acos and treatable traits: -omics approach to refine taxonomy of … · 2017-04-11 · acos and...
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ACOS and treatable traits: -omics approach to refine taxonomy of
obstructive airways disease
Professor Kian Fan Chung MD DSc
Experimental Studies, National Heart & Lung Institute, Imperial College London;
Biomedical Research Unit, Royal Brompton Hospital, London, UK
AIRWAY VISTA 2017Seoul, Korea
Conflict of interest
• Participation in Advisory Board meetings regarding asthma and COPD for GSK, AstraZeneca, Novartis, Johnson & Johnson, Boehringer Ingelheim and Actavis
• Research grant funding from Pfizer, GSK and Merck
• Speaking engagements: AstraZeneca, Merck, Novartis
• Investigator of IMI EU/EFPIA funded UBIOPRED Consortium on Severe Asthma
• No funding from tobacco industry
What is ACOS?
3
COPD ASTHMA
COPD ACOS ASTHMA
COPDCOPD
ACOS/D
ASTHMA
ACOS/DASTHMA
COPD ASTHMA Dutch hypothesis
British hypothesis
After John Riley, GSK
Asthma-COPD overlap (ACOS)
1. Prevalence: ACOS has a prevalence of 20% of patients with obstructive airways disease (asthma or COPD) and 2% in general population.
2. Increased illness burden: ACOS leads to significant health status impairment, increased exacerbations and increased hospitalisation
3. Treatment implications:(i) Non-recognition of asthma: potential for increased adverse events from LABA use
(ii) In COPD patients with asthma, increased response to ICS + LABA(iii) No recommendations for ACOS because not included in RCTs
4. Childhood onset: Prevention to the development of ACOS by studying early-life origins
From: Gibson & McDonald Thorax 2015; 70: 683
Severe asthma:
non-smoking
(308)
Severe asthma:
smoking & ex-
smoking (110)
Mild/Moderate
Asthma (98)
Non-asthma
(101)P-value
Age (yr) 50.9 54.5* 42.4 38.9 <0.001
Age at diagnosis 20 38* 14 NA <0.001
Female (%) 65.9 50.9* 50.00 38.61 <0.001
BMI (kg/m2) 29.08 29.56 25.88 25.31 <0.001
Exacerbations in past yr 2.48 2.55 0.37 0 <0.001
IgE (IU/ml) 119.5 126 89.4 23.45 <0.001
Atopy (%) 69 58 80 38 <0.001
Nasal polyps (%) 34.7 33.7 8.3 8.8 <0.001
Allergic rhinitis (%) 59.2 43.6* 60 16.7 <0.001
GERD (%) 47 63* 21 11 <0.001
FEV1 (% pred) 67.42 67.25 88.37 101.76 <0.001
Oral corticosteroids (%) 45.8 44.7 0 0 <0.001
Sputum eosinophils (%) 2.75 4.13 1.05 0.00 <0.001
Exhaled NO 27 23.5 25.50 19.00 <0.01
Demographics of UBIOPRED cohorts
Shaw et al: Clinical and inflammatory characteristics of the European U-BIOPRED adult severe asthma cohort.
European Respiratory Journal 46: 1308 (2015) * significant cf to non-smoking
(n)
UBIOPRED asthma clusters based on unsupervised clustering of 8 clinical features
• Cluster 1: Moderate-to-severe asthma;
well-controlled; medium to high dose ICS
• Cluster 2: Severe asthma; Late onset asthma; smoker or ex-smoker; airflow obstruction
• Cluster 3: Severe asthma; Oral corticosteroid-dependent; airflow obstruction
• Cluster 4: Severe asthma; Female; Obese;
frequent exacerbations
PARAMETERS USED
-Age of asthma onset
- Pack-years of smoking
- Body Mass Index (BMI)
- FEV1 % predicted
- FEV1/FVC
- Asthma Control Questionnaire:
ACQ-5
- Exacerbations in past year
-Medication Oral Corticosteroid
(OCS) daily dose
Lefaudeux et al 2016
