Skip to main content
Top
Published in: BMC Pulmonary Medicine 1/2017

Open Access 01-12-2017 | Research article

Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia

Authors: Yoonha Choi, Jiayi Lu, Zhanzhi Hu, Daniel G. Pankratz, Huimin Jiang, Manqiu Cao, Cristina Marchisano, Jennifer Huiras, Grazyna Fedorowicz, Mei G. Wong, Jessica R. Anderson, Edward Y. Tom, Joshua Babiarz, Urooj Imtiaz, Neil M. Barth, P. Sean Walsh, Giulia C. Kennedy, Jing Huang

Published in: BMC Pulmonary Medicine | Issue 1/2017

Login to get access

Abstract

Background

Clinical guidelines specify that diagnosis of interstitial pulmonary fibrosis (IPF) requires identification of usual interstitial pneumonia (UIP) pattern. While UIP can be identified by high resolution CT of the chest, the results are often inconclusive, making surgical lung biopsy necessary to reach a definitive diagnosis (Raghu et al., Am J Respir Crit Care Med 183(6):788–824, 2011). The Envisia genomic classifier differentiates UIP from non-UIP pathology in transbronchial biopsies (TBB), potentially allowing patients to avoid an invasive procedure (Brown et al., Am J Respir Crit Care Med 195:A6792, 2017). To ensure patient safety and efficacy, a laboratory developed test (LDT) must meet strict regulatory requirements for accuracy, reproducibility and robustness. The analytical characteristics of the Envisia test are assessed and reported here.

Methods

The Envisia test utilizes total RNA extracted from TBB samples to perform Next Generation RNA Sequencing. The gene count data from 190 genes are then input to the Envisia genomic classifier, a machine learning algorithm, to output either a UIP or non-UIP classification result. We characterized the stability of RNA in TBBs during collection and shipment, and evaluated input RNA mass and proportions on the limit of detection of UIP. We evaluated potentially interfering substances such as blood and genomic DNA. Intra-run, inter-run, and inter-laboratory reproducibility of test results were also characterized.

Results

RNA content within TBBs preserved in RNAprotect is stable for up to 14 days with no detectable change in RNA quality. The Envisia test is tolerant to variation in RNA input (5 to 30 ng), with no impact on classifier results. The Envisia test can tolerate dilution of non-UIP and UIP classification signals at the RNA level by up to 60% and 20%, respectively. Analytical specificity studies utilizing UIP and non-UIP samples mixed with genomic DNA (up to 30% relative input) demonstrated no impact to classifier results. The Envisia test tolerates up to 22% of blood contamination, well beyond the level observed in TBBs. The test is reproducible from RNA extraction through to Envisia test result (standard deviation of 0.20 for Envisia classification scores on > 7-unit scale).

