require more PC/SVs.Our results show that SVA/ISVA provide a convenient and effective approachto adjust for differential cell populations as well as other batch effects andpopulation stratification in epigenome-wide association studies.


453FA specific DNA methylation signature associated with NSD1+/- muta-tions in Sotos syndrome reveals a significant genome-wide loss ofDNA methylation (DNAm) targeting CGs in regulatory regions of keydevelopmental genes. S. Choufani1, C. Cytrynbaum2, A.L. Turinsky3, 4,Y.A. Chen1, D. Grafodatskaya1, J. Xiang1, M. Feigenberg2, B.Y.H. Chung5,D.J. Stavropoulos6, R. Mendoza-Londono2, D. Chitayat2, W.T. Gibson7, M.Reardon8, M. Brudno1,4,9, R. Weksberg1,2. 1) Program in Genetics andGenome Biology, Hosp Sick Children, Toronto ON, Canada; 2) Div Clin &Metabolic Gen, Hosp Sick Children, Toronto, ON, Canada; 3) MolecularStructure & Function, Hosp Sick Children, Toronto, ON, Canada; 4) Centrefor Computational Medicine, Hosp Sick Children, Toronto, ON, Canada; 5)Dept of Paediatrics & Adolescent Med, Li Ka Shing Faculty of Medicine,Hong Kong; 6) Paediatric Laboratory Medicine, Hosp Sick Children, Toronto,ON, Canada; 7) Dept. of Medical Genetics, UBC, Child and Family ResearchInstitute, Vancouver, BC, Canada; 8) Our Lady's Hospital for Sick Children,Crumlin, Dublin 12, Ireland; 9) Department of Computer Science and Don-nelly Centre, University of Toronto, Toronto, ON, Canada.

Sotos syndrome (SS) is characterized by somatic overgrowth and intellec-tual disability. Most SS cases (>75%) have mutations in NSD1 (nuclearreceptor-binding SET domain protein 1). NSD1 binds near promoter ele-ments and regulates transcription initiation and elongation via interactionswith H3-K36Me and RNA polymerase II. To determine if NSD1 mutationsimpact stable epigenetic marks such as DNA methylation (DNAm), we com-pared DNAm in peripheral blood DNA from SS cases with NSD1 mutations(NSD1+/−; n=20) to controls (n=30) using the Illumina Infinium450methyla-tion BeadChip. Differential DNAm analysis using non-parametric statistics(with correction for multiple testing) coupled with permutation analyses iden-tified a surprisingly high number (n=2157) of differentially methylated (DM)CG sites (with >20% difference in DNAm) between SS and controls. Thesesites were distributed across the genome; 95% demonstrated loss of DNAm.Using unsupervised hierarchical clustering of the 2157 DM CG sites, all SScases with NSD1 +/− clustered as a distinct group separate from controls.Moreover, DNAm at these sites clearly distinguished SS (NSD1+/−) fromWeaver syndrome (EZH2+/-, n=5), another overgrowth syndrome which hasconsiderable phenotypic overlap with SS. These results suggest that theseDM CG sites constitute a DNAm signature that is specific for NSD1+/−.Also, the DNAm signature was successfully used to reclassify NSD1 variantsof unknown significance (VUS) in six cases of SS into functionally damaging(n=1) and non-pathogenic (n=5) variants. The majority of these DM CGsmapped to enhancers and CpG island shores. Analysis of ChIP-seq datashowed that NSD1+/− specific CG sites are associated with reducedH3K36me3 marks in both normal blood and embryonic stem cells. Also,Ingenuity analysis showed enrichment in neural and cellular developmentpathways (p


456TGenome-wide DNA methylation profiles in fruit flies and the effectof huntingtin knockout. S. Erdin1, K. Dietz1,2, A. Ragavendran1, M.E.Talkowski1,3,5, J.A.Walker1,3, J.F. Gusella1,4,5. 1) Center for Human GeneticResearch, Massachusetts General Hospital, Boston, MA; 2) Louisiana StateUniversity Health Sciences Center, Shreveport, LA; 3) Department of Neurol-ogy, Harvard Medical School, Boston, MA; 4) Department of Genetics, Har-vard Medical School, Boston, MA; 5) Program in Medical and PopulationGenetics, Broad Institute, Cambridge, MA.

