Investigating neonatal health risk variables through cell-type specific methylome-wide association studies.

Adverse neonatal outcomes are a prevailing risk factor for both short- and long-term mortality and morbidity in infants. Given the importance of these outcomes, refining their assessment is paramount for improving prevention and care. Here we aim to enhance the assessment of these often correlated and multifaceted neonatal outcomes. To achieve this, we employ factor analysis to identify common and unique effects and further confirm these effects using criterion-related validity testing. This validation leverages methylome-wide profiles from neonatal blood. Specifically, we investigate nine neonatal health risk variables, including gestational age, Apgar score, three indicators of body size, jaundice, birth diagnosis, maternal preeclampsia, and maternal age. The methylomic profiles used for this research capture data from nearly all 28 million methylation sites in human blood, derived from the blood spot collected from 333 neonates, within 72 h post-birth. Our factor analysis revealed two common factors, size factor, that captured the shared effects of weight, head size, height, and gestational age and disease factor capturing the orthogonal shared effects of gestational age, combined with jaundice and birth diagnosis. To minimize false positives in the validation studies, validation was limited to variables with significant cumulative association as estimated through an in-sample replication procedure. This screening resulted in that the two common factors and the unique effects for gestational age, jaundice and Apgar were further investigated with full-scale cell-type specific methylome-wide association analyses. Highly significant, cell-type specific, associations were detected for both common effect factors and for Apgar. Gene Ontology analyses revealed multiple significant biologically relevant terms for the five fully investigated neonatal health risk variables. Given the established links between adverse neonatal outcomes and both immediate and long-term health, the distinct factor effects (representing the common and unique effects of the risk variables) and their biological profiles confirmed in our work, suggest their potential role as clinical biomarkers for assessing health risks and enhancing personalized care.

Methylome-wide association study of anxiety disorders.

Anxiety Disorders (ANX) such as panic disorder, generalized anxiety disorder, and phobias, are highly prevalent conditions that are moderately heritable. Evidence suggests that DNA methylation may play a role, as it is involved in critical adaptations to changing environments. Applying an enrichment-based sequencing approach covering nearly 28 million autosomal CpG sites, we conducted a methylome-wide association study (MWAS) of lifetime ANX in 1132 participants (618 cases/514 controls) from the Netherlands Study of Depression and Anxiety. Using epigenomic deconvolution, we performed MWAS for the main cell types in blood: granulocytes, T-cells, B-cells and monocytes. Cell-type specific analyses identified 280 and 82 methylome-wide significant associations (q-value < 0.1) in monocytes and granulocytes, respectively. Our top finding in monocytes was located in ZNF823 on chromosome 19 (p = 1.38 × 10-10) previously associated with schizophrenia. We observed significant overlap (p < 1 × 10-06) with the same direction of effect in monocytes (210 sites), T-cells (135 sites), and B-cells (727 sites) between this Discovery MWAS signal and a comparable replication dataset from the Great Smoky Mountains Study (N = 433). Overlapping Discovery-Replication MWAS signal was enriched for findings from published GWAS of ANX, major depression, and post-traumatic stress disorder. In monocytes, two specific sites in the FZR1 gene showed significant replication after Bonferroni correction with an additional 15 nominally replicated sites in monocytes and 4 in T-cells. FZR1 regulates neurogenesis in the hippocampus, and its knockout leads to impairments in associative fear memory and long-term potentiation in mice. In the largest and most extensive methylome-wide study of ANX, we identified replicable methylation sites located in genes of potential relevance for brain mechanisms of psychiatric conditions.

Genes implicated by a methylome-wide schizophrenia study in neonatal blood show differential expression in adult brain samples.

