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1.
Nat Commun ; 12(1): 4188, 2021 07 07.
Artigo em Inglês | MEDLINE | ID: mdl-34234121

RESUMO

Klebsiella pneumoniae is a leading cause of antimicrobial-resistant (AMR) healthcare-associated infections, neonatal sepsis and community-acquired liver abscess, and is associated with chronic intestinal diseases. Its diversity and complex population structure pose challenges for analysis and interpretation of K. pneumoniae genome data. Here we introduce Kleborate, a tool for analysing genomes of K. pneumoniae and its associated species complex, which consolidates interrogation of key features of proven clinical importance. Kleborate provides a framework to support genomic surveillance and epidemiology in research, clinical and public health settings. To demonstrate its utility we apply Kleborate to analyse publicly available Klebsiella genomes, including clinical isolates from a pan-European study of carbapenemase-producing Klebsiella, highlighting global trends in AMR and virulence as examples of what could be achieved by applying this genomic framework within more systematic genomic surveillance efforts. We also demonstrate the application of Kleborate to detect and type K. pneumoniae from gut metagenomes.


Assuntos
Proteínas de Bactérias/genética , Infecção Hospitalar/microbiologia , Infecções por Klebsiella/microbiologia , Klebsiella pneumoniae/genética , Tipagem Molecular/métodos , Antibacterianos/farmacologia , Antibacterianos/uso terapêutico , Infecção Hospitalar/diagnóstico , Infecção Hospitalar/tratamento farmacológico , Infecção Hospitalar/epidemiologia , Conjuntos de Dados como Assunto , Farmacorresistência Bacteriana Múltipla/genética , Monitoramento Epidemiológico , Microbioma Gastrointestinal/genética , Genoma Bacteriano , Humanos , Lactente , Recém-Nascido , Infecções por Klebsiella/diagnóstico , Infecções por Klebsiella/tratamento farmacológico , Infecções por Klebsiella/epidemiologia , Klebsiella pneumoniae/isolamento & purificação , Klebsiella pneumoniae/patogenicidade , Metagenoma/genética , Epidemiologia Molecular/métodos , Mutação , Filogenia , Software , Virulência/genética , Fatores de Virulência/genética , Sequenciamento Completo do Genoma , beta-Lactamases/genética
2.
Nat Commun ; 12(1): 4197, 2021 07 07.
Artigo em Inglês | MEDLINE | ID: mdl-34234139

RESUMO

Single cell RNA sequencing (scRNA-seq) is a powerful tool in detailing the cellular landscape within complex tissues. Large-scale single cell transcriptomics provide both opportunities and challenges for identifying rare cells playing crucial roles in development and disease. Here, we develop GapClust, a light-weight algorithm to detect rare cell types from ultra-large scRNA-seq datasets with state-of-the-art speed and memory efficiency. Benchmarking on diverse experimental datasets demonstrates the superior performance of GapClust compared to other recently proposed methods. When applying our algorithm to an intestine and 68 k PBMC datasets, GapClust identifies the tuft cells and a previously unrecognised subtype of monocyte, respectively.


Assuntos
Algoritmos , RNA-Seq/métodos , Análise de Célula Única/métodos , Conjuntos de Dados como Assunto , Células HEK293 , Humanos , Mucosa Intestinal/citologia , Células Jurkat , Software
3.
Nat Commun ; 12(1): 4192, 2021 07 07.
Artigo em Inglês | MEDLINE | ID: mdl-34234142

RESUMO

Most existing tools for constructing genetic prediction models begin with the assumption that all genetic variants contribute equally towards the phenotype. However, this represents a suboptimal model for how heritability is distributed across the genome. Therefore, we develop prediction tools that allow the user to specify the heritability model. We compare individual-level data prediction tools using 14 UK Biobank phenotypes; our new tool LDAK-Bolt-Predict outperforms the existing tools Lasso, BLUP, Bolt-LMM and BayesR for all 14 phenotypes. We compare summary statistic prediction tools using 225 UK Biobank phenotypes; our new tool LDAK-BayesR-SS outperforms the existing tools lassosum, sBLUP, LDpred and SBayesR for 223 of the 225 phenotypes. When we improve the heritability model, the proportion of phenotypic variance explained increases by on average 14%, which is equivalent to increasing the sample size by a quarter.


