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1.
NPJ Syst Biol Appl ; 5: 22, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31312515

RESUMO

Computational tools for multiomics data integration have usually been designed for unsupervised detection of multiomics features explaining large phenotypic variations. To achieve this, some approaches extract latent signals in heterogeneous data sets from a joint statistical error model, while others use biological networks to propagate differential expression signals and find consensus signatures. However, few approaches directly consider molecular interaction as a data feature, the essential linker between different omics data sets. The increasing availability of genome-scale interactome data connecting different molecular levels motivates a new class of methods to extract interactive signals from multiomics data. Here we developed iOmicsPASS, a tool to search for predictive subnetworks consisting of molecular interactions within and between related omics data types in a supervised analysis setting. Based on user-provided network data and relevant omics data sets, iOmicsPASS computes a score for each molecular interaction, and applies a modified nearest shrunken centroid algorithm to the scores to select densely connected subnetworks that can accurately predict each phenotypic group. iOmicsPASS detects a sparse set of predictive molecular interactions without loss of prediction accuracy compared to alternative methods, and the selected network signature immediately provides mechanistic interpretation of the multiomics profile representing each sample group. Extensive simulation studies demonstrate clear benefit of interaction-level modeling. iOmicsPASS analysis of TCGA/CPTAC breast cancer data also highlights new transcriptional regulatory network underlying the basal-like subtype as positive protein markers, a result not seen through analysis of individual omics data.

2.
Mol Cell Proteomics ; 18(8 suppl 1): S5-S14, 2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31126983

RESUMO

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

3.
J Proteome Res ; 2018 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-30411623

RESUMO

We present EBprotV2, a Perseus plugin for peptide-ratio-based differential protein abundance analysis in labeling-based proteomics experiments. The original version of EBprot models the distribution of log-transformed peptide-level ratios as a Gaussian mixture of differentially abundant proteins and nondifferentially abundant proteins and computes the probability score of differential abundance for each protein based on the reproducible magnitude of peptide ratios. However, the fully parametric model can be inflexible, and its R implementation is time-consuming for data sets containing a large number of peptides (e.g., >100 000). The new tool built in the C++ language is not only faster in computation time but also equipped with a flexible semiparametric model that handles skewed ratio distributions better. We have also developed a Perseus plugin for EBprotV2 for easy access to the tool. In addition, the tool now offers a new submodule (MakeGrpData) to transform label-free peptide intensity data into peptide ratio data for group comparisons and performs differential abundance analysis using mixture modeling. This approach is especially useful when the label-free data have many missing peptide intensity data points.

4.
Dev Cell ; 47(4): 425-438.e5, 2018 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-30344111

RESUMO

Liver disease is linked to a decreased capacity of hepatocytes to divide. In addition, cellular metabolism is important for tissue homeostasis and regeneration. Since metabolic changes are a hallmark of liver disease, we investigated the connections between metabolism and cell division. We determined global metabolic changes at different stages of liver regeneration using a combination of integrated transcriptomic and metabolomic analyses with advanced functional redox in vivo imaging. Our data indicate that blocking hepatocyte division during regeneration leads to mitochondrial dysfunction and downregulation of oxidative pathways. This resulted in an increased redox ratio and hyperactivity of alanine transaminase allowing the production of alanine and α-ketoglutarate from pyruvate when mitochondrial functions are impaired. Our data suggests that during liver regeneration, cell division leads to hepatic metabolic remodeling. Moreover, we demonstrate that hepatocytes are equipped with a flexible metabolic machinery able to adapt dynamically to changes during tissue regeneration.

5.
J Lipid Res ; 57(7): 1300-7, 2016 07.
Artigo em Inglês | MEDLINE | ID: mdl-27371261

RESUMO

We aimed to examine the prospective association between plasma FAs, oxylipins, and risk of acute myocardial infarction (AMI) in a Singapore Chinese population. A nested case-control study with 744 incident AMI cases and 744 matched controls aged 47-83 years was conducted within the Singapore Chinese Health Study. Nineteen plasma FAs and 12 oxylipins were quantified using MS. These were grouped into 12 FA clusters and 5 oxylipin clusters using hierarchical clustering, and their associations with AMI risk were assessed. Long-chain n-3 FAs [odds ratio (OR) = 0.67 per SD increase, 95% confidence interval (CI): 0.53-0.84, P < 0.001] and stearic acid (OR = 0.65, 95% CI: 0.44-0.97, P = 0.03) were inversely associated with AMI risk, whereas arachidonic acid (AA) was positively associated with AMI risk (OR = 1.25, 95% CI: 1.03-1.52, P = 0.02) in the multivariable model with adjustment for other FAs. Further adjustment for oxylipins did not substantially change these associations. An inverse association was observed between AA-derived oxylipin, thromboxane (TX)B2, and AMI risk (OR = 0.81, 95% CI: 0.71-0.93, P = 0.003). Circulating long-chain n-3 FAs and stearic acid were associated with a lower and AA was associated with a higher AMI risk in this Chinese population. The association between the oxylipin TXB2 and AMI requires further research.