Variables T1 (n = 69) – moderate– well-controlled
T2 (n = 56) – late onset – smoking – obstructive
T3 (n = 68) – severe--non-smoking – obstructive
T4 (n = 73) – female – obese – exacerbations
P-Value
Age (yrs) 43 ± 15 57 ± 10 53 ± 15 48 ± 14 < 0.001 1
Gender (female) 55% 57% 47% 84% < 0.001 3
On OCS (%)† 5.8% 48.2% 51.5% 41.1% < 0.001 2
Asthma onset (years)† 17 (5 – 30) 43 (31 – 52) 18 (5.8 – 37) 20 (7 – 37) < 0.001 2
FEV1% predicted† 89 ± 17 59 ± 16 49 ± 14 79 ± 15 < 0.001 1
FEV1/FVC† 0.74 ± 0.084 0.56 ± 0.098 0.51 ± 0.079 0.74 ± 0.083 < 0.001 1
ACQ_5† 0.8 (0.25 – 1.6) 2 (1.2 – 2.8) 2.4 (1.6 – 3.6) 2.6 (1.8 – 3.2) < 0.001 2
Excacerbations† 0 (0 – 1) 1 (0.75 – 3) 2 (1 – 3.25) 3 (2 – 4) < 0.001 2
BMI† 25 (22 – 28) 29 (26 – 33) 25 (23 – 29) 32 (27 – 36) < 0.001 2
Pack Years† 0 (0 – 0) 16 (4.9 – 26) 0 (0 – 0) 0 (0 – 0) < 0.001 2
ICS dose range (high) 37% 98% 97% 96% < 0.001 3
Blood eosinophils (103/µl) 0.20 (0.1 – 0.3) 0.30 (0.12 – 0.56) 0.22 (0.1 – 0.49) 0.2 (0.10 – 0.38) 0.0273 2
Blood neutrophils (103/µl) 4.0 (3.1 – 4.9) 5.1 (4.0 – 7.2) 5.1 (3.7 – 7.6) 4.7 (3.6 – 6.7) < 0.001 2
Sputum eosinophils (%) 0.78 (0.25 – 5.9) 4.9 (1.4 – 20) 3.7 (1.0 – 30) 2.4 (0.29 – 7.1) 0.0147 2
Sputum neutrophils (%) 54 (27 – 64) 60 (44. – 71) 63 (40 – 86) 49 (32 – 70) 0.268 2
1 Anova2 Kruskal – Wallis3 χ2
† included in the clustering
Characteristics of 4 clinical clusters
Mean ± SDMedian (IQR)
Lefaudeux et al 2017 JACI
UBIOPRED : smoking (cluster 2) vs non-smoking (cluster 3) of airflow obstruction
●Pathway analysis of sputum cell
transcriptomics
Regulation of actin cytoskeleton (ITGB1, FN1,ACTN2)Fibronectin matrix formation (ITGB1, FN1)
●Differentially-expressed proteins in sputumsupernatantsLYN: src non-receptor lyn tyrosine kinaseFUT5: Fucosyltransferase 5
Lefaudeux et al 2017 JACI
Japanese smoking clusters of severe asthma
Konno et al Ann ATS 2015; 123: 1771
Asthma-COPD Overlap syndrome:Phenotypes/endotypes
From: Bateman et al Lancet 2015:3;719
ACOSPhenotypes/endotypes
ACOSEosinophilic
ACOSAsthma in
smokers
Chronic airflowlimitation
Bronchodilatorresponse
Asthma COPD
Treatable traits of chronic airways disease
• Airflow limitation
• Eosinophilic airway inflammation
• Chronic bronchitis
• Airway bacterial colonisation
• Bronchiectasis
• Cough reflex hypersensitivity
• Pre-capillary pulmonary hypertension
• Chronic respiratory failure
● Deconditioning● Obesity● Cachexia● OSA● CVS disease● GORD● Upper airways diseaseRhinosinusitisVocal cord dysfunction● Psychiatric: DepressionAnxiety● Breathing pattern disorders● Persistent systemic inflammmation
Pulmonary Extrapulmonary
Agusti et al ERJ 2016: 47: 410
Severe Asthma: distribution of 3 ACOS features
311 NON-SMOKERS22 (7.1%) had none
of 3 traits
(11.6%)
(9.0%) (15.8%)
(18.3%)
(8.4%) (8.7%)(20.6%)
(56.3%) (63.3%)
110 SMOKERS6 (5.5%) with none of 3
traits
(36.4%)
(6.4%)
(14.5%)(4.5%)
(5.5%)
(11.8%)
67.3%70.9%
(63.6%)(54.7%)
P. Hekking
(14.0%)
Airflow limitation Airflow limitationEosinophilic inflamEosinophilic inflam
Bronchodilator respBronchodilator resp
Airflow obstruction No airflow obstruction
Non-smoker (n=175)
Smoker (n=74)
P value Non-smoker (n=131)
Smoker (n=235)
P value
Pb FEV1 (% pred) 63.5 69.9 0.01 91.3 90.1
Smoking (py) 2.0 20 <0.001 1.5 15 <0.001
