Biology subjects

Green, G.

Publications and source records attributed to Green, G..

12 recordsLinked to original sources

bioRxiv2026

Altered microglial communication in brains with Alzheimers Disease pathology

Microglia are the resident immune cells of the central nervous system and are highly versatile, continuously monitoring the brain microenvironment with their motile processes and responding to perturbations in diverse ways. Recent studies have revealed substantial functional heterogeneity among microglial states, suggesting that analyzing individual subpopulations is essential to capture specialized signaling programs and disease-associated interactions that would otherwise be obscured in bulk analyses. To better understand how these cells interact, we performed a ligand-receptor communication analysis using single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex, comprising 16 microglial subpopulations together with other myeloid cells identified in brain tissue, including macrophages and monocytes. We characterized the signaling roles of these cell populations, compared individuals with and without neuropathologically defined Alzheimers disease, and associated cell-pair interactions with AD-related clinical and neuropathological traits. We found that AD was characterized by altered microglial composition and rewiring of intercellular communication, including disease-specific signaling pathways and distinct interaction hubs. Lipid-associated microglia were associated with tau pathology, whereas nuclear receptor signaling microglia were linked to hippocampal sclerosis. These findings were replicated in three independent datasets. Overall, this work provides an initial but comprehensive map of microglial communication in the aging human brain and identifies candidate signaling interactions for future functional validation.

neuroscience↗

bioRxiv2026

NINTEDANIB AND PIRFENIDONE AFFECT GROWTH AND DIFFERENTIATION OF HUMAN ALVEOLAR TYPE 2 CELLS

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease characterized by epithelial cell senescence. Pirfenidone and nintedanib are approved drugs for the treatment of IPF. They significantly slow disease progression, but their mechanisms of action, especially on alveolar type 2 (AT2) cells, are poorly understood. We addressed this question by evaluating colony formation and growth of human AT2 cells co-cultured with fibroblasts in organoid culture in the presence of pirfenidone and nintedanib. We further evaluated molecular changes induced by these drugs via single cell RNA-seq of treated organoids. MethodsAT2 cells isolated from normal donor lungs or IPF patients were mixed with human fibroblasts in 3D culture and grown in the absence or presence of pirfenidone or nintedanib. After 14 days in culture, the organoids were quantified and cells extracted from Matrigel for single cell RNA-seq. ResultsAT2 cell organoids cultured in the presence of pirfenidone or nintedanib resulted in increased colony formation and, in the case of nintedanib, in larger colonies. We observed that untreated or pirfenidone treated AT2 cells lost surfactant protein C (SFTPC) expression and acquired an expression profile consistent with keratin (KRT)17high/KRT5- basaloid cells, whereas a larger proportion of nintedanib treated cells retained SFTPC expression. In contrast, AT2 cells treated with TGF{beta} inhibitor exhibited intermediate (SFTPC-/KRT17low) gene expression profile. ConclusionThese results suggest that nintedanib maintains an AT2-like expression state in culture and acts proximal to TGF{beta}. Conflict of Interest StatementPJW was supported by grants from Boehringer Ingelheim, Roche, Sanofi, Pliant and Arda Therapeutics and received personal fees from Boehringer Ingelheim and Sanofi. None of these companies had a role in the design or analysis of the study or in the writing of the manuscript. ASM, GP, JRR and DG are employees of Genetech. The other authors have no conflicts of interest to declare.

cell biology↗

bioRxiv2025

Gene module-trait network analysis uncovers cell type specific systems and genes relevant to Alzheimers Disease