Assuntos
Previsões/métodos , Modelos Genéticos , Herança Multifatorial , Medicina de Precisão/métodos , Característica Quantitativa Herdável , Estudos de Casos e Controles , Conjuntos de Dados como Assunto , Estudo de Associação Genômica Ampla , Humanos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Tamanho da Amostra , Software
4.
J Synchrotron Radiat ; 28(Pt 4): 1237-1244, 2021 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-34212889

RESUMO

During the COVID-19 pandemic, synchrotron beamlines were forced to limit user access. Performing routine measurements became a challenge. At the Life Science X-ray Scattering (LiX) beamline, new instrumentation and mail-in protocols have been developed to remove the access barrier to solution scattering measurements. Our efforts took advantage of existing instrumentation and coincided with the larger effort at NSLS-II to support remote measurements. Given the limited staff-user interaction for mail-in measurements, additional software tools have been developed to ensure data quality, to automate the adjustments in data processing, as users would otherwise rely on the experience of the beamline staff, and produce a summary of the initial assessments of the data. This report describes the details of these developments.


Assuntos
Espalhamento a Baixo Ângulo , Soluções/efeitos da radiação , Síncrotrons/instrumentação , Difração de Raios X/instrumentação , Tampões (Química) , COVID-19 , Coleta de Dados , Conjuntos de Dados como Assunto , Processamento Eletrônico de Dados , Pandemias , Robótica , SARS-CoV-2 , Software , Manejo de Espécimes , Água
6.
Nat Commun ; 12(1): 4172, 2021 07 07.
Artigo em Inglês | MEDLINE | ID: mdl-34234141

RESUMO

Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA's comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes.


Assuntos
DNA Tumoral Circulante/genética , Análise Mutacional de DNA/métodos , Inibidores de Checkpoint Imunológico/farmacologia , Neoplasias/genética , Sequenciamento Completo do Exoma/métodos , Adulto , Anticorpos Monoclonais Humanizados/farmacologia , Anticorpos Monoclonais Humanizados/uso terapêutico , Biomarcadores Tumorais/sangue , Biomarcadores Tumorais/genética , Biópsia , DNA Tumoral Circulante/sangue , Simulação por Computador , Conjuntos de Dados como Assunto , Resistencia a Medicamentos Antineoplásicos/genética , Feminino , Humanos , Inibidores de Checkpoint Imunológico/uso terapêutico , Masculino , Pessoa de Meia-Idade , Mutação , Neoplasias/sangue , Neoplasias/tratamento farmacológico , Neoplasias/mortalidade , Polimorfismo de Nucleotídeo Único , Prognóstico , Receptor de Morte Celular Programada 1/antagonistas & inibidores , Intervalo Livre de Progressão , Sensibilidade e Especificidade
7.
Nat Commun ; 12(1): 4237, 2021 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-34244483

RESUMO

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.


Assuntos
Encéfalo/fisiologia , Conectoma , Redes Reguladoras de Genes , Rede Nervosa/fisiologia , Adulto , Encéfalo/diagnóstico por imagem , Conjuntos de Dados como Assunto , Imagem de Difusão por Ressonância Magnética , Feminino , Perfilação da Expressão Gênica , Humanos , Masculino , Modelos Genéticos , Gêmeos
8.
Nat Commun ; 12(1): 4234, 2021 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-34244491

RESUMO

We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We present a hardware efficient methodology to realize the DEXAT neurons using tightly coupled circuit-device interactions and experimentally demonstrate the DEXAT neuron block using oxide based non-filamentary resistive switching devices. Using experimentally extracted parameters we simulate a full RSNN that achieves a classification accuracy of 96.1% on SMNIST dataset and 91% on Google Speech Commands (GSC) dataset. We also demonstrate full end-to-end real-time inference for speech recognition using real fabricated resistive memory circuit based DEXAT neurons. Finally, we investigate the impact of nanodevice variability and endurance illustrating the robustness of DEXAT based RSNNs.


