Deconvolution of whole blood DNA methylomes reveals immune cell type-specific differential methylation in Multiple Sclerosis
ABSTRACT: Whole blood is a highly convenient and informative tissue from which to sample DNA and RNA in epigenomic and functional genomic studies, but it is comprised of multiple distinct cell types and this complexity significantly impairs our ability to interpret downstream differential methylation and/or differential expression results. In this multiple sclerosis (MS)-focused study we utilised an application of current statistical deconvolution methods to interrogate whole blood DNA methylation data thereby enabling the methylome of several immune cell types to be analysed independently. Methylome profiling on cell type-purified blood samples revealed optimal CpG sets for use as robust immune cell markers in the statistical deconvolution process. We show that it is possible to identify differentially methylated (DM) loci in a cell type specific manner using statistical deconvolution. Finally, we demonstrate that deconvolution improved the biological relevance and interpretability of our DM results, significantly enhancing concordance of the identified DM loci with loci previously shown to be genetically or epigenetically associated with MS. Overall design: Case-Control design with whole blood methylomes of 14 healthy controls and 13 Multiple Sclerosis affected cases (1 failed bisulphite conversion) assayed. In addition, 8 of the healthy controls also have cell-type purified samples of neutrophils, CD4+ T cells, CD8+ T cells, NK cellsa, B cells and monocytes individually assayed.
Project description:PROBLEM:Decidual macrophages (dM?) of the mother and placental macrophages (Hofbauer cells, HC) of the fetus are deployed at a critical location: the feto-maternal interface. This study was conducted to compare the DNA methylome of maternal and fetal monocytes, dM?, and HC and thereby to determine the immunobiological importance of DNA methylation in pregnancy. METHOD OF STUDY:Paired samples were obtained from normal pregnant women at term not in labor and their neonates. Maternal monocytes (MMo) and fetal monocytes (FMo) were isolated from the peripheral blood of mothers and fetal cord blood, respectively. dM? and HC were obtained from the decidua of fetal membranes and placentas, respectively. DNA methylation profiling was performed using the Illumina Infinium Human Methylation27 BeadChip. Quantitative real-time PCR and Western Blot were performed for validation experiments. RESULTS:(i) Significant differences in DNA methylation were found in each comparison (MMo versus FMo, 65 loci; dM? versus HC, 266 loci; MMo versus dM?, 199 loci; FMo versus HC, 1030 loci). (ii) Many of the immune response-related genes were hypermethylated in fetal cells (FMo and HC) compared to maternal cells (MMo and dM?). (iii) Genes encoding markers of classical macrophage activation were hypermethylated, and genes encoding alternative macrophage activation were hypomethylated in dM? and HC compared to MMo and FMo, respectively. (iv) mRNA expressions of DNMT1, DNMT3A, and DNMT3B were significantly lower in dM? than in HC. (v) 5-azacytidine treatment increased expression of INCA1 in dM?. CONCLUSIONS:The findings herein indicate that DNA methylation patterns change during monocyte-macrophage differentiation at the feto-maternal interface. It is also suggested that DNA methylation is an important component of the biological machinery conferring an anti-inflammatory phenotype to macrophages at the feto-maternal interface.
Project description:Treatment of multiple sclerosis is effective when anti-inflammatory, neuroprotective and regenerative strategies are combined. Dendropanax morbiferus (DM) has anti-inflammatory, anti-oxidative properties, which may be beneficial for multiple sclerosis. However, there have been no reports on the effects of DM on myelination, which is critical for regenerative processes. To know whether DM benefits myelination, we checked differentiation and myelination of oligodendrocytes (OLs) in various primary culture systems treated with DM leaf EtOH extracts or control. DM extracts increased the OL membrane size in the mixed glial and pure OL precursor cell (OPC) cultures and changed OL-lineage gene expression patterns in the OPC cultures. Western blot analysis of DM-treated OPC cultures showed upregulation of MBP and phosphorylation of ERK1/2. In myelinating cocultures, DM extracts enhanced OL differentiation, followed by increased axonal contacts and myelin gene upregulations such as Myrf, CNP and PLP. Phytochemical analysis by LC-MS/MS identified multiple components from DM extracts, containing bioactive molecules such as quercetin, cannabidiol, etc. Our results suggest DM extracts enhance OL differentiation, followed by an increase in membrane size and axonal contacts, thereby indicating enhanced myelination. In addition, we found that DM extracts contain multiple bioactive components, warranting further studies in relation to finding effective components for enhancing myelination.
