Evaluation of the diagnostic accuracy of exome sequencing and its impact on diagnostic thinking for patients with rare disease in a publicly funded health care system: A prospective cohort study.

PURPOSE: To evaluate the diagnostic utility of publicly funded clinical exome sequencing (ES) for patients with suspected rare genetic diseases. METHODS: We prospectively enrolled 297 probands who met eligibility criteria and received ES across 5 sites in Ontario, Canada, and extracted data from medical records and clinician surveys. Using the Fryback and Thornbury Efficacy Framework, we assessed diagnostic accuracy by examining laboratory interpretation of results and assessed diagnostic thinking by examining the clinical interpretation of results and whether clinical-molecular diagnoses would have been achieved via alternative hypothetical molecular tests. RESULTS: Laboratories reported 105 molecular diagnoses and 165 uncertain results in known and novel genes. Of these, clinicians interpreted 102 of 105 (97%) molecular diagnoses and 6 of 165 (4%) uncertain results as clinical-molecular diagnoses. The 108 clinical-molecular diagnoses were in 104 families (35% diagnostic yield). Each eligibility criteria resulted in diagnostic yields of 30% to 40%, and higher yields were achieved when >2 eligibility criteria were met (up to 45%). Hypothetical tests would have identified 61% of clinical-molecular diagnoses. CONCLUSION: We demonstrate robustness in eligibility criteria and high clinical validity of laboratory results from ES testing. The importance of ES was highlighted by the potential 40% of patients that would have gone undiagnosed without this test.

Bridging clinical care and research in Ontario, Canada: Maximizing diagnoses from reanalysis of clinical exome sequencing data.

We examined the utility of clinical and research processes in the reanalysis of publicly-funded clinical exome sequencing data in Ontario, Canada. In partnership with eight sites, we recruited 287 families with suspected rare genetic diseases tested between 2014 and 2020. Data from seven laboratories was reanalyzed with the referring clinicians. Reanalysis of clinically relevant genes identified diagnoses in 4% (13/287); four were missed by clinical testing. Translational research methods, including analysis of novel candidate genes, identified candidates in 21% (61/287). Of these, 24 families have additional evidence through data sharing to support likely diagnoses (8% of cohort). This study indicates few diagnoses are missed by clinical laboratories, the incremental gain from reanalysis of clinically-relevant genes is modest, and the highest yield comes from validation of novel disease-gene associations. Future implementation of translational research methods, including continued reporting of compelling genes of uncertain significance by clinical laboratories, should be considered to maximize diagnoses.

Genomics4RD: An integrated platform to share Canadian deep-phenotype and multiomic data for international rare disease gene discovery.

Despite recent progress in the understanding of the genetic etiologies of rare diseases (RDs), a significant number remain intractable to diagnostic and discovery efforts. Broad data collection and sharing of information among RD researchers is therefore critical. In 2018, the Care4Rare Canada Consortium launched the project C4R-SOLVE, a subaim of which was to collect, harmonize, and share both retrospective and prospective Canadian clinical and multiomic data. Here, we introduce Genomics4RD, an integrated web-accessible platform to share Canadian phenotypic and multiomic data between researchers, both within Canada and internationally, for the purpose of discovering the mechanisms that cause RDs. Genomics4RD has been designed to standardize data collection and processing, and to help users systematically collect, prioritize, and visualize participant information. Data storage, authorization, and access procedures have been developed in collaboration with policy experts and stakeholders to ensure the trusted and secure access of data by external researchers. The breadth and standardization of data offered by Genomics4RD allows researchers to compare candidate disease genes and variants between participants (i.e., matchmaking) for discovery purposes, while facilitating the development of computational approaches for multiomic data analyses and enabling clinical translation efforts for new genetic technologies in the future.

Landscape of DNA methylation on the X chromosome reflects CpG density, functional chromatin state and X-chromosome inactivation.

X-chromosome inactivation (XCI) achieves dosage compensation between males and females through the silencing of the majority of genes on one of the female X chromosomes. Thus, the female X chromosomes provide a unique opportunity to study euchromatin and heterochromatin of allelic regions within the same nuclear environment. We examined the interplay of DNA methylation (DNAm) with CpG density, transcriptional activity and chromatin state at genes on the X chromosome using over 1800 female samples analysed with the Illumina Infinium Human Methylation450 BeadChip. DNAm was used to predict an inactivation status for 63 novel transcription start sites (TSSs) across 27 tissues. There was high concordance of inactivation status across tissues, with 62% of TSSs subject to XCI in all 27 tissues examined, whereas 9% escaped from XCI in all tissues, and the remainder showed variable escape from XCI between females in subsets of tissues. Inter-female and twin data supported a model of predominately cis-acting influences on inactivation status. The level of expression from the inactive X relative to the active X correlated with the amount of female promoter DNAm to a threshold of ∼30%, beyond which genes were consistently subject to inactivation. The inactive X showed lower DNAm than the active X at intragenic and intergenic regions for genes subject to XCI, but not at genes that escape from inactivation. Our categorization of genes that escape from X inactivation provides candidates for sex-specific differences in disease.

