Abstract
Asthma is a complex and heterogeneous disease. Various symptoms, underlying pathogenetic mechanisms, different responses to medication and prognosis are unmet need in clinic. This volume aims to elucidate how the “-omics” research applied in asthma such as “genomic, transcriptomic, proteomic, metabomic, et al” progresses and present the related series of important breakthroughs in asthma development, classification, prevention and drug sensitivity. Systemic biology, computational model and biostatistical database are discussed regarding big data storage, management and interpretation. Applying unbiased -omics combined with hypothesis-driven approach is one way to push forward our understanding of endotype of asthma and transform the current medication mode to a more précised one.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Choi H, Song WM, Zhang B. Linking childhood allergic asthma phenotypes with endotype through integrated systems biology: current evidence and research needs. Rev Environ Health. 2017;32(1-2):55–63. [PubMed: 28170342]
Ray A, Oriss TB, Wenzel SE. Emerging molecular phenotypes of asthma. Am J Physiol Lung Cell Mol Physiol. 2015;308(2):L130–40. [PubMed: 25326577]
Chung KF, Adcock IM. How variability in clinical phenotypes should guide research into disease mechanisms in asthma. Ann Am Thorac Soc. 2013;10(Suppl):S109–17. [PubMed: 24313760]
Chen R, Snyder M. Promise of personalized omics to precision medicine. Wiley Interdiscip Rev Syst Biol Med. 2013;5(1):73–82. [PubMed: 23184638]
Benson M. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment. J Intern Med. 2016;279(3):229–40. [PubMed: 26891944]
Wold B, Myers RM. Sequence census methods for functional genomics. Nat Methods. 2008;5(1):19–21. [PubMed: 18165803]
Heather JM, Chain B. The sequence of sequencers: the history of sequencing DNA. Genomics. 2016;107(1):1–8. [PubMed: 26554401]
Altelaar AF, Munoz J, Heck AJ. Next-generation proteomics: towards an integrative view of proteome dynamics. Nat Rev Genet. 2013;14(1):35–48. [PubMed: 23207911]
Xu YJ, Wang C, Ho WE, Ong CN. Recent developments and applications of metabolomics in microbiological investigations. Trends Anal Chem. 2014;56:37–48.
Ho WE, Xu YJ, Cheng C, Peh HY, Tannenbaum SR, Wong WS, et al. Metabolomics reveals inflammatory-linked pulmonary metabolic alterations in a murine model of house dust mite-induced allergic asthma. J Proteome Res. 2014;13(8):3771–82. [PubMed: 24956233]
Hindorff LA, MacArthur J, Morales J, Junkins HA, Hall PN, Klemm AK, et al.. A catalog of published genome-wide association studies [http://www.genome.gov/gwastudies]
Ober C, Yao TC. The genetics of asthma and allergic disease: a 21st century perspective. Immunol Rev. 2011;242(1):10–30. [PubMed: 21682736]
Meyers DA, Bleecker ER, Holloway JW, Holgate ST. Asthma genetics and personalised medicine. Lancet Respir Med. 2014;2(5):405–15. [PubMed: 24794577]
Bonnelykke K, Sleiman P, Nielsen K, Kreiner-Moller E, Mercader JM, Belgrave D, et al. A genome-wide association study identifies CDHR3 as a susceptibility locus for early childhood asthma with severe exacerbations. Nat Genet. 2014;46(1):51–5. [PubMed: 24241537]
Tantisira KG, Lasky-Su J, Harada M, Murphy A, Litonjua AA, Himes BE, et al. Genomewide association between GLCCI1 and response to glucocorticoid therapy in asthma. N Engl J Med. 2011;365(13):1173–83. [PubMed: 21991891]
Puente XS, Pinyol M, Quesada V, Conde L, Ordonez GR, Villamor N, et al. Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia. Nature. 2011;475(7354):101–5. [PubMed: 21642962]
Yick CY, Zwinderman AH, Kunst PW, Grunberg K, Mauad T, Dijkhuis A, et al. Transcriptome sequencing (RNA-Seq) of human endobronchial biopsies: asthma versus controls. Eur Respir J. 2013;42(3):662–70. [PubMed: 23314903]
Kumawat K, Koopmans T, Gosens R. beta-catenin as a regulator and therapeutic target for asthmatic airway remodeling. Expert Opin Ther Targets. 2014;18(9):1023–34. [PubMed: 25005144]
Xue R, Li R, Bai F. Single cell sequencing: technique, application, and future development. Sci Bull. 2015;60(1):33–42.
