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Biology subjects

Chioza, B.

Publications and source records attributed to Chioza, B..

6 recordsLinked to original sources

Schizophrenia-associated DNA methylation differences in the cortex are neuron-specific

Schizophrenia is a complex neuropsychiatric disorder in which genetic risk is thought to converge on cell type-specific regulatory mechanisms in the brain. We performed a cell type-resolved epigenome-wide association study (EWAS) of schizophrenia using fluorescence-activated nuclei sorting (FANS) to isolate neuron-enriched (NeuN+), oligodendrocyte-enriched (SOX10+) and other glial-enriched (NeuN-/SOX10-) nuclei populations alongside total prefrontal cortex nuclei fractions from 216 donors (104 schizophrenia cases and 112 controls). We identified 16 differentially methylated positions (DMPs) in neuron-enriched nuclei at experiment-wide significance and more than 400 additional neuronal DMPs at a discovery threshold. In contrast, no significant associations were identified in oligodendrocyte-enriched, glial-enriched or total nuclei fractions, demonstrating that schizophrenia-associated cortical methylomic variation is highly neuron-specific and largely masked in bulk tissue analyses. Neuronal DMPs exhibited a significant bias towards hypomethylation in schizophrenia and were enriched at loci implicated by genetic studies, including CACNA1C, CACNA1G and TRIO. Pathway analyses implicated genes involved in neurodevelopment, cell adhesion, synapse organisation, neurotransmission and synaptic plasticity. Schizophrenia-associated DNA methylation signatures identified in prefrontal cortex neurons showed correlated effects in neuronal nuclei isolated from the hippocampus and striatum, indicating partial conservation of disease-associated epigenetic alterations across brain regions. Together, these findings provide strong evidence for widespread neuron-specific epigenetic dysregulation in schizophrenia and highlight the importance of cell type-resolved approaches for elucidating the molecular mechanisms underlying psychiatric disease.

genomics↗

Optimised fluorescence-activated nuclei sorting for epigenomic analysis of cortical cell types

Increased understanding of the functional complexity of the genome has led to growing recognition of the role of non-sequence-based regulatory variation in disorders of the human central nervous system. Most genomic analyses of the brain are limited by the use of bulk tissue, which comprises a heterogeneous mix of different neural cell types with distinct epigenetic profiles, thereby limiting the ability to attribute regulatory changes to specific cell populations. Given the limited availability of human post-mortem tissue resources and the importance of integrating multi-omic data from the same samples, there is a critical need for methods that enable parallel, cell-type-resolved genomic profiling. We present optimised protocols using fluorescence-activated nuclei sorting (FANS) to isolate nuclei from different human and mouse brain cell types for downstream multi-omic analysis. Our approach enables the robust purification of neuronal, oligodendrocyte, microglial and other glial-origin nuclei from both adult and fetal brain tissue. We demonstrate that FANS-isolated nuclei are compatible with a wide range of genomic assays, including profiling of DNA modifications, histone modifications, chromatin accessibility, and gene expression. This protocol maximises the utility of limited post-mortem tissue resources and provides a unified workflow for comprehensive, cell-type-specific interrogation of molecular mechanisms involved in the brain.

genomics↗

Cell-type-specific DNA methylation dynamics in the prenatal and postnatal human cortex

The human cortex undergoes extensive epigenetic remodelling during development, although the precise temporal and cell-type-specific dynamics of DNA methylation remain incompletely understood. In this study, we profiled genome-wide DNA methylation across human cortex tissue from donors aged 6 post-conception weeks (pcw) to 108 years of age. We observed widespread, developmentally regulated, changes in DNA methylation, with pronounced shifts occurring during early- and mid-gestation that were distinct from age-associated modifications in the postnatal cortex. Using fluorescence-activated nuclei sorting (FANS), we optimized a protocol for the isolation of SATB2-positive neuronal nuclei, enabling the identification of cell-type-specific DNA methylation trajectories in developing neuronal and non-neuronal populations. Developmentally dynamic DNA methylation sites were significantly enriched near genes implicated in autism and schizophrenia, supporting a role for epigenetic dysregulation in neurodevelopmental disorders. Our findings underscore the prenatal period as a critical window of epigenomic plasticity in the central nervous system with important implications for understanding the genetic basis of neurodevelopmental phenotypes.

genomics↗

Guidance for the design and analysis of cell-type specific epigenetic epidemiology studies.

Recent studies on the role of epigenetics in disease have focused on DNA methylation profiled in bulk tissues limiting the detection of the cell-type affected by disease related changes. Advances in isolating homogeneous populations of cells now make it possible to identify DNA methylation differences associated with disease in specific cell-types. Critically, these datasets will require a bespoke analytical framework that can characterise whether the difference affects multiple or is specific to a particular cell-type. We take advantage of a large set of DNA methylation profiles (n = 751) obtained from five different purified cell populations isolated from human prefrontal cortex samples and evaluate the effects on study design, data preprocessing and statistical analysis for cell-specific studies, particularly for scenarios where multiple cell types are included. We describe novel quality control metrics that confirm successful isolation of purified cell populations, which when included in standard preprocessing pipelines provide confidence in the dataset. Our power calculations show substantial gains in detecting differentially methylated positions for some purified cell populations compared to bulk tissue analyses, countering concerns regarding the feasibility of generating large enough sample sizes for informative epidemiological studies. In a simulation study, we evaluated different regression models finding that this choice impacts on the robustness of the results. These findings informed our proposed two-stage framework for association analyses. Overall, our results provide guidance for cell-specific EWAS, establishing standards for study design and analysis, while showcasing the potential of cell-specific DNA methylation analyses to reveal links between epigenetic dysregulation and disease.

bioinformatics↗

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BackgroundDue to inter-individual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell-types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal- and three glial-cell subtypes for quantifying the cellular composition of the human cortex. ResultsWe tested eight reference panels containing different combinations of neuronal- and glial-cell types and characterized their performance in deconvoluting cell proportions from computationally reconstructed or empirically-derived human cortex DNA methylation data. Our analyses demonstrate that these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimers disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei. ConclusionsOur novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

genomics↗

DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types

Alzheimers disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. Utilizing extensive neuropathology data from the Brains for Dementia Research (BDR) cohort we performed the most systematic epigenome-wide association study (EWAS) of multiple measures of AD neuropathology yet undertaken, profiling DNA methylation in two cortical regions from 631 donors. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2,013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at novel loci not previously implicated in dementia. We subsequently characterized DNA methylation in purified nuclei populations - enriched for neurons, oligodendrocytes and microglia - exploring the extent to which cortex AD-associated DMPs reflect differences manifest in specific cell populations. We find that the majority of DMPs identified in bulk cortex tissue actually reflect DNA methylation differences occurring in non-neuronal cells, with dramatically increased effect sizes observed in microglia-enriched nuclei populations. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified neural cell-types.

genetics↗