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1
Pourghassemi, Behnam, Ardalan Amiri Sani und Aparna Chandramowlishwaran. „Only Relative Speed Matters“. ACM SIGMETRICS Performance Evaluation Review 48, Nr. 3 (05.03.2021): 113–19. http://dx.doi.org/10.1145/3453953.3453979.
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Causal profiling is a novel and powerful profiling technique that quantifies the potential impact of optimizing a code segment on the program runtime. A key application of causal profiling is to analyze what-if scenarios which typically require a large number of experiments. Besides, the execution of a program highly depends on the underlying machine resources, e.g., CPU, network, storage, so profiling results on one device does not translate directly to another. This is a major bottleneck in our ability to perform scalable performance analysis and greatly limits cross-platform software development. In this paper, we address the above challenges by leveraging a unique property of causal profiling: only relative performance of different resources affects the result of causal profiling, not their absolute performance. We first analytically model and prove causal profiling, the missing piece in the seminal paper. Then, we assert the necessary condition to achieve virtual causal profiling on a secondary device. Building upon the theory, we design VCoz, a virtual causal profiler that enables profiling applications on target devices using measurements on the host device. We implement a prototype of VCoz by tuning multiple hardware components to preserve the relative execution speeds of code segments. Our experiments on benchmarks that stress different system resources demonstrate that VCoz can generate causal profiling reports of Nexus 6P (an ARM-based device) on a host MacBook (x86 architecture) with less than 16% variance.
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Hill, Steven M., Nicole K. Nesser, Katie Johnson-Camacho, Mara Jeffress, Aimee Johnson, Chris Boniface, Simon E. F. Spencer et al. „Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling“. Cell Systems 4, Nr. 1 (Januar 2017): 73–83. http://dx.doi.org/10.1016/j.cels.2016.11.013.
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Gupta, Saumya, Aparna Radhakrishnan, Pandu Raharja-Liu, Gen Lin, Lars M. Steinmetz, Julien Gagneur und Himanshu Sinha. „Temporal Expression Profiling Identifies Pathways Mediating Effect of Causal Variant on Phenotype“. PLOS Genetics 11, Nr. 6 (03.06.2015): e1005195. http://dx.doi.org/10.1371/journal.pgen.1005195.
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Gutteridge, Alex, J. Michael Rukstalis, Daniel Ziemek, Mark Tié, Lin Ji, Rebeca Ramos-Zayas, Nancy A. Nardone et al. „Novel Pancreatic Endocrine Maturation Pathways Identified by Genomic Profiling and Causal Reasoning“. PLoS ONE 8, Nr. 2 (13.02.2013): e56024. http://dx.doi.org/10.1371/journal.pone.0056024.
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5
Pourghassemi, Behnam, Ardalan Amiri Sani und Aparna Chandramowlishwaran. „What-If Analysis of Page Load Time in Web Browsers Using Causal Profiling“. Proceedings of the ACM on Measurement and Analysis of Computing Systems 3, Nr. 2 (19.06.2019): 1–23. http://dx.doi.org/10.1145/3341617.3326142.
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Pourghassemi, Behnam, Ardalan Amiri Sani und Aparna Chandramowlishwaran. „What-If Analysis of Page Load Time in Web Browsers Using Causal Profiling“. ACM SIGMETRICS Performance Evaluation Review 47, Nr. 1 (17.12.2019): 87–88. http://dx.doi.org/10.1145/3376930.3376986.
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Rubin, Adam J., Kevin R. Parker, Ansuman T. Satpathy, Yanyan Qi, Beijing Wu, Alvin J. Ong, Maxwell R. Mumbach et al. „Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks“. Cell 176, Nr. 1-2 (Januar 2019): 361–76. http://dx.doi.org/10.1016/j.cell.2018.11.022.
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Khademi, Aria, und Vasant Honavar. „Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract)“. Proceedings of the AAAI Conference on Artificial Intelligence 34, Nr. 10 (03.04.2020): 13839–40. http://dx.doi.org/10.1609/aaai.v34i10.7192.
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ProPublica's analysis of recidivism predictions produced by Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) software tool for the task, has shown that the predictions were racially biased against African American defendants. We analyze the COMPAS data using a causal reformulation of the underlying algorithmic fairness problem. Specifically, we assess whether COMPAS exhibits racial bias against African American defendants using FACT, a recently introduced causality grounded measure of algorithmic fairness. We use the Neyman-Rubin potential outcomes framework for causal inference from observational data to estimate FACT from COMPAS data. Our analysis offers strong evidence that COMPAS exhibits racial bias against African American defendants. We further show that the FACT estimates from COMPAS data are robust in the presence of unmeasured confounding.
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Li, Weilong, Jan Baumbach, Martin J. Larsen, Afsaneh Mohammadnejad, Jesper Lund, Kaare Christensen, Lene Christiansen und Qihua Tan. „Differential long noncoding RNA profiling of BMI in twins“. Epigenomics 12, Nr. 17 (September 2020): 1531–41. http://dx.doi.org/10.2217/epi-2020-0033.
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Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.
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Legrand, Carine, und Francesca Tuorto. „RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data“. Nucleic Acids Research 48, Nr. 2 (28.11.2019): e7-e7. http://dx.doi.org/10.1093/nar/gkz1074.
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Abstract Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers the user an HTML page to scan own data regarding the following aspects: periodicity, ligation and digestion of footprints; reproducibility and batch effects of replicates; drug-related artifacts; unbiased codon enrichment including variability between mRNAs, for A, P and E sites; mining of some causal or confounding factors. We expect our pipeline to allow an optimal use of the wealth of information provided by ribosome profiling experiments.
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Aristizabal, Maria J., Ina Anreiter, Thorhildur Halldorsdottir, Candice L. Odgers, Thomas W. McDade, Anna Goldenberg, Sara Mostafavi et al. „Biological embedding of experience: A primer on epigenetics“. Proceedings of the National Academy of Sciences 117, Nr. 38 (17.10.2019): 23261–69. http://dx.doi.org/10.1073/pnas.1820838116.
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Biological embedding occurs when life experience alters biological processes to affect later life health and well-being. Although extensive correlative data exist supporting the notion that epigenetic mechanisms such as DNA methylation underlie biological embedding, causal data are lacking. We describe specific epigenetic mechanisms and their potential roles in the biological embedding of experience. We also consider the nuanced relationships between the genome, the epigenome, and gene expression. Our ability to connect biological embedding to the epigenetic landscape in its complexity is challenging and complicated by the influence of multiple factors. These include cell type, age, the timing of experience, sex, and DNA sequence. Recent advances in molecular profiling and epigenome editing, combined with the use of comparative animal and human longitudinal studies, should enable this field to transition from correlative to causal analyses.
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Odhams, Christopher A., Deborah S. Cunninghame Graham und Timothy J. Vyse. „Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease“. PLOS Genetics 13, Nr. 10 (23.10.2017): e1007071. http://dx.doi.org/10.1371/journal.pgen.1007071.
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Nurnberg, Sylvia T., Marie A. Guerraty, Robert C. Wirka, H. Shanker Rao, Milos Pjanic, Scott Norton, Felipe Serrano et al. „Genomic profiling of human vascular cells identifies TWIST1 as a causal gene for common vascular diseases“. PLOS Genetics 16, Nr. 1 (09.01.2020): e1008538. http://dx.doi.org/10.1371/journal.pgen.1008538.
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Owen, Jonathan P., Helen C. Rees, Ben C. Maddison, Linda A. Terry, Leigh Thorne, Roy Jackman, Garry C. Whitelam und Kevin C. Gough. „Molecular Profiling of Ovine Prion Diseases by Using Thermolysin-Resistant PrPSc and Endogenous C2 PrP Fragments“. Journal of Virology 81, Nr. 19 (25.07.2007): 10532–39. http://dx.doi.org/10.1128/jvi.00640-07.
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ABSTRACT Disease-associated PrP fragments produced upon in vitro or in vivo proteolysis can provide significant insight into the causal strain of prion disease. Here we describe a novel molecular strain typing assay that used thermolysin digestion of caudal medulla samples to produce PrPres signatures on Western blots that readily distinguished experimental sheep bovine spongiform encephalopathy (BSE) from classical scrapie. Furthermore, the accumulation of such PrPres species within the cerebellum also appeared to be dependent upon the transmissible spongiform encephalopathy (TSE) strain, allowing discrimination between two experimental strains of scrapie and grouping of natural scrapie isolates into two profiles. The occurrence of endogenously produced PrP fragments, namely, glycosylated and unglycosylated C2, within different central nervous system (CNS) regions is also described; this is the first detailed description of such scrapie-associated fragments within a natural host. The advent of C2 fragments within defined CNS regions, compared between BSE and scrapie cases and also between two experimental scrapie strains, appeared to be largely dependent upon the TSE strain. The combined analyses of C2 fragments and thermolysin-resistant PrP species within caudal medulla, cerebellum, and spinal cord samples allowed natural scrapie isolates to be separated into four distinct molecular profiles: most isolates produced C2 and PrPres in all CNS regions, a second group lacked detectable cerebellar C2 fragments, one isolate lacked both cerebellar PrPres and C2, and a further isolate lacked detectable C2 within all three CNS regions and also lacked cerebellar PrPres. This CNS region-specific deposition of disease-associated PrP species may reflect the natural heterogeneity of scrapie strains in the sheep population in the United Kingdom.
