scholarly journals Calling differential DNA methylation at cell-type resolution: addressing misconceptions and best practices

2021 ◽  
Author(s):  
Elior Rahmani ◽  
Brandon Jew ◽  
Regev Schweiger ◽  
Brooke Rhead ◽  
Lindsey A. Criswell ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Best Practices ◽  
Regression Model ◽  
Association Studies ◽  
Composition Analysis ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Interaction Terms ◽  
Mathematical Explanations ◽  
Cell Type Specific

AbstractWe benchmarked two approaches for the detection of cell-type-specific differential DNA methylation: Tensor Composition Analysis (TCA) and a regression model with interaction terms (CellDMC). Our experiments alongside rigorous mathematical explanations show that TCA is superior over CellDMC, thus resolving recent criticisms suggested by Jing et al. Following misconceptions by Jing and colleagues with modelling cell-type-specificity and the application of TCA, we further discuss best practices for performing association studies at cell-type resolution. The scripts for reproducing all of our results and figures are publicly available at github.com/cozygene/CellTypeSpecificMethylationAnalysis.

scholarly journals Identification of blood autosomal cis-expression quantitative trait methylation (cis-eQTMs) in children

2020 ◽  
Author(s):  
Carlos Ruiz-Arenas ◽  
Carles Hernandez-Ferrer ◽  
Marta Vives-Usano ◽  
Sergi Marí ◽  
Inés Quintela ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Quantitative Trait ◽  
Association Studies ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Biological Interpretation ◽  
Cell Type Specific ◽  
Using Data ◽  
The Relationship

AbstractBackgroundThe identification of expression quantitative trait methylation (eQTMs), defined as correlations between gene expression and DNA methylation levels, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis-eQTMs in child blood, using data from 832 children of the Human Early Life Exposome (HELIX) project.MethodsBlood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (transcription start site (TSS) within a window of 1 Mb) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, and cohort.ResultsWe identified 63,831 autosomal cis-eQTMs, representing 35,228 unique CpGs and 11,071 unique transcript clusters (TCs, genes). 74.3% of these cis-eQTMs were located at <250 kb, 60.0% showed an inverse relationship and 23.9% had at least one genetic variant associated with the methylation and expression levels. They were enriched for active blood regulatory regions. Adjusting for cellular composition decreased the number of cis-eQTMs to 37.7%, suggesting that some of them were cell type-specific. The overlap of child blood cis-eQTMs with those described in adults was small, and child and adult shared cis-eQTMs tended to be proximal to the TSS, enriched for genetic variants and with lower cell type specificity. Only half of the cis-eQTMs could be captured through annotation to the closest gene.ConclusionsThis catalogue of blood autosomal cis-eQTMs in children can help the biological interpretation of EWAS findings, and is publicly available at https://helixomics.isglobal.org/.

scholarly journals A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenglong You ◽  
Sijie Wu ◽  
Shijie C. Zheng ◽  
Tianyu Zhu ◽  
Han Jing ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Whole Blood ◽  
Immune Cell ◽  
Association Studies ◽  
Meta Analysis ◽  
Epigenetic Alterations ◽  
Cell Type ◽  
Hypersensitive Sites ◽  
A Cell ◽  
Cell Type Specific

Abstract Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

scholarly journals Calling differential DNA methylation at cell-type resolution: an objective status-quo

2019 ◽  
Author(s):  
Han Jing ◽  
Shijie C. Zheng ◽  
Charles E. Breeze ◽  
Stephan Beck ◽  
Andrew E. Teschendorff
Keyword(s):  
Dna Methylation ◽  
Association Studies ◽  
Cell Types ◽  
Status Quo ◽  
Specific Cell ◽  
Cell Type ◽  
Causal Pathways ◽  
Key Issues ◽  
Cell Type Specific ◽  
Different Cell Types

AbstractDue to cost and logistical reasons, Epigenome-Wide-Association Studies (EWAS) are normally performed in complex tissues, resulting in average DNA methylation profiles over potentially many different cell-types, which can obscure important cell-type specific associations with disease. Identifying the specific cell-types that are altered is a key hurdle for elucidating causal pathways to disease, and consequently statistical algorithms have recently emerged that aim to address this challenge. Comparisons between these algorithms are of great interest, yet here we find that the main comparative study so far was substantially biased and potentially misleading. By using this study as an example, we highlight some of the key issues that need to be considered to ensure that future assessments between methods are more objective.

scholarly journals Calling differential DNA methylation at cell-type resolution: avoiding misconceptions and promoting best practices

2021 ◽  
Author(s):  
Han Jing ◽  
Shijie C. Zheng ◽  
Charles E. Breeze ◽  
Stephan Beck ◽  
Andrew E. Teschendorff
Keyword(s):  
Dna Methylation ◽  
Best Practices ◽  
Important Task ◽  
Disease Development ◽  
Cell Type ◽  
Recent Commentary ◽  
Accurate Detection ◽  
Cell Type Specific ◽  
Statistical Algorithms

