Literature DB >> 25823891

Assessment of immune status using blood transcriptomics and potential implications for global health.

Damien Chaussabel1.   

Abstract

The immune system plays a key role in health maintenance and pathogenesis of a wide range of diseases. Leukocytes that are present in the blood convey valuable information about the status of the immune system. Blood transcriptomics, which consists in profiling blood transcript abundance on genome-wide scales, has gained in popularity over the past several years. Indeed, practicality and simplicity largely makes up for what this approach may lack in terms of cell population-level resolution. An extensive survey of the literature reveals increasingly widespread use across virtually all fields of medicine as well as across a number of different animal species, including model organisms but also animals of economical importance. Dissemination across such a wide range of disciplines holds the promise of adding a new perspective, breadth or context, to the considerable depth afforded by whole genome profiling of blood transcript abundance. Indeed, it is only through such contextualization that a truly global perspective will be gained from the use of systems approaches. Also discussed are opportunities that may arise for the fields of immunology and medicine from using blood transcriptomics as a common denominator for developing interactions and cooperation across fields of research that have traditionally been and largely remain compartmentalized. Finally, an argument is made for building immunology research capacity using blood transcriptomics platforms in low-resource and high-disease burden settings.
Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

Keywords:  Blood; Genomics; Omics; Systems immunology; Transcriptome

Mesh:

Year:  2015        PMID: 25823891     DOI: 10.1016/j.smim.2015.03.002

Source DB:  PubMed          Journal:  Semin Immunol        ISSN: 1044-5323            Impact factor:   11.130


  36 in total

1.  Gene expression analysis in peripheral blood cells of patients with hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC): identification of NRF2 pathway activation.

Authors:  Carolina Arenas Valencia; Liliana Lopez Kleine; Andres M Pinzon Velasco; Andrea Y Cardona Barreto; Clara E Arteaga Diaz
Journal:  Fam Cancer       Date:  2018-10       Impact factor: 2.375

2.  Distinct transcriptome profiles differentiate nonsteroidal anti-inflammatory drug-dependent from nonsteroidal anti-inflammatory drug-independent food-induced anaphylaxis.

Authors:  Rosa Muñoz-Cano; Mariona Pascal; Joan Bartra; Cesar Picado; Antonio Valero; Do-Kyun Kim; Stephen Brooks; Michael Ombrello; Dean D Metcalfe; Juan Rivera; Ana Olivera
Journal:  J Allergy Clin Immunol       Date:  2015-07-17       Impact factor: 10.793

3.  Blood transcriptomics identifies immune signatures indicative of infectious complications in childhood cancer patients with febrile neutropenia.

Authors:  Gabrielle M Haeusler; Alexandra L Garnham; Connie Sn Li-Wai-Suen; Julia E Clark; Franz E Babl; Zoe Allaway; Monica A Slavin; Francoise Mechinaud; Gordon K Smyth; Bob Phillips; Karin A Thursky; Marc Pellegrini; Marcel Doerflinger
Journal:  Clin Transl Immunology       Date:  2022-05-17

4.  The Immune Signatures data resource, a compendium of systems vaccinology datasets.

Authors:  Joann Diray-Arce; Helen E R Miller; Evan Henrich; Steven H Kleinstein; Mayte Suárez-Fariñas; Bram Gerritsen; Matthew P Mulè; Slim Fourati; Jeremy Gygi; Thomas Hagan; Lewis Tomalin; Dmitry Rychkov; Dmitri Kazmin; Daniel G Chawla; Hailong Meng; Patrick Dunn; John Campbell; Minnie Sarwal; John S Tsang; Ofer Levy; Bali Pulendran; Rafick Sekaly; Aris Floratos; Raphael Gottardo
Journal:  Sci Data       Date:  2022-10-20       Impact factor: 8.501

5.  Integrative multiomics analysis highlights immune-cell regulatory mechanisms and shared genetic architecture for 14 immune-associated diseases and cancer outcomes.

Authors:  Claire Prince; Ruth E Mitchell; Tom G Richardson
Journal:  Am J Hum Genet       Date:  2021-11-05       Impact factor: 11.043

6.  Blood Transcriptomics of Turbot Scophthalmus maximus: A Tool for Health Monitoring and Disease Studies.

Authors:  Paolo Ronza; José Antonio Álvarez-Dios; Diego Robledo; Ana Paula Losada; Roberto Romero; Roberto Bermúdez; Belén G Pardo; Paulino Martínez; María Isabel Quiroga
Journal:  Animals (Basel)       Date:  2021-04-30       Impact factor: 2.752

7.  Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.

Authors:  Matthew C Altman; Darawan Rinchai; Nicole Baldwin; Mohammed Toufiq; Elizabeth Whalen; Mathieu Garand; Basirudeen Syed Ahamed Kabeer; Mohamed Alfaki; Scott R Presnell; Prasong Khaenam; Aaron Ayllón-Benítez; Fleur Mougin; Patricia Thébault; Laurent Chiche; Noemie Jourde-Chiche; J Theodore Phillips; Goran Klintmalm; Anne O'Garra; Matthew Berry; Chloe Bloom; Robert J Wilkinson; Christine M Graham; Marc Lipman; Ganjana Lertmemongkolchai; Davide Bedognetti; Rodolphe Thiebaut; Farrah Kheradmand; Asuncion Mejias; Octavio Ramilo; Karolina Palucka; Virginia Pascual; Jacques Banchereau; Damien Chaussabel
Journal:  Nat Commun       Date:  2021-07-19       Impact factor: 14.919

8.  Variability of multi-omics profiles in a population-based child cohort.

Authors:  Marta Gallego-Paüls; Carles Hernández-Ferrer; Mariona Bustamante; Xavier Basagaña; Jose Barrera-Gómez; Chung-Ho E Lau; Alexandros P Siskos; Marta Vives-Usano; Carlos Ruiz-Arenas; John Wright; Remy Slama; Barbara Heude; Maribel Casas; Regina Grazuleviciene; Leda Chatzi; Eva Borràs; Eduard Sabidó; Ángel Carracedo; Xavier Estivill; Jose Urquiza; Muireann Coen; Hector C Keun; Juan R González; Martine Vrijheid; Léa Maitre
Journal:  BMC Med       Date:  2021-07-22       Impact factor: 8.775

9.  A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status.

Authors:  Victor Greiff; Pooja Bhat; Skylar C Cook; Ulrike Menzel; Wenjing Kang; Sai T Reddy
Journal:  Genome Med       Date:  2015-05-28       Impact factor: 11.117

10.  Mining the Dynamic Genome: A Method for Identifying Multiple Disease Signatures Using Quantitative RNA Expression Analysis of a Single Blood Sample.

Authors:  Samuel Chao; Changming Cheng; Choong-Chin Liew
Journal:  Microarrays (Basel)       Date:  2015-12-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.