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Chen, Junhui, Yuhuan Meng, Jinghui Zhou, Min Zhuo, Fei Ling, Yu Zhang, Hongli Du und Xiaoning Wang. „Identifying Candidate Genes for Type 2 Diabetes Mellitus and Obesity through Gene Expression Profiling in Multiple Tissues or Cells“. Journal of Diabetes Research 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/970435.
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Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically,DENND1B,LYN,MRPL30,POC1B,PRKCB,RP4-655J12.3,HIBADH, andTMBIM4were identified from the T2DM-control study, andBCAT1,BMP2K,CSRNP2,MYNN,NCKAP5L,SAP30BP,SLC35B4,SP1,BAP1,GRB14,HSP90AB1,ITGA5, andTOMM5were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.
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Simon, Daniel I. „Platelet Transcriptional Profiling and Atherothrombosis“. Blood 122, Nr. 21 (15.11.2013): SCI—54—SCI—54. http://dx.doi.org/10.1182/blood.v122.21.sci-54.sci-54.
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Abstract Platelets participate in events that immediately precede acute myocardial infarction. Because platelets lack nuclear DNA but retain megakaryocyte-derived mRNAs, the platelet transcriptome provides a novel window on gene expression preceding acute coronary events. We profiled platelet mRNA from patients with acute ST-segment–elevation myocardial infarction (STEMI, n=16) or stable coronary artery disease (n=44). The platelet transcriptomes were analyzed and single-gene models constructed to identify candidate genes with differential expression. We validated one candidate gene product by performing a prospective, nested case-control study (n=255 case-control pairs) among apparently healthy women to assess the risk of future cardiovascular events (nonfatal MI, nonfatal stroke, and cardiovascular death) associated with baseline plasma levels of the candidate protein. Platelets isolated from STEMI and coronary artery disease patients contained 54 differentially expressed transcripts. The strongest discriminators of STEMI in the microarrays were CD69 (odds ratio 6.2, P<0.001) and myeloid-related protein-14 (MRP-14 also known as S100A8/A9; odds ratio 3.3, P=0.002). In the validation study, the risk of a first cardiovascular event increased with each increasing quartile of MRP-8/14 (P trend <0.001) such that women with the highest levels had a 3.8-fold increase in risk of any vascular event (P<0.001). We evaluated vascular inflammation in wild-type and MRP-14-deficient (MRP-14-/-) mice that lack MRP-8/14 complexes with experimental arterial injury, vasculitis, or atherosclerosis. After femoral artery wire injury, MRP-14-/- mice had significant reductions in leukocyte accumulation, cellular proliferation, and neointimal formation compared with wild-type mice. In a cytokine-induced local Shwartzman-like reaction that produces thrombohemorrhagic vasculitis, MRP-14-/- mice had significant reductions in neutrophil accumulation, lesion severity, and hemorrhagic area. In response to high-fat feeding, mice doubly deficient in apolipoprotein E and MRP-8/14 complexes had attenuation in atherosclerotic lesion area and in macrophage accumulation in plaques compared with mice deficient in apolipoprotein E alone. These findings indicate that MRP-8/14 broadly regulates vascular inflammation and contributes to the biological response to vascular injury by promoting leukocyte recruitment. However, a causal role for MRP-14 in thrombosis has not been established and a viable molecular mechanism remains unknown. Here we show that time to thrombotic occlusion was prolonged markedly in MRP-14-/- mice. We observed that MRP-14 and MRP-8/14 are expressed in, and secreted by platelets, and that thrombus formation is reduced in whole blood from MRP-14-/- mice. Infusion of WT platelets or purified MRP-14 (or MRP-8/14) into MRP-14-/- mice shortened the carotid artery occlusion time, indicating that platelet-derived MRP-14 directly regulates thrombosis. Thus, a new pathway of inflammation and thrombosis involving MRP-14 is identified. MRP-14 represents a novel target for treating atherothrombotic disorders, including myocardial infarction and stroke. Disclosures: Simon: Cordis/J&J: Consultancy; Janssen/J&J: Consultancy; Medtronic Vascular: Consultancy; Merck: Consultancy; Medtronic Foundation: Research Funding.
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Jaeger, Savina, Junxia Min, Florian Nigsch, Miguel Camargo, Janna Hutz, Allen Cornett, Stephen Cleaver, Alan Buckler und Jeremy L. Jenkins. „Causal Network Models for Predicting Compound Targets and Driving Pathways in Cancer“. Journal of Biomolecular Screening 19, Nr. 5 (11.02.2014): 791–802. http://dx.doi.org/10.1177/1087057114522690.
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Gene-expression data are often used to infer pathways regulating transcriptional responses. For example, differentially expressed genes (DEGs) induced by compound treatment can help characterize hits from phenotypic screens, either by correlation with known drug signatures or by pathway enrichment. Pathway enrichment is, however, typically computed with DEGs rather than “upstream” nodes that are potentially causal of “downstream” changes. Here, we present graph-based models to predict causal targets from compound-microarray data. We test several approaches to traversing network topology, and show that a consensus minimum-rank score (SigNet) beat individual methods and could highly rank compound targets among all network nodes. In addition, larger, less canonical networks outperformed linear canonical interactions. Importantly, pathway enrichment using causal nodes rather than DEGs recovers relevant pathways more often. To further validate our approach, we used integrated data sets from the Cancer Genome Atlas to identify driving pathways in triple-negative breast cancer. Critical pathways were uncovered, including the epidermal growth factor receptor 2–phosphatidylinositide 3-kinase–AKT–MAPK growth pathway and ATR–p53–BRCA DNA damage pathway, in addition to unexpected pathways, such as TGF–WNT cytoskeleton remodeling, IL12-induced interferon gamma production, and TNFR–IAP (inhibitor of apoptosis) apoptosis; the latter was validated by pooled small hairpin RNA profiling in cancer cells. Overall, our approach can bridge transcriptional profiles to compound targets and driving pathways in cancer.
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Bhattacharya, Soumyaroop, und Thomas J. Mariani. „Array of hope: expression profiling identifies disease biomarkers and mechanism“. Biochemical Society Transactions 37, Nr. 4 (22.07.2009): 855–62. http://dx.doi.org/10.1042/bst0370855.
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High-throughput, genome-wide analytical technologies are now commonly used in all fields of medical research. The most commonly applied of these technologies, gene expression microarrays, have been shown to be both accurate and precise when properly implemented. For over a decade, microarrays have provided novel insight into many complex human diseases. Microarray-based discovery can be classified into three components, biomarker detection, disease (sub)classification and identification of causal mechanism, in order of accomplishment. Within the respiratory system, the application of microarrays has achieved significant success in all components, particularly with respect to lung cancer. Numerous studies over the last half-decade have applied this technology to the characterization of non-malignant respiratory diseases, animal models of respiratory disease and normal developmental processes. Studies of obstructive lung diseases by many groups, including our own, have yielded not only disease biomarkers, but also some novel putative pathogenic mechanisms. We have successfully used an integrative genomics approach, combining microarray analysis with human genetics, to identify susceptibility genes for COPD (chronic obstructive pulmonary disease). Interestingly, we find that the assessment of quantitative phenotypic variables enhances gene discovery. Our studies contribute to the identification of obstructive lung disease biomarkers, provide data associated with disease phenotypes and support the use of an integrated approach to move beyond marker identification to mechanism discovery.
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Tonui, Ronald, Joel Masanga, Remmy Kasili, Steven Runo und Amos Alakonya. „Identification of maize lethal necrosis disease causal viruses in maize and suspected alternative hosts through small RNA profiling“. Journal of Phytopathology 168, Nr. 7-8 (22.05.2020): 439–50. http://dx.doi.org/10.1111/jph.12908.
