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. Asthma deaths Then…….. and now….
Australia, 1979–2006
Figure 4.1: Deaths due to asthma per 100,000 population, 3-year moving average, by sex, all ages and people aged 5–34 years, 1979–2006
Note: Age-standardised to the Australian population as at 30 June Asthma classified according to International Statistical Classification of Diseases, 9th Revision (ICD-9) code 493 and 10th Revision (ICD-10) codes J45 and J46. Deaths coded to ICD-9 (1979–1996) were converted to ICD-10 (1997 onwards) using conversion factors (see Appendix 1 for details).
Sources: AIHW National Mortality Database; Australian Bureau of Statistics.
Australian Centre for Asthma Monitoring

6. Oral glucocorticosteroid (lowest dose)
Asthma Control
Oral glucocorticosteroid (lowest dose)
anti-IgE
antibodies
as needed rapid-
acting β2-agonist

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

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 Related quality of life impairment was associated with the number of management problems identified by the MDA
Health Status (SGRQ) by Diagnosis
McDonald VM et al, Age Ageing 2011:40;42-9

10. Older person with asthma
Dysfunctional breathing
Comorbidity
Obesity
Anxiety/Depression
Inflammation
Smoking
AFO
Exercise limitation
Increased inhaler error
Cognition
Infection
Hospitalisation
Non adherence
Tailored Pharmacotherapy Exercise Rehab Smoking cessation (Individualised education, WAP , Inhaler device assessment ) Vaccinations Assessment and specific management of comorbid conditions Breathing retraining Nutrition/Weight Management LABA
Gibson PG, McDonald VM, Marks GM. Lancet 2010; 376:803

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

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, 87years, ♀, Asthma
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’

14. Ester, 87years, ♀, Asthma Body Composition
BMD -T scores = total body 0, hip -0.8 = normal
ASMMI 5.9km/m2 = 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 Infections
Self Management Education with WAP

15. Outcomes Baseline 3 months 6 months FEV1 1.27 (77) 1.3 (81) 1.12 (66)
SGRQ
56.3
24.3
27.4
Exacerbations
4 past 12/12
0 past 3/12
0 past 6/12
6MWD
257.2
333.8
359.1
FENO
17.5
16.2 18
CRP
18.1
4.2
Nijmegen 37 41 29
ASMMI
5.9kg/m2
6kg/m2
BMI 22
24.2
HADS A|D
8|10
6|4
4|6

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

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 +
omalizumab
Allergen specific IgE
Bruselle A, Resp Med 2009

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. Inflammatory phenotyping
For
Refractory
Severe
Asthma
* ABPA, SAFS

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

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

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

27. Oral Corticosteroids Fewer courses Of steroids Were needed
For wheezing
attacks
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 1 2 3
When looking at how
EOS
NEUT
PAUCI

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. HC
Eos
Neut

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 ?
Mortality has reduced
Control has improved
Overdiagnosis
Overtreatment
People are still unwell
Next: ?
Cure
Prevention
New treatment: breakthroughs
Lifestyle