Assuntos
Ácido Araquidônico/sangue , Infarto do Miocárdio/sangue , Oxilipinas/sangue , Ácidos Esteáricos/sangue , Idoso , Idoso de 80 Anos ou mais , Grupo com Ancestrais do Continente Asiático , Estudos de Casos e Controles , Feminino , Humanos , Pessoa de Meia-Idade , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/patologia , Estudos Prospectivos , Fatores de Risco , Singapura
6.
Mol Syst Biol ; 12(1): 855, 2016 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-26792871

RESUMO

The relative importance of regulation at the mRNA versus protein level is subject to ongoing debate. To address this question in a dynamic system, we mapped proteomic and transcriptomic changes in mammalian cells responding to stress induced by dithiothreitol over 30 h. Specifically, we estimated the kinetic parameters for the synthesis and degradation of RNA and proteins, and deconvoluted the response patterns into common and unique to each regulatory level using a new statistical tool. Overall, the two regulatory levels were equally important, but differed in their impact on molecule concentrations. Both mRNA and protein changes peaked between two and eight hours, but mRNA expression fold changes were much smaller than those of the proteins. mRNA concentrations shifted in a transient, pulse-like pattern and returned to values close to pre-treatment levels by the end of the experiment. In contrast, protein concentrations switched only once and established a new steady state, consistent with the dominant role of protein regulation during misfolding stress. Finally, we generated hypotheses on specific regulatory modes for some genes.


Assuntos
Regulação da Expressão Gênica/genética , Biossíntese de Proteínas/genética , RNA Mensageiro/biossíntese , Transcrição Genética , Animais , Cinética , Mamíferos , Dobramento de Proteína , Processamento de Proteína Pós-Traducional , Proteômica , RNA Mensageiro/genética
7.
Proteomics ; 15(15): 2580-91, 2015 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-25913743

RESUMO

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/).


Assuntos
Algoritmos , Biologia Computacional/métodos , Modelos Teóricos , Proteoma/análise , Proteômica/métodos , Animais , Linhagem Celular Tumoral , Simulação por Computador , Fator de Crescimento Epidérmico/farmacologia , Células HCT116 , Células HeLa , Humanos , Marcação por Isótopo/métodos , Espectrometria de Massas/métodos , Camundongos , Peptídeos/análise , Peptídeos/metabolismo , Fosfoproteínas/análise , Fosfoproteínas/metabolismo , Proteoma/efeitos dos fármacos , Proteoma/metabolismo , Reprodutibilidade dos Testes
8.
Sleep Breath ; 19(4): 1147-54, 2015 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-25649251

RESUMO

PURPOSE: The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure for assessing sleep impairment. Although it was developed as a unidimensional instrument, there is much debate that it contains multidimensional latent constructs. We examined the dimensionality of the underlying factor structure of PSQI in Singapore, a rapidly industrialising Asian country with multi-ethnicities representing the Chinese, Malays and Indians. METHODS: The PSQI was administered through an interviewer-based questionnaire in two separate population-based cross-sectional surveys. An explanatory factor analysis (EFA) was first used to explore the underlying construct of the PSQI in both studies. Then, a confirmatory factor analysis (CFA) was conducted to evaluate an optimal factor model by comparing against other possible models identified in EFA. RESULTS: There are three correlated yet distinguishable factors that account for an individual's sleep experience from the same best-fit model obtained in both studies: perceived sleep quality, daily disturbances and sleep efficiency. Our three-factor structure of PSQI is superior to the originally intended unidimensional model. Our model also shows the best-fit indices when compared to the previously reported single-factor, two-factor and three-factor (by Cole et al.) models in a multi-ethnic Asian population. CONCLUSION: There is strong evidence that the PSQI contains a three-factor rather than a unidimensional structure in a multi-ethnic Asian population. Scoring the PSQI along their multidimensional perspectives may provide a more accurate understanding of the relationship between sleep impairment and health conditions rather than using a single global score.


Assuntos
Grupo com Ancestrais do Continente Asiático , Comparação Transcultural , Diversidade Cultural , Transtornos do Sono-Vigília/diagnóstico , Transtornos do Sono-Vigília/etnologia , Inquéritos e Questionários , Adolescente , Adulto , Idoso , Estudos Transversais , Humanos , Pessoa de Meia-Idade , Psicometria/estatística & dados numéricos , Reprodutibilidade dos Testes , Singapura , Transtornos do Sono-Vigília/epidemiologia , Adulto Jovem
9.
Influenza Other Respir Viruses ; 7(6): 1380-9, 2013 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-23829633

RESUMO

INTRODUCTION: Previous influenza pandemics had second and on occasion third waves in many countries that were at times more severe than the initial pandemic waves. OBJECTIVE: This study aims to determine the seroepidemiology of successive waves of H1N1pdm09 infections in Singapore and the overall risks of infection. METHODS: We performed a cohort study amongst 838 adults, with blood samples provided upon recruitment and at 5 points from 2009 to 2011 and tested by haemagglutination inhibition (HI) with A/California/7/2009 (H1N1pdm09). Surveys on key demographic and clinical information were conducted at regular intervals, and associations between seroconversion and these variables were investigated. RESULTS: After the initial wave from June to September 2009, second and third waves occurred from November 2009 to February 2010 and April to June 2010, respectively. Seroconversion was 13·5% during the first wave and decreased to 6·2% and 6·8% in subsequent waves. Across the three waves, the elderly and those with higher starting HI titres were at lower risk of seroconversion, while those with larger households were at greater risk. Those with higher starting HI titres were also less likely to have an acute respiratory infection. CONCLUSIONS: The second and third waves in Singapore had lower serological attack rates than the first wave. The elderly and those with higher HI titres had lower risk, while those in larger households had higher risk of seroconversion.


Assuntos
Vírus da Influenza A Subtipo H1N1/isolamento & purificação , Influenza Humana/epidemiologia , Influenza Humana/virologia , Pandemias , Adulto , Idoso , Anticorpos Antivirais/sangue , Estudos de Coortes , Feminino , Testes de Inibição da Hemaglutinação , Humanos , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Estudos Soroepidemiológicos , Singapura/epidemiologia , Adulto Jovem
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