Relevant bibliographies by topics / Blood transcriptomics

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Blood transcriptomics'

Author: Grafiati
Published: 14 March 2023

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Journal articles on the topic "Blood transcriptomics"

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Chen-Plotkin, Alice S. "Blood transcriptomics for Parkinson disease?" Nature Reviews Neurology 14, no. 1 (December 1, 2017): 5–6. http://dx.doi.org/10.1038/nrneurol.2017.166.

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Ronza, Paolo, José Antonio Álvarez-Dios, Diego Robledo, Ana Paula Losada, Roberto Romero, Roberto Bermúdez, Belén G. Pardo, Paulino Martínez, and María Isabel Quiroga. "Blood Transcriptomics of Turbot Scophthalmus maximus: A Tool for Health Monitoring and Disease Studies." Animals 11, no. 5 (April 30, 2021): 1296. http://dx.doi.org/10.3390/ani11051296.

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Blood transcriptomics is emerging as a relevant tool to monitor the status of the immune system and assist in diagnosis, prognosis, treatment and pathogenesis studies of diseases. In fish pathology, the potential of transcriptome profiling of blood is still poorly explored. Here, RNA sequencing was applied to analyze the blood transcriptional profile of turbot (Scophthalmus maximus), the most important farmed flatfish. The study was conducted in healthy specimens and specimens parasitized by the myxozoan Enteromyxum scophthalmi, which causes one of the most devastating diseases in turbot aquaculture. The blood of healthy turbot showed a transcriptomic profile mainly related to erythrocyte gas transportation function, but also to antigen processing and presentation. In moderately infected turbot, the blood reflected a broad inhibition of the immune response. Particularly, down-regulation of the B cell receptor signaling pathway was shared with heavily parasitized fish, which showed larger transcriptomic changes, including the activation of the inflammatory response. Turbot response to enteromyxosis proved to be delayed, dysregulated and ineffective in stopping the infection. The study evinces that blood transcriptomics can contribute to a better understanding of the teleost immune system and serve as a reliable tool to investigate the physiopathological status of fish.
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Staratschek-Jox, Andrea, Sabine Classen, Andrea Gaarz, Svenja Debey-Pascher, and Joachim L. Schultze. "Blood-based transcriptomics: leukemias and beyond." Expert Review of Molecular Diagnostics 9, no. 3 (April 2009): 271–80. http://dx.doi.org/10.1586/erm.09.9.

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Zhou, Jie, Bing Liu, and Yu Lan. "When blood development meets single-cell transcriptomics." Blood Science 1, no. 1 (August 2019): 65–68. http://dx.doi.org/10.1097/bs9.0000000000000007.

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Li, Shuzhao, Andrei Todor, and Ruiyan Luo. "Blood transcriptomics and metabolomics for personalized medicine." Computational and Structural Biotechnology Journal 14 (2016): 1–7. http://dx.doi.org/10.1016/j.csbj.2015.10.005.

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Williams, Cameron Gerard, Jessica A. Engel, Megan S. F. Soon, Evan Murray, Fei Chen, and Ashraful Haque. "Studying lymphocyte differentiation in the spleen via spatial transcriptomics." Journal of Immunology 206, no. 1_Supplement (May 1, 2021): 98.55. http://dx.doi.org/10.4049/jimmunol.206.supp.98.55.

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Abstract Immune cell positioning within secondary lymphoid tissues likely affects cell-cell interaction and subsequent immune responses. Techniques such as intra-vital imaging and multiplex immunohistochemistry provide insight into this, but require specialist reagents. To examine cell-cell interactions in dense tissue at whole-genome scale, we tested the feasibility of a single-cell spatial transcriptomics method, Slide-seq2. We first confirmed using murine gut tissue that small tertiary lymphoid structures, particularly rich in B cells, could be identified and examined at a cellular level in the small intestine. We then hypothesized that microanatomical alterations could be detected. To test this, we compared mouse spleens before and 7 days after infection with blood-stage malaria parasites. To increase the molecular resolution of our data, we integrated Slide-seq2 data with high-depth, droplet-based, scRNA-seq data, generated via Chromium controller from 10× Genomics. We found that Slide-seq2 produced sufficiently rich data to map cell types from an scRNA-seq reference. Some spatially defined transcriptomes appeared to derive from mixtures of cell types, indicating that further deconvolution of spatially resolved transcriptomic data was required. Via unsupervised clustering of whole transcriptomes, we confirmed that T and B cell zones within naïve mice became less ordered at the peak of malaria infection, reflecting T and B cell interaction. Ongoing analyses aim to define novel splenic T and B cell interactions during malaria, both in extra follicular areas as well as within the germinal center.
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Dong, Ruochen, Jonathon Russell, Seth Malloy, Kate Hall, Sarah E. Smith, Hua Li, Yongfu Wang, et al. "Using Spatial Transcriptomics to Reveal Fetal Liver Hematopoietic Stem Cell-Niche Interactions." Blood 138, Supplement 1 (November 5, 2021): 3284. http://dx.doi.org/10.1182/blood-2021-153748.