Variant ATRX syndrome with dysfunction of ATRX and MAGT1 genes.

A 0.8 kb intronic duplication in MAGT1 and a single base pair deletion in the last exon of ATRX were identified using a chromosome X-specific microarray and exome sequencing in a family with five males demonstrating intellectual disability (ID) and unusual skin findings (e.g., generalized pruritus). MAGT1 is an Mg²âº transporter previously associated with primary immunodeficiency and ID, whereas mutations in ATRX cause ATRX-ID syndrome. In patient cells, the function of ATRX was demonstrated to be abnormal based on altered RNA/protein expression, hypomethylation of rDNA, and abnormal cytokinesis. Dysfunction of MAGT1 was reflected in reduced RNA/protein expression and Mg²âº influx. The mutation in ATRX most likely explains the ID, whereas MAGT1 disruption could be linked to abnormal skin findings, as normal magnesium homeostasis is necessary for skin health. This work supports observations that multiple mutations collectively contribute to the phenotypic variability of syndromic ID, and emphasizes the importance of correlating clinical phenotype with genomic and cell function analyses.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta.

Background : Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results : Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, but reassuringly were robust to placental processing time. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions : This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. Further, we demonstrate that estimating epiphenotype variables from the DNAme data itself, when possible, provides both an independent check of clinically-obtained data and can provide a robust approach to compare variables across different datasets.

Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy.

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.  In utero exposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression. Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score > 8 to indicate symptomatic depressed mood ("maternally-depressed"), and we further classified cases into SSRI-exposed, maternally-depressed (n = 14); SSRI-exposed, not maternally-depressed (n = 6); SSRI non-exposed, maternally-depressed (n = 20); and SSRI non-exposed, not maternally-depressed (n = 24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n = 17 SSRI-exposed, n = 17 SSRI non-exposed). No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δß| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n = 31; males n = 33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off. We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment, as compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.

Comparing genome sequencing technologies to improve rare disease diagnostics: a protocol for the evaluation of a pilot project, Genome-wide Sequencing Ontario.

BACKGROUND: Genome-wide sequencing has emerged as a promising strategy for the timely diagnosis of rare diseases, but it is not yet available as a clinical test performed in Canadian diagnostic laboratories. We describe the protocol for evaluating a 2-year pilot project, Genome-wide Sequencing Ontario, to offer high-quality clinical genome-wide sequencing in Ontario, Canada. METHODS: The Genome-wide Sequencing Ontario protocol was codesigned by the Ontario Ministry of Health, the Hospital for Sick Children in Toronto and the Children's Hospital of Eastern Ontario in Ottawa. Enrolment of a prospective cohort of patients began on Apr. 1, 2021. Eligible cases with blood samples available for the index case and both parents (i.e., trios) are randomized to receive exome sequencing or genome sequencing. We will collect patient-level data and ascertain costs associated with the laboratory workflow for exome sequencing and genome sequencing. We will compare point estimates for the diagnostic utility and timeliness of exome sequencing and genome sequencing, and we will determine an incremental cost-effectiveness ratio (expressed as the incremental cost of genome sequencing versus exome sequencing per additional patient with a causal variant detected). INTERPRETATION: Findings from this work will provide robust evidence for the diagnostic utility, cost-effectiveness and timeliness of exome sequencing and genome sequencing, and will be disseminated via academic publications and policy briefs. Findings will inform provincial and cross-provincial policy related to the long-term organization, delivery and reimbursement of clinical-grade genome diagnostics for rare disease.

Profiling the small non-coding RNA transcriptome of the human placenta.

Proper functioning of the human placenta is critical for maternal and fetal health. While microRNAs (miRNAs) are known to impact placental gene expression, the effects of other small non-coding RNAs (sncRNAs) on the placental transcriptome are not well-established, and are emerging topics in the study of environmental influence on fetal development and reproductive health. Here, we assembled a cohort of 30 placental chorionic villi samples of varying gestational ages (M ± SD = 23.7 ± 11.3 weeks) to delineate the human placental sncRNA transcriptome through small RNA sequence analysis. We observed expression of 1544 sncRNAs, which include 48 miRNAs previously unannotated in humans. Additionally, 18,003 miRNA variants (isomiRs) were identified from the 654 observed miRNA species. This characterization of the term and pre-term placental sncRNA transcriptomes provides data fundamental to future investigations of their regulatory functions in the human placenta, and the baseline expression pattern needed for identifying changes in response to environmental factors, or under disease conditions.