Assuntos
Modelos Neurológicos , Redes Neurais de Computação , Neurônios/fisiologia , Computadores , Conjuntos de Dados como Assunto , Humanos , Nanoestruturas , Interface para o Reconhecimento da Fala
9.
Nat Commun ; 12(1): 4221, 2021 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-34244504

RESUMO

Deep learning algorithms trained on instances that violate the assumption of being independent and identically distributed (i.i.d.) are known to experience destructive interference, a phenomenon characterized by a degradation in performance. Such a violation, however, is ubiquitous in clinical settings where data are streamed temporally from different clinical sites and from a multitude of physiological sensors. To mitigate this interference, we propose a continual learning strategy, entitled CLOPS, that employs a replay buffer. To guide the storage of instances into the buffer, we propose end-to-end trainable parameters, termed task-instance parameters, that quantify the difficulty with which data points are classified by a deep-learning system. We validate the interpretation of these parameters via clinical domain knowledge. To replay instances from the buffer, we exploit uncertainty-based acquisition functions. In three of the four continual learning scenarios, reflecting transitions across diseases, time, data modalities, and healthcare institutions, we show that CLOPS outperforms the state-of-the-art methods, GEM1 and MIR2. We also conduct extensive ablation studies to demonstrate the necessity of the various components of our proposed strategy. Our framework has the potential to pave the way for diagnostic systems that remain robust over time.


Assuntos
Arritmias Cardíacas/diagnóstico , Tomada de Decisão Clínica/métodos , Sistemas de Apoio a Decisões Clínicas , Aprendizado Profundo , Conjuntos de Dados como Assunto , Eletrocardiografia , Humanos , Modelos Cardiovasculares , Curva ROC , Estações do Ano , Fatores de Tempo
10.
Nat Commun ; 12(1): 4418, 2021 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-34285202

RESUMO

Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.


Assuntos
Predisposição Genética para Doença , Testes Genéticos/métodos , Modelos Genéticos , Herança Multifatorial/genética , Tomada de Decisão Clínica/métodos , Conjuntos de Dados como Assunto , Estudo de Associação Genômica Ampla , Humanos , Polimorfismo de Nucleotídeo Único , Fatores de Risco , Software , Sequenciamento Completo do Genoma
11.
Nat Commun ; 12(1): 4430, 2021 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-34285206

RESUMO

The standard measure of distance in social networks - average shortest path length - assumes a model of "simple" contagion, in which people only need exposure to influence from one peer to adopt the contagion. However, many social phenomena are "complex" contagions, for which people need exposure to multiple peers before they adopt. Here, we show that the classical measure of path length fails to define network connectedness and node centrality for complex contagions. Centrality measures and seeding strategies based on the classical definition of path length frequently misidentify the network features that are most effective for spreading complex contagions. To address these issues, we derive measures of complex path length and complex centrality, which significantly improve the capacity to identify the network structures and central individuals best suited for spreading complex contagions. We validate our theory using empirical data on the spread of a microfinance program in 43 rural Indian villages.


Assuntos
Previsões/métodos , Disseminação de Informação , Modelos Teóricos , Rede Social , Simulação por Computador , Conjuntos de Dados como Assunto , Feminino , Humanos , Índia , Masculino , Grupo Associado , População Rural
13.
Nat Commun ; 12(1): 3258, 2021 05 31.
Artigo em Inglês | MEDLINE | ID: mdl-34059679

RESUMO

Autophagy can selectively target protein aggregates, pathogens, and dysfunctional organelles for the lysosomal degradation. Aberrant regulation of autophagy promotes tumorigenesis, while it is far less clear whether and how tumor-specific alterations result in autophagic aberrance. To form a link between aberrant autophagy selectivity and human cancer, we establish a computational pipeline and prioritize 222 potential LIR (LC3-interacting region) motif-associated mutations (LAMs) in 148 proteins. We validate LAMs in multiple proteins including ATG4B, STBD1, EHMT2 and BRAF that impair their interactions with LC3 and autophagy activities. Using a combination of transcriptomic, metabolomic and additional experimental assays, we show that STBD1, a poorly-characterized protein, inhibits tumor growth via modulating glycogen autophagy, while a patient-derived W203C mutation on LIR abolishes its cancer inhibitory function. This work suggests that altered autophagy selectivity is a frequently-used mechanism by cancer cells to survive during various stresses, and provides a framework to discover additional autophagy-related pathways that influence carcinogenesis.


