Olga G. Troyanskaya's research while affiliated with Princeton University and other places
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Publications (422)
BACKGROUND
Diffuse midline glioma (DMG), including Diffuse intrinsic pontine glioma (DIPG), is an aggressive brain tumor in children with limited treatment options. Recent developments of phase 1 clinical trials have shown early promise for chimeric antigen receptor (CAR) T cells in patients with DMG/DIPG. However, several barriers such as the abse...
Motivation: In recent years deep learning has become one of the central approaches in a number of applications, including many tasks in genomics. However, as models grow in depth and complexity, they either require more data or a strategic initialization technique to improve performance.
Results: In this project, we introduce cGen, a novel unsuperv...
Deciphering the regulatory code of gene expression and interpreting the transcriptional effects of genome variation are critical challenges in human genetics. Modern experimental technologies have resulted in an abundance of data, enabling the development of sequence-based deep learning models that link patterns embedded in DNA to the biochemical a...
Neurons from layer II of the entorhinal cortex (ECII) are the first to accumulate tau protein aggregates and degenerate during prodromal Alzheimer’s disease. Gaining insight into the molecular mechanisms underlying this vulnerability will help reveal genes and pathways at play during incipient stages of the disease. Here, we use a data-driven funct...
Protein–protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denatu...
Finely-tuned enzymatic pathways control cellular processes, and their dysregulation can lead to disease. Creating predictive and interpretable models for these pathways is challenging because of the complexity of the pathways and of the cellular and genomic contexts. Here we introduce Elektrum, a deep learning framework which addresses these challe...
Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA, a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells w...
To facilitate single cell multi-omics analysis and improve reproducibility, we present SPEEDI (Single-cell Pipeline for End to End Data Integration), a fully automated end-to-end framework for batch inference, data integration, and cell type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices...
Background
Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor. Recent immunotherapy studies, including CAR T cells, have shown limited success in GBM due to multiple barriers, such as on-target off-tumor toxicity, the blood-brain barrier, and the immunosuppressive tumor microenvironment (TME). To overcome these challenge...
Disclosure: F.M. Ruf-Zamojski: None. W. Cheng: None. Z. Zhang: None. M. Zamojski: None. G.R. Smith: None. X. Chen: None. N. Mendelev: None. G. Strupinsky: None. C.A. Alonso: None. L. Ongaro Gambino: None. X. Zhou: None. E. Brule: None. M.S. Amper: None. P. Hanna: None. V.D. Nair: None. C.L. Andoniadou: None. J.L. Turgeon: None. O. Troyanskaya: None...
Endurance exercise is an important health modifier. We studied cell-type specific adaptations of human skeletal muscle to acute endurance exercise using single-nucleus (sn) multiome sequencing in human vastus lateralis samples collected before and 3.5 hours after 40 min exercise at 70% VO2max in four subjects, as well as in matched time of day samp...
Human biology is rooted in highly specialized cell types programmed by a common genome, 98% of which is outside of genes. Genetic variation in the enormous noncoding space is linked to the majority of disease risk. To address the problem of linking these variants to expression changes in primary human cells, we introduce ExPectoSC, an atlas of modu...
Resolving chromatin-remodeling-linked gene expression changes at cell-type resolution is important for understanding disease states. Here we describe MAGICAL (Multiome Accessibility Gene Integration Calling and Looping), a hierarchical Bayesian approach that leverages paired single-cell RNA sequencing and single-cell transposase-accessible chromati...
Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA , a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells...
Finely-tuned enzymatic pathways control cellular processes, and their dysregulation can lead to disease. Creating predictive and interpretable models for these pathways is challenging because of the complexity of the pathways and of the cellular and genomic contexts. Here we introduce Elektrum, a deep learning framework which addresses these challe...
DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adult...
Periodontal disease is more common in individuals with rheumatoid arthritis (RA) who have detectable anti-citrullinated protein antibodies (ACPAs), implicating oral mucosal inflammation in RA pathogenesis. Here, we performed paired analysis of human and bacterial transcriptomics in longitudinal blood samples from RA patients. We found that patients...
Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well-characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework...
Resolving chromatin remodeling-linked gene expression changes at cell type resolution is important for understanding disease states. We describe MAGICAL, a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regula...
The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We va...
Astrocytes have been shown to play a central role in Alzheimer's Disease (AD). However, the genes and biological pathways underlying disease manifestation are unknown, and it is unclear whether regional molecular differences among astrocytes contribute to regional specificity of disease. Here, we began to address these challenges with integrated ex...
Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N...
Male sex is a major risk factor for SARS-CoV-2 infection severity. To understand the basis for this sex difference, we studied SARS-CoV-2 infection in a young adult cohort of United States Marine recruits. Among 2,641 male and 244 female unvaccinated and seronegative recruits studied longitudinally, SARS-CoV-2 infections occurred in 1,033 males and...
Background:
Marine recruits training at Parris Island experienced an unexpectedly high rate of SARS-CoV-2 infection, despite preventive measures including a supervised, 2-week, pre-entry quarantine. We characterize SARS-CoV-2 transmission in this cohort.
Methods:
Between May and November 2020, we monitored 2469 unvaccinated, mostly male, Marine...
Background:
Image-based machine learning tools hold great promise for clinical applications in pathology research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often lack the programming experience required for the setup and use of these tools which often rely on the use of command line i...
Nucleocapsid protein (N-protein) is required for multiple steps in betacoronaviruses replication. SARS-CoV-2-N-protein condenses with specific viral RNAs at particular temperatures making it a powerful model for deciphering RNA sequence specificity in condensates. We identify two separate and distinct double-stranded, RNA motifs (dsRNA stickers) th...
Epigenomic profiling has enabled large-scale identification of regulatory elements, yet we still lack a systematic mapping from any sequence or variant to regulatory activities. We address this challenge with Sei, a framework for integrating human genetics data with sequence information to discover the regulatory basis of traits and diseases. Sei l...
Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects....
Neurons from layer II of the entorhinal cortex (ECII) are the first to accumulate tau protein aggregates and degenerate
during prodromal Alzheimer’s disease. Here, we use a data-driven functional genomics approach to model ECII neurons in
silico and identify the proto-oncogene DEK as a potential driver of tau pathology. By modulating DEK levels in...
There is a need for better classification and understanding of tumor-infiltrating lymphocytes (TILs). Here, we applied advanced functional genomics to interrogate 9,000 human tumors and multiple single-cell sequencing sets using benchmarked T cell states, comprehensive T cell differentiation trajectories, human and mouse vaccine responses, and othe...
Background Molecular characterization of nephropathies may facilitate pathophysiologic insight, development of targeted therapeutics, and transcriptome-based disease classification. Although membranous nephropathy (MN) is a common cause of adult-onset nephrotic syndrome, the molecular pathways of kidney damage in MN require further definition.
Meth...
Young adults infected with SARS-CoV-2 are frequently asymptomatic or develop only mild disease. Because capturing representative mild and asymptomatic cases require active surveillance, they are less characterized than moderate or severe cases of COVID-19. However, a better understanding of SARS-CoV-2 asymptomatic infections might shed light into t...
Despite their importance in tissue homeostasis and renewal, human pituitary stem cells (PSCs) are incompletely characterized. We describe a human single nucleus RNA-seq and ATAC-seq resource from pediatric, adult, and aged postmortem pituitaries (snpituitaryatlas.princeton.edu) and characterize cell-type-specific gene expression and chromatin acces...
The scaling of single-cell data exploratory analysis with the rapidly growing diversity and quantity of single-cell omics datasets demands more interpretable and robust data representation that is generalizable across datasets. Here, we have developed a ‘linearly interpretable’ framework that combines the interpretability and transferability of lin...
Amyloid-β peptide (Aβ) accumulation in the brain is a hallmark of Alzheimer’s Disease. An important mechanism of Aβ clearance in the brain is uptake and degradation by microglia. Presenilin 1 (PS1) is the catalytic subunit of γ-secretase, an enzyme complex responsible for the maturation of multiple substrates, such as Aβ. Although PS1 has been exte...