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Abstract The hematopoietic stem cell (HSC) microenvironment, termed the niche, supports the proliferation, self-renewal, and differentiation abilities of HSCs. The definitive HSCs emerge from the hemogenic endothelium in the aorta-gonad-mesonephros (AGM) region after E11.5, and then migrate to the fetal liver after E12.5 for expansion. After E17.5, HSCs migrate to the bone marrow and reside in the bone marrow for the postnatal stage and adulthood. Because the fetal liver is thought to be a harbor for the rapid expansion of HSCs, numerous studies have focused on the fetal liver HSC niche in the search for novel niche factors and niche cells that support HSC expansion. However, to our knowledge, there are no successes in translating the niche factors to a clinical application for the expansion of HSCs ex vivo. In this study, we are using cutting-edge spatial transcriptomics to comprehensively study the transcriptomics and interactions between HSCs and the niche cells in the fetal liver, and in search of the niche cells and factors for HSC expansion. To understand the spatial distribution and interactions between HSCs and niche cells in the fetal liver, we introduced 2 spatial transcriptomic methods, slide-seq, and 10x Visium, in our study on E14.5 mouse fetal liver. By integrating with a parallel single-cell sequencing analysis, we revealed the spatial transcriptomics of HSCs and potential niche cells, including hepatoblasts, endothelium cells, macrophages, megakaryocytes, and hepatic stellate cells/perivascular mesenchymal cells (PMCs) in E14.5 mouse fetal liver. Interestingly, we found that the PMCs were characterized by enriched N-cadherin expression. Both slide-seq and 10x Visium showed that the N-cadherin-expressing PMCs are enriched in the portal vessel area. Importantly, the majority of fetal liver HSCs are in close proximity to N-cadherin-expressing PMCs, indicating a supportive role of N-cadherin-expressing PMCs in HSC maintenance. Subsequent CellPhoneDB (CPDB) analysis demonstrated that the N-cadherin-expressing PMCs are major niche-signaling senders with an enriched expression of niche factors, such as CXCL12 and KITL, and stemness pathway-related ligands, such as IGF1, IGF2, TGFβ2, TGFβ3, JAG2, and DLK1, indicating N-cadherin-expressing PMCs could be the major niche cells in supporting HSCs in the fetal liver. This finding was consistent with our previous finding that N-cadherin-expressing bone and marrow stromal progenitor cells can maintain reserve HSCs in the adult bone marrow. Moreover, CPDB analysis indicated that other potential niche cells, such as endothelium cells, macrophages, and megakaryocytes, may support HSCs in different signal transduction pathways. For example, endothelium cells have an enriched expression of KITL, IGF2, DLL1, TGFβ1, and TGFβ2; macrophages have enriched expression of KITL, IFNγ, and TGFβ1; megakaryocytes have enriched expression of PF4, JAG2 and TGFβ1. Intriguingly, our previous studies showed that megakaryocytes could promote HSC expansion under stress conditions in the bone marrow. To investigate the potential role of N-cadherin-expressing cells in supporting fetal liver HSCs, we generated an N-cad CreER;Cxcl12 and an N-cad CreER;Scf mouse model to conditionally knockout the well-studied niche factors, CXCL12 and SCF, in N-cadherin-expressing cells. Conditional knockout of either Cxcl12 or Scf in N-cadherin-expressing cells resulted in an increase in the number of HSCs. Moreover, conditional knockout of Cxcxl12 in N-cadherin-expressing cells also resulted in a myeloid-biased differentiation. We postulate that the knockout of Cxcl12 or Scf in N-cadherin-expressing cells leads to the migration of HSCs towards other potential niche cells, such as macrophages and megakaryocytes, which may induce HSC expansion and biased differentiation. In summary, by using cutting-edge spatial transcriptomics, we revealed a comprehensive spatial transcriptomics of HSCs and niche cells in E14.5 mouse fetal liver. The N-cadherin-expressing cells in the fetal liver is a major niche in maintaining HSCs, while other potential niches may be responsible for the expansion of HSCs. In the future, we will use multiple approaches, such as spatial transcriptomics and fluorescence in situ hybridization (FISH), to verify the distribution changes of HSCs in N-cad CreER;Cxcl12 mouse, and to reveal the niches in support of the expansion of HSCs. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
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Pantaleo, Ester, Alfonso Monaco, Nicola Amoroso, Angela Lombardi, Loredana Bellantuono, Daniele Urso, Claudio Lo Lo Giudice, et al. "A Machine Learning Approach to Parkinson’s Disease Blood Transcriptomics." Genes 13, no. 5 (April 21, 2022): 727. http://dx.doi.org/10.3390/genes13050727.

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The increased incidence and the significant health burden associated with Parkinson’s disease (PD) have stimulated substantial research efforts towards the identification of effective treatments and diagnostic procedures. Despite technological advancements, a cure is still not available and PD is often diagnosed a long time after onset when irreversible damage has already occurred. Blood transcriptomics represents a potentially disruptive technology for the early diagnosis of PD. We used transcriptome data from the PPMI study, a large cohort study with early PD subjects and age matched controls (HC), to perform the classification of PD vs HC in around 550 samples. Using a nested feature selection procedure based on Random Forests and XGBoost we reached an AUC of 72% and found 493 candidate genes. We further discussed the importance of the selected genes through a functional analysis based on GOs and KEGG pathways.
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GRIGORYEV, D., T. WATKINS, L. GAO, A. GRANT, M. STOCKTONPORTER, H. WATSON, R. MATHIAS, M. GITTENS, C. CHEADLE, and K. BARNES. "Transcriptomics of Peripheral Blood from Asthmatics Living in Barbados." Journal of Allergy and Clinical Immunology 121, no. 2 (February 2008): S259. http://dx.doi.org/10.1016/j.jaci.2007.12.1027.

