Abstract
Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging. Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machinelearning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD. Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPDLongitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data. Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r =20.16 [P<0.001] in the Tissue→Airway group; r =20.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up. Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD".
| Original language | English (US) |
|---|---|
| Pages (from-to) | 294-302 |
| Number of pages | 9 |
| Journal | American journal of respiratory and critical care medicine |
| Volume | 201 |
| Issue number | 3 |
| DOIs | |
| State | Published - Feb 1 2020 |
Keywords
- Bronchitis
- CT imaging
- Chronic obstructive pulmonary disease
- Clustering
- Emphysema
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine
- Critical Care and Intensive Care Medicine
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Disease progression modeling in chronic obstructive pulmonary disease. / Young, Alexandra L.; Bragman, Felix J.S.; Rangelov, Bojidar; Han, Meilan K.; Galbán, Craig J.; Lynch, David A.; Hawkes, David J.; Alexander, Daniel C.; Hurst, John R.; Crapo, James D.; Silverman, Edwin K.; Make, Barry J.; Regan, Elizabeth A.; Beaty, Terri; Begum, Ferdouse; Castaldi, Peter J.; Cho, Michael; DeMeo, Dawn L.; Boueiz, Adel R.; Foreman, Marilyn G.; Halper-Stromberg, Eitan; Hayden, Lystra P.; Hersh, Craig P.; Hetmanski, Jacqueline; Hobbs, Brian D.; Hokanson, John E.; Laird, Nan; Lange, Christoph; Lutz, Sharon M.; McDonald, Merry Lynn; Parker, Margaret M.; Qiao, Dandi; Regan, Elizabeth A.; Silverman, Edwin K.; Wan, Emily S.; Won, Sungho; Sakornsakolpat, Phuwanat; Prokopenko, Dmitry; Qaisi, Mustafa Al; Coxson, Harvey O.; Gray, Teresa; Hoffman, Eric A.; Humphries, Stephen; Jacobson, Francine L.; Judy, Philip F.; Kazerooni, Ella A.; Kluiber, Alex; Lynch, David A.; Newell, John D.; Regan, Elizabeth A.; Ross, James C.; Estepar, Raul San Jose; Schroeder, Joyce; Sieren, Jered; Stinson, Douglas; Stoel, Berend C.; Tschirren, Juerg; Van Beek, Edwin; Van Ginneken, Bram; Van Rikxoort, Eva; Washko, George; Wilson, Carla G.; Jensen, Robert; Everett, Douglas; Crooks, Jim; Moore, Camille; Strand, Matt; Wilson, Carla G.; Hokanson, John E.; Hughes, John; Kinney, Gregory; Lutz, Sharon M.; Pratte, Katherine; Young, Kendra A.; Bhatt, Surya; Bon, Jessica; Make, Barry J.; Martinez, Carlos; Murray, Susan; Regan, Elizabeth A.; Soler, Xavier; Wilson, Carla G.; Bowler, Russell P.; Kechris, Katerina; Banaei-Kashani, Farnoush; Curtis, Jeffrey L.; Martinez, Carlos H.; Pernicano, Perry G.; Hanania, Nicola; Alapat, Philip; Atik, Mustafa; Bandi, Venkata; Boriek, Aladin; Guntupalli, Kalpatha; Guy, Elizabeth; Nachiappan, Arun; Parulekar, Amit; DeMeo, Dawn L.; Hersh, Craig P.; Jacobson, Francine L.; Washko, George; Barr, R. Graham; Austin, John; D'Souza, Belinda; Pearson, Gregory