AbstractThe accurate detection of cell-type specific DNA methylation alterations in the context of general epigenome studies is an important task to improve our understanding of epigenomics in disease development. Although a number of statistical algorithms designed to address this problem have emerged, the task remains challenging. Here we show that a recent commentary by Rahmani et al, that aims to address misconceptions and best practices in the field, continues to suffer from critical misconceptions in how statistical algorithms should be compared and evaluated. In addition, we report contradictory results on real EWAS datasets.

scholarly journals Cell type‐specific DNA methylation analysis of the prefrontal cortex of patients with schizophrenia

2021 ◽  
Author(s):  
Junko Ueda ◽  
Miki Bundo ◽  
Yutaka Nakachi ◽  
Kiyoto Kasai ◽  
Tadafumi Kato ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Prefrontal Cortex ◽  
Cell Type ◽  
Methylation Analysis ◽  
Cell Type Specific ◽  
Dna Methylation Analysis

scholarly journals A scalable platform for the development of cell-type-specific viral drivers

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Sinisa Hrvatin ◽  
Christopher P Tzeng ◽  
M Aurel Nagy ◽  
Hume Stroud ◽  
Charalampia Koutsioumpa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heterologous Gene Expression ◽  
High Specificity ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Cell Type Specific ◽  
The Many ◽  
Dna Regulatory Elements

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research.

scholarly journals Partitioning heritability by functional category using GWAS summary statistics

2015 ◽  
Author(s):  
Hilary Kiyo Finucane ◽  
Brendan Bulik-Sullivan ◽  
Alexander Gusev ◽  
Gosia Trynka ◽  
Yakir Reshef ◽  
...  
Keyword(s):  
Association Studies ◽  
Smoking Behavior ◽  
Complex Diseases ◽  
New Method ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Cell Type ◽  
Genome Wide ◽  
Cell Type Specific

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

scholarly journals Transcribed enhancers in the human brain identify novel disease risk mechanisms

2021 ◽  
Author(s):  
Pengfei Dong ◽  
Gabriel E. Hoffman ◽  
Pasha Apontes ◽  
Jaroslav Bendl ◽  
Samir Rahman ◽  
...  
Keyword(s):  
Human Brain ◽  
Disease Risk ◽  
Association Studies ◽  
Population Level ◽  
Cell Type ◽  
Level Variation ◽  
Functional Interpretation ◽  
Neuropsychiatric Diseases ◽  
Order Of Magnitude ◽  
Cell Type Specific

Enhancer RNAs (eRNAs) constitute an important tissue- and cell-type-specific layer of the regulome. Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of eRNAs in the human brain. We jointly analyzed cell type-specific transcriptome and regulome data to identify 30,795 neuronal and 23,265 non-neuronal eRNAs, expanding the catalog of known human brain eRNAs by an order of magnitude. Examination of the population-level variation of the transcriptome and regulome in 1,382 brain samples identified reproducible changes affecting cis- and trans-co-regulation of eRNA-gene modules in schizophrenia. We show that 13% of schizophrenia heritability is jointly mediated in cis by brain gene and eRNA expression. Inclusion of eRNAs in transcriptome-wide association studies facilitated fine-mapping and functional interpretation of disease loci. Overall, our study characterizes the eRNA-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states.

scholarly journals Differences in DNA methylation of white blood cell types at birth and in adulthood reflect postnatal immune maturation and influence accuracy of cell type prediction

2018 ◽  
Author(s):  
Meaghan J Jones ◽  
Louie Dinh ◽  
Hamid Reza Razzaghian ◽  
Olivia de Goede ◽  
Julia L MacIsaac ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Immune System ◽  
Blood Cell ◽  
Cord Blood ◽  
White Blood Cell ◽  
Blood Cells ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Specific ◽  
The Impact

AbstractBackgroundDNA methylation profiling of peripheral blood leukocytes has many research applications, and characterizing the changes in DNA methylation of specific white blood cell types between newborn and adult could add insight into the maturation of the immune system. As a consequence of developmental changes, DNA methylation profiles derived from adult white blood cells are poor references for prediction of cord blood cell types from DNA methylation data. We thus examined cell-type specific differences in DNA methylation in leukocyte subsets between cord and adult blood, and assessed the impact of these differences on prediction of cell types in cord blood.ResultsThough all cell types showed differences between cord and adult blood, some specific patterns stood out that reflected how the immune system changes after birth. In cord blood, lymphoid cells showed less variability than in adult, potentially demonstrating their naïve status. In fact, cord CD4 and CD8 T cells were so similar that genetic effects on DNA methylation were greater than cell type effects in our analysis, and CD8 T cell frequencies remained difficult to predict, even after optimizing the library used for cord blood composition estimation. Myeloid cells showed fewer changes between cord and adult and also less variability, with monocytes showing the fewest sites of DNA methylation change between cord and adult. Finally, including nucleated red blood cells in the reference library was necessary for accurate cell type predictions in cord blood.ConclusionChanges in DNA methylation with age were highly cell type specific, and those differences paralleled what is known about the maturation of the postnatal immune system.

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