Schizophrenia is a disabling disorder involving genetic predisposition in combination with environmental influences that likely act via dynamic alterations of the epigenome and the transcriptome but its detailed pathophysiology is largely unknown. We performed cell-type specific methylome-wide association study of neonatal blood (N = 333) from individuals who later in life developed schizophrenia and controls. Suggestively significant associations (P < 1.0 × 10-6) were detected in all cell-types and in whole blood with methylome-wide significant associations in monocytes (P = 2.85 × 10-9-4.87 × 10-9), natural killer cells (P = 1.72 × 10-9-7.82 × 10-9) and B cells (P = 3.8 × 10-9). Validation of methylation findings in post-mortem brains (N = 596) from independent schizophrenia cases and controls showed significant enrichment of transcriptional differences (enrichment ratio = 1.98-3.23, P = 2.3 × 10-3-1.0 × 10-5), with specific highly significant differential expression for, for example, BDNF (t = -6.11, P = 1.90 × 10-9). In addition, expression difference in brain significantly predicted schizophrenia (multiple correlation = 0.15-0.22, P = 3.6 × 10-4-4.5 × 10-8). In summary, using a unique design combining pre-disease onset (neonatal) blood methylomic data and post-disease onset (post-mortem) brain transcriptional data, we have identified genes of likely functional relevance that are associated with schizophrenia susceptibility, rather than confounding disease associated artifacts. The identified loci may be of clinical value as a methylation-based biomarker for early detection of increased schizophrenia susceptibility.

A single-nucleus transcriptomics study of alcohol use disorder in the nucleus accumbens.

Gene expression studies offer promising opportunities to better understand the processes underlying alcohol use disorder (AUD). As cell types differ in their function, gene expression profiles will typically vary across cell types. When studying bulk tissue, failure to account for this cellular diversity has a detrimental impact on the ability to detect disease associations. We therefore assayed the transcriptomes of 32,531 individual nuclei extracted from the nucleus accumbens (NAc) of nine donors with AUD and nine controls (72% male). Our study identified 17 clearly delineated cell types. We detected 26 transcriptome-wide significant differentially expressed genes (DEGs) that mainly involved medium spiny neurons with both D1-type and D2-type dopamine receptors, microglia (MGL) and oligodendrocytes. A higher than expected number of DEGs replicated in an existing single nucleus gene expression study of alcohol dependence in the prefrontal cortex (enrichment ratio 1.91, p value 0.019) with two genes remaining significant after a Bonferroni correction. Our most compelling result involved CD53 in MGL that replicated in the same cell type in the prefrontal cortex and was previously implicated in studies of DNA methylation, bulk gene expression and genetic variants. Several DEGs were previously reported to be associated with AUD (e.g., PER1 and MGAT5). The DEGs for MSN.3 seemed involved in neurodegeneration, disruption of circadian rhythms, alterations in glucose metabolism and changes in synaptic plasticity. For MGL, the DEGs implicated neuroinflammation and immune-related processes and for OLI, disruptions in myelination. This identification of the specific cell-types from which the association signals originate will be key for designing proper follow-up experiments and, eventually, novel clinical interventions.

A methylation study implicates the rewiring of brain neural circuits during puberty in the emergence of sex differences in depression symptoms.

BACKGROUND: Women are 1.5-3 times more likely to suffer from depression than men. This sex bias first emerges during puberty and then persists across the reproductive years. As the cause remains largely elusive, we performed a methylation-wide association study (MWAS) to generate novel hypotheses. METHODS: We assayed nearly all 28 million possible methylation sites in blood in 595 blood samples from 487 participants aged 9-17. MWASs were performed to identify methylation sites associated with increasing sex differences in depression symptoms as a function of pubertal stage. Epigenetic deconvolution was applied to perform analyses on a cell-type specific level. RESULTS: In monocytes, a substantial number of significant associations were detected after controlling the FDR at 0.05. These results could not be explained by plasma testosterone/estradiol or current/lifetime trauma. Our top results in monocytes were significantly enriched (ratio of 2.48) for genes in the top of a large genome-wide association study (GWAS) meta-analysis of depression and neurodevelopment-related Gene Ontology (GO) terms that remained significant after correcting for multiple testing. Focusing on our most robust findings (70 genes overlapping with the GWAS meta-analysis and the significant GO terms), we find genes coding for members of each of the major classes of axon guidance molecules (netrins, slits, semaphorins, ephrins, and cell adhesion molecules). Many of these genes were previously implicated in rodent studies of brain development and depression-like phenotypes, as well as human methylation, gene expression and GWAS studies. CONCLUSIONS: Our study suggests that the emergence of sex differences in depression may be related to the differential rewiring of brain circuits between boys and girls during puberty.