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Fallik, Seth Wyatt. „The methodological struggles of racial profiling research: a causal question that automobile stop data has yet to answer“. Criminal Justice Studies 32, Nr. 1 (17.12.2018): 32–49. http://dx.doi.org/10.1080/1478601x.2018.1558057.
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Nemoto, Kentaro, Kazuhisa Yanagi, Masato Aketagawa, D. Kanda, I. Yoshida und M. Uchidate. „A Study on Surface Material Measures for Areal Surface Texture Measuring Instruments: Measuring Conditions for the Areal Profiling“. Key Engineering Materials 381-382 (Juni 2008): 241–44. http://dx.doi.org/10.4028/www.scientific.net/kem.381-382.241.
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This paper describes the software gauge data for surface texture standard using the non-causal 2D auto-regressive model (A-R model). This model can provide with 3D irregular surface topography and intentional geometrical characteristics from specified surface texture parameters. The measurement area consists of a periodical combination of the generated sampling area data. The surface roughness parameters introduced from the gauge data on a defined evaluation area can be insensitive to size and location of the evaluation area size. Adequate measuring conditions to utilize the surface material measures were investigated and then the evaluation area and sampling distance for areal profiling by a stylus instrument were clarified.
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Gilbert, Jessica R., Mkael Symmonds, Michael G. Hanna, Raymond J. Dolan, Karl J. Friston und Rosalyn J. Moran. „Profiling neuronal ion channelopathies with non-invasive brain imaging and dynamic causal models: Case studies of single gene mutations“. NeuroImage 124 (Januar 2016): 43–53. http://dx.doi.org/10.1016/j.neuroimage.2015.08.057.
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Ando, Tatsuya, Miyuki Suguro, Takeshi Kobayashi, Masao Seto und Hiroyuki Honda. „Selection of causal gene sets for lymphoma prognostication from expression profiling and construction of prognostic fuzzy neural network models“. Journal of Bioscience and Bioengineering 96, Nr. 2 (Januar 2003): 161–67. http://dx.doi.org/10.1016/s1389-1723(03)90119-8.
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Gandal, Michael J., Jillian R. Haney, Neelroop N. Parikshak, Virpi Leppa, Gokul Ramaswami, Chris Hartl, Andrew J. Schork et al. „Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap“. Science 359, Nr. 6376 (08.02.2018): 693–97. http://dx.doi.org/10.1126/science.aad6469.
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The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders—autism, schizophrenia, bipolar disorder, depression, and alcoholism—compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism–based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.
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Beekman, Chapman, Zhenze Jiang, Brian M. Suzuki, Jonathan M. Palmer, Daniel L. Lindner, Anthony J. O’Donoghue, Giselle M. Knudsen und Richard J. Bennett. „Characterization of PdCP1, a serine carboxypeptidase from Pseudogymnoascus destructans, the causal agent of White-nose Syndrome“. Biological Chemistry 399, Nr. 12 (27.11.2018): 1375–88. http://dx.doi.org/10.1515/hsz-2018-0240.
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Abstract Pseudogymnoascus destructans is a pathogenic fungus responsible for White-nose Syndrome (WNS), a disease afflicting multiple species of North American bats. Pseudogymnoascus destructans infects susceptible bats during hibernation, invading dermal tissue and causing extensive tissue damage. In contrast, other Pseudogymnoascus species are non-pathogenic and cross-species comparisons may therefore reveal factors that contribute to virulence. In this study, we compared the secretome of P. destructans with that from several closely related Pseudogymnoascus species. A diverse set of hydrolytic enzymes were identified, including a putative serine peptidase, PdCP1, that was unique to the P. destructans secretome. A recombinant form of PdCP1 was purified and substrate preference determined using a multiplexed-substrate profiling method based on enzymatic degradation of a synthetic peptide library and analysis by mass spectrometry. Most peptide substrates were sequentially truncated from the carboxyl-terminus revealing that this enzyme is a bona fide carboxypeptidase. Peptides with arginine located close to the carboxyl-terminus were rapidly cleaved, and a fluorescent substrate containing arginine was therefore used to characterize PdCP1 activity and to screen a selection of peptidase inhibitors. Antipain and leupeptin were found to be the most potent inhibitors of PdCP1 activity.
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Kulyté, Agné, Silvia Lorente-Cebrián, Hui Gao, Niklas Mejhert, Thorhallur Agustsson, Peter Arner, Mikael Rydén und Ingrid Dahlman. „MicroRNA profiling links miR-378 to enhanced adipocyte lipolysis in human cancer cachexia“. American Journal of Physiology-Endocrinology and Metabolism 306, Nr. 3 (01.02.2014): E267—E274. http://dx.doi.org/10.1152/ajpendo.00249.2013.
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Cancer cachexia is associated with pronounced adipose tissue loss due to, at least in part, increased fat cell lipolysis. MicroRNAs (miRNAs) have recently been implicated in controlling several aspects of adipocyte function. To gain insight into the possible impact of miRNAs on adipose lipolysis in cancer cachexia, global miRNA expression was explored in abdominal subcutaneous adipose tissue from gastrointestinal cancer patients with ( n = 10) or without ( n = 11) cachexia. Effects of miRNA overexpression or inhibition on lipolysis were determined in human in vitro differentiated adipocytes. Out of 116 miRNAs present in adipose tissue, five displayed distinct cachexia-associated expression according to both microarray and RT-qPCR. Four (miR-483–5p/-23a/-744/-99b) were downregulated, whereas one (miR-378) was significantly upregulated in cachexia. Adipose expression of miR-378 associated strongly and positively with catecholamine-stimulated lipolysis in adipocytes. This correlation is most probably causal because overexpression of miR-378 in human adipocytes increased catecholamine-stimulated lipolysis. In addition, inhibition of miR-378 expression attenuated stimulated lipolysis and reduced the expression of LIPE, PLIN1, and PNPLA2, a set of genes encoding key lipolytic regulators. Taken together, increased miR-378 expression could play an etiological role in cancer cachexia-associated adipose tissue loss via effects on adipocyte lipolysis.
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Reeve, Erica, Take Naseri, Tim Martyn, Caroline Bollars und Anne-Marie Thow. „Developing a context-specific nutrient profiling system for food policy in Samoa“. Health Promotion International 34, Nr. 6 (02.11.2018): e94-e105. http://dx.doi.org/10.1093/heapro/day089.
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Abstract The objective of this study was to develop a transparent system for defining ‘less healthy’ foods to underpin effective policy to reduce noncommunicable diseases in Samoa, replacing a fatty-meat ban lifted for accession to the WTO. In the absence of nutrition survey data, we calculated nutrient availability using food acquisition data from Samoa's Household Income and Expenditure Surveys. Together with published literature and local food composition data, we identified foods and nutrients (i) consumed in amounts greater than those recommended for good health and (ii) with a demonstrated causal link to health conditions of concern. Nutrient thresholds were developed based on desired level of decrease per nutrient per person necessary to reduce population intake in line with specific targets. We found average energy and sodium consumption to be higher than recommended, and foods high in sugar and saturated fat being consumed in large amounts. We selected a threshold-based, category-specific model to provide straightforward policy administration and incentivise healthy production and import, and then applied and tested nutrient thresholds across 7 threshold groups. The validation process indicated that the development of a nutrient profiling system to identify less healthy food items in Samoa provided a stronger basis for local policymaking. This study contributes to global understanding of approaches to developing a robust and transparent basis for policies to improve diets in lower income countries, and is relevant to other settings with high rates of noncommunicable diseases and similar resource and data constraints.
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Keiper, F. J., M. S. Haque, M. J. Hayden und R. F. Park. „Genetic Diversity in Australian Populations of Puccinia graminis f. sp. avenae“. Phytopathology® 96, Nr. 1 (Januar 2006): 96–104. http://dx.doi.org/10.1094/phyto-96-0096.
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Sequence-tagged microsatellite profiling was used to develop 110 microsatellites for Puccinia graminis f. sp. tritici (causal agent of wheat stem rust). Low microsatellite polymorphism was exhibited among 10 pathogenically diverse P. graminis f. sp. tritici isolates collected from Australian cereal growing regions over a period of at least 70 years, with two polymorphic loci detected, each revealing two alleles. Limited cross-species amplification was observed for the wheat rust pathogens, P. triticina (leaf rust) and P. striiformis f. sp. tritici (stripe rust). However, very high transferability was revealed with P. graminis f. sp. avenae (causal agent of oat stem rust) isolates. A genetic diversity study of 47 P. graminis f. sp. avenae isolates collected from an Australia-wide survey in 1999, and a historical group of 16 isolates collected from Australian cereal growing regions from 1971 to 1996, revealed six polymorphic microsatellite loci with a total of 15 alleles. Genetic analysis revealed the presence of several clonal lineages and subpopulations in the pathogen population, and wide dispersal of identical races and genotypes throughout Australian cereal-growing regions. These findings demonstrated the dynamic population structure of this pathogen in Australia and concur with the patterns of diversity observed in pathogenicity studies.