Assuntos
Carcinogênese/genética , Macroautofagia/genética , Proteínas de Membrana/genética , Modelos Genéticos , Proteínas Musculares/genética , Neoplasias/genética , Algoritmos , Animais , Carcinogênese/patologia , Linhagem Celular Tumoral , Simulação por Computador , Análise Mutacional de DNA , Conjuntos de Dados como Assunto , Técnicas de Silenciamento de Genes , Glicogênio/metabolismo , Humanos , Estimativa de Kaplan-Meier , Proteínas de Membrana/metabolismo , Camundongos , Proteínas Associadas aos Microtúbulos/metabolismo , Proteínas Musculares/metabolismo , Mutação , Neoplasias/mortalidade , Neoplasias/patologia , Via de Pentose Fosfato/genética , Domínios e Motivos de Interação entre Proteínas/genética , Proteoma/genética , RNA-Seq , Análise Serial de Tecidos , Efeito Warburg em Oncologia , Ensaios Antitumorais Modelo de Xenoenxerto
15.
BMC Plant Biol ; 21(1): 280, 2021 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-34154536

RESUMO

Alternative splicing (AS) increases the diversity of transcripts and proteins through the selection of different splice sites and plays an important role in the growth, development and stress tolerance of plants. With the release of the reference genome of the tea plant (Camellia sinensis) and the development of transcriptome sequencing, researchers have reported the existence of AS in tea plants. However, there is a lack of a platform, centered on different RNA-seq datasets, that provides comprehensive information on AS.To facilitate access to information on AS and reveal the molecular function of AS in tea plants, we established the first comprehensive AS database for tea plants (TeaAS, http://www.teaas.cn/index.php ). In this study, 3.96 Tb reads from 66 different RNA-seq datasets were collected to identify AS events. TeaAS supports four methods of retrieval of AS information based on gene ID, gene name, annotation (non-redundant/Kyoto encyclopedia of genes and genomes/gene ontology annotation or chromosomal location) and RNA-seq data. It integrates data pertaining to genome annotation, type of AS event, transcript sequence, and isoforms expression levels from 66 RNA-seq datasets. The AS events resulting from different environmental conditions and that occurring in varied tissue types, and the expression levels of specific transcripts can be clearly identified through this online database. Moreover, it also provides two useful tools, Basic Local Alignment Search Tool and Generic Genome Browser, for sequence alignment and visualization of gene structure.The features of the TeaAS database make it a comprehensive AS bioinformatics platform for researchers, as well as a reference for studying AS events in woody crops. It could also be helpful for revealing the novel biological functions of AS in gene regulation in tea plants.


Assuntos
Processamento Alternativo , Camellia sinensis/genética , Bases de Dados Genéticas , Conjuntos de Dados como Assunto , RNA de Plantas , RNA-Seq
16.
Viruses ; 13(6)2021 05 28.
Artigo em Inglês | MEDLINE | ID: mdl-34071557

RESUMO

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19. To evaluate immune dysregulation in different diseases, we used four separate datasets, including RNA-sequencing data from human left ventricular cardiac muscle samples of patients with dilated or ischemic cardiomyopathy and healthy controls; RNA-sequencing data of whole blood samples from patients with single or recurrent event VTE and healthy controls; RNA-sequencing data of human peripheral blood mononuclear cells (PBMCs) from patients with and without obstructive CAD; and RNA-sequencing data of platelets from COVID-19 subjects and healthy controls. We found similar immune dysregulation profiles between patients with CVDs and COVID-19 patients. Interestingly, cardiomyopathy patients display the most similar immune landscape to COVID-19 patients. Additionally, COVID-19 patients experience greater upregulation of cytokine- and inflammasome-related genes than patients with CVDs. In all, patients with CVDs have a significant overlap of cytokine- and inflammasome-related gene expression profiles with that of COVID-19 patients, possibly explaining their greater vulnerability to severe COVID-19.