Alzheimers Disease (AD) is marked by the accumulation of pathology, neuronal loss, and gliosis and frequently accompanied by cognitive decline. Understanding brain cell interactions is key to identifying new therapeutic targets to slow its progression. Here, we used systems biology methods to analyze single-nucleus RNA sequencing (snRNASeq) data generated from dorsolateral prefrontal cortex (DLPFC) tissues of 424 participants in the Religious Orders Study or the Rush Memory and Aging Project (ROSMAP). We identified modules of co-regulated genes in seven major cell types, assigned them to coherent cellular processes, and assessed which modules were associated with AD traits such as cognitive decline, tangle density, and amyloid-{beta} deposition. Coexpression network structure was conserved in the majority of modules across cell types, but we also found distinct communities with altered connectivity, especially when compared to bulk RNASeq, suggesting cell-specific gene co-regulation. These coexpression modules can also capture signatures of cell subpopulations and be influenced by cell proportions. Using a Bayesian network framework, we modeled the direction of relationships between the modules and AD progression. We highlight two key modules, a microglia module (mic_M46), associated with tangles; and an astrocyte module (ast_M19), associated with cognitive decline. Our work provides cell-specific molecular networks modeling the molecular events leading to AD.

systems biology↗

bioRxiv2024

A chromosome-level genome assembly of the Hispid cotton rat (Sigmodon hispidus), a model for human pathogenic virus infections

BackgroundThe cotton rat (Sigmodon hispidus), a rodent species native to the Americas, has emerged as a valuable laboratory model of infections by numerous human pathogens including poliovirus and respiratory syncytial virus (RSV). ResultsHere we report the first reference assembly of the cotton rat genome organized at a chromosomal level, providing annotation of 24,878 protein-coding genes. Data from PCR-free whole genome sequencing, linked-read sequencing and RNA sequencing from pooled cotton rat tissues were analyzed to assemble and annotate this novel genome sequence. Spectral karyotyping data using fluorescent probes derived from mouse chromosomes facilitated the assignment of cotton rat orthologs to syntenic chromosomes, comprising 25 autosomes and a sex chromosome in the haploid genome. Comparative phylome analysis revealed both gains and losses of numerous genes including immune defense genes against pathogens. We identified thousands of recently retrotransposed L1 and SINE B2 elements, revealing widespread genetic innovations unique to this species. ConclusionsWe anticipate that annotation and characterization of the first chromosome-level cotton rat genome assembly as described here will enable and accelerate ongoing investigations into its host defenses against viral and other pathogens, genome biology and mammalian evolution.

genomics↗

bioRxiv2022

A cross-disease human microglial framework identifies disease-enriched subsets and tool compounds for microglial polarization.

Human microglia play a pivotal role in neurological diseases, but few targeted therapies that directly modulate microglial state or function exist due to an incomplete understanding of microglial heterogeneity. We use single-cell RNA sequencing to profile live human microglia from autopsies or surgical resections across diverse neurological diseases and central nervous system regions. We observe a central divide between oxidative and heterocyclic metabolism and identify subsets associated with antigen presentation, motility, and proliferation. Specific subsets are enriched in susceptibility genes for neurodegenerative diseases or the disease-associated microglial signature. We validate subtypes in situ with an RNAscope-immunofluorescence pipeline and leverage our dataset as a classification resource, finding that iPSC model systems recapitulate substantial in vivo heterogeneity. Finally, we identify and validate candidates for chemically inducing subtype-specific states in vitro, showing that Camptothecin downregulates the transcriptional signature of disease-enriched subsets and upregulates a signature previously shown to be depleted in Alzheimers.

neuroscience↗

bioRxiv2020

Multi-cellular communities are perturbed in the aging human brain and with Alzheimer's disease

The role of different cell types and their interactions in Alzheimers disease (AD) is an open question. Here we pursued it by assembling a high-resolution cellular map of the aging frontal cortex by single nucleus RNA-seq of 24 individuals with different clinicopathologic characteristics. We used the map to infer the neocortical cellular architecture of 638 individuals profiled by bulk RNA-seq, providing the sample size necessary for identifying statistically robust associations. We uncovered diverse cell populations associated with AD, including inhibitory neuronal subtypes and oligodendroglial states. We further recovered a network of multicellular communities, each composed of coordinated subpopulations of neuronal, glial and endothelial cells, and found that two of these communities are altered in AD. Finally, we used mediation analyses to prioritize cellular changes that might contribute to cognitive decline. Thus, our deconstruction of the aging neocortex provides a roadmap for evaluating the cellular microenvironments underlying AD and dementia.