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Farup, Per G., und Maria G. Maseng. „Are Faecal Microbiota Analyses on Species-Level Suitable Clinical Biomarkers? A Pilot Study in Subjects with Morbid Obesity“. Microorganisms 9, Nr. 3 (23.03.2021): 664. http://dx.doi.org/10.3390/microorganisms9030664.
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Background: An abnormal faecal microbiota could be a causal factor for disease. This study evaluated a new method for faecal microbiota analysis in subjects with obesity and irritable bowel syndrome. Methods: The study had a matched case-control design. Forty-six subjects with morbid obesity (defined as BMI > 40 or >35 kg/m2 with obesity-related complications) of whom 23 had irritable bowel syndrome (IBS), were compared with 46 healthy volunteers. The faecal microbiota was analysed with Precision Microbiome Profiling (PMP™) which quantified 104 bacteria species. The primary aim was comparisons between the cases and controls. Results: Two men and 44 women with a mean age of 43.6 years were included in each of the groups; BMI in the groups was (mean and SD) 41.9 (3.5) and 22.5 (1.5) kg/m2, respectively. Seventeen bacterial species showed statistically significant differences between the groups after adjusting for multiple testing. In a post hoc analysis, the sensitivity and specificity were 78%. Alpha diversity was lower in the group with obesity. In subjects with morbid obesity, no clinically significant differences were seen between subjects with and without IBS or from before to six months after bariatric surgery. Conclusions: The results encourage further evaluation of the new microbiome profiling tool.
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Pan, Yunzhi, Weidan Pu, Xudong Chen, Xiaojun Huang, Yan Cai, Haojuan Tao, Zhiming Xue et al. „Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data“. Schizophrenia Bulletin 46, Nr. 3 (04.01.2020): 623–32. http://dx.doi.org/10.1093/schbul/sbz112.
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Abstract The diagnosis of schizophrenia is thought to embrace several distinct subgroups. The manifold entities in a single clinical patient group increase the variance of biological measures, deflate the group-level estimates of causal factors, and mask the presence of treatment effects. However, reliable neurobiological boundaries to differentiate these subgroups remain elusive. Since cortical thinning is a well-established feature in schizophrenia, we investigated if individuals (patients and healthy controls) with similar patterns of regional cortical thickness form naturally occurring morphological subtypes. K-means algorithm clustering was applied to regional cortical thickness values obtained from 256 structural MRI scans (179 patients with schizophrenia and 77 healthy controls [HCs]). GAP statistics revealed three clusters with distinct regional thickness patterns. The specific patterns of cortical thinning, clinical characteristics, and cognitive function of each clustered subgroup were assessed. The three clusters based on thickness patterns comprised of a morphologically impoverished subgroup (25% patients, 1% HCs), an intermediate subgroup (47% patients, 46% HCs), and an intact subgroup (28% patients, 53% HCs). The differences of clinical features among three clusters pertained to age-of-onset, N-back performance, duration exposure to treatment, total burden of positive symptoms, and severity of delusions. Particularly, the morphologically impoverished group had deficits in N-back performance and less severe positive symptom burden. The data-driven neuroimaging approach illustrates the occurrence of morphologically separable subgroups in schizophrenia, with distinct clinical characteristics. We infer that the anatomical heterogeneity of schizophrenia arises from both pathological deviance and physiological variance. We advocate using MRI-guided stratification for clinical trials as well as case–control investigations in schizophrenia.
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Zenil, Hector, Narsis A. Kiani, Ming-mei Shang und Jesper Tegnér. „Algorithmic Complexity and Reprogrammability of Chemical Structure Networks“. Parallel Processing Letters 28, Nr. 01 (März 2018): 1850005. http://dx.doi.org/10.1142/s0129626418500056.
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Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of applying a computational interventional calculus based on the principles of algorithmic probability to chemical structure networks. We profile the sensitivity of the elements and covalent bonds in a chemical structure network algorithmically, asking whether reprogrammability affords information about thermodynamic and chemical processes involved in the transformation of different compound classes. We arrive at numerical results suggesting a correspondence between some physical, structural and functional properties. Our methods are capable of separating chemical classes that reflect functional and natural differences without considering any information about atomic and molecular properties. We conclude that these methods, with their links to chemoinformatics via algorithmic, probability hold promise for future research.
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Puig, Oscar, I.-Ming Wang, Ping Cheng, Pris Zhou, Sophie Roy, Doris Cully, Mette Peters, Yair Benita, John Thompson und Tian-Quan Cai. „Transcriptome profiling and network analysis of genetically hypertensive mice identifies potential pharmacological targets of hypertension“. Physiological Genomics 42A, Nr. 1 (September 2010): 24–32. http://dx.doi.org/10.1152/physiolgenomics.00010.2010.
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Hypertension is a condition with major cardiovascular and renal complications, affecting nearly a billion patients worldwide. Few validated gene targets are available for pharmacological intervention, so there is a need to identify new biological pathways regulating blood pressure and containing novel targets for treatment. The genetically hypertensive “blood pressure high” (BPH), normotensive “blood pressure normal” (BPN), and hypotensive “blood pressure low” (BPL) inbred mouse strains are an ideal system to study differences in gene expression patterns that may represent such biological pathways. We profiled gene expression in liver, heart, kidney, and aorta from BPH, BPN, and BPL mice and determined which biological processes are enriched in observed organ-specific signatures. As a result, we identified multiple biological pathways linked to blood pressure phenotype that could serve as a source of candidate genes causal for hypertension. To distinguish in the kidney signature genes whose differential expression pattern may cause changes in blood pressure from those genes whose differential expression pattern results from changes in blood pressure, we integrated phenotype-associated genes into Genetic Bayesian networks. The integration of data from gene expression profiling and genetics networks is a valuable approach to identify novel potential targets for the pharmacological treatment of hypertension.
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Hall, Ashley, Sara Bandres-Ciga, Monica Diez-Fairen, John P. Quinn und Kimberley J. Billingsley. „Genetic Risk Profiling in Parkinson’s Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways“. International Journal of Molecular Sciences 21, Nr. 19 (04.10.2020): 7332. http://dx.doi.org/10.3390/ijms21197332.
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Parkinson’s disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ‘’complex’’ PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies and how this may be utilized to generate polygenic risk scores (PRS), which may be used in the prediction of risk and trajectory of PD. We also comment on how pathway-specific genetic profiling can be used to gain insight into PD-related biological pathways, and how this may be further utilized to nominate causal PD genes and potentially druggable therapeutic targets. Finally, we outline the current limits of our understanding of PD genetics and the potential contribution of variation currently uncaptured in genetic studies, focusing here on uncatalogued structural variants.
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Cao, Song, Yun Liu, Wenting Sun, Li Zhao, Lin Zhang, Xinkui Liu und Tian Yu. „Genome-Wide Expression Profiling of Anoxia/Reoxygenation in Rat Cardiomyocytes Uncovers the Role of MitoKATPin Energy Homeostasis“. Oxidative Medicine and Cellular Longevity 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/756576.
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Mitochondrial ATP-sensitive potassium channel (mitoKATP) is a common end effector of many protective stimuli in myocardial ischemia-reperfusion injury (MIRI). However, the specific molecular mechanism underlying its myocardial protective effect is not well elucidated. We characterized an anoxia/reoxygenation (A/R) model using freshly isolated adult rat cardiomyocytes. MitoKATPstatus was interfered with its specific opener diazoxide (DZ) or blocker 5-hydroxydecanote (5-HD). Digital gene expression (DGE) and bioinformatic analysis were deployed. Three energy metabolism related genes (MT-ND6, Idh2,andAcadl) were upregulated when mitoKATPopened. In addition, as many as 20 differentially expressed genes (DEGs) were significantly enriched in five energy homeostasis correlated pathways (PPAR, TCA cycle, fatty acid metabolism, and peroxisome). These findings indicated that mitoKATPopening in MIRI resulted in energy mobilization, which was confirmed by measuring ATP content in cardiomyocytes. These causal outcomes could be a molecular mechanism of myocardial protection of mitoKATPand suggested that the mitoKATPopening plays a physiologic role in triggering cardiomyocytes’ energy homeostasis during MIRI. Strategies of modulating energy expenditure during myocardial ischemia-reperfusion may be promising approaches to reduce MIRI.