The mRNA-1273 vaccine is effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and was granted emergency use authorization by the Food and Drug Administration . Clinical studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Ha...
Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which...
Interpreting the effects of genetic variants is key to understanding individual susceptibility to disease and designing personalized therapeutic approaches. Modern experimental technologies are enabling the generation of massive compendia of human genome sequence data and associated molecular and phenotypic traits, together with genome-scale expres...
Sequence is at the basis of how the genome shapes chromatin organization, regulates gene expression, and impacts traits and diseases. Epigenomic profiling efforts have enabled large-scale identification of regulatory elements, yet we still lack a sequence-based map to systematically identify regulatory activities from any sequence, which is necessa...
Commonly prescribed antidepressants, such as selective serotonin reuptake inhibitors (SSRIs) take weeks to achieve therapeutic benefits 1, 2 . The underlying mechanisms of why antidepressants take weeks or months to reverse depressed mood are not understood. Using a single cell sequencing approach, we analyzed gene expression changes in mice subjec...
Experimental approaches to study tissue specificity enable insight into the nature and organization of the cell types and tissues that constitute complex multicellular organisms. Machine learning provides a powerful tool to investigate and interpret tissue-specific experimental data. In this Review, we first provide a brief introduction to key sing...
Motivation
CRISPR/Cas9 is a revolutionary gene-editing technology that has been widely utilized in biology, biotechnology and medicine. CRISPR/Cas9 editing outcomes depend on local DNA sequences at the target site and are thus predictable. However, existing prediction methods are dependent on both feature and model engineering, which restricts thei...
Despite their importance in tissue homeostasis and renewal, human pituitary stem cells (PSCs) are incompletely characterized. We describe a human single nucleus (sn) RNAseq and ATACseq resource from pediatric, adult, and aged pituitaries (snpituitaryatlas.princeton.edu) and characterize cell type-specific gene expression and chromatin accessibility...
Betacoronavirus SARS-CoV-2 infections caused the global Covid-19 pandemic. The nucleocapsid protein (N-protein) is required for multiple steps in the betacoronavirus replication cycle. SARS-CoV-2-N-protein is known to undergo liquid-liquid phase separation (LLPS) with specific RNAs at particular temperatures to form condensates. We show that N-prot...
To provide a multi-omics resource and investigate transcriptional regulatory mechanisms, we profile the transcriptome, chromatin accessibility, and methylation status of over 70,000 single nuclei (sn) from adult mouse pituitaries. Paired snRNAseq and snATACseq datasets from individual animals highlight a continuum between developmental epigenetical...
The pituitary gland regulates key physiological functions, including growth, sexual maturation, reproduction, and lactation. Here, we present a paired single-nuclei (sn) transcriptome and chromatin accessibility characterization of six post-mortem human pituitaries. These samples were from juvenile, adult, and elderly male and female subjects. Well...
Convolutional neural networks (CNNs) have become a standard for analysis of biological sequences. Tuning of network architectures is essential for a CNN’s performance, yet it requires substantial knowledge of machine learning and commitment of time and effort. This process thus imposes a major barrier to broad and effective application of modern de...
Treatment of solid cancers with chimeric antigen receptor (CAR) T cells is plagued by the lack of ideal target antigens that are both absolutely tumor specific and homogeneously expressed. We show that multi-antigen prime-and-kill recognition circuits provide flexibility and precision to overcome these challenges in the context of glioblastoma. A s...
To enable large-scale analyses of regulatory logic in model species, we developed DeepArk, a set of deep learning models of the cis-regulatory codes of four widely-studied species: Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, and Mus musculus DeepArk accurately predicts the presence of thousands of different context-specific regula...
Systematic study of tissue-specific function of enhancers and their disease associations is a major challenge. We present an integrative machine-learning framework, FENRIR, that integrates thousands of disparate epigenetic and functional genomics datasets to infer tissue-specific functional relationships between enhancers for 140 diverse human tiss...