Human placental piwi-interacting RNA transcriptome is characterized by expression from the DLK1-DIO3 imprinted region.

The placenta is vital to embryonic development and requires a finely-tuned pattern of gene expression, achieved in part by its unique epigenetic landscape. Piwi-interacting RNAs (piRNAs) are a class of small-non-coding RNA with established roles as epigenetic regulators of gene expression, largely via methylation of targeted DNA sequences. The expression of piRNAs have mainly been described in germ cells, but a fraction have been shown to retain expression in adult somatic tissues. To aid in understanding the contribution of these regulators in the placenta, we provide the first description of the piRNA transcriptome in human placentas. We find 297 piRNAs to be preferentially expressed in the human placenta, a subset of which are expressed at higher levels relative to testes samples. We also observed a large proportion of placental piRNAs to be expressed from a single locus, as distinct from canonical cluster locations associated with transposable element silencing. Finally, we find that 15 of the highest-expressed placental piRNAs maps to the DLK1-DIO3 locus, suggesting a link to placental biology. Our findings suggest that piRNAs could contribute to the molecular networks defining placental function in humans, and a biological impact of piRNA expression beyond germ cells.

Accurate ethnicity prediction from placental DNA methylation data.

BACKGROUND: The influence of genetics on variation in DNA methylation (DNAme) is well documented. Yet confounding from population stratification is often unaccounted for in DNAme association studies. Existing approaches to address confounding by population stratification using DNAme data may not generalize to populations or tissues outside those in which they were developed. To aid future placental DNAme studies in assessing population stratification, we developed an ethnicity classifier, PlaNET (Placental DNAme Elastic Net Ethnicity Tool), using five cohorts with Infinium Human Methylation 450k BeadChip array (HM450k) data from placental samples that is also compatible with the newer EPIC platform. RESULTS: Data from 509 placental samples were used to develop PlaNET and show that it accurately predicts (accuracy = 0.938, kappa = 0.823) major classes of self-reported ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), and produces ethnicity probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP arrays (> 2.5 million SNP) and ancestry informative markers (n = 50 SNPs). PlaNET's ethnicity classification relies on 1860 HM450K microarray sites, and over half of these were linked to nearby genetic polymorphisms (n = 955). Our placental-optimized method outperforms existing approaches in assessing population stratification in placental samples from individuals of Asian, African, and Caucasian ethnicities. CONCLUSION: PlaNET provides an improved approach to address population stratification in placental DNAme association studies. The method can be applied to predict ethnicity as a discrete or continuous variable and will be especially useful when self-reported ethnicity information is missing and genotyping markers are unavailable.

No evidence for association of MTHFR 677C>T and 1298A>C variants with placental DNA methylation.

Background: 5,10-Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme in one-carbon metabolism that ensures the availability of methyl groups for methylation reactions. Two single-nucleotide polymorphisms (SNPs) in the MTHFR gene, 677C>T and 1298A>C, result in a thermolabile enzyme with reduced function. These variants, in both the maternal and/or fetal genes, have been associated with pregnancy complications including miscarriage, neural tube defects (NTDs), and preeclampsia (PE), perhaps due to altered capacity for DNA methylation (DNAm). In this study, we assessed the association between MTHFR 677TT and 1298CC genotypes and risk of NTDs, PE, or normotensive intrauterine growth restriction (nIUGR). Additionally, we assessed whether these high-risk genotypes are associated with altered DNAm in the placenta. Results: In 303 placentas screened for this study, we observed no significant association between the occurrence of NTDs (N = 55), PE (early-onset: N = 28, late-onset: N = 20), or nIUGR (N = 21) and placental (fetal) MTHFR 677TT or 1298CC genotypes compared to healthy pregnancies (N = 179), though a trend of increased 677TT genotype in PE/IUGR together was observed (OR 2.53, p = 0.048). DNAm was profiled in 10 high-risk 677 (677TT + 1298AA), 10 high-risk 1298 (677CC + 1298CC), and 10 reference (677CC + 1298AA) genotype placentas. Linear modeling identified no significantly differentially methylated sites between high-risk 677 or 1298 and reference placentas at a false discovery rate < 0.05 and Δß ≥ 0.05 using the Illumina Infinium HumanMethylation450 BeadChip. Using a differentially methylated region analysis or separating cytosine-guanine dinucleotides (CpGs) by CpG density to reduce multiple comparisons also did not identify differential methylation. Additionally, there was no consistent evidence for altered methylation of repetitive DNA between high-risk and reference placentas. Conclusions: We conclude that large-scale, genome-wide disruption in DNAm does not occur in placentas with the high-risk MTHFR 677TT or 1298CC genotypes. Furthermore, there was no evidence for an association of the 1298CC genotype and only a tendency to higher 677TT in pregnancy complications of PE/IUGR. This may be due to small sample sizes or folate repletion in our Canadian population attenuating effects of the high-risk MTHFR variants. However, given our results and the conflicting results in the literature, investigations into alternative mechanisms that may explain the link between MTHFR variants and pregnancy complications, or in populations at risk of folate deficiencies, are warranted.