D.N.; Rozenshtein, Anna; Thomashow, Byron; MacIntyre, Neil; McAdams, H. Page; Washington, Lacey; McEvoy, Charlene; Tashjian, Joseph; Wise, Robert; Brown, Robert; Hansel, Nadia N.; Horton, Karen; Lambert, Allison; Putcha, Nirupama; Casaburi, Richard; Adami, Alessandra; Budoff, Matthew; Fischer, Hans; Porszasz, Janos; Rossiter, Harry; Stringer, William; Sharafkhaneh, Amir; Lan, Charlie; Wendt, Christine; Bell, Brian; Foreman, Marilyn G.; Berkowitz, Eugene; Westney, Gloria; Bowler, Russel P.; Lynch, David A.; Rosiello, Richard; Pace, David; Criner, Gerard; Ciccolella, David; Cordova, Francis; Dass, Chandra; D'Alonzo, Gilbert; Desai, Parag; Jacobs, Michael; Kelsen, Steven; Kim, Victor; Mamary, A. James; Marchetti, Nathaniel; Satti, Aditi; Shenoy, Kartik; Steiner, Robert M.; Swift, Alex; Swift, Irene; Vega-Sanchez, Maria Elena; Dransfield, Mark; Bailey, William; Bhatt, Surya; Iyer, Anand; Nath, Hrudaya; Wells, J. Michael; Ramsdell, Joe; Friedman, Paul; Soler, Xavier; Yen, Andrew; Comellas, Alejandro P.; Hoth, Karin F.; Newell, John D.; Thompson, Brad; Kazerooni, Ella A.; Martinez, Carlos H.; Billings, Joanne; Begnaud, Abbie; Allen, Tadashi; Sciurba, Frank; Bon, Jessica; Chandra, Divay; Fuhrman, Carl; Weissfeld, Joel; Anzueto, Antonio; Adams, Sandra; Maselli-Caceres, Diego; Ruiz, Mario E.
In: American journal of respiratory and critical care medicine, Vol. 201, No. 3, 01.02.2020, p. 294-302.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Disease progression modeling in chronic obstructive pulmonary disease
AU - Young, Alexandra L.
AU - Bragman, Felix J.S.
AU - Rangelov, Bojidar
AU - Han, Meilan K.
AU - Galbán, Craig J.
AU - Lynch, David A.
AU - Hawkes, David J.
AU - Alexander, Daniel C.
AU - Hurst, John R.
AU - Crapo, James D.
AU - Silverman, Edwin K.
AU - Make, Barry J.
AU - Regan, Elizabeth A.
AU - Beaty, Terri
AU - Begum, Ferdouse
AU - Castaldi, Peter J.
AU - Cho, Michael
AU - DeMeo, Dawn L.
AU - Boueiz, Adel R.
AU - Foreman, Marilyn G.
AU - Halper-Stromberg, Eitan
AU - Hayden, Lystra P.
AU - Hersh, Craig P.
AU - Hetmanski, Jacqueline
AU - Hobbs, Brian D.
AU - Hokanson, John E.
AU - Laird, Nan
AU - Lange, Christoph
AU - Lutz, Sharon M.
AU - McDonald, Merry Lynn
AU - Parker, Margaret M.
AU - Qiao, Dandi
AU - Regan, Elizabeth A.
AU - Silverman, Edwin K.
AU - Wan, Emily S.
AU - Won, Sungho
AU - Sakornsakolpat, Phuwanat
AU - Prokopenko, Dmitry
AU - Qaisi, Mustafa Al
AU - Coxson, Harvey O.
AU - Gray, Teresa
AU - Hoffman, Eric A.
AU - Humphries, Stephen
AU - Jacobson, Francine L.
AU - Judy, Philip F.
AU - Kazerooni, Ella A.
AU - Kluiber, Alex
AU - Lynch, David A.
AU - Newell, John D.
AU - Regan, Elizabeth A.
AU - Ross, James C.
AU - Estepar, Raul San Jose
AU - Schroeder, Joyce
AU - Sieren, Jered
AU - Stinson, Douglas
AU - Stoel, Berend C.
AU - Tschirren, Juerg
AU - Van Beek, Edwin
AU - Van Ginneken, Bram
AU - Van Rikxoort, Eva
AU - Washko, George
AU - Wilson, Carla G.
AU - Jensen, Robert
AU - Everett, Douglas
AU - Crooks, Jim
AU - Moore, Camille
AU - Strand, Matt
AU - Wilson, Carla G.
