Joe Burrage

The paper introduces PIPPA, a pipeline for processing large-scale ATAC-seq data, showing that peak calling performance varies by dataset and recommending parameters for high-confidence chromatin accessibility profiles.

The paper introduces optimized fluorescence-activated nuclei sorting (FANS) protocols to isolate cell-type-specific nuclei from human and mouse brain tissue for multi-omic analysis.

The paper identifies cell-type-specific DNA methylation differences in autism, revealing female-specific X chromosome alterations in microglia.

The paper identifies neuron-specific DNA methylation differences in schizophrenia using cell type-resolved epigenome-wide association study in prefrontal cortex nuclei.

This study identifies DNA methylation differences between microsatellite stable and microsatellite instable colorectal cancers, revealing MLH1-independent markers of mismatch repair deficiency and the impact of anatomical location.

This study identifies neuron-specific DNA methylation changes in Parkinson's disease prefrontal cortex, revealing hypermethylation at seven novel loci and highlighting the importance of cell-type-specific analysis.

The paper provides guidance for designing and analyzing cell-type specific epigenetic epidemiology studies using DNA methylation data from purified cell populations.

The paper develops a multivariate methylation risk score using blood DNA methylation data to predict dementia risk and cognitive impairment in Alzheimer's and Parkinson's disease cohorts.

The paper develops and validates deconvolution models using DNA methylation data to estimate cell-type proportions in the human cortex, finding glial cells are twice as abundant as neurons and linking cell-type proportions to Alzheimer's disease neuropathology.

The paper quantifies DNA methylation changes in human fetal pancreas development, identifying developmental differentially methylated positions and their genomic distribution.

The paper identifies DNA methylation signatures in Alzheimer's disease cortex, showing most changes are driven by non-neuronal cell types.

This paper introduces and validates a metric to assess the accuracy of cellular deconvolution in DNA methylation studies, showing it identifies biases in different demographic groups.

The paper develops a novel epigenetic clock for fetal brain development to predict prenatal age in iPSCs and derived neurons, showing they remain epigenetically fetal despite differentiation.

This study examines DNA methylation differences across blood cell types and tissues, showing that whole blood DNAm reflects contributions from multiple cell types rather than being cell-type specific.

The paper develops a novel DNA methylation clock optimized for human cortex tissue, outperforming existing clocks and highlighting issues with previous associations between DNA methylation age and neurodegenerative phenotypes.

This study identifies DNA methylation changes in blood samples from psychosis patients, including treatment-resistant schizophrenia, and links them to biological age, smoking, and cellular composition.

This study shows major surgery causes acute DNA methylation changes in immune-related genes, linked to inflammation markers like CRP and IL-6, persisting until hospital discharge.

The paper identifies mQTLs and pleiotropic associations between DNAm, gene expression, and complex traits using SMR and a large UK cohort.

The paper examines the properties of the Horvath epigenetic clock in older individuals and finds age acceleration measures are age-dependent and may lead to misleading associations with diseases like Alzheimer's.