Dual methylation and hydroxymethylation study of alcohol use disorder.

Using an integrative, multi-tissue design, we sought to characterize methylation and hydroxymethylation changes in blood and brain associated with alcohol use disorder (AUD). First, we used epigenomic deconvolution to perform cell-type-specific methylome-wide association studies within subpopulations of granulocytes/T-cells/B-cells/monocytes in 1132 blood samples. Blood findings were then examined for overlap with AUD-related associations with methylation and hydroxymethylation in 50 human post-mortem brain samples. Follow-up analyses investigated if overlapping findings mediated AUD-associated transcription changes in the same brain samples. Lastly, we replicated our blood findings in an independent sample of 412 individuals and aimed to replicate published alcohol methylation findings using our results. Cell-type-specific analyses in blood identified methylome-wide significant associations in monocytes and T-cells. The monocyte findings were significantly enriched for AUD-related methylation and hydroxymethylation in brain. Hydroxymethylation in specific sites mediated AUD-associated transcription in the same brain samples. As part of the most comprehensive methylation study of AUD to date, this work involved the first cell-type-specific methylation study of AUD conducted in blood, identifying and replicating a finding in DLGAP1 that may be a blood-based biomarker of AUD. In this first study to consider the role of hydroxymethylation in AUD, we found evidence for a novel mechanism for cognitive deficits associated with AUD. Our results suggest promising new avenues for AUD research.

A targeted solution for estimating the cell-type composition of bulk samples.

BACKGROUND: To avoid false-positive findings and detect cell-type specific associations in methylation and transcription investigations with bulk samples, it is critical to know the proportions of the major cell-types. RESULTS: We present a novel approach that allows for precise estimation of cell-type proportions using only a few highly informative methylation markers. The most reliable estimates were obtained with 17 amplicons (34 CpGs) using the MuSiC estimator, for which the average correlations between the estimated and the true cell-type proportions were 0.889. Furthermore, the estimates were not significantly different from the true values (P = 0.95) indicating that the estimator is unbiased and the standard deviation of the estimates further indicate high precision. Moreover, the overall variability of the estimates as measured by the Root Mean Squared Error (RMSE), which is a function of both bias and precision, was low (mean RMSE = 0.038). Taken together, these results indicate that the approach produced reliable estimates that are both unbiased and highly precise. CONCLUSION: This cost-effective approach for estimating cell-type proportions in bulk samples allows for enhanced targeted analysis, which in turn will minimize the risk of reporting false-positive findings and allowing for detection of cell-type specific associations. The approach is applicable across platforms and can be extended to assess cell-type proportions for various tissues.

Methylomic Investigation of Problematic Adolescent Cannabis Use and Its Negative Mental Health Consequences.