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Djami-Tchatchou, Arnaud Thierry, Lerato Bame Tsalaemang Matsaunyane, Chimdi Mang Kalu und Khayalethu Ntushelo. „Gene expression and evidence of coregulation of the production of some metabolites of chilli pepper inoculated with Pectobacterium carotovorum ssp. carotovorum“. Functional Plant Biology 46, Nr. 12 (2019): 1114. http://dx.doi.org/10.1071/fp18244.
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Chilli pepper (Capsicum annuum L.) is susceptible to Pectobacterium carotovorum subsp. carotovorum (Pcc), the causal agent of soft rot disease in crops. Understanding the molecular principles of systemic acquired resistance, which is poorly understood in chilli pepper, represents an important step towards understanding inducible defence responses and can assist in designing appropriate intervention strategies for crop disease management. Accordingly, we investigated (via real-time PCR and metabolomics profiling) the molecular response of chilli pepper to Pcc by characterisation of the crucial metabolic regulators involved in the establishment of defence response. We profiled 13 key inducible defence response genes, which included MYB transcriptor factor, ethylene response element-binding protein, suppressor of the G2 allele of Skp1, cytochrome P450, small Sar1 (GTPase), hydroxycinnamoyl-CoA:quinate hydroxycinnamoyl transferase, pathogenesis-related protein 1a, endo-1,3-β-glucanase, chitinase, proteinase inhibitor, defensin, coiled-coil-nucleotide-binding site-leucine-rich repeat (CC–NBS–LRR) resistance and phenylalanine ammonia lyase. In addition, we determined metabolomic shifts induced by Pcc in pepper. The PCR results revealed a significant induction of the selected plant defence-related genes in response to Pcc inoculation; the metabolomic profiling showed that of 99 primary metabolites profiled the quantities of acetylcarnitine, adenosine, adenosine 3′,5′ cyclic monophosphate, guanosine 3′,5′ cyclic monophosphate and inosine decreased in pepper leaves inoculated with Pcc.
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Zhu, Mengyan, Yong Li, Cheng Ding, Jiaqi Wang, Yangyang Ma, Zhao Li, Xiaoyan Zhang und Ping Wang. „Proteomic Profiling Change and Its Implies in the Early Mycosis Fungoides (MF) Using Isobaric Tags for Relative and Absolute Quantification (iTRAQ)“. BioMed Research International 2020 (23.11.2020): 1–13. http://dx.doi.org/10.1155/2020/9237381.
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Purpose. Mycosis fungoides (MF) is the most common T-cell lymphoma, with indolent biologic behavior in the early stage and features of invasive in the tumor stage. The diagnosis of MF is still ambiguous and difficult. We focused on the proteomic profiling change in the pathogenesis of early MF and identified candidate biomarkers for early diagnosis. Methods. We collected peripheral blood samples of MF patients and healthy individuals (HI) performed proteomic profiling analysis using isobaric tags for relative and absolute quantification (iTRAQ) platform. Differently expressed proteins (DEPs) were filtered, and involved biological functions were analyzed through Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software. Results. We identified 78 DEPs including fifty proteins were upregulated and 28 proteins were downregulated in the MF group with HI as a control. Total DEPs were analyzed according to the biological regulation and metabolic process through GO analysis. The pathways of LXR/RXR activation and FXR/RXR activation were significantly activated, in which APOH, CLU, and ITIH4 were involved. The top annotated disease and function network was (Cancer, Organismal Injury and Abnormalities, Reproductive System Disease), with a key node CLU. These DEPs were involved in cancer, including thyroid carcinoma, head and neck carcinoma, and cancer of secretory structure, in which CLU, GNAS, and PKM played an indirect role in the occurrence and development of cancer. Relevant causal network was IL12 (family), which is related to GNAS, PKM, and other DEPs. Conclusion. Proteomic profiling of early-stage MF provided candidate protein biomarkers such as CLU, GNAS, and PKM, which benefit the early diagnosis and understanding of the mechanism of MF development. Besides, lipid metabolism may be one of the pathogenesis of MF, and IL12 was a potential marker for the diagnosis and treatment of early MF.
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Rajasekaran, Namakkal S., Matthew A. Firpo, Brett A. Milash, Robert B. Weiss und Ivor J. Benjamin. „Global expression profiling identifies a novel biosignature for protein aggregation R120GCryAB cardiomyopathy in mice“. Physiological Genomics 35, Nr. 2 (Oktober 2008): 165–72. http://dx.doi.org/10.1152/physiolgenomics.00297.2007.
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Protein aggregation cardiomyopathy is a life-threatening manifestation of a multisystem disorder caused by the exchange mutation in the gene encoding the human small heat shock protein αB-crystallin (hR120GCryAB). Genetic studies in mice have established cardiac hR120GCryAB expression causes increased activity of glucose 6-phosphate dehydrogenase (G6PD) and “reductive stress” (Rajasekaran et al., Cell 130: 427–439, 2007). However, the initiating molecular events in the pathogenesis of this novel toxic gain-of-function mechanism remain poorly defined. In an integrated systems approach using gene expression profiling, we identified a “biosignature,” whose features can be validated to predict the onset, rate of progression, and clinical outcome of R120GCryAB cardiomyopathy. At the 3 mo disease-related but compensated stage, we demonstrate that transcripts were only upregulated in three distinct pathways: stress response (e.g., Hsp70, Hsp90), glutathione metabolism (Gpx1, Gpx3, glutathione S-transferase), and complement and coagulation cascades in hR120GCryAB transgenic mouse hearts compared with either hCryAB WT transgenic mice or nontransgenic controls. In 6 mo old myopathic hearts, ribosomal synthesis and cellular remodeling associated with increased cardiac hypertrophy were additional upregulated pathways. In contrast, the predominant downregulated pathways were for oxidative phosphorylation, fatty acid metabolism, intermediate metabolism, and energetic balance, supporting their primary pathogenic roles by which G6PD-dependent reductive stress causes cardiac decompensation and overt heart failure in hR120GCryAB cardiomyopathy. This study extends and confirms our previous findings that reductive stress is a causal mechanism for hR120G CryAB cardiomyopathy and demonstrates that alteration in glutathione pathway gene expression is an early biosignature with utility for presymptomatic detection.
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Zeiss, Dylan R., Msizi I. Mhlongo, Fidele Tugizimana, Paul A. Steenkamp und Ian A. Dubery. „Metabolomic Profiling of the Host Response of Tomato (Solanum lycopersicum) Following Infection by Ralstonia solanacearum“. International Journal of Molecular Sciences 20, Nr. 16 (14.08.2019): 3945. http://dx.doi.org/10.3390/ijms20163945.
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Tomato (Solanum lycopersicum) is an important dietary source of bioactive phytochemicals and active breeding programs constantly produce new cultivars possessing superior and desirable traits. The phytopathogenic Ralstonia solanacearum, the causal agent of bacterial wilt, is a highly destructive bacterial disease with a high economic impact on tomato production. This study followed an untargeted metabolomic approach involving four tomato cultivars and aimed at the identification of secondary metabolites involved in plant defense after infection with R. solanacearum. Liquid chromatography coupled to mass spectrometry (LC-MS) in combination with multivariate data analysis and chemometric modelling were utilized for the identification of discriminant secondary metabolites. The total of 81 statistically selected features were annotated belonging to the metabolite classes of amino acids, organic acids, fatty acids, various derivatives of cinnamic acid and benzoic acids, flavonoids and steroidal glycoalkaloids. The results indicate that the phenylpropanoid pathway, represented by flavonoids and hydroxycinnamic acids, is of prime importance in the tomato defense response. The hydroxycinnamic acids esters of quinic acid, hexoses and glucaric acids were identified as signatory biomarkers, as well as the hydroxycinnamic acid amides to polyamines and tyramine. Interestingly, the rapid and differential accumulation of putrescine, dopamine, and tyramine derivatives, along with the presence of a newly documented metabolite, feruloyl serotonin, were documented in the infected plants. Metabolite concentration variability in the different cultivar tissues point to cultivar-specific variation in the speed and manner of resource redistribution between the host tissues. These metabolic phenotypes provide insights into the differential metabolic signatures underlying the defense metabolism of the four cultivars, defining their defensive capabilities to R. solanacearum.
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Narain, Niven, Michael Kiebish, Vivek Vishnudas, Vladimir Tolstikov, Gregory Miller, Stephane Gesta, Elder Granger und Rangaprasad Sarangarajan. „CSAO-1. Interrogative Biology: Unraveling insights into causal disease drivers by use of a dynamic systems biology and Bayesian AI to identify the intersect of disease and healthy signatures“. Neuro-Oncology Advances 3, Supplement_2 (01.07.2021): ii1. http://dx.doi.org/10.1093/noajnl/vdab070.001.
