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What does asthma look like for different people? ……Asthma phenotypes Thurs September 19 11.30am-12.00pm.

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Presentation on theme: "What does asthma look like for different people? ……Asthma phenotypes Thurs September 19 11.30am-12.00pm."— Presentation transcript:

1 What does asthma look like for different people? ……Asthma phenotypes Thurs September 19 11.30am-12.00pm

2 What is a phenotype ? The observable characteristics of an individual resulting from the interaction of its genotype with the environment

3 What is a phenotype ? Phenotype : observable qualities of an individual = gene X environment Clinical Phenotype : Clinically important observable qualities of an organism  Han MLK etal, AJRCCM 2010;182:598 Endotype: endogenous mechanism that underlies a phenotype  Anderson GP, Lancet 2008; 372:1107

4 Phenotypes, why bother ?

5 Australia, 1979–2006 Asthma deaths Then…….. and now…. Australian Centre for Asthma Monitoring

6 Asthma Control Oral glucocorticosteroid (lowest dose) anti-IgE antibodies as needed rapid- acting β 2 -agonist

7 People vary in how they respond to treatment Are you the average ? Or are you an Individual ? Zeiger RS et al. J Allergy Clin Immunol. 2006;117:45–52. responder Little response

8 Clinical phenotypes that don’t fit Obesity…. 50% Smoking….30% Asthma-COPD Overlap Asthma in the elderly Severe Asthma…10%

9 Older people with airway disease: age >55, multiple problems, irrespective of the diagnosis Health Status (SGRQ) by Diagnosis Health Related quality of life impairment was associated with the number of management problems identified by the MDA McDonald VM et al, Age Ageing 2011:40;42-9

10 Older person with asthma Older person with asthma Dysfunctional breathing Comorbidity Obesity Anxiety/Depres sion Inflammation Smoking AFO Exercise limitation Increased inhaler error Cognition Infection Hospitalisation Non adherence Gibson PG, McDonald VM, Marks GM. Lancet 2010; 376:803

11 Airway disease in older people Gibson PG, McDonald VM, Marks GM. Lancet 2010; 376:803 1.Multidimensional Assessment 2. Biomarkers drive Pharmacotherapy 3. Case manager

12 Ester, 87 years, ♀, Asthma Presents to clinic following admission Exacerbation of asthma and worsening depressive symptoms Background –  Asthma since age 7  Depression, AF, HT, heart failure, TIAs, Cataracts, GORD: CCI= 7 Never Smoker Exacerbation history – 4 courses of antibiotics in the past 12 months

13 Ester’s perspective ‘I get puffed so easily, I can’t walk up hills. I stop doing things because my breathing gets worse, my biggest problem is getting puffed’ ‘I feel useless’ ‘No I don’t think rehab is for me, I don’t want that. It’s too much effort, I would rather just do exercise at home. I don’t want to do the group stuff’ Ester, 87years, ♀, Asthma

14 Body Composition BMD -T scores = total body 0, hip -0.8 = normal ASMMI 5.9km/m 2 = normal Slow gait speed & unable to do 5 chair rises Pulmonary Rehab + home based resistance training 3 X week Airway Inflammation= normal No sputum, FENO 17.5ppb Maintenance ICS/LABA Systemic Inflammation= YES CRP mg/mL 18.1 Simvastatin 20mg Breathing dysfunction = YES Nijmegen 37 Breath retraining Anxiety/Depression = YES HADS (A) 8 (D) 10 Depression management – Paroxetine 20mg + counselling Frequent InfectionsSelf Management Education with WAP

15 Outcomes Baseline3 months6 months FEV11.27 (77)1.3 (81)1.12 (66) SGRQ56.324.327.4 Exacerbations4 past 12/120 past 3/120 past 6/12 6MWD257.2333.8359.1 FENO17.516.218 CRP18.14.2 Nijmegen374129 ASMMI5.9kg/m26kg/m2 BMI2224.224.3 HADS A|D8|106|44|6

16 Treatment Effects multidimensional assessment and intervention McDonald VM, Gibson PG et al. ERS 2010McDonald VM, Higgins I, Wood L, Gibson PG. Thorax 2013; 68:691

17 ‘hidden’ phenotypes genes and environment

18 Phenotype = gene X environment Gene = DNA How do you tell when it is relevant? The gene has to be doing something, And you tell that from…. RNA Protein We call that a biomarker.

19 Inflammatory phenotyping It means: Biomarker + specific treatment + = reduced exacerbations Bruselle A, Resp Med 2009 omalizumab Allergen specific IgE

20 Inflammatory phenotyping It means : Biomarker + specific treatment Anti IL5 mAb = Haldar NEJM 2009; Nair NEJM 2009

21 Exacerbation rate by phenotype McDonald V, Clin Exp Allergy 2013

22 * ABPA, SAFS Inflammatory phenotyping For Refractory Severe Asthma

23 Managing Asthma in Pregnancy Biomarker: The Protein: an enzyme, iNOS. When active it produces a gas, called Nitric oxide, or FENO That is measured in your breath

24 Powell et al, Lancet 2011 Treatment guided By symptoms Treatment guided by FeNO + symptoms 106 women With asthma 104 women With asthma Managing Asthma in Pregnancy OR

25 Powell et al, Lancet 2011 Asthma attacks were reduced By Half Managing Asthma in Pregnancy FENO guided treatment reduces attacks FeNO Symptoms

26 Powell et al, Lancet 2011 210 mothers with asthma, 214 beautiful babies What happened to them? Less babies in NICU Fewer attacks bronchiolitis Managing Asthma in Pregnancy What about the babies ? FeNO % Mattes J, Thorax 2013, in press

27 Fewer courses Of steroids Were needed For wheezing attacks Oral Corticosteroids Mattes J, Thorax 2013, in press

28 ‘hidden’ phenotypes, genes and environment Biomarker is FENO

29 ‘hidden’ phenotypes, genes and environment ‘gene chips’

30 Transcriptomics: Baines K, JACI, 2011 187 genes 24 genes 258 genes 12 3 EOSNEUTPAUCI

31 Sputum gene expression biomarkers for asthma phenotype Microarray screening approach to identify sputum biomarkers for eosinophilic, neutrophilic and paucigranulocytic asthma. Candidate biomarkers (n=35) were tested and 27 validated using qPCR in 3 studies (discovery, clinical validation, ICS response). A combination of 6 genes including CLC, CPA3, DNASE1L3, IL1B, ALPL, CXCR2, can predict asthma inflammatory phenotypes from each other and healthy controls. Eos Neut HC

32 Gene signature can predict ICS response Steroid response trial: n=71 people with asthma treated with 1000ug fluticasone per day, 28 days

33 ‘hidden’ phenotypes, genes and environment ‘gene chips’

34 Phenotypes…. Now to next ? Now: Mortality has reduced Control has improved Overdiagnosis Overtreatment People are still unwell Next : ? Cure Prevention New treatment: breakthroughs Lifestyle

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