neuroscience↗

bioRxiv2019

Telomere Dysfunction Drives Chronic Lung Allograft Dysfunction Pathology

RationaleTelomere dysfunction is associated with multiple fibrotic lung processes, including chronic lung allograft dysfunction (CLAD) which is a major limitation to long-term survival following lung transplantation. Although shorter donor telomere lengths are associated with an increased risk of CLAD, it is unknown whether short telomeres are a cause or consequence of CLAD pathology.\n\nObjectiveOur objective was to test whether telomere dysfunction contributes to pathologic changes seen in CLAD.\n\nMethods and ResultsHistopathologic and molecular analysis of human CLAD lungs demonstrated shortened telomeres in lung epithelial cells quantified by teloFISH, increased numbers of surfactant protein C immunoreactive type II alveolar epithelial cells (AECs), and increased expression of senescence markers (beta-galactosidase, p16, p53 and p21) in lung epithelial cells. Telomere repeat binding factor 1 flox/flox (TRF1F/F) mice were crossed with tamoxifen inducible SCGB1a1-cre mice to generate SCGB1a1-creTRF1 F/F mice. Following 9 months of tamoxifen-induced deletion of TRF1 in club cells, mice developed mixed obstructive and restrictive lung physiology, small airway obliteration on micro-computed tomography, a 4-fold decrease in telomere length in airway epithelial cells, collagen deposition around bronchioles and adjacent lung parenchyma, increased type II AEC numbers, expression of senescence-associated beta-galactosidase in epithelial cells and decreased SCGB1a1 expression in airway epithelial cells.\n\nConclusionsThese findings demonstrate that telomere dysfunction isolated to club cells leads to airway-centric lung remodeling and fibrosis similar to that observed in patients with CLAD and suggest that lung epithelial cell telomere dysfunction may be a molecular driver of CLAD.

cell biology↗

bioRxiv2019

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

IntroductionTumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.\n\nObjectiveHere we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase 3 clinical trial.\n\nMethodsIn the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne(R) CDx assay.\n\nResultsTMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearmans r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearmans r = 0.90).\n\nConclusionsParameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.\n\nKey PointsO_LITumor mutational burden (TMB) is a clinically relevant biomarker for efficacy of immunotherapy in patients with cancer\nC_LIO_LIVariations in TMB assessment parameters can shift the final TMB value. Harmonization and standardization are important to the successful clinical implementation of TMB testing\nC_LIO_LITMB values assessed by different methods are highly correlated. Harmonization of TMB testing in patients with cancer is therefore achievable\nC_LI

bioinformatics↗

bioRxiv2019

Tau pathology in early Alzheimer’s disease disrupts selective neurophysiological networks dynamics

The role of aggregation of misfolded Tau protein in the pathogenesis of Alzheimers disease is the subject of rapid biomarker development and new therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography (E/MEG) in combination with [18F]AV1451 PET scanning to quantify Tau-dependent network disruption. Using a graph theoretical approach to MEG connectivity, we quantified nodal measures of functional segregation, centrality and efficiency of information transfer. We correlated these metrics against the nodes uptake of [18F]AV1451. There were both regional- and frequency-specific effects of Tau levels on the efficiency of information transfer and network segregation in early AD. Tau correlated with temporal regional participation coefficient (in delta, theta, beta bands); and temporal lobar eigenvector centrality (in theta, alpha, beta bands), but greater eccentricity at higher frequencies (gamma). The results support the translational development of neurophysiological "signatures" as biomarkers of Alzheimers disease, with potential to facilitate experimental medicines studies.