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Abstract The past decade has been witness to an explosive proliferation of data analytics modalities, all seeking to unravel insight into large-scale data sets. Machine learning and AI methodologies now occupy a central role in analyses of data sets that range in nature from genomics, “omics”, clinical, real-world evidence, and demographic data. Despite advances in data analytics/machine learning, access to complex population level clinical and related datasets, translating information into actionable guidance in human health and disease remains a challenge. Interrogative Biology, a systems biology/AI platform generates an unbiased, data-informed network for identifying targets (disease drivers) and biomarkers for disease interception at the point of transition to dysregulation, preceding clinical phenotype. The data topology is enabled by a systematic acquisition and interrogation of longitudinal bio-samples of clinically annotated human matrices (e.g. blood, urine, saliva, tissues) subjected to comprehensive multi-omic (genomic, proteomics, lipidomics and metabolomics) profiling over time. The molecular profiles are integrated with clinical health information using Bayesian artificial intelligence analytics, bAIcis, to generate causal network maps of overall health. Differentials between “health” and “disease” network maps identifies drivers (targets and biomarkers) of disease and are rapidly validated in orthogonal wet-lab disease specific perturbed model systems. Target information imputed into the bAIcis framework can define therapeutic strategies including identification of existing drugs and bio-actives for corrective response. Using a combination of clinic based sampling and dried blood spot analysis for longitudinal dynamic monitoring of markers of health-disease status provides opportunity for proactive clinical management and intervention for corrective response in advance of major deterioration of health status. Taken together, the approach herein allows for health surveillance based on in-depth biological profiling of alterations in the patient narrative to guide treatment modalities and strategies in a longitudinal and dynamic manner to identify, track, intercept, and arrest human disease.
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Celik, Mustafa, Alper Şen, İsmail Koyuncu und Ataman Gönel. „Plasma-Free Amino Acid Profiling of Nasal Polyposis Patients“. Combinatorial Chemistry & High Throughput Screening 22, Nr. 9 (01.01.2020): 657–62. http://dx.doi.org/10.2174/1386207322666190920110324.
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Aim and Objective:: To determine the mechanisms present in the etiopathogenesis of nasal polyposis. It is not clear whether amino acids contribute in a causal way to the development of the disease. Therefore, the aim of this study was to determine the plasma-free amino acid profile in patients with nasal polyposis and to compare the results with a healthy control group. Materials and Methods:: This was a prospective controlled study that took place in the Otolaryngology Department at the Harran University Faculty of Medicine between April 2017 and April 2018. Plasmafree amino acid profile levels were studied in serum samples taken from a patient group and a healthy control group. Patients who were diagnosed with bilateral diffuse nasal polyposis and were scheduled for surgical interventions were included in this study. Individuals whose age, gender, and body mass index values were compatible with that of the patient group and who did not have any health problems were included in the control group. All the participants whose levels of plasma-free amino acid were thought to be affected by one or more of the following factors were excluded from the study: smoking and alcohol use, allergic rhinitis presence, the presence of acute or chronic sinusitis, a history of endoscopic sinus surgery, unilateral nasal masses, a history of chronic drug use, systemic or topical steroid use in the last three months for any reason, and liver, kidney, hematological, cardiovascular, metabolic, neurological, or psychiatric disorders or malignancies. Results: In patients with nasal polyposis, 3-methyl histidine (3-MHIS: nasal polyposis group (ng) = 3.22 (1.92 – 6.07); control group (cg) = 1.21 (0.77 – 1.68); p = 0.001); arginine (arg: ng = 98.95 (70.81 – 117.75); cg = 75.10 (54.49 – 79.88); p = 0.005); asparagine (asn: ng = 79.84 (57.50 – 101.44); cg = 60.66 (46.39 – 74.62); p = 0.021); citrulline (cit: ng = 51.83 (43.81 – 59.78); cg = 38.33 (27.81 – 53.73); p = 0.038); cystine (cys: ng = 4.29 (2.43 – 6.66); cg = 2.41 (1.51 – 4.16); p = 0.019); glutamic acid (glu: ng = 234.86 (128.75 – 286.66); cg = 152.37 (122.51 – 188.34); p = 0.045); histidine (his: ng = 94.19 (79.34 – 113.99); cg = 74.80 (62.76 – 98.91); p = 0.018); lysine (lys: ng = 297.22 (206.55 – 371.25); cg = 179.50 (151.58 – 238.02); p = 0.001); ornithine (ng = 160.62 (128.36 – 189.32); cg = 115.91 (97.03 – 159.91); p = 0.019); serine (ser: ng = 195.15 (151.58 – 253.07); cg = 83.07 (67.44 – 92.44); p = 0.001); taurine (tau: ng = 74.69 (47.00 – 112.13); cg = 53.14 (33.57 – 67.31); p = 0.006); tryptophan (trp: ng = 52.31 (33.81 – 80.11); cg = 34.44 (25.94 – 43.07); p = 0.005), homocitrulline (ng = 1.75 (1.27 – 2.59); cg = 0.00 (0.00 – 0.53); p = 0.001); norvaline (ng = 6.90 (5.61 – 9.18); cg = 4.93 (3.74 – 7.13); p = 0.021); argininosuccinic acid (ng = 14.33 (10.06 – 25.65); cg = 12.22 (5.77 – 16.87) p = 0.046); and plasma concentrations were significantly higher than in the healthy control group (p <0.05). However, the gamma-aminobutyric acid (gaba: ng = 0.16 (0.10 – 0.24); cg = 0.21 (0.19 – 0.29); p = 0.010) plasma concentration was significantly lower in the nasal polyposis group than in the healthy control group. Conclusion: In this study, plasma levels of 15 free amino acids were significantly higher in the nasal polyposis group than in the healthy control group. A plasma level of 1 free amino acid was found to be significantly lower in the nasal polyposis group compared to the healthy control group. Therefore, it is important to determine the possibility of using the information obtained to prevent the recurrence of the condition and to develop effective treatment strategies. This study may be a milestone for studies of this subject. However, this study needs to be confirmed by further studies conducted in a larger series.
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Belcastro, Vincenzo, Carine Poussin, Stephan Gebel, Carole Mathis, Walter K. Schlage, Rosemarie B. Lichtner, Sibille Quadt-Humme, Sandra Wagner, Julia Hoeng und Manuel C. Peitsch. „Systematic Verification of Upstream Regulators of a Computable Cellular Proliferation Network Model on Non-Diseased Lung Cells Using a Dedicated Dataset“. Bioinformatics and Biology Insights 7 (Januar 2013): BBI.S12167. http://dx.doi.org/10.4137/bbi.s12167.
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We recently constructed a computable cell proliferation network (CPN) model focused on lung tissue to unravel complex biological processes and their exposure-related perturbations from molecular profiling data. The CPN consists of edges and nodes representing upstream controllers of gene expression largely generated from transcriptomics datasets using Reverse Causal Reasoning (RCR). Here, we report an approach to biologically verify the correctness of upstream controller nodes using a specifically designed, independent lung cell proliferation dataset. Normal human bronchial epithelial cells were arrested at G1/S with a cell cycle inhibitor. Gene expression changes and cell proliferation were captured at different time points after release from inhibition. Gene set enrichment analysis demonstrated cell cycle response specificity via an overrepresentation of proliferation related gene sets. Coverage analysis of RCR-derived hypotheses returned statistical significance for cell cycle response specificity across the whole model as well as for the Growth Factor and Cell Cycle sub-network models.
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Drew, J. E., D. K. Mercer, C. Mayer, A. J. Farquharson, P. C. Morrice, J. R. Arthur und G. G. Duthie. „Oxidative stress in colon tissue induced by vitamin E depletion“. Biochemical Society Transactions 32, Nr. 6 (26.10.2004): 979–81. http://dx.doi.org/10.1042/bst0320979.
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Inflammatory disorders of the bowel and colon cancer are associated with elevated indices of oxidative stress. Analogous elevations in markers of oxidative stress and loss of cell-membrane integrity are also observed in the colons of rats deficient in vitamin E (D-α-tocopherol), the major lipid-soluble antioxidant in biological systems. The causal relationship between colon pathologies associated with oxidative stress and dietary deficiency in antioxidant vitamins such as vitamin E is still uncertain. Investigation of potential mechanisms by which lack of dietary vitamin E may lead to clinically relevant pathological changes in colon tissue was conducted using gene expression profiling strategies on vitamin E-sufficient and -deficient rats. Morphological changes and increased indices of lipid peroxidation were linked to vitamin E deficiency. These changes in colon tissue are potentially important in disease pathogenesis of the colon linked with oxidative stress or other direct consequences of inadequate levels of vitamin E.