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Blanchard, E. M., S. Domhan, L. Ma, C. Schwager, S. Ambika, L. A. Martin, J. Debus, P. J. Hesketh, L. Hlatky, and A. Abdollahi. "Peripheral blood transcriptomics-based molecular predictors of breast cancer." Journal of Clinical Oncology 28, no. 15_suppl (May 20, 2010): e21018-e21018. http://dx.doi.org/10.1200/jco.2010.28.15_suppl.e21018.

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Dissertations / Theses on the topic "Blood transcriptomics"

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Krishnan, Unni. "Novel coronary atherothrombosis genes identified by blood cell transcriptomics." Thesis, University of Leicester, 2013. http://hdl.handle.net/2381/28136.

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Rationale: Coronary artery disease (CAD) is a complex phenotype with multiple genetic and environmental risk factors. The circulating monocyte plays a key role in CAD and contributes to atherogenesis, plaque progression and atherothrombosis, especially through its interactions with platelets. This study tested the hypothesis that gene expression profiling of monocytes in a resting state, and following platelet-mediated stimulation would identify novel molecules that may determine the inherited risk of CAD. Methods: Four groups of subjects were recruited: patients with a premature MI (PMI) <65 years (n=19) and age/gender matched healthy controls (n=19), healthy young men with a strong family history of PMI (n=22) and matched controls with no significant family history of CAD (n=17). Monocyte RNA was extracted before and after platelet-mediated stimulation (for 4 hours) from all subjects for whole genome microarray analysis. Differentially expressed genes were validated by QPCR and those genes with similar trends in expression in the PMI patients and the healthy young men with a family history of PMI were selected for further analysis. These were tested in silico in CARDIoGRAM, a large scale genome wide association study (GWAS) to identify genetic variants that showed either strong associations with CAD or with gene expression in monocytes (expression quantitative trait locus - eQTL). Results: This work revealed similar trends in differential expression of specific monocyte genes between PMI patients and healthy men with a strong genetic risk of PMI compared with their respective healthy controls. These include genes implicated in lipid metabolism (ACAD10), sterol transport (CYP27A1, ARV1) and inflammation (CCL3, EGR1). Of these, ACAD10 and CYP27A1 were the genes which were most statistically significant. In the follow-up analysis of these genes, a genetic variant (rs2238151) in ACAD10 showed a significant association with risk of CAD (risk allele frequency (RAF): 0.63, OR: 1.08, corrected p: 5.85x10[superscript -6]) and MI (RAF: 0.57, OR: 1.09, corrected p: 6.24x10[superscript -6]) in the CARDIoGRAM GWAS meta-analysis and a variant in CYP27A1 (rs933994) was noted to be an eQTL for CYP27A1 expression in monocytes (p=2.9x10[superscript-70]). Conclusions: Gene expression profiling in resting and stimulated monocytes from subjects with premature CAD and those with an increased genetic risk of CAD have revealed novel gene variants which associate with susceptibility to CAD.
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Marin, Sergio. "An examination of peripheral blood to reflect transcriptomic adaptation to physical exercise training in sedentary men compared with sex-matched athletic phenotypes." Thesis, Federation University Australia, 2021. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/182594.

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There is renewed interest in exercise genomics that peripheral blood RNA expression may be important to understand exercise mediated adaptations to exercise. However, there is little direct supporting evidence. Therefore, this thesis involved two studies to examine the relationship between RNA expression and exercise, and two experimental studies to examine relationships and adaptive response of peripheral blood RNA in sedentary compared with athletic phenotypes. In the first two studies, we conducted both meta-analysis and network meta-analysis to examine current randomised controlled trial (RCT) evidence to determine current best evidence on the link between RNA expression and athletic phenotype in addition to head-to-head comparison of different exercise types to induce differential expression of RNA transcripts in sedentary compared with athletic phenotypes. We observed that current available body of RCTs in peripheral blood exercise genomics presents too large heterogeneity in study design, methodological and data reporting aspects. Thus, we concluded that peripheral blood cannot be established as a valid source for identifying, neither the effect of physical exercise training on transcriptomic markers nor the distinction of divergent transcriptomic profiles in response to different exercise modalities. In the third and fourth studies, we aimed to determine whether peripheral blood RNA and circular RNA (circRNA) expression was different between sedentary and athletic phenotypes, and whether these transcripts were consistent in response to exercise training in exercise-naïve men. To achieve this, we conducted two STROBE compliant observational experiments of n=71 participants with distinct athletic phenotypes. We concluded that peripheral blood transcriptome expression might allow for identification of divergent athletic phenotypes, although this is not supported by further examination of peripheral blood RNA expression levels in response to an exercise training intervention. The sum of works presented in this thesis does not agree with many propositions relating to the strength of evidence in peripheral blood transcriptomics literature. This is principally due to the heterogeneity and lack of consistency of research in this field which is currently insufficient to provide any strong conclusions. In conclusion, peripheral blood RNA and circRNA do not yet offer useful avenues to predict the adaptive response to different exercise types in athletic and non-athletic men.
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Stöber, Regina [Verfasser], Jan Georg [Akademischer Betreuer] Hengstler, and Frank [Gutachter] Wehner. "Transcriptomics-based prediction of human hepatotoxic blood concentrations of chemicals / Regina Stöber. Betreuer: Jan Georg Hengstler. Gutachter: Frank Wehner." Dortmund : Universitätsbibliothek Dortmund, 2016. http://d-nb.info/1112347623/34.