The definitive presence of DNA methylation in Drosophila melanogasterhas not yet been established and, if present, the epigenetic role at specificloci will need to be determined. We previously detected different DNA methyl-ation levels in male and female wild type fruit flies using immunologicalmethods with antibodies specific for 5'-Methylcystosine (5mC) and 5'-Hydroxymethlcystosine, suggesting genome-wide methylation is present. Inthis study, we hypothesized that (a) DNA methylation is present in the maleand female adult flies, (b) the pattern of DNA methylation is gender-specific,and (c) the loss of huntingtin protein results in genome-wide differentialmethylation compared to wild-type flies. We conducted a methylated DNAimmunoprecipitation (meDIP) sequencing experiment that profiles methyla-tion patterns on a genome-wide scale based on enrichment using antibodiesspecific for 5mC. Extracting DNA from the adult fly’s brain, we prepared eightsequencing libraries with 47.3 million 50 bp paired-end reads on average foreach of wild-type and huntingtin-null male and female flies with 5mC and5hmC specific antibodies and their counterparts with no antibodies for com-parison. For analysis, we followed a computational protocol involving: qualityfiltering of reads by Sickle, sequence alignment to the fruit fly referencegenome by BWA and subsequent filtering of alignments by SamTools. Toidentify peaks and differentially methylated regions and their annotation, weused standard tools specifically designed for meDIP-seq analysis, Medipsand peak callers, MACS and Homer. Our preliminary results based ondifferentially methylated regions identified by Medips relying on edgeR’sstatistical analysis (FDR < 0.001) and methylation peaks identified by MACS(p-value < 1e−5) confirm the presence of global DNA methylation in the fly,reveals genome-wide gender-specific differences, and suggest differentialmethylation associated with loss of huntingtin. Replication of these findingsand further downstream analyses are ongoing, but these data confirm thepresence of methylated DNA sites in Drosophila melanogaster and suggesta significant role of huntingtin in epigenetic modification.

457FA novel method for identification and quantification of consistentlydifferentially methylated genomic regions. C. Fann1, C.L. Hsiao1, C.J.Chang2. 1) Epidemiology & Genetics, Inst Biomed Sci, Acad Sinica, Taipei,Taiwan; 2) Graduate Institute of Clinical Medical Science, Chang GungUniversity, Taoyuan, Taiwan.

Advances in biotechnology have resulted in large-scale studies of DNAmethylation. A differentially methylated region (DMR) is a genomic regionwith multiple adjacent CpG sites that exhibit different methylation statusesamong multiple samples. Many so-called ‘supervised’ methods have beenestablished to identify DMRs between two or more comparison groups.Methods for the identification of DMRs without reference to phenotypicinformation are, however, less well studied. An alternative ‘unsupervised’approach was proposed, in which DMRs in studied samples were identifiedwith consideration of nature dependence structure of methylation measure-ments between neighboring probes from tiling arrays. Through simulationstudy, we investigated effects of dependencies between neighboring probeson determining DMRs where a lot of spurious signals would be producedif the methylation data were analyzed independently of the probe. In contrast,our newly proposed method could successfully correct for this effect with awell-controlled type I error and a comparable statistical power. Identificationof DMRs in a population of samples is vital for understanding methylationvariation within a dataset. By applying to two real datasets, we demonstratethat our method provides a more global picture of methylation variationeither between groups or between individuals in a single screen.


458TEpigenetic changes in relation to asbestos exposure in malignantpleural mesothelioma. G. Fiorito1 ,2, S. Guarrera1, E. Casalone1 ,2, M.Betti3, E. Aldieri4, D. Ferrante5, C. Di Gaetano1 ,2, F. Rosa1, A. Russo1 ,2,S. Tunesi5, M. Padoan5, A. Aspesi3, C. Casadio6, F. Ardissone7, E. Ruffini8,P.G. Betta9, R. Libener9, R. Guaschino10, E. Piccolini11, D. Mirabelli12, 13, C.Magnani5, 13, I. Dianzani3, 13, G. Matullo1, 2. 1) Human Genetics Foundation,HuGeF, I-10126 Turin, Italy; 2) Department of Medical Sciences, Universityof Turin, I-10100, Turin, Italy; 3) Laboratory of Genetic Pathology, Depart-ment Health Sciences, University of Piemonte Orientale, I-28100, Novara,Italy; 4) Department of Oncology, University of Turin, I-10126, Turin, Italy; 5)CPO-Piemonte and Unit of Medical Statistics and Epidemiology, DepartmentTranslational Medicine, University of Piemonte Orientale, I-28100, Novara,Italy; 6) Thoracic Surgery Unit, University of Piemonte Orientale, I-28100,Novara, Italy; 7) Chest Surgery, Department of Clinical and Biological Sci-ences, University of Turin, I-10043, Orbassano, Italy; 8) Thoracic SurgeryUnit, University of Turin, I-10126, Turin, Italy; 9) Pathology Unit, AziendaOspedaliera Nazionale SS, Antonio e Biagio e Cesare Arrigo, I-15121,Alessandria, Italy; 10) Transfusion Centre, Azienda Ospedaliera NazionaleSS, Antonio e Biagio e Cesare Arrigo, I-15121, Alessandria, Italy; 11) Pneu-mology Unit, Santo Spirito Hospital, I-15033, Casale Monferrato, Italy; 12)Unit of Cancer Epidemiology, CPO-Piemonte and University of Turin, I-10126, Turin, Italy; 13) Interdepartmental Center for Studies on Asbestosand other Toxic Particulates ‘G. Scansetti ’, University of Turin, I-10125,Turin, Italy.