Kanter I, Kalisky T. Single cell transcriptomics: methods and applications. Front Oncol. 2015;5:53. [PubMed: 25806353]
Roadmap Epigenomics C, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518(7539):317–30. [PubMed: 25693563]
Laird PW. Principles and challenges of genomewide DNA methylation analysis. Nat Rev Genet. 2010;11(3):191–203. [PubMed: 20125086]
Elbehidy RM, Youssef DM, El-Shal AS, Shalaby SM, Sherbiny HS, Sherief LM, et al. MicroRNA-21 as a novel biomarker in diagnosis and response to therapy in asthmatic children. Mol Immunol. 2016;71:107–14. [PubMed: 26874829]
Midyat L, Gulen F, Karaca E, Ozkinay F, Tanac R, Demir E, et al. MicroRNA expression profiling in children with different asthma phenotypes. Pediatr Pulmonol. 2016;51(6):582–7. [PubMed: 26422695]
Cravatt BF, Simon GM, Yates JR 3rd. The biological impact of mass-spectrometry-based proteomics. Nature. 2007;450(7172):991–1000. [PubMed: 18075578]
Wu L, Han DK. Overcoming the dynamic range problem in mass spectrometry-based shotgun proteomics. Expert Rev Proteomics. 2006;3(6):611–9. [PubMed: 17181475]
van der Greef J, Hankemeier T, McBurney RN. Metabolomics-based systems biology and personalized medicine: moving towards n = 1 clinical trials? Pharmacogenomics. 2006;7(7):1087–94. [PubMed: 17054418]
Jung J, Kim SH, Lee HS, Choi GS, Jung YS, Ryu DH, et al. Serum metabolomics reveals pathways and biomarkers associated with asthma pathogenesis. Clin Exp Allergy: J Br Soc Allergy Clin Immunol. 2013;43(4):425–33. [PubMed: 23517038]
Caldeira M, Perestrelo R, Barros AS, Bilelo MJ, Morete A, Camara JS, et al. Allergic asthma exhaled breath metabolome: a challenge for comprehensive two-dimensional gas chromatography. J Chromatogr A. 2012;1254:87–97. [PubMed: 22835687]
Izquierdo-Garcia JL, Peces-Barba G, Heili S, Diaz R, Want E, Ruiz-Cabello J, NMR-based I. Metabolomic analysis of exhaled breath condensate accurate? Eur Respir J. 2011;37(2):468–70. [PubMed: 21282813]
Miller CA, Slusher LB, Vesell ES. Polymorphism of theophylline metabolism in man. J Clin Invest. 1985;75(5):1415–25. [PubMed:4039734]
Liang SQ, Chen XL, Deng JM, Wei X, Gong C, Chen ZR, et al. Beta-2 adrenergic receptor (ADRB2) gene polymorphisms and the risk of asthma: a meta-analysis of case-control studies. PLoS ONE. 2014;9(8):e104488. [PubMed: 25111792]
Wysocki K, Conley Y, Wenzel S. Epigenome variation in severe asthma. Biol Res Nur. 2015;17(3):263–9. [PubMed: 25288825]
Fernald GH, Capriotti E, Daneshjou R, Karczewski KJ, Altman RB. Bioinformatics challenges for personalized medicine. Bioinformatics. 2011;27(13):1741–8. [PubMed: 21596790]
Groom CR, Bruno IJ, Lightfoot MP, Ward SC. The Cambridge structural database. Acta Crystallogr Sect B: Struct Sci Cryst Eng Mater. 2016;72(Pt 2):171–9. [PubMed: 27048719]
Coimbatore Narayanan B, Westbrook J, Ghosh S, Petrov AI, Sweeney B, Zirbel CL, et al. The Nucleic Acid Database: new features and capabilities. Nucleic Acids Res. 2014;42(Database issue):D114–22. [PubMed: 24185695]
Lu YF, Goldstein DB, Angrist M, Cavalleri G. Personalized medicine and human genetic diversity. Cold Spring Harb Perspect Med. 2014;4(9):a008581. [PubMed: 25059740]
Ideker T, Dutkowski J, Hood L. Boosting signal-to-noise in complex biology: prior knowledge is power. Cell. 2011;144(6):860–3. [PubMed: 21414478]
Mirnezami R, Nicholson J, Darzi A. Preparing for precision medicine. N Engl J Med. 2012;366(6):489–91. [PubMed: 22256780]
Khoury MJ, Gwinn ML, Glasgow RE, Kramer BS. A population approach to precision medicine. Am J Prev Med. 2012;42(6):639–45. [PubMed: 22608383]
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Chen, Z., Wang, X. (2018). Omics Approaches: A Useful Tool in Asthma Precision Medicine. In: Wang, X., Chen, Z. (eds) Genomic Approach to Asthma. Translational Bioinformatics, vol 12. Springer, Singapore. https://doi.org/10.1007/978-981-10-8764-6_1
Download citation
DOI: https://doi.org/10.1007/978-981-10-8764-6_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8763-9
Online ISBN: 978-981-10-8764-6
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)