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Lansink, Lianne Ida Maria. "Blood-stage Plasmodium parasite control by antibody-mediated inhibition and impaired maturation in response to host inflammation in vivo." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/228523/1/Lianne%20Ida%20Maria_Lansink_Thesis.pdf.

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This thesis examined the molecular mechanisms that are at the basis of parasite-host interactions during malaria infection, specifically focussing on antibody function and interactions during inflammation. Plasmodium parasites were recently discovered to grow slower during acute infection. This project built on that evidence and identified a role for inflammation as well as detected an initial response by the parasite to inflammation.
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Boileau, Adeline. "Biomarqueurs transcriptomiques sanguins des maladies cardiovasculaires." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0186/document.

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Les maladies cardiovasculaires (MCV) représentent la première cause de mortalité dans le Monde et en Europe. Le diagnostic et la prédiction de l’évolution des MCV reposent actuellement sur l’utilisation de biomarqueurs protéiques, mais doivent être améliorés pour optimiser la prise en charge des patients. Le transcriptome sanguin comprend l’ensemble des molécules ARN circulantes, qui sont présentes dans les cellules sanguines et libres dans le sang. Parmi elles, les ARN messagers (ARNm) codent pour des protéines alors que de petits ARN non codants, les microARNs (miARNs), répriment l’expression de leurs gènes cibles. Nous avons émis l’hypothèse que le transcriptome sanguin, et en particulier les ARNm et les miARNs, avaient un potentiel de biomarqueur, diagnostique ou pronostique, dans les MCV. En premier lieu, nous avons montré que l’héparine endogène pouvait induire une inhibition de la transcription inverse couplée à la PCR quantitative lors de la mesure des miARNs circulants et que ce paramètre devait être pris en compte lors de l’étude du transcriptome sanguin. Nous avons ensuite montré que 3 transcrits (codants pour les gènes LMNB1, LTBP4, TGFBR1) exprimés dans le sang total, étaient des prédicteurs indépendants de l’altération de la fonction cardiaque à 4 mois post-IM. De plus, l’ajout de ces 3 transcrits dans un modèle de prédiction contenant des variables cliniques augmente la valeur prédictive de ce modèle. Dans une troisième étude, nous avons montré que les niveaux circulants de miR-574-5p étaient capables de discriminer les patients porteurs d’un AAT des personnes saines. De plus, le miR-574-5p est encapsulé dans des vésicules extracellulaires dans le sang, suggérant un rôle paracrine. Au cours des quatrième et cinquième études, nous avons montré que les niveaux circulants de miR-122-5p étaient des prédicteurs indépendants de l’évolution neurologique et de la survie à moyen terme post-AC, et capable d’améliorer les modèles de prédiction existants. Nous avons également identifié le miR-574-5p comme prédicteur indépendant de l’évolution neurologique post-AC, spécifiquement chez les femmes. En conclusion, ce travail de thèse a permis la découverte ou la confirmation de la valeur de biomarqueurs potentiels de transcrits et miARNs dans différentes MCV. Cependant, leur capacité de biomarqueur devra être validée dans d’autres études à grande échelle et à l’aide d’autres techniques avant d’envisager leur utilisation en clinique
Cardiovascular disease (CVD) is the main cause of mortality in the World and in Europe. Diagnosis and prediction of outcome of CVD currently rely on the use of protein biomarkers, but should be improved to optimize patient healthcare. Blood transcriptome contains all RNA molecules present in blood cells and in the acellular compartment. Among them, messenger RNA (mRNA) code for proteins whereas small non coding RNA, microRNA (miRNA), have a regulatory function by repressing the expression of their target genes. We hypothesized that blood transcriptome, mRNA and miRNA in particular, had a potential as biomarker, diagnostic or prognostic, in CVD. In a first study, we showed that endogenous heparin could lead to an inhibition of reverse transcription and quantitative PCR reaction used to measure miRNAs expressed in the blood, and that this parameter should be considered for studies on blood transcriptome. Secondly, we showed that 3 transcripts (coding for genes LMNB1, LTBP4, TGFBR1) expressed in whole blood, were independent predictors of cardiac function alteration at 4 months post-MI. Furthermore, the inclusion of these 3 transcripts in a prediction model containing clinical variables had an incremental predictive value. In a third study, we showed that circulating levels of miR-574-5p were able to discriminate patients with TAA from healthy controls. Furthermore, miR-574-5p was encapsulated in extracellular vesicles in the blood, suggesting a paracrine role. In the fourth and fifth studies, we showed that circulating levels of miR-122-5p were independent predictors of neurological outcome and survival at middle term post-CA, and were able to increase the prediction value of existing models. We also identified miR-574-5p as an independent predictor of neurological outcome post-CA, specifically in women. To conclude, this work allowed the discovery or the confirmation of the potential biomarker value of transcripts and miRNAs in different CVD. However, their biomarker value should be validated in other large scale studies and with other methods of measurement before foreseeing their clinical utilization
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Mok, Bobo. "Genomic and transcriptomic variation in blood stage Plasmodium falciparum /." Stockholm : Karolinska institutet, 2007. http://diss.kib.ki.se/2007/978-91-7357-291-0/.

