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. Some of the methods are ‘reference based’ in that they require a priori defined reference DNA methylation profiles of cell types that are present in the tissue of interest, while other algorithms are ‘reference free.’ At present, however, it is unclear how best to adjust for cell-type heterogeneity, as this may also largely depend on the type of tissue and phenotype being considered. Here, we provide a critical review of the major existing algorithms for correcting cell-type composition in the context of Illumina Infinium Methylation Beadarrays, with the aim of providing useful recommendations to the EWAS community

A performance model for a local VoD system

Theme: Trends in Information Systems Engineering and Wireless Multimedia CommunicationsA multimedia information system provides an effective means to convey information to users. This paper studies the problem of carrying out video on demand (VoD) application over a high speed LAN to support Computer Supported Collaborative Working (CSCW) for people working in a local collaborative environment. A multimedia information system using HP 100VG-AnyLAN is proposed and setup for this purpose. Based on this system, a performance model is developed, which can be used to determine the requirement of network bandwidth and evaluate the system performance.published_or_final_versio

Techniques for improving block error rate of LDPC decoders

Author name used in this publication: F. C. M. LauAuthor name used in this publication: C. K. TseAuthor name used in this publication: S. C. WongRefereed conference paper2005-2006 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

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. We show that this leads to a marginal but statistically significant improvement of cell-count estimates in whole blood as well as in mixtures involving epithelial cell-types. Using this framework we compare a widely used state-of-the-art reference-based algorithm (called constrained projection) to two non-constrained approaches including CIBERSORT and a method based on robust partial correlations. We conclude that the widely-used constrained projection technique may not always be optimal. Instead, we find that the method based on robust partial correlations is generally more robust across a range of different tissue types and for realistic noise levels. We call the combined algorithm which uses DHS data and robust partial correlations for inference, EpiDISH (Epigenetic Dissection of Intra-Sample Heterogeneity). Finally, we demonstrate the added value of EpiDISH in an EWAS of smoking. CONCLUSIONS: Estimating cell-type fractions and subsequent inference in EWAS may benefit from the use of non-constrained reference-based cell-type deconvolution methods

A Scoping Survey to Inform Design of Digital Dementia Risk Reduction Interventions for Adults Concerned about their Cognitive Health

Background: Digital dementia risk reduction interventions are cost-effective and scalable. However, it is unknown how they are perceived by people already experiencing cognitive concerns or decline. Objective: To understand the current use, interest, and preferences for online learning courses and interest in learning about factors influencing brain health and dementia risk among adults ≥45. To explore potential differences between individuals experiencing cognitive concerns and those without. Methods: Adults aged 45 and older completed a survey on technology use and healthy ageing (n = 249, Mean age = 65.6, 76.3% female). The Memory Assessment Clinic-Questionnaire was used to assess subjective memory decline, and 153 participants met the study criteria for cognitive concerns (≥25). Results: Almost all participants (98.4%) reported using two or more digital devices, and 51.8% reported increasing device usage following COVID-19. Most (92.1%) were interested in learning about healthy living and memory within an online course, and over 80% indicated a high interest in learning about dementia risk factors. People with cognitive concerns were more likely to report using a 'routine or system' to aid memory than people without (82.4% versus 62.9%, p = 0.001). However, no significant difference was found in technology use, course preferences, or interest in learning about different risk factors. Conclusions: We conclude that adults 45 years and over are interested in online methods for learning about brain health and offer unique insights into adapting dementia prevention programs for cognitive concerns

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. In addition, we performed an integrative multi-omic analysis of matched DNA methylation, copy number, mutational and transcriptomic data for these six cancer types. RESULTS: We here demonstrate that bivalently and PRC2 marked transcription factors highly expressed in a normal tissue are more likely to be silenced in the corresponding tumour type compared with non-housekeeping genes that are also highly expressed in the same normal tissue. Integrative multi-omic analysis of matched DNA methylation, copy number, mutational and transcriptomic data for six different matching cancer types reveals that in-cis promoter hypermethylation, and not in-cis genomic loss or genetic mutation, emerges as the predominant mechanism associated with silencing of these transcription factors in cancer. However, we also observe that some silenced bivalently/PRC2 marked transcription factors are more prone to copy number loss than promoter hypermethylation, pointing towards distinct, mutually exclusive inactivation patterns. CONCLUSIONS: These data provide statistical evidence that inactivation of cell fate-specifying transcription factors in cancer is an important step in carcinogenesis and that it occurs predominantly through a mechanism associated with promoter hypermethylation

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

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. Users can upload their data to infer cell-type composition and differentially methylated cytosines in individual cell-types (DMCTs) for a range of different tissues. Availability and implementation EpiDISH web server is implemented with Shiny in R, and is freely available at https://www.biosino.org/EpiDISH/

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. We further validate our reference in the context of oral cancer, where it correctly predicts an increased IC infiltration in cancer but suppressed in patients with highest smoking exposure. Finally, our method can improve the specificity of differentially methylated CpG calls in epithelial cancer. CONCLUSION: The degree and variation of IC contamination in complex epithelial tissues is substantial. We provide a valuable resource and tool for assessing the epithelial purity and IC contamination of samples and for identifying differential methylation in such complex tissues