OBJECTIVE: The impact of adolescent cannabis use is a pressing public health question owing to the high rates of use and links to negative outcomes. This study considered the association between problematic adolescent cannabis use and methylation. METHOD: Using an enrichment-based sequencing approach, a methylome-wide association study (MWAS) was performed of problematic adolescent cannabis use in 703 adolescent samples from the Great Smoky Mountain Study. Using epigenomic deconvolution, MWASs were performed for the main cell types in blood: granulocytes, T cells, B cells, and monocytes. Enrichment testing was conducted to establish overlap between cannabis-associated methylation differences and variants associated with negative mental health effects of adolescent cannabis use. RESULTS: Whole-blood analyses identified 45 significant CpGs, and cell type-specific analyses yielded 32 additional CpGs not identified in the whole-blood MWAS. Significant overlap was observed between the B-cell MWAS and genetic studies of education attainment and intelligence. Furthermore, the results from both T cells and monocytes overlapped with findings from an MWAS of psychosis conducted in brain tissue. CONCLUSION: In one of the first methylome-wide association studies of adolescent cannabis use, several methylation sites located in genes of importance for potentially relevant brain functions were identified. These findings resulted in several testable hypotheses by which cannabis-associated methylation can impact neurological development and inflammation response as well as potential mechanisms linking cannabis-associated methylation to potential downstream mental health effects.

DNA methylation and histone acetylation changes to cytochrome P450 2E1 regulation in normal aging and impact on rates of drug metabolism in the liver.

Aging is associated with reduced liver function that may increase the risk for adverse drug reactions in older adults. We hypothesized that age-related changes to epigenetic regulation of genes involved in drug metabolism may contribute to this effect. We reviewed published epigenome-wide studies of human blood and identified the cytochrome P450 2E1 (CYP2E1) gene as a top locus exhibiting epigenetic changes with age. To investigate potential functional changes with age in the liver, the primary organ of drug metabolism, we obtained liver tissue from mice aged 4-32 months from the National Institute on Aging. We assayed global DNA methylation (5-methylcytosine, 5mC), hydroxymethylation (5-hydroxymethylcytosine, 5hmC), and locus-specific 5mC and histone acetylation changes around mouse Cyp2e1. The mouse livers exhibit significant global decreases in 5mC and 5hmC with age. Furthermore, 5mC significantly increased with age at two regulatory regions of Cyp2e1 in tandem with decreases in its gene and protein expressions. H3K9ac levels also changed with age at both regulatory regions of Cyp2e1 investigated, while H3K27ac did not. To test if these epigenetic changes are associated with varying rates of drug metabolism, we assayed clearance of the CYP2E1-specific probe drug chlorzoxazone in microsome extracts from the same livers. CYP2E1 intrinsic clearance is associated with DNA methylation and H3K9ac levels at the Cyp2e1 locus but not with chronological age. This suggests that age-related epigenetic changes may influence rates of hepatic drug metabolism. In the future, epigenetic biomarkers could prove useful to guide dosing regimens in older adults.

Cell Type-Specific Methylome-wide Association Studies Implicate Neurotrophin and Innate Immune Signaling in Major Depressive Disorder.

BACKGROUND: We sought to characterize methylation changes in brain and blood associated with major depressive disorder (MDD). As analyses of bulk tissue may obscure association signals and hamper the biological interpretation of findings, these changes were studied on a cell type-specific level. METHODS: In 3 collections of human postmortem brain (n = 206) and 1 collection of blood samples (N = 1132) of MDD cases and controls, we used epigenomic deconvolution to perform cell type-specific methylome-wide association studies within subpopulations of neurons/glia for the brain data and granulocytes/T cells/B cells/monocytes for the blood data. Sorted neurons/glia from a fourth postmortem brain collection (n = 58) were used for validation purposes. RESULTS: Cell type-specific methylome-wide association studies identified multiple findings in neurons/glia that were detected across brain collections and were reproducible in physically sorted nuclei. Cell type-specific analyses in blood samples identified methylome-wide significant associations in T cells, monocytes, and whole blood that replicated findings from a past methylation study of MDD. Pathway analyses implicated p75 neurotrophin receptor/nerve growth factor signaling and innate immune toll-like receptor signaling in MDD. Top results in neurons, glia, bulk brain, T cells, monocytes, and whole blood were enriched for genes supported by genome-wide association studies for MDD and other psychiatric disorders. CONCLUSIONS: We both replicated and identified novel MDD-methylation associations in human brain and blood samples at a cell type-specific level. Our results provide mechanistic insights into how the immune system may interact with the brain to affect MDD susceptibility. Importantly, our findings involved associations with MDD in human samples that implicated many closely related biological pathways. These disease-linked sites and pathways represent promising new therapeutic targets for MDD.

Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples.

We present the first large-scale methylome-wide association studies (MWAS) for major depressive disorder (MDD) to identify sites of potential importance for MDD etiology. Using a sequencing-based approach that provides near-complete coverage of all 28 million common CpGs in the human genome, we assay methylation in MDD cases and controls from both blood (N = 1132) and postmortem brain tissues (N = 61 samples from Brodmann Area 10, BA10). The MWAS for blood identified several loci with P ranging from 1.91 × 10-8 to 4.39 × 10-8 and a resampling approach showed that the cumulative association was significant (P = 4.03 × 10-10) with the signal coming from the top 25,000 MWAS markers. Furthermore, a permutation-based analysis showed significant overlap (P = 5.4 × 10-3) between the MWAS findings in blood and brain (BA10). This overlap was significantly enriched for a number of features including being in eQTLs in blood and the frontal cortex, CpG islands and shores, and exons. The overlapping sites were also enriched for active chromatin states in brain including genic enhancers and active transcription start sites. Furthermore, three loci located in GABBR2, RUFY3, and in an intergenic region on chromosome 2 replicated with the same direction of effect in the second brain tissue (BA25, N = 60) from the same individuals and in two independent brain collections (BA10, N = 81 and 64). GABBR2 inhibits neuronal activity through G protein-coupled second-messenger systems and RUFY3 is implicated in the establishment of neuronal polarity and axon elongation. In conclusion, we identified and replicated methylated loci associated with MDD that are involved in biological functions of likely importance to MDD etiology.

Convergence of evidence from a methylome-wide CpG-SNP association study and GWAS of major depressive disorder.

DNA methylation is an epigenetic modification that provides stability and diversity to the cellular phenotype. It is influenced by both genetic sequence variation and environmental factors, and can therefore potentially account for variation of heritable phenotypes and disorders. Therefore, methylome-wide association studies (MWAS) are promising complements to genome-wide association studies (GWAS) of genetic variants. Of particular interest are methylation sites (CpGs) that are created or destroyed by the alleles of single-nucleotide polymorphisms (SNPs), as these so-called CpG-SNPs may show variation in methylation levels on top of what can be explained by the sequence variation. Using sequencing-based data from 1132 major depressive disorder (MDD) cases and controls, we performed a MWAS of 970,414 common CpG-SNPs. The analysis identified 27 suggestively significant (P < 1.00 × 10-5) CpG-SNPs associations. Furthermore, the MWAS results were over-represented (odds ratios ranging 1.36-5.00; P ranging 4.9 × 10-3-8.1 × 10-2) among findings from three recent GWAS for MDD-related phenotypes. Overlapping loci included, e.g., ROBO2, ASIC2, and DCC. As the CpG-SNP analysis accounts for the number of alleles that creates CpGs, the methylation differences could not be explained by differences in allele frequencies. Thus, the results show that the MWAS and GWASs provide independent lines of evidence for the involvement of these loci in MDD. In conclusion, our methylation study of MDD contributes novel information about loci of relevance that complements previous findings and generates new hypothesis about MDD etiology, such as that the functional effects of genetic association may be partly mediated and/or enhanced by the methylation status in these loci.

A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA.