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Braga, D. "TRANSCRIPTOMIC ANALYSIS IN SEPTIC SHOCK PATIENTS." Doctoral thesis, Università degli Studi di Milano, 2017. http://hdl.handle.net/2434/473670.

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Introduction Septic shock, also defined as distributive shock, is a complication of sepsis, characterized by pronounced hypotension, followed by anomalous distribution of blood at vessels, organs and tissues. The hemodynamic, cellular and metabolic alterations described in septic shock patients lead to a mortality that is at present around 40%. Septic shock patients develop dysfunctions or failure to multiple organs (MOF) but the molecular mechanisms triggering tissue injury remain largely undetermined and a specific treatment for septic shock is still not available. Aim This work is part of the European Project ShockOmics, a multicentric, prospective, observational study, whose aim is to identify with a multiscale approach, molecular biomarkers in septic shock patients who develop acute heart failure. The specific aim of the present Research project is to investigate the modifications induced by septic shock on transcriptional profile, using blood cells as RNA source. This investigation is performed at different timepoints starting from admission of the patient to the intensive care unit (ICU). Materials and Methods Septic shock patients were recruited in the ICUs of Geneva and Bruxelles University Hospitals, that are Partners of ShockOmics Project. Blood samples were collected in the acute phase of the disease at ICU admission (T1), after the appropriate pharmacological intervention (T2 ) and at steady state on day 7 of the ICU stay (T3). RNA was extracted from whole blood and RNA sequencing was used to evaluate the expression level of genes, long non coding RNAs and microRNAs. We explored the dataset using PCA and unsupervised hierarchical clustering and we identified differentially expressed genes and microRNAs across conditions. Gene Ontology analysis was used to identify relevant biological processes involved in shock. We identified microRNA regulatory targets with an in silico target prediction. Results We identified two main gene expression profiles corresponding to the acute phase of shock and to the condition of steady state. Between the acute phase of shock (day 1) and the steady state condition (day 7) we observed in patients at day 7 a downregulation of pathways of the innate immune response (Toll-like receptor and C-type lectin receptors pathways) and of acute inflammation (IL-1 receptor family and alarmins) and the upregulation in the same patients of genes of the adaptive immunity related to B and T lymphocytes activation. A transcriptional regulation was observed also for genes with antimicrobial function and protease activity and for genes involved in carbohydrate metabolism, lipid inflammatory pathway, transport of vesicles and protein synthesis. miR-125a-5p and miR-150-5p, with a predicted regulatory role in the MAPK pathway, and miR-193a-3p were differentially expressed in the acute and steady state condition. Conclusion We observed a significant modulation of multiple classes of genes involved in defense response to pathogens, immunity, inflammation and metabolism. From these results it appears that in septic shock a relevant change in the transcriptomic profile of blood cells is induced, in order to counteract the pathogens and as a consequence of the hemodynamic changes underlying the circulatory failure. The transcriptomic profile of septic shock patients showed inter patient variability reflecting the complexity of the shock condition and of the individual response to treatment. Specific signatures could turn out by combining clinical data and expression profile and could be used to better classify septic shock patients.
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Ballantine, Lucy Elizabeth. "Transcriptomic analysis of peripheral blood monocytes and synovial macrophages in inflammatory arthritis." Thesis, University of Glasgow, 2011. http://theses.gla.ac.uk/2825/.