Malignant pleural mesothelioma (MPM) is a rare and aggressive tumorstrongly associated with asbestos exposure. Only 5–17% of individualsexposed to asbestos develop MPM, suggesting the involvement of otherenvironmental, genetic and epigenetic risk factors. DNA methylation is animportant mechanism of gene silencing in human malignancies. The relation-ship between aberrant DNA methylation and inflammation has been docu-mented in many types of cancers, including MPM. Asbestos exposure maycontribute to MPM onset through this relationship. We conducted an epigen-ome-wide scan to identify differentially methylated regions (DMR) in 40 MPMcases versus 40 controls, and in asbestos high-exposed versus low-exposedsubjects. Methylation status was measured for about 470K CpG sites inDNA from whole blood, using the HumanMethylation450 BeadChip (Illumina,S. Diego, CA). Logistic regression analysis after adjustment for age, genderand center of recruitment showed no significant association with MPM ofany single CpG methylation profile. However, a regional analysis showedmultiple significant signals in several genomic regions. In particular, a signifi-cant decreased methylation (P


459FGenetic Ancestry Explains Differences in Global and Local MethylationPatterns in the GALA II Study. J.M. Galanter1, C.R. Gignoux1, S.S. Oh1,D.G. Torgerson1, C. Eng1, S. Huntsman1, L. Roth1, D. Hu1, S. Sen1, M.Pino-Yanes1, E. Nguyen1, P. Avila2, H.J. Farber3, A. Davis4, E. Birgino-Buenaventura5, M.A. Lenoir6, K. Meade4, D. Serebrisky7, S. Thyne8, W.Rodriguez-Cintrón 9, R. Kumar10, J.R. Rodriguez-Santana11, E.G.Burchard1. 1) University of California, San Francisco San Francisco, CA;2) Feinberg School of Medicine, Northwestern University, Chicago, IL; 3)Baylor College of Medicine and Texas Children’s Hospital, Houston, TX; 4)Children's Hospital and Research Center Oakland, Oakland, CA; 5) KaiserPermanente-Vallejo Medical Center, Vallejo, CA; 6) Bay Area Pediatrics,Oakland, CA; 7) Jacobi Medical Center, Bronx, NY; 8) San Francisco Gen-eral Hospital, San Francisco, CA; 9) Veterans Carribean Health System,San Juan, PR; 10) The Ann and Robert H. Lurie Children’s Hospital ofChicago, Chicago, IL; 11) Centro de Neumologia Pediatrica, San Juan, PR.

Epigenetic modification of the genome through methylation plays a key rolein the regulation of diverse cellular processes. Changes in DNA methylationpatterns have been associated with many complex diseases. Recent studieshave found significant differences in the methylation patterns of peripheralblood between African Americans and non-Hispanic Whites. In this study,we leveraged estimates of genomic ancestry in 575 Latino children of multi-ple Latino ethnicities (Puerto Rican, Mexican, and other) enrolled in theGALA II study of childhood asthma to determine whether differences in globaland local methylation patterns between ethnic groups could be explained byancestry. We measured DNA methylation at ~450,000 markers using theIllumina Infinium HumanMethylation450 BeadChip. We used multidimen-sional scaling to determine global methylation patterns. Ethnicity was signifi-cantly associated with the sixth principal coordinate (p < 2 × 10−16 for theoverall effect of ethnicity on PC6 and for the comparison of Puerto Ricansto Mexicans). Native American ancestry, when added to the model, wasalso highly associated with the principal coordinate, and its inclusion in themodel eliminated the significance of the association between ethnicity andthe methylation pattern measured by PC6. We then performed an epigen-ome-wide association study between ethnicity and methylation at each site.There was a significant association between ethnicity and local methylationpatterns at 1356 sites at a Bonferoni corrected significance level (1.4 ×10−7). We performed a mediation analysis to determine the extent to whichgenomic ancestry mediated the effect of ethnicity on local methylation. Ofthe 316 methylation sites with a p-value less than 1 × 10−10, 40 (13%)were significantly mediated by Native American ancestry. The median pro-portion of the effect of ethnicity on methylation mediated by Native Americanancestry was 66% across all sites. An epigenome-wide association studybetween Native American Ancestry and methylation found 309 sites with aBonferoni corrected significance level of 1.4 × 10−7 or below. These findingshave broad implications for the study of methylation patterns across popula-tions and for disease association studies. There significant differences inmethylation patterns between ethnic groups that are due to ancestry differ-ences in those groups. These differences should be accounted for in per-forming epigenome wide disease association studies.

460TA fast and simple method for whole genome bisulfite sequencinglibrary preparation from ultra-low DNA input: Pico-MethylSeq librarypreparation kit. K. Giang, T. Chung, X. Sun, X. Jia. Zymo Research Corpo-ration, Irvine, CA.

The distribution of 5-methylcytosine (5-mC) in DNA within the eukaryoticgenome is known to greatly affect gene regulation and is currently a majortopic of research. Studies on DNA methylation have been aided by advance-ments in bisulfite conversion and next-gen sequencing technologies which,when coupled, provide single-base resolution of 5-mC in the whole genome.Many whole-genome bisulfite sequencing (WGBS) library preparation proto-cols designed to analyze 5-mC distribution in the whole genome employbisulfite to convert unmethylated cytosine bases to uracil after the librarypreparation and whi

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