Assuntos
COVID-19/imunologia , COVID-19/fisiopatologia , Cardiomiopatias/imunologia , Doença da Artéria Coronariana/imunologia , Tromboembolia Venosa/imunologia , COVID-19/complicações , COVID-19/genética , Cardiomiopatias/complicações , Cardiomiopatias/genética , Doença da Artéria Coronariana/complicações , Doença da Artéria Coronariana/genética , Citocinas/genética , Conjuntos de Dados como Assunto , Humanos , Hospedeiro Imunocomprometido/genética , Inflamassomos/genética , Contagem de Linfócitos , Gravidade do Paciente , RNA-Seq , Tromboembolia Venosa/complicações
17.
Nucleic Acids Res ; 49(W1): W174-W184, 2021 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-34060634

RESUMO

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.


Assuntos
Algoritmos , Bases de Dados Factuais , Avaliação Pré-Clínica de Medicamentos , Quimioterapia Combinada , Internet , COVID-19/tratamento farmacológico , Visualização de Dados , Conjuntos de Dados como Assunto , Sinergismo Farmacológico , Doença pelo Vírus Ebola/tratamento farmacológico , Humanos , Aprendizado de Máquina , Malária/tratamento farmacológico , Neoplasias/tratamento farmacológico
18.
J Cancer Res Clin Oncol ; 147(8): 2309-2322, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34080067

RESUMO

PURPOSE: Our study was aimed to understand the importance of LIMD1-VHL-HIF1α pathway in development of bladder carcinoma (BlCa) in association with arsenic prevalence. METHODS: At first, the mRNA expression pattern of the genes of this pathway (LIMD1, VHL and HIF1α) was checked in GEO datasets and in our samples. Next, genetic and epigenetic profiling of LIMD1 and VHL was done in our sample pool, validated in T24 BlCa cell line. The results were next correlated with various clinico-pathological parameters. RESULTS: Differential under-expression of LIMD1 and VHL genes was found in muscle-invasive BlCa (MIBC) in comparison to non-muscle-invasive BlCa (NMIBC). However, HIF1α protein, but mRNA, was found to be overexpressed among the MIBC samples; depicting the probability of HIF1α protein stabilization. Analysis of genetic and epigenetic profiles of LIMD1 and VHL exposed a frequent promoter methylation of LIMD1 gene in MIBC samples. Further, in-depth look into the results unveiled that the high nuclear expression of HIF1α was significantly correlated with genetic alterations of LIMD1, alone or in combination with VHL. Moreover, treating the T24 cells with a de-methylating agent (5-aza-2'-deoxycytidine) re-expressed the methylated LIMD1 and VHL genes, which in turn, reduced the HIF1α protein level significantly. Additionally, patients with high arsenic content (> 112 ng/g, AsH) seemed to have recurrent promoter methylation in LIMD1, as well as co-methylation/alteration of LIMD1 and VHL gene. Lastly, high nuclear expression of HIF1α in association with co-alteration of VHL and LIMD1 showed the worst overall survival (OS) among the patients. CONCLUSION: To conclude, MIBC samples portrayed higher alterations in VHL and LIMD1, thereby, stabilizing HIF1α protein and lowering the OS of patients.


Assuntos
Carcinoma de Células de Transição/diagnóstico , Subunidade alfa do Fator 1 Induzível por Hipóxia/genética , Peptídeos e Proteínas de Sinalização Intracelular/genética , Proteínas com Domínio LIM/genética , Neoplasias da Bexiga Urinária/diagnóstico , Proteína Supressora de Tumor Von Hippel-Lindau/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Intoxicação por Arsênico/diagnóstico , Intoxicação por Arsênico/epidemiologia , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma de Células de Transição/epidemiologia , Carcinoma de Células de Transição/genética , Carcinoma de Células de Transição/patologia , Linhagem Celular Tumoral , Núcleo Celular/genética , Núcleo Celular/metabolismo , Núcleo Celular/patologia , Comorbidade , Metilação de DNA , Conjuntos de Dados como Assunto , Feminino , Regulação Neoplásica da Expressão Gênica , Inativação Gênica , Humanos , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Peptídeos e Proteínas de Sinalização Intracelular/metabolismo , Proteínas com Domínio LIM/metabolismo , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Prevalência , Prognóstico , Análise de Sobrevida , Neoplasias da Bexiga Urinária/epidemiologia , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/patologia , Proteína Supressora de Tumor Von Hippel-Lindau/metabolismo
19.
Nat Commun ; 12(1): 3394, 2021 06 07.
Artigo em Inglês | MEDLINE | ID: mdl-34099641