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Background: Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are two distinct forms of chronic auto-immunity; understanding the transcriptomic profiles of key leukocyte subsets implicated in these arthritides could improve the diagnosis and treatment of patients. Current microarray analyses of samples derived from RA and PsA patients have examined the genetic profiles of whole blood or diseased tissue which, although informative, can mask the genetic contributions of individual cell types. Monocytes and macrophages are a cellular subset known to play a major role in PsA and RA through the production of pro-inflammatory chemokines, cytokines and destructive proteinases. Aim: To define the transcriptome in CD14+ cells separated from the blood and synovial fluid of PsA and RA patients, and to then compare and contrast that signature in health and disease. Thereafter to define the relevant activities of selected novel moieties described in the foregoing analysis. Methods & Results: The transcriptomic profiles of healthy, RA and PsA CD14+ blood cells were remarkably similar - few genes could distinguish diseased from healthy CD14+ cells. Comparison of the genetic signature of the RA and PsA synovial fluid CD14+ cells revealed that just over 50% of the differentially expressed genes were shared between the two disease groups. Furthermore, analysing the canonical pathways in the synovial fluid cells compared to the matched peripheral blood of both patient groups surprisingly revealed Liver X receptor (LXR) activation pathway as the most significantly upregulated pathway: this pathway has been previously shown by our group to play a pro-inflammatory role in arthritis. Examination of specific upregulated mRNAs in the synovial fluid CD14+ cells from both disease types revealed two novel genes that had not previously been associated with arthritis, the lysosomal enzyme legumain and the cell surface molecule plexin A1. Legumain was demonstrated to be present in RA and PsA CD14+ cells by RNA and protein analysis and was physiologically active. Incubation of CD14+ cells with patient synovial fluid under hypoxic conditions also potentiated legumain expression. Plexin A1 was confirmed to be expressed at the mRNA level within RA synovium. siRNA knockdown of plexin A1 suggested that it may play a pro-inflammatory role within macrophages since subsequent treatment of these macrophages with LPS resulted in decreased TNFα production. However, investigations into the identity of the specific ligands for plexin A1 in arthritis, known as semaphorins, were inconclusive. I finally generated microarray data to evaluate the transcriptome of macrophages activated via cel contact with activated T cells. Such cells shared only a small percentage of genes with those dysregulated in the RA and PsA synovial fluid derived CD14+ cells suggesting that this model at the time points chosen may not be an appropriate in vitro representation of articular macrophages. An imaging system of this in vitro model was also established to visualise the dynamic nature of the T cell – macrophage interactions and demonstrated that variables such as duration or method of T cell activation could alter the number and duration of interactions between the two cell types. Conclusions: These studies demonstrate that the CD14+ cells isolated from the blood are similar transcriptomically between healthy controls and RA and PsA patients. The synovial fluid CD14+ cells from RA and PsA patients exhibit substantial overlap in terms of their genetic profile. Two novel molecules expressed by diseased patients namely plexin A1 and legumain have been identified and their preliminary characteristics in the context of synovitis have been defined.
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Eckold, C. "The effects of co-morbidities on blood transcriptomes in tuberculosis patients before and during treatment." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2018. http://researchonline.lshtm.ac.uk/4648205/.

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The blood transcriptome in tuberculosis (TB) has been well described, it is distinct from healthy controls and other diseases, and is being developed as a biomarker for risk of disease progression, disease severity and treatment response. But TB patients, especially those from high TB-burden countries, often have comorbidities, so the described transcriptomic signature may not be an accurate representation of a typical population. Whether this signature remains constant in different patient phenotypes is an important question. The effect of HIV-1 and also type 2 diabetes (T2DM) on the transcriptomic profile of TB was investigated, using microarray and RNA-seq technology, respectively. Both comorbidities increase the risk of developing active TB, but the underlying mechanism in T2DM is unknown. The potentially beneficial effects of the anti-diabetes drug metformin, on the transcriptome of healthy donors, were also investigated, as existing reports indicate it could behave as an adjuvant for TB therapy. The effect on the TB blood transcriptome signature of HIV-1 coinfection was studied in collaboration with the PanACEA consortium, and T2DM (HbA1c > 6:5) and prediabetes (HbA1c > 5:7 & < 6:5) in the TANDEM consortium. It was found that the TB treatment response transcriptomic signatures could still be observed with HIV-1 coinfection. Both T2DM and pre-diabetes affected the blood transcriptome: increased in ammatory profile with down-regulated type I interferon response genes. This could be indicative of an enhanced immunopathological response in TB/DM and of the important role of type I interferons in susceptibility to TB. Because patients with pre-diabetes had similar transcriptomes to TB/DM, albeit of lower magnitude, it shows that even at intermediate levels of hyperglycaemia there is an immune dysfunction. Metformin had an anti-in ammatory effect in healthy donors in the context of M. tuberculosis stimulation, indicating its potentially beneficial role in TB/DM treatment.
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Amnebrink, Dennis. "Transcriptomic profiling of marine bacteria between development and senescence phases of a phytoplankton bloom." Thesis, Linnéuniversitetet, Institutionen för biologi och miljö (BOM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-79200.

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Bacterioplankton provide important ecosystem functions by carrying out biogeochemical cycling of organic matter. Playing an important role in the microbial loop they help remineralize carbon and nutrients. Bacteria also interact with phytoplankton during phytoplankton blooms. However, fundamental understanding on the underlying molecular mechanisms involved in the degradation of phytoplankton-derived organic matter is still in its infancy. Therefore, we analysed data from a mesocosm experiment following a natural phytoplankton-bloom from an upwelling system in the North- East Atlantic Ocean. The purpose was to contribute a mechanistic understanding based on functional gene expression analysis of natural microbial assemblages. Our results show the difference in functional gene expression within a bacterial metacommunity and how this functional response drastically switches between bloom build up and senescence. Transcripts showed a broad change in gene expression involving major SEED categories, with the bloom senescence phase exhibiting a higher relative abundance in major categories such as Carbohydrates, Protein Metabolism and Amino Acids and Derivatives. Within these categories genes connected to carbon utilization and transport systems (Ton and Tol) as well as chemotaxis showed a higher abundance during bloom senescence. The change in functionality based on transcripts showed a different bacterial community composition appearing over a very short time. We thus conclude that the bacterial functional gene expression response between build-up and degradation bloom phases is remarkably different and associated with a change in the identity of bacteria with active expression. Our findings highlight the importance of bacterial substrate specialists with different functional roles during different time points of phytoplankton blooms.
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Book chapters on the topic "Blood transcriptomics"

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Warnat-Herresthal, Stefanie, Marie Oestreich, Joachim L. Schultze, and Matthias Becker. "Artificial Intelligence in Blood Transcriptomics." In Artificial Intelligence in Medicine, 1109–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-64573-1_262.

