Variations in Innate Immune Cell Subtypes Correlate with Epigenetic Clocks, Inflammaging and Health Outcomes.

Epigenetic clocks in blood have shown promise as tools to quantify biological age, displaying robust associations with morbidity and all-cause mortality. Whilst the effect of cell-type heterogeneity on epigenetic clock estimates has been explored, such studies have been limited to studying heterogeneity within the adaptive immune system. Much less is known about whether heterogeneity within the innate immune system can impact epigenetic clock estimates and their associations with health outcomes.

Unified high-resolution immune cell fraction estimation in blood tissue from birth to old age.

Variations in immune-cell fractions can confound or hamper interpretation of DNAm-based biomarkers in blood. Although cell-type deconvolution can address this challenge for cord and adult blood, currently there is no method applicable to blood from other age groups, including infants and children. Here we construct and extensively validate a DNAm reference panel, called UniLIFE, for 19 immune cell-types, applicable to blood tissue of any age.

Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates.

Background: RNA velocity analysis of single cells offers the potential to predict temporal dynamics from gene expression. In many systems, RNA velocity has been observed to produce a vector field that qualitatively reflects known features of the system. However, the limitations of RNA velocity estimates are still not well understood.

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes.

Background: Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition.

Universal prediction of cell-cycle position using transfer learning.

Background: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data.

Limb development genes underlie variation in human fingerprint patterns.

Fingerprints are of long-standing practical and cultural interest, but little is known about the mechanisms that underlie their variation. Using genome-wide scans in Han Chinese cohorts, we identified 18 loci associated with fingerprint type across the digits, including a genetic basis for the long-recognized "pattern-block" correlations among the middle three digits. In particular, we identified a variant near EVI1 that alters regulatory activity and established a role for EVI1 in dermatoglyph patterning in mice.

recount3: summaries and queries for large-scale RNA-seq expression and splicing.

We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features.

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

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.

EpiDISH web server: Epigenetic Dissection of Intra-Sample-Heterogeneity with online GUI.

Summary: It is well recognized that cell-type heterogeneity hampers the interpretation of Epigenome-Wide Association Studies (EWAS). Many tools have emerged to address this issue, including several R/Bioconductor packages that infer cell-type composition. Here we present a web application for cell-type deconvolution, which offers the functionality of our EpiDISH Bioconductor/R package in a user-friendly GUI environment.

ebGSEA: an improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies.

Motivation: The biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies (EWAS) remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips.

Results: We present a novel GSEA method, called ebGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene.

Identification of differentially methylated cell types in epigenome-wide association studies.

An outstanding challenge of epigenome-wide association studies (EWASs) performed in complex tissues is the identification of the specific cell type(s) responsible for the observed differential DNA methylation. Here we present a statistical algorithm called CellDMC ( https://github.com/sjczheng/EpiDISH ), which can identify differentially methylated positions and the specific cell type(s) driving the differential methylation.

Cell and tissue type independent age-associated DNA methylation changes are not rare but common.

Age-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic 'clocks' that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific.

A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix.

Aim: An outstanding challenge in epigenome studies is the estimation of cell-type proportions in complex epithelial tissues.

Materials & Methods: Here, we construct and validate a DNA methylation reference and algorithm for complex tissues that contain epithelial, immune and nonimmune stromal cells.

Results: Using this reference, we show that easily accessible tissues such as saliva, buccal and cervix exhibit substantial variation in immune cell (IC) contamination.

Cell-type deconvolution in epigenome-wide association studies: a review and recommendations.

A major challenge faced by epigenome-wide association studies (EWAS) is cell-type heterogeneity. As many EWAS have already demonstrated, adjusting for changes in cell-type composition can be critical when analyzing and interpreting findings from such studies. Because of their importance, a great number of different statistical algorithms, which adjust for cell-type composition, have been proposed.

A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies.

Background: Intra-sample cellular heterogeneity presents numerous challenges to the identification of biomarkers in large Epigenome-Wide Association Studies (EWAS). While a number of reference-based deconvolution algorithms have emerged, their potential remains underexplored and a comparative evaluation of these algorithms beyond tissues such as blood is still lacking.

Results: Here we present a novel framework for reference-based inference, which leverages cell-type specific DNAse Hypersensitive Site (DHS) information from the NIH Epigenomics Roadmap to construct an improved reference DNA methylation database.

Correlation of an epigenetic mitotic clock with cancer risk.

Background: Variation in cancer risk among somatic tissues has been attributed to variations in the underlying rate of stem cell division. For a given tissue type, variable cancer risk between individuals is thought to be influenced by extrinsic factors which modulate this rate of stem cell division. To date, no molecular mitotic clock has been developed to approximate the number of stem cell divisions in a tissue of an individual and which is correlated with cancer risk.

The multi-omic landscape of transcription factor inactivation in cancer.

Background: Hypermethylation of transcription factor promoters bivalently marked in stem cells is a cancer hallmark. However, the biological significance of this observation for carcinogenesis is unclear given that most of these transcription factors are not expressed in any given normal tissue.

Methods: We analysed the dynamics of gene expression between human embryonic stem cells, fetal and adult normal tissue, as well as six different matching cancer types.

DNA Methylation Signatures in Vaginal Fluid Samples for Detection of Cervical and Endometrial Cancer.

Objective: A noninvasive tool that allows individuals to be monitored who are at risk of developing a malignancy is an unmet need. Such a test would need to consist of a molecular signature that allows for gradual judgment to assess the efficacy of preventive strategies. Here we performed a proof-of-principle study to test whether a DNA methylation (DNAme) signature in fluid collected from the vagina is able to identify women with cervical or endometrial cancer.

Epigenetic drift, epigenetic clocks and cancer risk.

It is well-established that the DNA methylation landscape of normal cells undergoes a gradual modification with age, termed as 'epigenetic drift'. Here, we review the current state of knowledge of epigenetic drift and its potential role in cancer etiology. We propose a new terminology to help distinguish the different components of epigenetic drift, with the aim of clarifying the role of the epigenetic clock, mitotic clocks and active changes, which accumulate in response to environmental disease risk factors.