The Kidney Precision Medicine Project will advance understanding of chronic kidney disease attributed to diabetes or hypertension and acute kidney injury through a protocol kidney biopsy used for deep phenotyping with state-of-the-art methodology. To guide scientific inquiry toward clinically meaningful benefit, patients are equal partners for prio...
Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from partic...
Convolutional neural networks (CNN) have become a standard approach for modeling genomic sequences. CNNs can be effectively built by Neural Architecture Search (NAS) by trading computing power for accurate neural architectures. Yet, the consumption of immense computing power is a major practical, financial, and environmental issue for deep learning...
[This corrects the article DOI: 10.1371/journal.pone.0237773.].
Despite the strong genetic basis of psychiatric disorders, the underlying molecular mechanisms are largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional regulation, from splicing to translation to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. However, quantifyi...
The mRNA-1273 vaccine was recently determined to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from interim Phase 3 results. Human studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model th...
The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, doe...
Understanding the changes in diverse molecular pathways underlying the development of breast tumors is critical for improving diagnosis, treatment, and drug development. Here, we used RNA-profiling of canine mammary tumors (CMTs) coupled with a robust analysis framework to model molecular changes in human breast cancer. Our study leveraged a key ad...
Background
The enrichment of late‐onset Alzheimer’s disease (LOAD) GWAS variants in noncoding regions of the genome reveals new potential for modeling disease risk. Yet, identifying noncoding causal variants and the cell types in which they are functional remains challenging. Translating noncoding variants into novel mouse models can elucidate phen...
Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using mul...
Background
The efficacy of public health measures to control the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been well studied in young adults.
Methods
We investigated SARS-CoV-2 infections among U.S. Marine Corps recruits who underwent a 2-week quarantine at home followed by a second supervised 2-week quar...
We report that the SARS-CoV-2 nucleocapsid protein (N-protein) undergoes liquid-liquid phase separation (LLPS) with viral RNA. N-protein condenses with specific RNA genomic elements under physiological buffer conditions and condensation is enhanced at human body temperatures (33°C and 37°C) and reduced at room temperature (22°C). RNA sequence and s...
COVID-19 morbidity and mortality are increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidne...
Precise discrimination of tumor from normal tissues remains a major roadblock for therapeutic efficacy of chimeric antigen receptor (CAR) T cells. Here, we perform a comprehensive in silico screen to identify multi-antigen signatures that improve tumor discrimination by CAR T cells engineered to integrate multiple antigen inputs via Boolean logic,...
Microglial cells play a key role in brain homeostasis from development to adulthood. Here we show the involvement of a site-specific phosphorylation of Presenilin 1 (PS1) in microglial development. Profiles of microglia-specific transcripts in different temporal stages of development, combined with multiple systematic transcriptomic analysis and qu...
Convolutional neural networks (CNNs) have become a standard for analysis of biological sequences. Tuning of network architectures is essential for CNN's performance, yet it requires substantial knowledge of machine learning and commitment of time and effort. This process thus imposes a major barrier to broad and effective application of modern deep...
Malignancy in cancer is a consequence of the progressive accumulation of mutations in a tumor, with profound implications for drug selection and treatment. However, in human studies, inter-patient variability obscures molecular signatures of tumor progression because patients usually present with a single mammary tumor. In contrast, dogs frequently...
A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction o...
A bstract
The Kidney Precision Medicine Project (KPMP) plans to construct a spatially specified tissue atlas of the human kidney at a cellular resolution with near comprehensive molecular details. The atlas will have maps of healthy, acute kidney injury and chronic kidney disease tissues. To construct such maps, we integrate different data sets tha...
Background
Rheumatoid arthritis, like many inflammatory diseases, is characterized by episodes of quiescence and exacerbation (flares). The molecular events leading to flares are unknown.
Methods
We established a clinical and technical protocol for repeated home collection of blood in patients with rheumatoid arthritis to allow for longitudinal RN...
