Targeted omics and systems medicine: Personalising care

The Lancet Respiratory Medicine

Volumn 2, Issue 10, 2014, Pages 785-787

  Zhang, Huan ^a   Gustafsson, Mika ^a   Nestor, Colm ^a   Chung, Kian Fan ^b,c   Benson, Mikael ^a,d  

^a LINKÖPING UNIVERSITY   (Sweden)

^b NATIONAL HEART AND LUNG INSTITUTE   (United Kingdom)

^c ROYAL BROMPTON AND HAREFIELD NHS FOUNDATION TRUST   (United Kingdom)

^d LINKÖPING UNIVERSITY HOSPITAL   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; IMMUNOGLOBULIN E ANTIBODY; MESSENGER RNA; UNTRANSLATED RNA;

ASTHMA; BIOINFORMATICS; BIOMICS; CHRONIC OBSTRUCTIVE LUNG DISEASE; COMPUTER PROGRAM; COST EFFECTIVENESS ANALYSIS; DNA METHYLATION; DRUG COST; GENE EXPRESSION; GENE MAPPING; GENETIC TRANSCRIPTION; GENETIC VARIABILITY; HAY FEVER; HIGH RISK PATIENT; HUMAN; NONHUMAN; NOTE; PERSONALIZED MEDICINE; PROTEIN EXPRESSION; PROTEIN PROTEIN INTERACTION; RESPIRATORY TRACT DISEASE; RISK ASSESSMENT; TRANSCRIPTOMICS; GENOMICS; RESPIRATORY TRACT DISEASES;

GENOMICS; HUMANS; PRECISION MEDICINE; RESPIRATORY TRACT DISEASES;

EID: 84908024712     PISSN: 22132600     EISSN: 22132619     Source Type: Journal    
DOI: 10.1016/S2213-2600(14)70188-2     Document Type: Note

References (15)

1. Chung KF, Wenzel SE, Brozek JL, et al. International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Eur Respir J 2014, 43:343-373.
2. Chung KF New treatments for severe treatment-resistant asthma: targeting the right patient. Lancet Respir Med 2013, 1:639-652.
3. Wenzel S, Ford L, Pearlman D, et al. Dupilumab in persistent asthma with elevated eosinophil levels. N Engl J Med 2013, 368:2455-2466.
4. Nestor CE, Barrenäs F, Wang H, et al. DNA methylation changes separate allergic patients from healthy controls and may reflect altered CD4+ T-cell population structure. PLoS Genet 2014, 10:e1004059.
5. Barabási A-L, Gulbahce N, Loscalzo J Network medicine: a network-based approach to human disease. Nat Rev Genet 2011, 12:56-68.
6. Ward S, Scope A, Rafia R, et al. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: a systematic review and cost-effectiveness analysis. Health Technol Assess 2013, 17:1-302.
7. McShane LM, Cavenagh MM, Lively TG, et al. Criteria for the use of omics-based predictors in clinical trials. Nature 2013, 502:317-320.
8. Clermont G, Auffray C, Moreau Y, et al. Bridging the gap between systems biology and medicine. Genome Med 2009, 1:88.
9. Bruhn S, Fang Y, Barrenäs F, et al. A generally applicable translational strategy identifies S100A4 as a candidate gene in allergy. Sci Transl Med 2014, 6:218ra4. 218ra4.
10. Zhang H, Nestor CE, Zhao S, et al. Profiling of human CD4+ T-cell subsets identifies the TH2-specific noncoding RNA GATA3-AS1. J Allergy Clin Immunol 2013, 132:1005-1008.
11. Kabesch M Epigenetics in asthma and allergy. Curr Opin Allergy Clin Immunol 2014, 14:62-68.
12. Gustafsson M, Edstrom M, Gawel D, et al. Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment. Genome Med 2014, 6:17.
13. Wang H, Gottfries J, Barrenäs F, Benson M Identification of novel biomarkers in seasonal allergic rhinitis by combining proteomic, multivariate and pathway analysis. PLoS One 2011, 6:e23563.
14. Auffray C, Adcock IM, Chung KF, Djukanovic R, Pison C, Sterk PJ An integrative systems biology approach to understanding pulmonary diseases. Chest 2010, 137:1410-1416.
15. Mapstone M, Cheema AK, Fiandaca MS, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med 2014, 20:415-418.