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Walcott, Farzana L., Christina M. Annunziata, Eduardo M. Sotomayor und Antonio Tito Fojo. „Effect of metformin chemoprevention on metabolomics profiles in Li-Fraumeni Syndrome (LFS).“ Journal of Clinical Oncology 35, Nr. 15_suppl (20.05.2017): 1556. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.1556.
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1556 Background: LFS is a highly-penetrant, autosomal dominant, cancer predisposition disorder characterized by early onset cancer; germline mutations in TP53are present in 70% of LFS. We previously observed metformin inhibition on mitochondrial function in LFS patients. Metformin may reduce TCA cycle and glycolytic intermediates during cellular transformation, indicating inhibition of complex I of the mitochondria. To further explore this, we performed untargeted metabolomics profiling on stored serum of study participants. To our knowledge, there are no previous studies of metabolomics profiling in LFS patients treated with metformin. Methods: Adult LFS patients (≥18 years old) were enrolled for 20 weeks. Metformin was initiated at 500 mg per day and increased in 500 mg dose increments every two weeks to a maintenance dose of 2000 mg of metformin. Patients were taken off metformin for the last six weeks of the study (week 20). Global biochemical profiles were determined in human serum samples collected in 21 patients, each providing one sample at baseline, week 14 (on 2000 mg metformin) and week 20 (off metformin). Metabolomics analyses were performed by Metabolon, Inc. Results: Treatment with metformin induced a strong metabolic signature of increased fatty acid beta-oxidation in LFS patients. Acylcarnitines, long chain fatty acids, and 3-hydroxy fatty acids were significantly elevated following metformin treatment. TCA cycle intermediates, aconitate, malate, and fumarate were also increased as were levels of ketone body 3-hydroxybutyrate (BHBA)indicating robust β-oxidation, presumably to support increased energy production via the TCA cycle. Clearance of metformin results in normalization of levels to comparable baseline values, indicating a causal role of metformin in these changes. Conclusions: Global metabolomics profiling suggests an increase in TCA cycle intermediates and a strong signature of fatty acid oxidation with metformin treatment in LFS, suggesting metformin effect on the mitochondria and TCA cycle is more dynamic than previously shown. LFS patients may have distinct metabolic profiles which may be altered by treatment with metformin. Funding: ASCO Young Investigator’s Award 2016. Clinical trial information: NCT01981525.
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Zhu, Hong, Long-Fei Wu, Xing-Bo Mo, Xin Lu, Hui Tang, Xiao-Wei Zhu, Wei Xia et al. „Rheumatoid arthritis–associated DNA methylation sites in peripheral blood mononuclear cells“. Annals of the Rheumatic Diseases 78, Nr. 1 (08.10.2018): 36–42. http://dx.doi.org/10.1136/annrheumdis-2018-213970.
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ObjectivesTo identify novel DNA methylation sites significant for rheumatoid arthritis (RA) and comprehensively understand their underlying pathological mechanism.MethodsWe performed (1) genome-wide DNA methylation and mRNA expression profiling in peripheral blood mononuclear cells from RA patients and health controls; (2) correlation analysis and causal inference tests for DNA methylation and mRNA expression data; (3) differential methylation genes regulatory network construction; (4) validation tests of 10 differential methylation positions (DMPs) of interest and corresponding gene expressions; (5) correlation between PARP9 methylation and its mRNA expression level in Jurkat cells and T cells from patients with RA; (6) testing the pathological functions of PARP9 in Jurkat cells.ResultsA total of 1046 DNA methylation positions were associated with RA. The identified DMPs have regulatory effects on mRNA expressions. Causal inference tests identified six DNA methylation–mRNA–RA regulatory chains (eg, cg00959259-PARP9-RA). The identified DMPs and genes formed an interferon-inducible gene interaction network (eg, MX1, IFI44L, DTX3L and PARP9). Key DMPs and corresponding genes were validated their differences in additional samples. Methylation of PARP9 was correlated with mRNA level in Jurkat cells and T lymphocytes isolated from patients with RA. The PARP9 gene exerted significant effects on Jurkat cells (eg, cell cycle, cell proliferation, cell activation and expression of inflammatory factor IL-2).ConclusionsThis multistage study identified an interferon-inducible gene interaction network associated with RA and highlighted the importance of PARP9 gene in RA pathogenesis. The results enhanced our understanding of the important role of DNA methylation in pathology of RA.
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Peters, Susan, Douglas Walker, Gary Miller, Marc Chadeau-Hyam, Paolo Vineis, Valentina Gallo und Roel Vermeulen. „O6E.4 Metabolome and exposome profiling: new opportunities to study risk factors for parkinson’s disease“. Occupational and Environmental Medicine 76, Suppl 1 (April 2019): A60.1—A60. http://dx.doi.org/10.1136/oem-2019-epi.161.
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Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer disease and is imposing an increasing social and economic burden in ageing populations. Although the role of environmental factors has been recognised, few established risk factors have been consistently identified. Evidence that exposure to pesticides, herbicides and metals increase PD risk is suggestive, but further research is needed to identify specific compounds that may play a causal role.Large established prospective population studies offer an important opportunity for investigating risk factors in relatively rare diseases such as PD. Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, 734 incident PD cases have been ascertained, for whom pre-diagnostic blood has been stored. A nested case-control study will be conducted, where one control per case will be selected by incidence density sampling matched by age at recruitment, sex and study centre.Untargeted metabolomics can simultaneously characterize thousands of endogenous and exogenous compounds within a biological sample: the metabolome. Metabolome wide association studies (MWAS) have identified significant differences in the metabolomic profile of older adults with and without PD. We will employ an innovative approach combining liquid and gas phase chromatography with ultra-high-resolution mass spectrometry (LC/GC-UHRMS), to identify exogenous chemical exposures (e.g. pollutants, pesticides and medications), the exposome, in addition to the metabolome.Disease specific variability in blood metabolite compositions may signify the presence of mechanistic aberrations contributing to PD pathogenesis. The combination of metabolome and exposome profiling provides a measure of the continuum from exposure to disease. Allowing previously unavailable richness and depth for characterizing the metabolome and exposome upon which novel discoveries in PD can be made.The EPIC cohort allows us to perform a to study the metabolome and exposome well before disease onset, to eliminate possible effects of levodopa medication or disease-related processes.
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Guan, P., S. F. Wong, J. Q. Lim, C. C. Y. Ng, P. L. Soong, C. Q. X. Sim, C. K. Ong et al. „Mutational Signatures in Mandibular Ameloblastoma Correlate with Smoking“. Journal of Dental Research 98, Nr. 6 (27.03.2019): 652–58. http://dx.doi.org/10.1177/0022034519837248.
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Ameloblastoma is a rare tumor of odontogenic epithelium, the low incidence rate of which precludes statistical determination of its molecular characterizations. Despite recent genomic and transcriptomic profiling, the etiology of ameloblastomas remains poorly understood. Risk factors of ameloblastoma development are also largely unknown. Whole exome sequencing was performed on 11 mandibular ameloblastoma samples. We identified 2 convergent mutational signatures in ameloblastoma: 1) a signature found in multiple types of lung cancers with probable etiology of tobacco carcinogens (COSMIC signature 4) and 2) a signature present in gingivobuccal oral squamous cell carcinoma and correlated with tobacco-chewing habits (COSMIC signature 29). These mutational signatures highlight tobacco usage or related mutagens as one possible risk factor of ameloblastoma, since the association of BRAF mutations and smoking was demonstrated in multiple studies. In addition to BRAF hotspot mutations (V600E), we observed clear inter- and intratumor heterogeneities. Interestingly, prior to BRAF mutation, important genes regulating odontogenesis mutated (e.g., corepressor BCOR), possibly playing important roles in tumorigenesis. Furthermore, recurrent mutations in the CDC73 gene, the germline mutations of which predispose patients to the development of jaw tumors, were found in 2 patients, which may lead to recurrence if not targeted by therapeutic drugs. Our unbiased profiling of coding regions of ameloblastoma genomes provides insights to the possible etiology of mandibular ameloblastoma and highlights potential disease risk factors for screening and prevention, especially for Asian patients. Because of the limited sample size and incomplete habitual, dietary, and occupational data, a causal link between tobacco usage and ameloblastoma still requires further investigations.
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Yong, Hannah E. J., und Shiao-Yng Chan. „Current approaches and developments in transcript profiling of the human placenta“. Human Reproduction Update 26, Nr. 6 (12.10.2020): 799–840. http://dx.doi.org/10.1093/humupd/dmaa028.