RESUMO

The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants' effect on gene expressions in native chromatin context via direct perturbation are low-throughput. Existing high-throughput computational predictors thus have lacked large gold standard sets of regulatory variants for training and validation. Here, we leverage a set of 14,807 putative causal eQTLs in humans obtained through statistical fine-mapping, and we use 6121 features to directly train a predictor of whether a variant modifies nearby gene expression. We call the resulting prediction the expression modifier score (EMS). We validate EMS by comparing its ability to prioritize functional variants with other major scores. We then use EMS as a prior for statistical fine-mapping of eQTLs to identify an additional 20,913 putatively causal eQTLs, and we incorporate EMS into co-localization analysis to identify 310 additional candidate genes across UK Biobank phenotypes.


Assuntos
Mapeamento Cromossômico/métodos , Biologia Computacional/métodos , Locos de Características Quantitativas , Aprendizado de Máquina Supervisionado , Adulto , Estudos de Coortes , Conjuntos de Dados como Assunto , Perfilação da Expressão Gênica , Humanos , Polimorfismo de Nucleotídeo Único
20.
Medicine (Baltimore) ; 100(24): e26271, 2021 Jun 18.
Artigo em Inglês | MEDLINE | ID: mdl-34128858

RESUMO

BACKGROUND: Thymic epithelial tumors (TETs), originating from the thymic epithelial cells, are the most common primary neoplasms of the anterior mediastinum. Emerging evidence demonstrated that the competing endogenous RNAs (ceRNAs) exerted a crucial effect on tumor development. Hence, it is urgent to understand the regulatory mechanism of ceRNAs in TETs and its impact on tumor prognosis. METHODS: TETs datasets were harvested from the UCSC Xena as the training cohort, followed by differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) at different pathologic type (A, AB, B, and TC) identified via DESeq2 package. clusterProfiler package was utilized to carry out gene ontology and Kyoto encyclopedia of genes and genomes functional analysis on the DEmRNAs. Subsequently, the lncRNA-miRNA-mRNA regulatory network was constructed to screen the key DEmRNAs. After the key DEmRNAs were verified in the external cohort from Gene Expression Omnibus database, their associated-ceRNAs modules were used to perform the K-M and Cox regression analysis to build a prognostic significance for TETs. Lastly, the feasibility of the prognostic significance was validated by receiver operating characteristic (ROC) curves and the area under the curve. RESULTS: Finally, a total of 463 DEmRNAs, 87 DElncRNAs, and 20 DEmiRNAs were obtained from the intersection of differentially expressed genes in different pathological types of TETs. Functional enrichment analysis showed that the DEmRNAs were closely related to cell proliferation and tumor development. After lncRNA-miRNA-mRNA network construction and external cohort validation, a total of 4 DEmRNAs DOCK11, MCAM, MYO10, and WASF3 were identified and their associated-ceRNA modules were significantly associated with prognosis, which contained 3 lncRNAs (lncRNA LINC00665, lncRNA NR2F1-AS1, and lncRNA RP11-285A1.1), 4 mRNAs (DOCK11, MCAM, MYO10, and WASF3), and 4 miRNAs (hsa-mir-143, hsa-mir-141, hsa-mir-140, and hsa-mir-3199). Meanwhile, ROC curves verified the accuracy of prediction ability of the screened ceRNA modules for prognosis of TETs. CONCLUSION: Our study revealed that ceRNAs modules might exert a crucial role in the progression of TETs. The mRNA associated-ceRNA modules could effectively predict the prognosis of TETs, which might be the potential prognostic and therapeutic markers for TETs patients.


Assuntos
Biologia Computacional/estatística & dados numéricos , MicroRNAs/análise , Neoplasias Epiteliais e Glandulares/genética , RNA Longo não Codificante/análise , RNA Mensageiro/análise , Neoplasias do Timo/genética , Biomarcadores Tumorais/genética , Estudos de Coortes , Biologia Computacional/métodos , Conjuntos de Dados como Assunto , Progressão da Doença , Regulação Neoplásica da Expressão Gênica/genética , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Valor Preditivo dos Testes , Prognóstico , Modelos de Riscos Proporcionais , Curva ROC
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