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Parnell, Grant P., and David R. Booth. "Whole Blood Transcriptomic Analysis to Identify Clinical Biomarkers of Drug Response." In Methods in Molecular Biology, 35–43. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0956-8_3.

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Solomon, Brad, and Carl Kingsford. "Improved Search of Large Transcriptomic Sequencing Databases Using Split Sequence Bloom Trees." In Lecture Notes in Computer Science, 257–71. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56970-3_16.

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Farid, A. H., S. S. Moore, and U. Basu. "The assembly of the mink blood transcriptoms generated by the next generation sequencing using the dog genome." In Proceedings of the Xth International Scientific Congress in fur animal production, 490. Wageningen: Wageningen Academic Publishers, 2012. http://dx.doi.org/10.3920/978-90-8686-760-8_80.

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Rinchai, Darawan, Davide Bedognetti, and Darawan Chaussabel. "Blood Transcriptomic Approaches to Cancer Immunotherapy." In Cancer Immunotherapy Principles and Practice. 2nd ed. New York, NY: Springer Publishing Company, 2021. http://dx.doi.org/10.1891/9780826137432.0043.

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Rockett, John. "Blood-Derived Transcriptomic Profiles as a Means to Monitor Levels of Toxicant Exposure and the Effects of Toxicants on Inaccessible Target Tissues." In Surrogate Tissue Analysis, 65–76. Informa Healthcare, 2005. http://dx.doi.org/10.1201/9781420038095.ch5.

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Nahar, Jesmin, Kevin S. Tickle, and A. B. M. Shawkat Ali. "Pattern Discovery from Biological Data." In Dynamic and Advanced Data Mining for Progressing Technological Development, 168–223. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-908-3.ch009.

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Extracting useful information from structured and unstructured biological data is crucial in the health industry. Some examples include medical practitioner’s need to identify breast cancer patient in the early stage, estimate survival time of a heart disease patient, or recognize uncommon disease characteristics which suddenly appear. Currently there is an explosion in biological data available in the data bases. But information extraction and true open access to data are require time to resolve issues such as ethical clearance. The emergence of novel IT technologies allows health practitioners to facilitate the comprehensive analyses of medical images, genomes, transcriptomes, and proteomes in health and disease. The information that is extracted from such technologies may soon exert a dramatic change in the pace of medical research and impact considerably on the care of patients. The current research will review the existing technologies being used in heart and cancer research. Finally this research will provide some possible solutions to overcome the limitations of existing technologies. In summary the primary objective of this research is to investigate how existing modern machine learning techniques (with their strength and limitations) are being used in the indent of heartbeat related disease and the early detection of cancer in patients. After an extensive literature review these are the objectives chosen: to develop a new approach to find the association between diseases such as high blood pressure, stroke and heartbeat, to propose an improved feature selection method to analyze huge images and microarray databases for machine learning algorithms in cancer research, to find an automatic distance function selection method for clustering tasks, to discover the most significant risk factors for specific cancers, and to determine the preventive factors for specific cancers that are aligned with the most significant risk factors. Therefore we propose a research plan to attain these objectives within this chapter. The possible solutions of the above objectives are: new heartbeat identification techniques show promising association with the heartbeat patterns and diseases, sensitivity based feature selection methods will be applied to early cancer patient classification, meta learning approaches will be adopted in clustering algorithms to select an automatic distance function, and Apriori algorithm will be applied to discover the significant risks and preventive factors for specific cancers. We expect this research will add significant contributions to the medical professional to enable more accurate diagnosis and better patient care. It will also contribute in other area such as biomedical modeling, medical image analysis and early diseases warning.
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Nahar, Jesmin, Kevin S. Tickle, and A. B. M. Shawkat Ali. "Pattern Discovery from Biological Data." In Machine Learning, 724–68. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch403.

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Extracting useful information from structured and unstructured biological data is crucial in the health industry. Some examples include medical practitioner’s need to identify breast cancer patient in the early stage, estimate survival time of a heart disease patient, or recognize uncommon disease characteristics which suddenly appear. Currently there is an explosion in biological data available in the data bases. But information extraction and true open access to data are require time to resolve issues such as ethical clearance. The emergence of novel IT technologies allows health practitioners to facilitate the comprehensive analyses of medical images, genomes, transcriptomes, and proteomes in health and disease. The information that is extracted from such technologies may soon exert a dramatic change in the pace of medical research and impact considerably on the care of patients. The current research will review the existing technologies being used in heart and cancer research. Finally this research will provide some possible solutions to overcome the limitations of existing technologies. In summary the primary objective of this research is to investigate how existing modern machine learning techniques (with their strength and limitations) are being used in the indent of heartbeat related disease and the early detection of cancer in patients. After an extensive literature review these are the objectives chosen: to develop a new approach to find the association between diseases such as high blood pressure, stroke and heartbeat, to propose an improved feature selection method to analyze huge images and microarray databases for machine learning algorithms in cancer research, to find an automatic distance function selection method for clustering tasks, to discover the most significant risk factors for specific cancers, and to determine the preventive factors for specific cancers that are aligned with the most significant risk factors. Therefore we propose a research plan to attain these objectives within this chapter. The possible solutions of the above objectives are: new heartbeat identification techniques show promising association with the heartbeat patterns and diseases, sensitivity based feature selection methods will be applied to early cancer patient classification, meta learning approaches will be adopted in clustering algorithms to select an automatic distance function, and Apriori algorithm will be applied to discover the significant risks and preventive factors for specific cancers. We expect this research will add significant contributions to the medical professional to enable more accurate diagnosis and better patient care. It will also contribute in other area such as biomedical modeling, medical image analysis and early diseases warning.
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Conference papers on the topic "Blood transcriptomics"

