There are more than 700 genes that encode proteins that function in epigenetic regulation and chromatin modification. Germline variants in these genes (typically heterozygous) are associated with rare neurodevelopmental disorders (NDDs) characterized by growth abnormalities and intellectual and developmental delay. Advancements in next-generation sequencing have dramatically increased the detection of pathogenic sequence variants in genes encoding epigenetic machinery associated with NDDs and, concurrently, the number of clinically uninterpretable variants classified as variants of uncertain significance (VUS). Recently, DNA methylation (DNAm) signatures, disorder-specific patterns of DNAm change, have emerged as a functional tool that provides insights into disorder pathophysiology and can classify pathogenicity of variants in NDDs. To date, our group and others have identified DNAm signatures for more than 60 Mendelian neurodevelopmental disorders caused by variants in genes encoding epigenetic machinery. There is broad interest in both the research and clinical communities to develop and catalog DNAm signatures in rare NDDs, but there are challenges in optimizing study design considerations and availability of platforms that integrate bioinformatics tools with the appropriate statistical framework required to analyze genome-wide DNAm data. We previously published EpigenCentral, a platform for analysis of DNAm data in rare NDDs. In this article, we utilize the published Weaver syndrome dataset to provide step-by-step protocols for using EpigenCentral for exploratory analysis to identify DNAm signatures and for classification of NDD variants. We also provide important considerations for experimental design and interpretation of DNAm results. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Exploratory analysis to identify disorder-specific DNAm signatures Basic Protocol 2: Classification of variants associated with neurodevelopmental disorders.
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http://dx.doi.org/10.1002/cpz1.597 | DOI Listing |
Background: People living with the human immunodeficiency virus (HIV) are at a greater risk of developing hepatocellular carcinoma (HCC), potentially due to the stimulation of inflammation by HIV infection. Inflammation-related DNA methylation signatures obtained in liquid biopsy, such as circulating cell-free DNA (cfDNA), may serve as promising minimally invasive biomarkers that can inform diagnosis of HCC.
Methods: Using data from 249 individuals with HIV (114 individuals with normal liver conditions, 69 with fibrosis, 30 with cirrhosis, and 36 with HCC), we constructed a cfDNA methylation-based inflammation score (inflammation-DNAm score) based on 54 CpGs previously associated with circulating C-reactive protein concentrations.
medRxiv
November 2024
Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA.
Introduction: Distinguishing between molecular changes that precede dementia onset and those resulting from the disease is challenging with cross-sectional studies.
Methods: We studied blood DNA methylation (DNAm) differences and incident dementia in two large longitudinal cohorts: the Offspring cohort of the Framingham Heart Study (FHS) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We analyzed blood DNAm samples from over 1,000 cognitively unimpaired subjects.
Res Sq
November 2024
Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA.
Sci Rep
November 2024
Division of Inflammation and Infection, Lab 1, Floor 12, Linköping University, 58185, Linköping, Sweden.
Tuberculosis (TB) poses a significant global health threat, with high mortality rates if left untreated. Current sputum-based TB treatment monitoring methods face numerous challenges, particularly in relation to sample collection and analysis. This pilot study explores the potential of TB status assessment using DNA methylation (DNAm) signatures, which are gaining recognition as diagnostic and predictive tools for various diseases.
View Article and Find Full Text PDFBackground: Approximately one-third of breast cancer (BC) patients show poorer cognitive function (CF) before receiving adjuvant therapy compared with age-matched healthy controls. However, the biological mechanisms driving CF variation in the context of BC remain unclear. In this study, we aimed to identify genes and biological pathways associated with CF in postmenopausal women with early-stage hormone receptor-positive (HR+) BC using DNA methylation (DNAm) data, a dynamic regulator of gene activity.
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