Age (yr) 55.2 56.5 45.4 50.1
Asthma onset (yr) 24.5 39 <0.001 18 34 0.02
Gender (male %) 41.1 52.7 24.4 40
BMI 28.6 28.7 29.9 31.4
Atopy (%) 67.2 62.2 71.3 42.9 0.007
Exacerbations/yr 2.0 2.0 2.0 2.5
History of COPD (%)
4.6 14.9 <0.004 3.1 8.6 0.001
Oral steroids (%) 49.4 47.2 39.2 40
Sputum eos (%) 3.8 4.5 1.4 0.96
Sputum DE Genes 3 0
Non-smoker vs smoker with regards to airflow limitation
Eosinophilia No eosinophilia
Non-smoker (n=197)
Smoker (n=78)
P value Non-smoker (n=107)
Smoker (n=28)
P value
Sputum eos (%) 6.2 5.4 0.20 0.32
Blood eos (L) 0.36 0.30 0.1 0.1
Pb FEV1 (% pred) 73.5 77.5 78.5 72.7
Smoking (p-yr) 2 17.4 <0.001 1.5 19.4 <0.001
Age (yr) 52.9 54.9 47.5 53.4 0.062
Asthma onset (yr) 25 41.5 <0.001 16 30 0.02
Gender (male %) 37.6 43.6 28 64.3 0.001
BMI 28.8 29.4 29.4 30.4
Atopy (%) 70.8 60.3 67 46.4 0.1
Exacerbations/yr 2.0 2.0 2.0 3.0
History of COPD (%)
4.6 15.4 <0.001 2.8 7.1 0.02
Oral steroids (%) 42.8 40.5 51.5 60
Sputum DE Genes 109 0
Non-smoker to smoker with regards to eosinophilia
Gene Ontology (Biological Process) p-value
BP cell migration 2.40e-02
BP regulation of cell migration 2.89e-02
BP single-organism cellular process 1.90e-02
BP regulation of protein autophosphorylation 3.56e-02
BP regulation of response to stimulus 3.87e-02
BP single-organism metabolic process 6.43e-03
Pathway analysis of DEGs in sputum cells from smokers vs non-smokers in eosinophilic asthma
Severe Asthma Molecular Phenotypes(from U-BIOPRED sputum analysis)
Th2-like inflammation Less Th2-like inflammation
“Severe Asthma”
FEV1
Symptoms
Exacerbations
Bacterial infection
Inflammasome
Moderate airflow obstruction
More eczema
Neutrophilic/
Eosinophilic
Severe asthma
Airflow obstruction
Nasal polyps
High OCS use
Corticosteroid insensitivity
Highly Eosinophilic
Oxidative stress/Ageing
Less exacerbations
Mild Airflow obstruction
Paucigranulocytic/
eosinophilic
TAC1 TAC2 TAC3
GTPase: RASAL3Metabolism of steroid: UGT2B28
TSLP Receptor: CRLF2
T cell Receptor: TRGC2, TRGV9, TARPProtease: PRSS33
Eosinophil lysophospholipase CLC
Cytokine promoting Th17 differentiation: VSTM1
Lactose binding: LGALS12Suppressor of cytokine signaling: SOCS2
IL33 Receptor: IL1RL1Eotaxin Receptor: CCR3
Phosphatase: PTPN7
Tryptase: TPSB2Carboxypeptidase: CPA3Arachidonate 15-Lipoxygenase: ALOX15
G-protein coupled receptor: GPR42Transcriptional factor: OLIG2, SATB1
IL3 Receptor: IL3RA
B cell surface: CD24Actin: FAM101BATPase: ATP2A3Cytokine: CSF1
Multiple cytokine receptors &
Enzymes (protease, lipase)
28 genes
Receptor: TREML2, CLEC4D,IFIH1,SIGLEC5,LILRA5
Cytokine: CXCL10(IP10, ligand of CXCR3), TNFSF10(TRAIL)
GTPase: GIAMP4
Adaptor : REPS2, SPATA13
Transcriptional activator : CREB5
Ubiquitination : WDFY3, UBE2D1
Transcriptional activator : NMI
Caspase : CASP4
Chromatin replication : BAZ1A
IFN-induced protein: IFIT2, IFIT3,IFI16,MNDA
GTP cyclohydrolase : GCH1
TNF-induced protein: TNFAIP3
GTPase: RHOH
Caspase inhibitor : CARD16
Neutrophil function : S100A9
TNF and INF regulationPattern recognition receptor
27 genes
Fatty acid metabolism: ME1
Intracellular vesicle and organelle transport: MYO6, LMAN1
CAMP-Dependent Protein Kinase: PRKACBMitochondrial ribosomal proteins: MRPS15, MRPS21