We recently showed that, after optimization, our methyl-CpG binding domain sequencing (MBD-seq) application approximates the methylome-wide coverage obtained with whole-genome bisulfite sequencing (WGB-seq), but at a cost that enables adequately powered large-scale association studies. A prior drawback of MBD-seq is the relatively large amount of genomic DNA (ideally >1 µg) required to obtain high-quality data. Biomaterials are typically expensive to collect, provide a finite amount of DNA, and may simply not yield sufficient starting material. The ability to use low amounts of DNA will increase the breadth and number of studies that can be conducted. Therefore, we further optimized the enrichment step. With this low starting material protocol, MBD-seq performed equally well, or better, than the protocol requiring ample starting material (>1 µg). Using only 15 ng of DNA as input, there is minimal loss in data quality, achieving 93% of the coverage of WGB-seq (with standard amounts of input DNA) at similar false/positive rates. Furthermore, across a large number of genomic features, the MBD-seq methylation profiles closely tracked those observed for WGB-seq with even slightly larger effect sizes. This suggests that MBD-seq provides similar information about the methylome and classifies methylation status somewhat more accurately. Performance decreases with <15 ng DNA as starting material but, even with as little as 5 ng, MBD-seq still achieves 90% of the coverage of WGB-seq with comparable genome-wide methylation profiles. Thus, the proposed protocol is an attractive option for adequately powered and cost-effective methylome-wide investigations using (very) low amounts of DNA.

Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome.

Methylome-wide association studies are typically performed using microarray technologies that only assay a very small fraction of the CG methylome and entirely miss two forms of methylation that are common in brain and likely of particular relevance for neuroscience and psychiatric disorders. The alternative is to use whole genome bisulfite (WGB) sequencing but this approach is not yet practically feasible with sample sizes required for adequate statistical power. We argue for revisiting methylation enrichment methods that, provided optimal protocols are used, enable comprehensive, adequately powered and cost-effective genome-wide investigations of the brain methylome. To support our claim we use data showing that enrichment methods approximate the sensitivity obtained with WGB methods and with slightly better specificity. However, this performance is achieved at <5% of the reagent costs. Furthermore, because many more samples can be sequenced simultaneously, projects can be completed about 15 times faster. Currently the only viable option available for comprehensive brain methylome studies, enrichment methods may be critical for moving the field forward.

A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects.

The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 × 10(-8)). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10(-30)). To examine biological themes, we selected 70 DMRs with false discovery rate of <0.1. Of these, 42 showed hypomethylation and 28 showed hypermethylation with age. Hypermethylated DMRs were more likely to overlap with CpG islands and shores. Hypomethylated DMRs were more likely to be in regions associated with polycomb/regulatory proteins (e.g. EZH2) or histone modifications H3K27ac, H3K4m1, H3K4m2, H3K4m3 and H3K9ac. Among genes implicated by the top DMRs were protocadherins, homeobox genes, MAPKs and ryanodine receptors. Several of our DMRs are at genes with potential relevance for age-related disease. This study successfully demonstrates the application of next-generation sequencing to MWAS, by interrogating a large proportion of the methylome and returning potentially novel age DMRs, in addition to replicating several loci implicated in previous studies using microarrays.

Testing two models describing how methylome-wide studies in blood are informative for psychiatric conditions.

AIM: As the primary relevant tissue (brain) for psychiatric disorders is commonly not available, we aimed to investigate whether blood can be used as a proxy in methylation studies on the basis of two models. In the 'signature' model methylation-disease associations occur because a disease-causing factor affected methylation in the blood. In the 'mirror-site' model the methylation status in the blood is correlated with the corresponding disease-causing site in the brain. MATERIALS, METHODS & RESULTS: Methyl-binding domain enrichment and next-generation sequencing of the blood, cortex and hippocampus from four haloperidol-treated and ten untreated C57BL/6 mice revealed high levels of correlation in methylation across tissues. Despite the treatment inducing a large number of methylation changes, this correlation remains high. CONCLUSION: Our results show that, consistent with the signature model, factors that affect brain processes (i.e., haloperidol) leave biomarker signatures in the blood and, consistent with the mirror-site model, the methylation status of many sites in the blood mirror those in the brain.