neuroscience↗

bioRxiv2018

Pathogen Detection and Microbiome Analysis of Infected Wheat Using a Portable DNA Sequencer

Fungal diseases of plants are responsible for major losses in agriculture, highlighting the need for rapid and accurate identification of plant pathogens. Disease outcomes are often defined not only by the main pathogen but are influenced by diverse microbial communities known as the microbiome at sites of infection. Here we present the first use of whole genome sequencing from a portable DNA sequencing device as a method for detection of fungal pathogens from wheat (Triticum aestivum). The data revealed that our method is robust and applicable to the diagnosis of fungal diseases including wheat stripe rust (caused by Puccinia striiformis f. sp. tritici), septoria tritici blotch (caused by Zymoseptoria tritici) and yellow leaf spot (caused by Pyrenophora tritici repentis). We also identified a bacterial genus Pseudomonas co-present with Puccinia and Zymoseptoria infections but not Pyrenophora infections. One limitation of the method is the over-representation of redundant wheat genome sequences in the sample. This could be addressed by amplicon-based sequencing approaches in future studies. Our work outlines a new approach for the detection of a broad range of plant pathogens and associated microbes using a portable sequencer, providing the basis for future development of a system for on-site disease monitoring.

plant biology↗

bioRxiv2017

Metagenomics for chronic meningitis: clarifying interpretation and diagnosis

ImportanceIdentifying infectious causes of subacute and chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed.\n\nObjectiveTo present a case series of patients with diagnostically challenging subacute and chronic meningitis in whom metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF), supported by a statistical framework generated from mNGS sequencing of non-infectious patients and environmental controls, identified a pathogen.\n\nDesignCase series. Using mNGS data from the CSF of 94 non-infectious neuroinflammatory cases and 24 water and reagent controls, we developed and implemented a weighted scoring metric based on z-scores at the species and genus level for both nucleotide and protein databases to prioritize and rank mNGS results. We performed mNGS on total RNA extracted from CSF of patients with subacute or chronic meningitis and highlight seven cases representing a diverse array of pathogens.\n\nSettingA multi-center study of mNGS pathogen discovery in patients with suspected neuroinflammatory conditions.\n\nParticipantsPatients with diagnostically challenging subacute or chronic meningitis enrolled in a research study of mNGS performed on CSF.\n\nInterventionmNGS was performed on total RNA extracted from CSF (0.25-0.5 mL). A weighted z-score was used to filter out environmental contaminants and facilitate efficient data triage and analysis.\n\nMain Outcomes1) Pathogens identified by mNGS and 2) ability of a statistical model to prioritize, rank, and simplify mNGS results.\n\nResultsmNGS identified parasitic worms, fungi and viruses in seven subjects: Taenia solium (n=2), Cryptococcus neoformans, human immunodeficiency virus-1, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis. Evaluating mNGS data with a weighted z-score based scoring algorithm effectively separated bona fide pathogen sequences from spurious environmental sequences.\n\nConclusions and RelevancemNGS of CSF identified a diversity of microbial pathogens in patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for one year, the first case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of Candida dubliniensis meningitis. Filtering metagenomic data with a scoring algorithm greatly clarified data interpretation and highlights the difficulties attributing biological significance to organisms that may be present in control samples used for metagenomic sequencing studies.\n\nKey PointsQuestion: How can metagenomic next-generation sequencing of cerebrospinal fluid be leveraged to aid in the diagnosis of patients with subacute or chronic meningitis?\n\nFindings: Metagenomic next-generation sequencing identified parasitic worms, fungi and viruses in a case series of seven subjects. A database of water-only and healthy patient controls enabled application of a z-score based scoring algorithm to effectively separate bona fide pathogen sequences from spurious environmental sequences.\n\nMeaning: Our scoring algorithm greatly simplified data interpretation in a series of patients with a wide range of challenging infectious causes of subacute or chronic meningitis identified by metagenomic next-generation sequencing.

microbiology↗

bioRxiv2017

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