A mechanistic understanding of the SARS-CoV-2 viral replication cycle is essential to develop new therapies for the COVID-19 global health crisis. In this study, we show that the SARS-CoV-2 nucleocapsid protein (N-protein) undergoes liquid-liquid phase separation (LLPS) with the viral genome, and propose a model of viral packaging through LLPS. N-p...
The pituitary regulates growth, reproduction and other endocrine systems. To investigate transcriptional network epigenetic mechanisms, we generated paired single nucleus (sn) transcriptome and chromatin accessibility profiles in single mouse pituitaries and genome-wide sn methylation datasets. Our analysis provided insight into cell type epigeneti...
A major obstacle to treating Alzheimer’s disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neuron-type-specific molecular profiles across the lifetime of the healthy mouse, which we generated us...
Despite the strong genetic basis of psychiatric disorders, the molecular origins of these diseases are still largely unmapped. RNA-binding proteins (RBPs) are responsible for most post- transcriptional regulation, from splicing to translational to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. Here,...
COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in...
In mood disorders, psychomotor and sensory abnormalities are prevalent, disabling, and intertwined with emotional and cognitive symptoms. Corticostriatal neurons in motor and somatosensory cortex are implicated in these symptoms, yet mechanisms of their vulnerability are unknown. Here, we demonstrate that S100a10 corticostriatal neurons exhibit dis...
Congenital abnormalities of the kidney and urinary tract are amongst the most common birth defects affecting 3% of newborns. The human kidney develops over a 30-week period in which a nephron progenitor pool gives rise to around a million nephrons. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by wh...
To enable large-scale analyses of regulatory logic in model species, we developed DeepArk (https://DeepArk.princeton.edu), a set of deep learning models of the cis -regulatory codes of four widely-studied species: Caenorhabditis elegans , Danio rerio , Drosophila melanogaster , and Mus musculus . DeepArk accurately predicts the presence of thousand...
Scaling single-cell data exploratory analysis with the rapidly growing diversity and quantity of single-cell omics datasets demands more interpretable and robust data representation that is generalizable across datasets. To address this challenge, here we developed a novel 'quasilinear' framework that combines the interpretability and transferabili...
With biomedical research transitioning into data-rich science, machine learning provides a powerful toolkit for extracting knowledge from large-scale biological datasets. The increasing availability of comprehensive kidney omics compendia (transcriptomics, proteomics, metabolomics, genome sequencing), as well as other data modalities such as electr...
To define cellular mechanisms underlying kidney function and failure, the Kidney Precision Medicine Project (KPMP) analyzes biopsy tissue in a multi-center research network to build cell-level process maps of kidney. This study aimed to establish a single cell RNA sequencing strategy to use cell level transcriptional profiles from kidney biopsies i...
Filtered through the analytical power of artificial intelligence, the wealth of available biomedical data promises to revolutionize cancer research, diagnosis and care. In this Viewpoint, six experts discuss some of the challenges, exciting developments and future questions arising at the interface of machine learning and oncology.
Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate 3-dimensional (3D) molecular atlases of healthy and diseased kidney biopsies using mul...
To mark the 15th anniversary of Nature Methods, we asked scientists from across diverse fields of basic biology research for their views on the most exciting and essential methodological challenges that their communities are poised to tackle in the near future.
Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experimen...
Citations
... Genes driving associations with CSF tau levels in deep layers of EC have generally more significant enrichment, primarily in metabolic pathways (e.g., cellular respiration, electron transport chain), while those driving associations with tau levels in layer II neurons are more enriched in proteostasis pathways (e.g., protein destabilization) ( Figure 5C, D). Metabolic [35] and proteostatic [36,37] contributions to vulnerability of EC are among the very pathways previously suggested to underlie EC vulnerability, and several identified influential genes, such as VPS26A, have connections with EC vulnerability in both cell types. The fact that seismic does not find any association between microglia and CSF tau further suggests that microglia might not be the main drivers of tau pathology, but rather the drivers of the clinical manifestations of AD. ...