Ubiquitination: TULP4, ZYG11B, BTBD1, RNF135
Proteinase inhibitor: CSTA
Toll-like receptor: TLR7Cell adhesion regulation: CTNND1
Anti-viral enzyme: OAS1
Pre-mRNA splicing: ZCRB1, LSM5
Lectin receptor: LMAN1, CD302
Cytochrome C oxidase: COA6
Methyltransferase: METTL5Acetyltransferase: NAA20, ACAA2Fuctosidase: FUCA1Adenosine deaminase: CECR1
Aldehyde dehydrogenase: ALDH1A1
Phospholipase: PLBD1Glycolipid metabolism: PYURF
Multiple metabolic and ubiquitination enzymes
31 genes
TAC1 TAC2 TAC3
Genes characterising each transcriptomic- associated cluster
GSE8545 (Chest 2008; 133: 1344)
Epithelial brushings from 18 normal non-smokers, 18 normal smokers and 18 smokers
with COPD (GOLD I or II).
TAC1: T2
TAC3: Mitochondrial OxPHOSTAC2: inflammasome
GSVA of TAC signatures in epithelial gene expressionfrom smokers and COPD subjects
P<0.01P<0.0005
P<0.05
Groningen & Leiden Univ study of Corticosteroids in Obstructive Lung Disease (GLUCOLD)
Irreversible airflow limitation(Post-bronch FEV1 and FEV1/IVC<90% CI of pred value)Chronic respiratory symptomsAll current or ex-smokers(≥10 pack years)
Van den Berge et al Thorax 2014; 69: 14-23
Bronchial biopsies from 162 patients with COPD before and after treatment with fluticasone.
GSE36221: van den Berge et al Thorax 2014;69(1):14-23)
Gene set variation analysis (GSVA) of TAC signatures in bronchial biopsies gene expression of COPD patients
(GLUCOLD)
0 6 30
TAC1 : T2 TAC3: mito OxPHOSTAC2: inflammasome
P<0.05P<10-4
months0 6 30
months
0 6 30
months
Corticosteroid-insensitiveCorticosteroid-sensitive
ACOSPhenotypes
ACOS-asthma smoking phenotype
Polosa & Thomson ERJ 2013;41:716.
Smoking ‘Asthma’
ACOSEosinophilic
ACOSAsthma in
smokers
Asthma/COPD
ACOSChronic airflow
limitationBronchodilator
response
Molecular phenotyping
Conclusions• Smoking asthmatics form a distinct asthma ACOS
phenotype • Smoking may impact on ACOS features including
airflow obstruction, and eosinophilic inflammation, as may non-smoking factors
• Molecular phenotyping reveals that asthma-ACOS may consist of T2 and non-T2 pathways independent of smoking
• Similar molecular phenotypes are present in COPD, perhaps with a predominance of mitochondrial OxPHOS.
• Molecular phenotyping remains the future of ACOS.
University of Amsterdam, University of
Southampton, Imperial College London, University
of Manchester, University of Nottingham, Fraunhofer
Institute Hannover, CNRS-EISBM Lyon, Université
de Méditerranee Montpellier, Karolinska Institute
Stockholm, University Hospital Umea, University Tor
Vergata Rome, Università Cattolica del Sacro Cuore
Rome, University of Catania, Hvidore Hospital
Copenhagen, University Hospital Copenhagen,
Haukeland University Bergen, Semmelweis
University Budapest, Jagiellonian University Krakow,
University Hospital Bern, University of Ghent
EFPIA Partners
Novartis
Almirall
Amgen
AstraZeneca
Boehringer Ingelheim
Chiesi
GlaxoSmithKline
Johnson & Johnson / Janssen
Merck
UCB
Roche /Genentech
SME’s
Aerocrine
BioSci Consulting
Synairgen
Philips Research
Patient organisations
Asthma UK
European Lung Foundation
EFA
Int Primary Care
Respiratory Group
Lega Italiano Anti Fumo
Netherlands Asthma
Foundation
website hosted by the ELF: www.ubiopred.eu
Funded bythe European Union