Biology subjects

Nachun, D.

Publications and source records attributed to Nachun, D..

9 recordsLinked to original sources

bioRxiv2026

Somatic mutations reveal the ontogeny of human microglia

Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimers disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.

immunology↗

bioRxiv2025

SuSiE 2.0: improved methods and implementations for genetic fine-mapping and phenotype prediction

Sum of Single Effects regression (SuSiE) has become widely adopted for genetic fine-mapping, yet its original implementation faces architectural limitations that hinder extensibility and performance. We present SuSiE 2.0, featuring a modular redesign for extensibility, up to 5x speed improvements for summary statistics applications, and several useful extensions including SuSiE-ash, a new method that improves calibration when strong signals coexist with moderate effects. Simulations and real data benchmarks demonstrate performance across diverse genetic architectures, highlighting improved calibration of SuSiE-ash for fine-mapping under complex polygenic backgrounds with 1.5-3x FDR reduction while maintaining power, and revealing SuSiE-based methods as effective yet underappreciated tools for TWAS prediction.

bioinformatics↗

bioRxiv2025

Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

genomics↗

bioRxiv2024

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimers disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden--significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PI-CALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

genomics↗

bioRxiv2022

PRC2 clock: a universal biomarker of aging and rejuvenation

DNA methylation (DNAm) is one of the most reliable biomarkers for aging across many mammalian tissues. While the age-dependent global loss of DNAm has been well characterized, age-dependent DNAm gain is less specified. Multiple studies have demonstrated that polycomb repressive complex 2 (PRC2) targets are enriched among the CpG sites which gain methylation with age. However, a systematic whole-genome examination of all PRC2 targets in the context of aging methylome as well as whether these associations are pan-tissue or tissue-specific is lacking. Here, by analyzing DNAm data from different assays and from multiple young and old human and mouse tissues, we found that low-methylated regions (LMRs) which are highly bound by PRC2 in embryonic stem cells gain methylation with age in all examined somatic mitotic cells. We also estimated that this epigenetic change represents around 90% of the age-dependent DNAm gain genome-wide. Therefore, we propose the "PRC2 clock," defined as the average DNAm in PRC2 LMRs, as a universal biomarker of cellular aging in somatic cells. In addition, we demonstrate the application of this biomarker in the evaluation of different anti-aging interventions, including dietary restriction and partial epigenetic reprogramming.

genomics↗

bioRxiv2021

Nonsense-mediated decay is highly stable across individuals and tissues.

Precise interpretation of the effects of protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA-sequencing of the Genotype Tissue Expression v8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency <=1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, including ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstrate in silico that utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.

genomics↗

bioRxiv2019

Systems analysis of blood transcriptomes in dementia patients reveals an innate immune response shared across disorders

The role of peripheral inflammation in dementia is an important but complex topic. We present here the largest cohort of peripheral blood gene expression data ever assembled from patients with dementia and matching controls. Importantly, this cohort includes individuals from a diverse set of dementia disorders, including Alzheimers Disease (AD), mild cognitive impairment (MCI), and multiple disorders within the frontotemporal dementia (FTD) spectrum. We found strong transcriptional evidence of an innate immune inflammatory response, mediated by monocytes and neutrophils, in AD, MCI, and two FTD subtypes, PSP and nfvPPA. This transcriptional inflammatory response is enriched for genetic risk for AD, in part because it is also enriched for microglial genes, which have previously been implicated in AD risk. Finally, we show that this transcriptional response is strongly enriched for binding of the transcription factors PU.1 and RELA, which have previously been linked to AD risk and progression.

bioinformatics↗

bioRxiv2019

Synaptic and Gene Regulatory Mechanisms in Schizophrenia, Autism, and 22q11.2 CNV Mediated Risk for Neuropsychiatric Disorders

Background22q11.2 copy number variants (CNVs) are among the most highly penetrant genetic risk variants for developmental neuropsychiatric disorders such as schizophrenia (SCZ) and autism spectrum disorder (ASD). However, the specific mechanisms through which they confer risk remain unclear. MethodsUsing a functional genomics approach, we integrated transcriptomic data from the developing human brain, genome-wide association findings for SCZ and ASD, protein interaction data, and pathophysiological signatures of SCZ and ASD to: 1) organize genes into the developmental cellular and molecular systems within which they operate; 2) identify neurodevelopmental processes associated with polygenic risk for SCZ and ASD across the allelic frequency spectrum; and 3) elucidate pathways and individual genes through which 22q11.2 CNVs may confer risk for each disorder. ResultsPolygenic risk for SCZ and ASD converged on partially overlapping gene networks involved in synaptic function and transcriptional regulation, with ASD risk variants additionally enriched for networks involved in neuronal differentiation during fetal development. The 22q11.2 locus formed a large protein network that disproportionately affected SCZ- and ASD-associated neurodevelopmental networks, including loading highly onto synaptic and gene regulatory pathways. SEPT5, PI4KA, and SNAP29 genes are candidate drivers of 22q11.2 synaptic pathology relevant to SCZ and ASD, and DGCR8 and HIRA are candidate drivers of disease-relevant alterations in gene regulation. ConclusionsThe current approach provides a powerful framework to identify neurodevelopmental processes affected by diverse risk variants for SCZ and ASD, and elucidate the mechanisms through which highly penetrant multi-gene CNVs contribute to disease risk.

systems biology↗

bioRxiv2018

Transcriptional profiling of isogenic Friedreich ataxia induced pluripotent stem cell-derived neurons

Friedreich ataxia (FRDA) is a rare childhood neurodegenerative disorder with no effective treatment. FRDA is caused by transcriptional silencing of the FXN gene and consequent loss of the essential mitochondrial protein frataxin. Based on the knowledge that a GAA*TTC repeat expansion in the first intron of FXN leads to heterochromatin formation and gene silencing, we have shown that members of the 2-aminobenzamide family of histone deacetylase inhibitors (HDACi) reproducibly increase FXN mRNA levels in induced pluripotent stem cell (iPSC)-derived FRDA neuronal cells and in peripheral blood mononuclear cells from patients treated with the drug in a phase I clinical trial. How the reduced expression of frataxin leads to neurological and other systemic symptoms in FRDA patients remains unclear. Similarly to other triplet repeat disorders, it is not known why only specific cells types are affected in the disease, primarily the large sensory neurons of the dorsal root ganglia and cardiomyocytes. The combination of iPSC technology and genome editing techniques offers the unique possibility of addressing these questions in a relevant cell model of the disease, without the confounding effect of different genetic backgrounds. We derived a set of isogenic iPSC lines that differ only in the length of the GAA*TTC repeats, using \"scarless\" gene-editing methods (helper-dependent adenovirus-mediated homologous recombination). To uncover the gene expression signature due to GAA*TTC repeat expansion in FRDA neuronal cells and the effect of HDACi on these changes, we performed transcriptomic analysis of iPSC-derived central nervous system (CNS) and isogenic sensory neurons by RNA sequencing. We find that multiple cellular pathways are commonly affected by the loss of frataxin in CNS and peripheral nervous system neurons and these changes are partially restored by HDACi treatment.

neuroscience↗