AU - Hokanson, John E.
AU - Hughes, John
AU - Kinney, Gregory
AU - Lutz, Sharon M.
AU - Pratte, Katherine
AU - Young, Kendra A.
AU - Bhatt, Surya
AU - Bon, Jessica
AU - Make, Barry J.
AU - Martinez, Carlos
AU - Murray, Susan
AU - Regan, Elizabeth A.
AU - Soler, Xavier
AU - Wilson, Carla G.
AU - Bowler, Russell P.
AU - Kechris, Katerina
AU - Banaei-Kashani, Farnoush
AU - Curtis, Jeffrey L.
AU - Martinez, Carlos H.
AU - Pernicano, Perry G.
AU - Hanania, Nicola
AU - Alapat, Philip
AU - Atik, Mustafa
AU - Bandi, Venkata
AU - Boriek, Aladin
AU - Guntupalli, Kalpatha
AU - Guy, Elizabeth
AU - Nachiappan, Arun
AU - Parulekar, Amit
AU - DeMeo, Dawn L.
AU - Hersh, Craig P.
AU - Jacobson, Francine L.
AU - Washko, George
AU - Barr, R. Graham
AU - Austin, John
AU - D'Souza, Belinda
AU - Pearson, Gregory D.N.
AU - Rozenshtein, Anna
AU - Thomashow, Byron
AU - MacIntyre, Neil
AU - McAdams, H. Page
AU - Washington, Lacey
AU - McEvoy, Charlene
AU - Tashjian, Joseph
AU - Wise, Robert
AU - Brown, Robert
AU - Hansel, Nadia N.
AU - Horton, Karen
AU - Lambert, Allison
AU - Putcha, Nirupama
AU - Casaburi, Richard
AU - Adami, Alessandra
AU - Budoff, Matthew
AU - Fischer, Hans
AU - Porszasz, Janos
AU - Rossiter, Harry
AU - Stringer, William
AU - Sharafkhaneh, Amir
AU - Lan, Charlie
AU - Wendt, Christine
AU - Bell, Brian
AU - Foreman, Marilyn G.
AU - Berkowitz, Eugene
AU - Westney, Gloria
AU - Bowler, Russel P.
AU - Lynch, David A.
AU - Rosiello, Richard
AU - Pace, David
AU - Criner, Gerard
AU - Ciccolella, David
AU - Cordova, Francis
AU - Dass, Chandra
AU - D'Alonzo, Gilbert
AU - Desai, Parag
AU - Jacobs, Michael
AU - Kelsen, Steven
AU - Kim, Victor
AU - Mamary, A. James
AU - Marchetti, Nathaniel
AU - Satti, Aditi
AU - Shenoy, Kartik
AU - Steiner, Robert M.
AU - Swift, Alex
AU - Swift, Irene
AU - Vega-Sanchez, Maria Elena
AU - Dransfield, Mark
AU - Bailey, William
AU - Bhatt, Surya
AU - Iyer, Anand
AU - Nath, Hrudaya
AU - Wells, J. Michael
AU - Ramsdell, Joe
AU - Friedman, Paul
AU - Soler, Xavier
AU - Yen, Andrew
AU - Comellas, Alejandro P.
AU - Hoth, Karin F.
AU - Newell, John D.
AU - Thompson, Brad
AU - Kazerooni, Ella A.
AU - Martinez, Carlos H.
AU - Billings, Joanne
AU - Begnaud, Abbie
AU - Allen, Tadashi
AU - Sciurba, Frank
AU - Bon, Jessica
AU - Chandra, Divay
AU - Fuhrman, Carl
AU - Weissfeld, Joel
AU - Anzueto, Antonio
AU - Adams, Sandra
AU - Maselli-Caceres, Diego
AU - Ruiz, Mario E.