DNA methylation profiling of acute chorioamnionitis-associated placentas and fetal membranes: insights into epigenetic variation in spontaneous preterm births.

BACKGROUND: Placental inflammation, often presenting as acute chorioamnionitis (aCA), is commonly associated with preterm birth. Preterm birth can have both immediate and long-term adverse effects on the health of the baby. Developing biomarkers of inflammation in the placenta can help to understand its effects and potentially lead to new approaches for rapid prenatal diagnosis of aCA. We aimed to characterize epigenetic variation associated with aCA in placenta (chorionic villi) and fetal membranes (chorion and amnion) to better understand how aCA may impact processes that lead to preterm birth. This study lays the groundwork for development of novel biomarkers for aCA. METHODS: Samples from 44 preterm placentas (chorionic villi) as well as matched chorion and amnion for 16 of these cases were collected for this study. These samples were profiled using the Illumina Infinium HumanMethylation850 BeadChip to measure DNA methylation (DNAm) at 866,895 CpGs across the genome. An additional 78 placental samples were utilized to independently validate the array findings by pyrosequencing. RESULTS: Using a false discovery rate of < 0.15 and average group difference in DNAm of > 0.05, 66 differentially methylated (DM) CpG sites were identified between aCA cases and non-aCA cases in chorionic villi. For the majority of these 66 DM CpGs, the DNAm profile of the aCA cases as compared to the non-aCA cases trended in the direction of the blood cell DNAm. Interestingly, neutrophil-specific DNAm signatures, but not those associated with other immune cell types, were capable of separating aCA cases from the non-aCA cases. CONCLUSIONS: Our results suggest that aCA-associated placentas showed altered DNAm signatures that were not observed in the absence of aCA. This DNAm profile is consistent with the activation of the innate immune response in the placenta and/or reflect increase in neutrophils as a response to inflammation.

Profiling placental and fetal DNA methylation in human neural tube defects.

BACKGROUND: The incidence of neural tube defects (NTDs) declined by about 40 % in Canada with the introduction of a national folic acid (FA) fortification program. Despite the fact that few Canadians currently exhibit folate deficiency, NTDs are still the second most common congenital abnormality. FA fortification may have aided in reducing the incidence of NTDs by overcoming abnormal one carbon metabolism cycling, the process which provides one carbon units for methylation of DNA. We considered that NTDs persisting in a folate-replete population may also occur in the context of FA-independent compromised one carbon metabolism, and that this might manifest as abnormal DNA methylation (DNAm). Second trimester human placental chorionic villi, kidney, spinal cord, brain, and muscle were collected from 19 control, 22 spina bifida, and 15 anencephalic fetuses in British Columbia, Canada. DNA was extracted, assessed for methylenetetrahydrofolate reductase (MTHFR) genotype and for genome-wide DNAm using repetitive elements, in addition to the Illumina Infinium HumanMethylation450 (450k) array. RESULTS: No difference in repetitive element DNAm was noted between NTD status groups. Using a false discovery rate <0.05 and average group difference in DNAm ≥0.05, differentially methylated array sites were identified only in (1) the comparison of anencephaly to controls in chorionic villi (n = 4 sites) and (2) the comparison of spina bifida to controls in kidney (n = 3342 sites). CONCLUSIONS: We suggest that the distinctive DNAm of spina bifida kidneys may be consequent to the neural tube defect or reflective of a common etiology for abnormal neural tube and renal development. Though there were some small shifts in DNAm in the other tested tissues, our data do not support the long-standing hypothesis of generalized altered genome-wide DNAm in NTDs. This finding may be related to the fact that most Canadians are not folate deficient, but it importantly opens the field to the investigation of other epigenetic and non-epigenetic mechanisms in the etiology of NTDs.

The human placental methylome.