High quality methylome-wide investigations through next-generation sequencing of DNA from a single archived dry blood spot.

The potential importance of DNA methylation in the etiology of complex diseases has led to interest in the development of methylome-wide association studies (MWAS) aimed at interrogating all methylation sites in the human genome. When using blood as biomaterial for a MWAS the DNA is typically extracted directly from fresh or frozen whole blood that was collected via venous puncture. However, DNA extracted from dry blood spots may also be an alternative starting material. In the present study, we apply a methyl-CpG binding domain (MBD) protein enrichment-based technique in combination with next generation sequencing (MBD-seq) to assess the methylation status of the ~27 million CpGs in the human autosomal reference genome. We investigate eight methylomes using DNA from blood spots. This data are compared with 1,500 methylomes previously assayed with the same MBD-seq approach using DNA from whole blood. When investigating the sequence quality and the enrichment profile across biological features, we find that DNA extracted from blood spots gives comparable results with DNA extracted from whole blood. Only if the amount of starting material is ≤ 0.5µg DNA we observe a slight decrease in the assay performance. In conclusion, we show that high quality methylome-wide investigations using MBD-seq can be conducted in DNA extracted from archived dry blood spots without sacrificing quality and without bias in enrichment profile as long as the amount of starting material is sufficient. In general, the amount of DNA extracted from a single blood spot is sufficient for methylome-wide investigations with the MBD-seq approach.

Estimation of CpG coverage in whole methylome next-generation sequencing studies.

BACKGROUND: Methylation studies are a promising complement to genetic studies of DNA sequence. However, detailed prior biological knowledge is typically lacking, so methylome-wide association studies (MWAS) will be critical to detect disease relevant sites. A cost-effective approach involves the next-generation sequencing (NGS) of single-end libraries created from samples that are enriched for methylated DNA fragments. A limitation of single-end libraries is that the fragment size distribution is not observed. This hampers several aspects of the data analysis such as the calculation of enrichment measures that are based on the number of fragments covering the CpGs. RESULTS: We developed a non-parametric method that uses isolated CpGs to estimate sample-specific fragment size distributions from the empirical sequencing data. Through simulations we show that our method is highly accurate. While the traditional (extended) read count methods resulted in severely biased coverage estimates and introduces artificial inter-individual differences, through the use of the estimated fragment size distributions we could remove these biases almost entirely. Furthermore, we found correlations of 0.999 between coverage estimates obtained using fragment size distributions that were estimated with our method versus those that were "observed" in paired-end sequencing data. CONCLUSIONS: We propose a non-parametric method for estimating fragment size distributions that is highly precise and can improve the analysis of cost-effective MWAS studies that sequence single-end libraries created from samples that are enriched for methylated DNA fragments.

MBD-seq as a cost-effective approach for methylome-wide association studies: demonstration in 1500 case--control samples.

AIM: We studied the use of methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq) as a cost-effective screening tool for methylome-wide association studies (MWAS). MATERIALS & METHODS: Because MBD-seq has not yet been applied on a large scale, we first developed and tested a pipeline for data processing using 1500 schizophrenia cases and controls plus 75 technical replicates with an average of 68 million reads per sample. This involved the use of technical replicates to optimize quality control for multi- and duplicate-reads, an in silico experiment to identify CpGs in loci with alignment problems, CpG coverage calculations based on multiparametric estimates of the fragment size distribution, a two-stage adaptive algorithm to combine data from correlated adjacent CpG sites, principal component analyses to control for confounders and new software tailored to handle the large data set. RESULTS: We replicated MWAS findings in independent samples using a different technology that provided single base resolution. In an MWAS of age-related methylation changes, one of our top findings was a previously reported robust association involving GRIA2. Our results also suggested that owing to the many confounding effects, a considerable challenge in MWAS is to identify those effects that are informative about disease processes. CONCLUSION: This study showed the potential of MBD-seq as a cost-effective tool in large-scale disease studies.