Project description:Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer's disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).
Project description:Aberrant cytosine 5-methylation underlies many deregulated elements of cancer. Among paired non-small cell lung cancers (NSCLC), we sought to profile DNA 5-methyl-cytosine features which may underlie genome-wide deregulation. In one of the more dense interrogations of the methylome, we sampled 1.2 million CpG sites from twenty-four NSCLC tumor (T)-non-tumor (NT) pairs using a methylation-sensitive restriction enzyme- based HELP-microarray assay. We found 225,350 differentially methylated (DM) sites in adenocarcinomas versus adjacent non-tumor tissue that vary in frequency across genomic compartment, particularly notable in gene bodies (GB; p<2.2E-16). Further, when DM was coupled to differential transcriptome (DE) in the same samples, 37,056 differential loci in adenocarcinoma emerged. Approximately 90% of the DM-DE relationships were non-canonical; for example, promoter DM associated with DE in the same direction. Of the canonical changes noted, promoter (PR) DM loci with reciprocal changes in expression in adenocarcinomas included HBEGF, AGER, PTPRM, DPT, CST1, MELK; DM GB loci with concordant changes in expression included FOXM1, FERMT1, SLC7A5, and FAP genes. IPA analyses showed adenocarcinoma-specific promoter DMxDE overlay identified familiar lung cancer nodes [tP53, Akt] as well as less familiar nodes [HBEGF, NQO1, GRK5, VWF, HPGD, CDH5, CTNNAL1, PTPN13, DACH1, SMAD6, LAMA3, AR]. The unique findings from this study include the discovery of numerous candidate The unique findings from this study include the discovery of numerous candidate methylation sites in both PR and GB regions not previously identified in NSCLC, and many non-canonical relationships to gene expression. These DNA methylation features could potentially be developed as risk or diagnostic biomarkers, or as candidate targets for newer methylation locus-targeted preventive or therapeutic agents.
Project description:DNA methylation has been implicated in a number of diseases and other phenotypes. It is, therefore, of interest to identify and understand the genetic determinants of methylation and epigenomic variation. We investigated the extent to which genetic variation in cis-DNA sequence explains variation in CpG dinucleotide methylation in publicly available data for four brain regions from unrelated individuals, finding that 3-4% of CpG loci assayed were heritable, with a mean estimated narrow-sense heritability of 30% over the heritable loci. Over all loci, the mean estimated heritability was 3%, as compared with a recent twin-based study reporting 18%. Heritable loci were enriched for open chromatin regions and binding sites of CTCF, an influential regulator of transcription and chromatin architecture. Additionally, heritable loci were proximal to genes enriched in several known pathways, suggesting a possible functional role for these loci. Our estimates of heritability are conservative, and we suspect that the number of identified heritable loci will increase as the methylome is assayed across a broader range of cell types and the density of the tested loci is increased. Finally, we show that the number of heritable loci depends on the window size parameter commonly used to identify candidate cis-acting single-nucleotide polymorphism variants.
Project description:BACKGROUND:Although many DNA methylation (DNAm) alterations observed in peripheral whole blood/leukocytes and serum have been considered as potential diagnostic markers for cancer, their origin and their specificity for cancer (e.g., vs inflammatory diseases) remain unclear. METHODS:From publicly available datasets, we identified changes in the methylation of blood-borne DNA for multiple cancers and inflammatory diseases. We compared the identified changes with DNAm difference between myeloid and lymphoid cells extracted from two datasets. RESULTS:At least 94.7% of the differentially methylated DNA loci (DM loci) observed in peripheral whole blood/leukocytes and serum of cancer patients overlapped with DM loci that distinguish between myeloid and lymphoid cells and >99.9% of the overlapped DM loci had consistent alteration states (hyper- or hypomethylation) in cancer samples compared to normal controls with those in myeloid cells compared to lymphoid cells (binomial test, P-value <2.2 × 10(-16)). Similar results were observed for DM loci in peripheral whole blood/leukocytes in patients with rheumatoid arthritis or inflammatory bowel diseases. The direct comparison between DM loci observed in the peripheral whole blood/leukocytes of patients with inflammatory diseases and DM loci observed in the peripheral whole blood of patients with cancer showed that DM loci detected from cancer and inflammatory diseases also had significantly consistent alteration states (binomial test, P-value <2.2 × 10(-16)). CONCLUSIONS:DNAm changes observed in the peripheral whole blood/leukocytes and serum of cancer patients and in the peripheral whole blood/leukocytes of inflammatory disease patients are predominantly determined by the increase of myeloid cells and the decrease of lymphoid cells under the disease conditions, in the sense that their alteration states in disease samples compared to normal controls mainly reflect the DNAm difference between myeloid and lymphoid cells. These analyses highlight the importance of comparing cancer and inflammatory disease directly for the identification of cancer-specific diagnostic biomarkers.