This review provides an overview of the unique features of DNA methylation in the human placenta. We discuss the importance of understanding placental development, structure, and function in the interpretation of DNA methylation data. Examples are given of how DNA methylation is important in regulating placental-specific gene expression, including monoallelic expression and X-chromosome inactivation in the placenta. We also discuss studies of global DNA methylation changes in the context of placental pathology and environmental exposures.

Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells.

BACKGROUND: Genome-wide DNA methylation (DNAm) studies have proven extremely useful to understand human hematopoiesis. Due to their active DNA content, nucleated red blood cells (nRBCs) contribute to epigenetic and transcriptomic studies derived from whole cord blood. Genomic studies of cord blood hematopoietic cells isolated by fluorescence-activated cell sorting (FACS) may be significantly altered by heterotopic interactions with nRBCs during conventional cell sorting. RESULTS: We report that cord blood T cells, and to a lesser extent monocytes and B cells, physically engage with nRBCs during FACS. These heterotopic interactions resulted in significant cross-contamination of genome-wide epigenetic and transcriptomic data. Formal exclusion of erythroid lineage-specific markers yielded DNAm profiles (measured by the Illumina 450K array) of cord blood CD4 and CD8 T lymphocytes, B lymphocytes, natural killer (NK) cells, granulocytes, monocytes, and nRBCs that were more consistent with expected hematopoietic lineage relationships. Additionally, we identified eight highly differentially methylated CpG sites in nRBCs (false detection rate <5 %, |Δß| >0.50) that can be used to detect nRBC contamination of purified hematopoietic cells or to assess the impact of nRBCs on whole cord blood DNAm profiles. Several of these erythroid markers are located in or near genes involved in erythropoiesis (ZFPM1, HDAC4) or immune function (MAP3K14, IFIT1B), reinforcing a possible immune regulatory role for nRBCs in early life. CONCLUSIONS: Heterotopic interactions between erythroid cells and white blood cells can result in contaminated cell populations if not properly excluded during cell sorting. Cord blood nRBCs have a distinct DNAm profile that can significantly skew epigenetic studies. Our findings have major implications for the design and interpretation of genome-wide epigenetic and transcriptomic studies using human cord blood.

Improved reporting of DNA methylation data derived from studies of the human placenta.

Epigenetic variation is increasingly hypothesized as a mechanism underlying the effect of the in utero environment on long-term postnatal health; however, there is currently little clear data to support this in humans. A number of biological and technical factors provide challenges for the design of clinical epigenetic studies: from the type of cells or tissues that are available to the large range of predicted confounders that may impact findings. The human placenta, in addition to other neonatal tissues and whole blood, is commonly sampled for the study of epigenetic modifications. However there is little conformity for the most appropriate methods for study design, data analysis, and importantly, data interpretation. Here we present general recommendations for the reporting of DNA methylation in biological samples, with specific focus on the placenta. We outline key guidelines for: (1) placental sampling, (2) data analysis and presentation, and (3) interpretation of DNA methylation data. We emphasize the need to consider methodological noise, increase statistical power and to ensure appropriate adjustment for biological covariates. Finally, we highlight that epigenetic changes may be non-pathological and not necessarily translate into disease-associated changes. Improved reporting of DNA methylation data will be critical to identify epigenetic-based effects and to better understand the full phenotypic impact of these widely-reported epigenomic changes.

Different measures of "genome-wide" DNA methylation exhibit unique properties in placental and somatic tissues.

DNA methylation of CpGs located in two types of repetitive elements-LINE1 (L1) and Alu-is used to assess "global" changes in DNA methylation in studies of human disease and environmental exposure. L1 and Alu contribute close to 30% of all base pairs in the human genome and transposition of repetitive elements is repressed through DNA methylation. Few studies have investigated whether repetitive element DNA methylation is associated with DNA methylation at other genomic regions, or the biological and technical factors that influence potential associations. Here, we assess L1 and Alu DNA methylation by Pyrosequencing of consensus sequences and using subsets of probes included in the Illumina Infinium HumanMethylation27 BeadChip array. We show that evolutionary age and assay method affect the assessment of repetitive element DNA methylation. Additionally, we compare Pyrosequencing results for repetitive elements to average DNA methylation of CpG islands, as assessed by array probes classified into strong, weak and non-islands. We demonstrate that each of these dispersed sequences exhibits different patterns of tissue-specific DNA methylation. Correlation of DNA methylation suggests an association between L1 and weak CpG island DNA methylation in some of the tissues examined. We caution, however, that L1, Alu and CpG island DNA methylation are distinct measures of dispersed DNA methylation and one should not be used in lieu of another. Analysis of DNA methylation data is complex and assays may be influenced by environment and pathology in different or complementary ways.