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... That is done to expand the dataset, and prevent model memorization, forcing the model to learn features of the sequence. We log-transformed gene expression values w/ the pseudocount of 0.1, similar to [16,19]. LinearRegression implementation from scikit package was used for each of the tissues separately, and spearman score was used from the scipy.stats ...
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... Ontology GO [3] KEGG-Pathway [4] Enrichment STRING [5] 1 Department of Physics, Chuo University, Bunkyo, Tokyo 112-8551, Japan a) kugenuma5555@gmail.com 1.2 [6] MRSA [7] [6] * 1 [8] MRSA MSSA [9] 2. ...
Reference: TDbasedUFEを用いた黄色ブドウ球菌敗血症におけるメチシリン耐性の解析
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... ; https://doi.org/10.1101/2023.09.26.558914 doi: bioRxiv preprint the +/-100kb region around the transcription start site in a peak-agnostic manner, and uses a linear model to find regulatory circuits supported by the coincidence of the expression of the target gene, the expression of the TF and the local chromatin accessibility of the TF's binding site. 39 Samples for each subject (both pre and post timepoints) were pooled, and CREMA was applied to extract regulatory circuits specific to each subject and cell type. Circuits were selected if they were replicated in at least two of the four subjects in the exercise group and satisfied at least one of the following two criteria: 1) the target gene and the TF both showed significant differential expression between pre-and post-exercise; 2) the target gene and the cis-regulatory site both showed significant differential expression and differential accessibility respectively between pre-and post-exercise. ...
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... In this section, we study the performance of the eight CpGs on asymptomatic cases. Using a recent public dataset GSE219037 [33], we obtained the following in Table 5. Table 5. Performance of individual classifiers and combined max-competing classifiers using blood sample dataset GSE219037 to classify asymptomatic Marines and healthy controls into their respective groups. ...
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... RA disease flares are associated with breaches of oral mucosa and the transient presence of oral bacteria in the blood 199 . Here, an epidemiological link exists between ACPA + RA and periodontitis 200 , a microbial disease characterized by loss of the periodontal ligament and alveolar bone, culminating in tooth loss. ...
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... These functional networks are constructed using a Bayesian probabilistic framework based on biological information from thousands of integrated '-omics' datasets (for example, gene coexpression, transcription factor binding and protein-protein interactions) [30][31][32] . The Bayesian machine learning model automatically upweights datasets that are informative for the tissue of interest, thereby achieving tissue specificity in the integration [33][34][35][36] . By identifying closely connected proteins that share functional associations, albeit not necessarily via direct PPIs, these functional networks provide maps of predicted protein behavior in diverse cellular pathways. ...
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... 15,19 These studies and others have been critical to build foundational understanding of the pathogenesis underlying the varying clinical manifestations of this novel disease. 17,19,20 A limitation of much of the prior work is a focus on sampling at the time of the illness of interest, such as sampling patients while already in the ICU and comparing them with outpatients or those requiring only low-level supplemental oxygen. This is highly effective when the goal is to compare disease pathogenesis underlying each of these active states. ...
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... This strategy has been successfully applied by DC3 (ref. 88) and MAGICAL 166 . Despite some highthroughput alternatives 167,168 , chromosome conformation capture techniques pose new challenges owing to their sparse nature 169 and the facts that they still require integration with other modalities and their protocol can be hard to reproduce 170,171 . ...
... Increased integrin αvβ6 in human CKD kidneys is positively associated with inflammatory mediators and immune infiltration To explore the relationship between inflammation and integrin αvβ6 in kidney fibrosis, we initiated our study with a bioinformatic analysis of public RNA profiles from CKD patients. According to the inclusion criteria detailed in the methods, we selected the dataset GSE180394 [11], which contains kidney biopsies from healthy individuals and CKD patients with different etiologies, including diabetic nephropathy (DN), lupus nephritis (LN), hypertensive nephropathy (HN), IgA nephropathy (IgAN), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and minimal change disease (MCD). Our finding from this dataset showed that ITGB6, the gene encoding integrin αvβ6, was elevated in the kidneys of CKD patients compared to healthy controls (Fig. 1A). ...