Project description:BACKGROUND:Multiple Sclerosis (MS) is a chronic inflammatory disease and a leading cause of progressive neurological disability among young adults. DNA methylation, which intersects genes and environment to control cellular functions on a molecular level, may provide insights into MS pathogenesis. METHODS:We measured DNA methylation in CD4+ T cells (n?=?31), CD8+ T cells (n?=?28), CD14+ monocytes (n =?35) and CD19+ B cells (n?=?27) from relapsing-remitting (RRMS), secondary progressive (SPMS) patients and healthy controls (HC) using Infinium HumanMethylation450 arrays. Monocyte (n?=?25) and whole blood (n =?275) cohorts were used for validations. FINDINGS:B cells from MS patients displayed most significant differentially methylated positions (DMPs), followed by monocytes, while only few DMPs were detected in T cells. We implemented a non-parametric combination framework (omicsNPC) to increase discovery power by combining evidence from all four cell types. Identified shared DMPs co-localized at MS risk loci and clustered into distinct groups. Functional exploration of changes discriminating RRMS and SPMS from HC implicated lymphocyte signaling, T cell activation and migration. SPMS-specific changes, on the other hand, implicated myeloid cell functions and metabolism. Interestingly, neuronal and neurodegenerative genes and pathways were also specifically enriched in the SPMS cluster. INTERPRETATION:We utilized a statistical framework (omicsNPC) that combines multiple layers of evidence to identify DNA methylation changes that provide new insights into MS pathogenesis in general, and disease progression, in particular. FUND: This work was supported by the Swedish Research Council, Stockholm County Council, AstraZeneca, European Research Council, Karolinska Institutet and Margaretha af Ugglas Foundation.
Project description:We created a fast, robust and general C+ + implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol.http://broadinstitute.org/mpg/snpsea.Supplementary data are available at Bioinformatics online.
Project description:OBJECTIVE:Multiple sclerosis (MS) is one of the leading neurodegenerative causes of physical disability world-wide. Genetic aberrations of autoimmunity pathway components have been demonstrated to significantly influence MS development. Cluster of Differentiation 58 (CD58) is pertained to a group of genes which had been assayed in several recent association studies. Given the significance of CD58 in modulation of T regulatory cells that control autoimmune responses, the present study was conducted to investigate the frequency of rs12044852 polymorphism and its effect on the outcome of interferon beta (IFN-?) therapy in a subset of Iranian MS patients. MATERIALS AND METHODS:Two hundred MS patients and equal number of healthy controls were recruited to be genotyped in an experimental case-control based study through polymerase chain reaction using specific sequence primers (PCR-SSP). Relapsing remitting multiple sclerosis (RRMS) patients administered IFN-? therapy were followed up with clinical visits every three months up to two years. The mean of multiple sclerosis severity score (MSSS) and expanded disability status scale (EDSS) were measured to monitor the change in severity of MS in response to IFN-? therapy. Pearson's Chi-square and analysis of variance (ANOVA) tests were the main statistical methods used in this study. RESULTS:Strong association was found between the CC genotype and onset of MS (p=0.001, OR=2.22). However, there was no association between rs12044852 and various classifications and severity of MS. Pharmacogenetics-based analysis indicated that carriers of CC genotype had the highest MSSS score compared to others, implying a negative impact of rs12044852 on response to IFN-? therapy. CONCLUSION:Taken together, our findings revealed the critical effect of rs12044852 polymorphism of CD58 on the progression of MS disease. This indicates that genotyping of MS patients may expedite achieving personalized medical management of MS patients.
Project description:DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.