N1 - Funding Information: Supported by Engineering and Physical Sciences Research Council (EPSRC) grants EP/H046410/1 and EP/K502959/1 (F.J.S.B.); University College London Hospitals (UCLH) NIHR Research Capability Funding Senior Investigator Award under grant RCF107/DH/2014 (F.J.S.B. and D.J.H.); EPSRC Doctoral Prize Fellowship and MRC Skills Development Fellowship (A.L.Y.); EPSRC Centre For Doctoral Training in Medical Imaging grant EP/L016478/1 and Industrial Fellowship from the Royal Commission for the Exhibition of 1851 (B.R.); an industrial CASE studentship with funding from GlaxoSmithKline Research and Development, Agreement BIDS3000032413 (B.R.); the European Union's Horizon 2020 research and innovation program under grant agreement 666992 (D.C.A.); EPSRC grants M020533, M006093, and J020990 (D.C.A.). This work was supported by the UCLH NIHR Biomedical Research Centre. The COPDGene Study was supported by Award U01 HL089897 and Award U01 HL089856 from the NHLBI. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHLBI or the NIH. The COPDGene project is also supported by the Chronic Obstructive Pulmonary Disease Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion. The ECLIPSE study was sponsored by GlaxoSmithKline. The study sponsor did not place any restrictions regarding statements made in this manuscript. A Steering Committee and a Scientific Committee comprising academic and sponsor representatives developed the original ECLIPSE study design, had full access to the study data, and were responsible for decisions regarding publications. Funding Information: *Joint first authors. ‡M.K.H. is Associate Editor of AJRCCM. Her participation complies with American Thoracic Society requirements for recusal from review and decisions for authored works. Supported by Engineering and Physical Sciences Research Council (EPSRC) grants EP/H046410/1 and EP/K502959/1 (F.J.S.B.); University College London Hospitals (UCLH) NIHR Research Capability Funding Senior Investigator Award under grant RCF107/DH/2014 (F.J.S.B. and D.J.H.); EPSRC Doctoral Prize Fellowship and MRC Skills Development Fellowship (A.L.Y.); EPSRC Centre For Doctoral Training in Medical Imaging grant EP/L016478/1 and Industrial Fellowship from the Royal Commission for the Exhibition of 1851 (B.R.); an industrial CASE studentship with funding from GlaxoSmithKline Research and Development, Agreement BIDS3000032413 (B.R.); the European Union’s Horizon 2020 research and innovation program under grant agreement 666992 (D.C.A.); EPSRC grants M020533, M006093, and J020990 (D.C.A.). This work was supported by the UCLH NIHR Biomedical Research Centre. The COPDGene Study was supported by Award U01 HL089897 and Award U01 HL089856 from the NHLBI. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHLBI or the NIH. The COPDGene project is also supported by the Chronic Obstructive Pulmonary Disease Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion. The ECLIPSE study was sponsored by GlaxoSmithKline. The study sponsor did not place any restrictions regarding statements made in this manuscript. A Steering Committee and a Scientific Committee comprising academic and sponsor representatives developed the original ECLIPSE study design, had full access to the study data, and were responsible for decisions regarding publications. Publisher Copyright: Copyright © 2020 by the American Thoracic Society.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging. Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machinelearning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD. Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPDLongitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data. Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r =20.16 [P<0.001] in the Tissue→Airway group; r =20.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up. Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD".
AB - Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging. Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machinelearning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD. Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPDLongitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data. Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r =20.16 [P<0.001] in the Tissue→Airway group; r =20.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up. Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD".
KW - Bronchitis
KW - CT imaging
KW - Chronic obstructive pulmonary disease
KW - Clustering
KW - Emphysema
UR - http://www.scopus.com/inward/record.url?scp=85078816116&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078816116&partnerID=8YFLogxK
U2 - 10.1164/rccm.201908-1600OC
DO - 10.1164/rccm.201908-1600OC
M3 - Article
C2 - 31657634
AN - SCOPUS:85078816116
VL - 201
SP - 294
EP - 302
JO - American Review of Respiratory Disease
JF - American Review of Respiratory Disease
SN - 1073-449X
IS - 3
ER -