Conclusions

The Envisia test demonstrates the robust analytical performance required of an LDT. Envisia can be used to inform the diagnoses of patients with suspected IPF.
Appendix
Available only for authorised users
Literature
1.
go back to reference Travis WD, King TE, Bateman ED, Lynch DA, Capron F, Center D, Colby TV, Cordier JF, DuBois RM, Galvin J, et al. American thoracic society/european respiratory society international multidisciplinary consensus classification of the idiopathic interstitial pneumonias. Am J Respir Crit Care Med. 2002; 165(2):277–304.CrossRef Travis WD, King TE, Bateman ED, Lynch DA, Capron F, Center D, Colby TV, Cordier JF, DuBois RM, Galvin J, et al. American thoracic society/european respiratory society international multidisciplinary consensus classification of the idiopathic interstitial pneumonias. Am J Respir Crit Care Med. 2002; 165(2):277–304.CrossRef
2.
go back to reference Travis WD, Costabel U, Hansell DM, King Jr TE, Lynch DA, Nicholson AG, Ryerson CJ, Ryu JH, Selman M, Wells AU, et al. An official american thoracic society/european respiratory society statement: update of the international multidisciplinary classification of the idiopathic interstitial pneumonias. Am J Respir Crit Care Med. 2013; 188(6):733–48.CrossRefPubMed Travis WD, Costabel U, Hansell DM, King Jr TE, Lynch DA, Nicholson AG, Ryerson CJ, Ryu JH, Selman M, Wells AU, et al. An official american thoracic society/european respiratory society statement: update of the international multidisciplinary classification of the idiopathic interstitial pneumonias. Am J Respir Crit Care Med. 2013; 188(6):733–48.CrossRefPubMed
3.
go back to reference Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, Colby TV, Cordier JF, Flaherty KR, Lasky JA, et al. An official ats/ers/jrs/alat statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med. 2011; 183(6):788–824.CrossRefPubMedPubMedCentral Raghu G, Collard HR, Egan JJ, Martinez FJ, Behr J, Brown KK, Colby TV, Cordier JF, Flaherty KR, Lasky JA, et al. An official ats/ers/jrs/alat statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med. 2011; 183(6):788–824.CrossRefPubMedPubMedCentral
4.
go back to reference Pankratz DG, Choi Y, Imtiaz U, Fedorowicz GM, Anderson JD, Colby TB, Myers JL, Lynch DA, Brown KK, Flaherty KR, et al. Usual interstitial pneumonia can be detected in transbronchial biopsies using machine learning. Ann Am Thorac Soc. 2017; 14(11):1646–54. doi:10.1513/AnnalsATS.201612-947OC.CrossRefPubMed Pankratz DG, Choi Y, Imtiaz U, Fedorowicz GM, Anderson JD, Colby TB, Myers JL, Lynch DA, Brown KK, Flaherty KR, et al. Usual interstitial pneumonia can be detected in transbronchial biopsies using machine learning. Ann Am Thorac Soc. 2017; 14(11):1646–54. doi:10.​1513/​AnnalsATS.​201612-947OC.CrossRefPubMed
5.
go back to reference Brown KK, Choi Y, Colby TV, Flaherty KR, Groshong S, Imtiaz U, Lynch DA, Myers JL, Steele MP, Martinez FJ, Pankratz DG, Walsh PS, Huang J, Barth NM, Raghu G, Kennedy GC. Prospective validation of a genomic classifier for usual interstitial pneumonia in transbronchial biopsies. Am J Respir Crit Care Med. 2017; 195:A6792. Brown KK, Choi Y, Colby TV, Flaherty KR, Groshong S, Imtiaz U, Lynch DA, Myers JL, Steele MP, Martinez FJ, Pankratz DG, Walsh PS, Huang J, Barth NM, Raghu G, Kennedy GC. Prospective validation of a genomic classifier for usual interstitial pneumonia in transbronchial biopsies. Am J Respir Crit Care Med. 2017; 195:A6792.
6.
go back to reference Choi Y, Liu TT, Pankratz DG, Colby TV, Barth NM, Lynch DA, Walsh PS, Raghu G, Kennedy GC, Huang J. Identification of usual interstitial pneumonia pattern using RNA-seq and machine learning: challenges and solutions. Asia Pacific Bioinformatics Conference. BMC Genomics. 2018. In press. Choi Y, Liu TT, Pankratz DG, Colby TV, Barth NM, Lynch DA, Walsh PS, Raghu G, Kennedy GC, Huang J. Identification of usual interstitial pneumonia pattern using RNA-seq and machine learning: challenges and solutions. Asia Pacific Bioinformatics Conference. BMC Genomics. 2018. In press.
8.
go back to reference Kim SY, Diggans J, Pankratz D, Huang J, Pagan M, Sindy N, Tom E, Anderson J, Choi Y, Lynch DA, et al. Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data. Lancet Respir Med. 2015; 3(6):473–82.CrossRefPubMed Kim SY, Diggans J, Pankratz D, Huang J, Pagan M, Sindy N, Tom E, Anderson J, Choi Y, Lynch DA, et al. Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data. Lancet Respir Med. 2015; 3(6):473–82.CrossRefPubMed
9.
go back to reference Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for rna-seq data with deseq2. Genome Biol. 2014; 15(12):1.CrossRef Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for rna-seq data with deseq2. Genome Biol. 2014; 15(12):1.CrossRef
10.
go back to reference Teutsch S, Bradley L, Palomaki G, Haddow J, Piper M, Calonge N, et al. The evaluation of genomic applications in practice and prevention (egapp) initiative: methods of the egapp working group. Genet Med. 2009; 11(1):3–14.CrossRefPubMedPubMedCentral Teutsch S, Bradley L, Palomaki G, Haddow J, Piper M, Calonge N, et al. The evaluation of genomic applications in practice and prevention (egapp) initiative: methods of the egapp working group. Genet Med. 2009; 11(1):3–14.CrossRefPubMedPubMedCentral
Metadata
Title
Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia
Authors
Yoonha Choi
Jiayi Lu
Zhanzhi Hu
Daniel G. Pankratz
Huimin Jiang
Manqiu Cao
Cristina Marchisano
Jennifer Huiras
Grazyna Fedorowicz
Mei G. Wong
Jessica R. Anderson
Edward Y. Tom
Joshua Babiarz
Urooj Imtiaz
Neil M. Barth
P. Sean Walsh
Giulia C. Kennedy
Jing Huang
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Pulmonary Medicine / Issue 1/2017
Electronic ISSN: 1471-2466
DOI
https://doi.org/10.1186/s12890-017-0485-4

Other articles of this Issue 1/2017

BMC Pulmonary Medicine 1/2017 Go to the issue
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discuss last year's major advances in heart failure and cardiomyopathies.