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Abstract BACKGROUND The placenta is the active interface between mother and foetus, bearing the molecular marks of rapid development and exposures in utero. The placenta is routinely discarded at delivery, providing a valuable resource to explore maternal-offspring health and disease in pregnancy. Genome-wide profiling of the human placental transcriptome provides an unbiased approach to study normal maternal–placental–foetal physiology and pathologies. OBJECTIVE AND RATIONALE To date, many studies have examined the human placental transcriptome, but often within a narrow focus. This review aims to provide a comprehensive overview of human placental transcriptome studies, encompassing those from the cellular to tissue levels and contextualize current findings from a broader perspective. We have consolidated studies into overarching themes, summarized key research findings and addressed important considerations in study design, as a means to promote wider data sharing and support larger meta-analysis of already available data and greater collaboration between researchers in order to fully capitalize on the potential of transcript profiling in future studies. SEARCH METHODS The PubMed database, National Center for Biotechnology Information and European Bioinformatics Institute dataset repositories were searched, to identify all relevant human studies using ‘placenta’, ‘decidua’, ‘trophoblast’, ‘transcriptome’, ‘microarray’ and ‘RNA sequencing’ as search terms until May 2019. Additional studies were found from bibliographies of identified studies. OUTCOMES The 179 identified studies were classifiable into four broad themes: healthy placental development, pregnancy complications, exposures during pregnancy and in vitro placental cultures. The median sample size was 13 (interquartile range 8–29). Transcriptome studies prior to 2015 were predominantly performed using microarrays, while RNA sequencing became the preferred choice in more recent studies. Development of fluidics technology, combined with RNA sequencing, has enabled transcript profiles to be generated of single cells throughout pregnancy, in contrast to previous studies relying on isolated cells. There are several key study aspects, such as sample selection criteria, sample processing and data analysis methods that may represent pitfalls and limitations, which need to be carefully considered as they influence interpretation of findings and conclusions. Furthermore, several areas of growing importance, such as maternal mental health and maternal obesity are understudied and the profiling of placentas from these conditions should be prioritized. WIDER IMPLICATIONS Integrative analysis of placental transcriptomics with other ‘omics’ (methylome, proteome and metabolome) and linkage with future outcomes from longitudinal studies is crucial in enhancing knowledge of healthy placental development and function, and in enabling the underlying causal mechanisms of pregnancy complications to be identified. Such understanding could help in predicting risk of future adversity and in designing interventions that can improve the health outcomes of both mothers and their offspring. Wider collaboration and sharing of placental transcriptome data, overcoming the challenges in obtaining sufficient numbers of quality samples with well-defined clinical characteristics, and dedication of resources to understudied areas of pregnancy will undoubtedly help drive the field forward.
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Tian, Yanli, Yuqiang Zhao, Xuezi Chen, Yuanfeng Dai, Wenjun Zhao, Baishi Hu und R. R. Walcott. „Evidence for a Novel Phylotype of Pseudomonas syringae Causing Bacterial Leaf Blight of Cantaloupe in China“. Plant Disease 101, Nr. 10 (Oktober 2017): 1746–52. http://dx.doi.org/10.1094/pdis-01-17-0110-re.
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Bacterial leaf blight (BLB) has caused severe yield losses in cantaloupe (Cucumis melo L.) in the major melon-growing regions of China since the beginning of the twentieth century. Historically, Pseudomonas syringae pv. lachrymans was considered to be the causal agent of BLB of cantaloupe and angular leaf spot of cucumber. In the process of characterizing bacteria isolated from cantaloupe, we observed that putative P. syringae pv. lachrymans yielded negative results in P. syringae pv. lachrymans-specific PCR assays. This suggested that the P. syringae pv. lachrymans-like strains from cantaloupe were distinct from those recovered from cucumber. To investigate the differences between P. syringae pv. lachrymans-like strains isolated from cantaloupe and cucumber, 13 P. syringae strains isolated from cantaloupe [12 from China and 1 from Zimbabwe (NCPPB2916)] and 7 additional P. syringae reference strains were analyzed by catabolic profiling, phylogenetic analysis by multilocus sequence analysis (MLSA) and pathogenicity tests on cantaloupe leaflets. Catabolic profiling and MLSA based on 10 housekeeping genes and 2 hypersensitive response and pathogenicity (hrp) genes allowed us to differentiate strains isolated from cantaloupe and cucumber. Pseudomonas syringae pv. lachrymans strains isolated from cucumber clustered with genomospecies 2, and 13 P. syringae strains isolated from cantaloupe belonged to genomospecies 1. While all cantaloupe strains were closely related to P. syringae pv. aptata, they could be differentiated from this pathovar based on metabolic tests and MLSA. Pathogenicity tests showed that all strains isolated from cantaloupe and cucumber were only pathogenic on their original hosts. Based on these observations we conclude that P. syringae pv. lachrymans strains recovered from cantaloupe in China represent a novel phylotype.
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Rhee, Eugene P., und Robert E. Gerszten. „Metabolomics and Cardiovascular Biomarker Discovery“. Clinical Chemistry 58, Nr. 1 (01.01.2012): 139–47. http://dx.doi.org/10.1373/clinchem.2011.169573.
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Abstract BACKGROUND Metabolomics, the systematic analysis of low molecular weight biochemical compounds in a biological specimen, has been increasingly applied to biomarker discovery. CONTENT Because no single analytical method can accommodate the chemical diversity of the entire metabolome, various methods such as nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) have been employed, with the latter coupled to an array of separation techniques including gas and liquid chromatography. Whereas NMR can provide structural information and absolute quantification for select metabolites without the use of exogenous standards, MS tends to have much higher analytical sensitivity, enabling broader surveys of the metabolome. Both NMR and MS can be used to characterize metabolite data either in a targeted manner or in a nontargeted, pattern-recognition manner. In addition to technical considerations, careful sample selection and study design are important to minimize potential confounding influences on the metabolome, including diet, medications, and comorbitidies. To this end, metabolite profiling has been applied to human biomarker discovery in small-scale interventions, in which individuals are extremely well phenotyped and able to serve as their own biological controls, as well as in larger epidemiological cohorts. Understanding how metabolites relate to each other and to established risk markers for diseases such as diabetes and renal failure will be important in evaluating the potential value of these metabolites as clinically useful biomarkers. SUMMARY Applied to both experimental and epidemiological study designs, metabolite profiling has begun to highlight the breadth metabolic disturbances that accompany human disease. Experimental work in model systems and integration with other functional genomic approaches will be required to establish a causal link between select biomarkers and disease pathogenesis.
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Wu, Jiaojiao, Jing Gao, Weishuai Bi, Jiaojie Zhao, Xiumei Yu, Zaifeng Li, Daqun Liu, Bo Liu und Xiaodong Wang. „Genome-Wide Expression Profiling of Genes Associated with the Lr47-Mediated Wheat Resistance to Leaf Rust (Puccinia triticina)“. International Journal of Molecular Sciences 20, Nr. 18 (11.09.2019): 4498. http://dx.doi.org/10.3390/ijms20184498.
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Puccinia triticina (Pt), the causal agent of wheat leaf rust, is one of the most destructive fungal pathogens threatening global wheat cultivations. The rational utilization of leaf rust resistance (Lr) genes is still the most efficient method for the control of such diseases. The Lr47 gene introgressed from chromosome 7S of Aegilops speltoides still showed high resistance to the majority of Pt races collected in China. However, the Lr47 gene has not been cloned yet, and the regulatory network of the Lr47-mediated resistance has not been explored. In the present investigation, transcriptome analysis was applied on RNA samples from three different wheat lines (“Yecora Rojo”, “UC1037”, and “White Yecora”) carrying the Lr47 gene three days post-inoculation with the epidemic Pt race THTT. A comparison between Pt-inoculated and water-inoculated “Lr47-Yecora Rojo” lines revealed a total number of 863 upregulated (q-value < 0.05 and log2foldchange > 1) and 418 downregulated (q-value < 0.05 and log2foldchange < −1) genes. Specifically, differentially expressed genes (DEGs) located on chromosomes 7AS, 7BS, and 7DS were identified, ten of which encoded receptor-like kinases (RLKs). The expression patterns of these RLK genes were further determined by a time-scale qRT-PCR assay. Moreover, heatmaps for the expression profiles of pathogenesis-related (PR) genes and several transcription factor gene families were generated. Using a transcriptomic approach, we initially profiled the transcriptional changes associated with the Lr47-mediated resistance. The identified DEGs, particularly those genes encoding RLKs, might serve as valuable genetic resources for the improvement of wheat resistance to Pt.