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Todorova, VK, ML Beggs, IB Dhakal, LJ Hennings, I. Makhoul, and VS Klimberg. "P5-20-05: Peripheral Blood Transcriptomics and Doxorubicin Cardiotoxicity." In Abstracts: Thirty-Fourth Annual CTRC‐AACR San Antonio Breast Cancer Symposium‐‐ Dec 6‐10, 2011; San Antonio, TX. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/0008-5472.sabcs11-p5-20-05.

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Cesaroni, Matteo, Jessica Schreiter, Loqmane Seridi, Jarrat Jordan, Marc Chevrier, Nando Bansal, Theresa Pattery, and Jorge Villacian. "AB0499 FINGERSTICK BLOOD TRANSCRIPTOMICS: A PATIENT-CENTRIC APPROACH TO ENABLE PRECISION MEDICINE?" In Annual European Congress of Rheumatology, EULAR 2019, Madrid, 12–15 June 2019. BMJ Publishing Group Ltd and European League Against Rheumatism, 2019. http://dx.doi.org/10.1136/annrheumdis-2019-eular.4834.

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Grigoryev, Dmitry N., Stephen C. Mathai, Tonya Watkins, Chris Cheadle, Laura Hummers, Fredrick M. Wigley, Roger A. Johns, Kathleen C. Barnes, and Paul M. Hassoun. "Effect Of Pulmonary Arterial Hypertension On Transcriptomics Of Peripheral Blood Mononuclear Cells." In American Thoracic Society 2010 International Conference, May 14-19, 2010 • New Orleans. American Thoracic Society, 2010. http://dx.doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a4878.

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Jiang, Y., O. Gruzieva, T. Wang, E. Forno, N. Boutaoui, T. Sun, E. Acosta-Pérez, et al. "Transcriptomics of Atopy and Atopic Asthma in White Blood Cells from Children and Adolescents." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a1058.

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Faner Canet, Maria Rosa, Jarrett Morrow, Guillaume Noell, Alejandra Lopez-Giraldo, Tamara Cruz, Ruth Tal-Singer, Bruce E. Miller, et al. "LATE-BREAKING ABSTRACT: Network-based meta-analysis of lung, sputum and blood transcriptomics in COPD." In ERS International Congress 2016 abstracts. European Respiratory Society, 2016. http://dx.doi.org/10.1183/13993003.congress-2016.oa1776.

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Lu, R., R. Suryadevara, Z. Xu, D. Jain, A. Gregory, B. D. Hobbs, N. Lichtblau, et al. "Comparison of Lung and Blood Transcriptomics Reveals Shared Emphysema-Associated Pathways and Alternatively Spliced Genes." In American Thoracic Society 2022 International Conference, May 13-18, 2022 - San Francisco, CA. American Thoracic Society, 2022. http://dx.doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a3479.

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Singh, Dave, John H. Riley, Steve Fox, Ruth Tal-Singer, Hana Muellerova, and Bartolome Celli. "Prediction Of A COPD Exacerbation Phenotype Using Blood Transcriptomic Markers." In American Thoracic Society 2011 International Conference, May 13-18, 2011 • Denver Colorado. American Thoracic Society, 2011. http://dx.doi.org/10.1164/ajrccm-conference.2011.183.1_meetingabstracts.a2254.

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Nikolopoulos, D., A. Filia, K. Katsiki, T. Manolakou, A. Pieta, N. Kapsala, G. Bertsias, A. Fanouriakis, and D. Boumpas. "PO.1.8 Distinct transcriptomic signature of peripheral blood in neuropsychiatric lupus." In 13th European Lupus Meeting, Stockholm (October 5–8, 2022). Lupus Foundation of America, 2022. http://dx.doi.org/10.1136/lupus-2022-elm2022.42.

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Zeng, C., G. C. Motta Ribeiro, T. Hinoshita, M. A. Lessa, C. Kosour, K. Grogg, J. Hutchinson, R. M. Baron, T. Winkler, and M. F. Vidal Melo. "One-Lung Ventilation Causes Blood Transcriptomic Changes in Intact and Endotoxemic Sheep." In American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a4104.

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Castaldi, P. "Blood Transcriptomic and Proteomic Biomarkers of Electronic Nicotine Delivery Systems Use in the COPDGene Study." In American Thoracic Society 2021 International Conference, May 14-19, 2021 - San Diego, CA. American Thoracic Society, 2021. http://dx.doi.org/10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3097.

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