We previously identified a MUC5B gene promoter-variant that is a risk allele for sporadic and familial Idiopathic Pulmonary Fibrosis/Usual Interstitial Pneumonia (IPF/UIP). This allele was strongly ...associated with increased MUC5B gene expression in lung tissue from unaffected subjects. Despite the strong association of this airway epithelial marker with disease, little is known of mucin expressing structures or of airway involvement in IPF/UIP.
Immunofluorescence was used to subtype mucus cells according to MUC5B and MUC5AC expression and to identify ciliated, basal, and alveolar type II (ATII) cells in tissue sections from control and IPF/UIP subjects. Staining patterns were quantified for distal airways (Control and IPF/UIP) and in honeycomb cysts (HC).
MUC5B-expressing cells (EC) were detected in the majority of control distal airways. MUC5AC-EC were identified in half of these airways and only in airways that contained MUC5B-EC. The frequency of MUC5B+ and MUC5AC+ distal airways was increased in IPF/UIP subjects. MUC5B-EC were the dominant mucus cell type in the HC epithelium. The distal airway epithelium from control and IPF/UIP subjects and HC was populated by basal and ciliated cells. Most honeycombing regions were distinct from ATII hyperplasic regions. ATII cells were undetectable in the overwhelming majority of HC.
The distal airway contains a pseudostratified mucocilary epithelium that is defined by basal epithelial cells and mucus cells that express MUC5B predominantly. These data suggest that the HC is derived from the distal airway.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The current usual interstitial pneumonitis (UIP)/idiopathic pulmonary fibrosis CT scan classification system excludes probable UIP as a diagnostic category. We sought to determine the predictive ...effect of probable UIP on CT scan on histology and the effect of the promoter polymorphism in MUC5B (rs35705950) on histologic and CT scan UIP diagnosis. METHODS The cohort included 201 subjects with pulmonary fibrosis who had lung tissue samples obtained within 1 year of chest CT scan. UIP diagnosis on CT scan was categorized as inconsistent with, indeterminate, probable, or definite UIP by two to three pulmonary radiologists. Tissue slides were scored by two expert pulmonary pathologists. All subjects with available DNA (N = 200) were genotyped for rs35705950. RESULTS The proportion of CT scan diagnoses were as follows: inconsistent with (69 of 201, 34.3%), indeterminate (72 of 201, 35.8%), probable (34 of 201, 16.9%), and definite (26 of 201, 12.9%) UIP. Subjects with probable UIP on CT scan were more likely to have histologic probable/definite UIP than subjects with indeterminate UIP on CT scan (82.4% 28 of 34 vs 54.2% 39 of 72; P = .01). CT scan and microscopic honeycombing were not associated with each other ( P = .76). The minor (T) allele of the MUC5B polymorphism was associated with concordant CT scan and histologic UIP diagnosis ( P = .03). CONCLUSIONS Probable UIP on CT scan is associated with a higher rate of histologic UIP than indeterminate UIP on CT scan suggesting that they are distinct groups and should not be combined into a single CT scan category as currently recommended by guidelines. CT scan and microscopic honeycombing may be dissimilar entities. The T allele at rs35705950 predicts a UIP diagnosis by both chest CT scan and histology.
Acute lung injury (ALI) is well defined in humans, but there is no agreement as to the main features of acute lung injury in animal models. A Committee was organized to determine the main features ...that characterize ALI in animal models and to identify the most relevant methods to assess these features. We used a Delphi approach in which a series of questionnaires were distributed to a panel of experts in experimental lung injury. The Committee concluded that the main features of experimental ALI include histological evidence of tissue injury, alteration of the alveolar capillary barrier, presence of an inflammatory response, and evidence of physiological dysfunction; they recommended that, to determine if ALI has occurred, at least three of these four main features of ALI should be present. The Committee also identified key "very relevant" and "somewhat relevant" measurements for each of the main features of ALI and recommended the use of least one "very relevant" measurement and preferably one or two additional separate measurements to determine if a main feature of ALI is present. Finally, the Committee emphasized that not all of the measurements listed can or should be performed in every study, and that measurements not included in the list are by no means "irrelevant." Our list of features and measurements of ALI is intended as a guide for investigators, and ultimately investigators should choose the particular measurements that best suit the experimental questions being addressed as well as take into consideration any unique aspects of the experimental design.
Idiopathic pulmonary fibrosis (IPF) is an untreatable lung disease with a median survival of only 3-5 years that is diagnosed using a combination of clinical, radiographic and pathologic criteria. ...Histologically, IPF is characterised by usual interstitial pneumonia (UIP), a fibrosing interstitial pneumonia with a pattern of heterogeneous, subpleural regions of fibrotic and remodelled lung. We hypothesised that gene expression profiles of lung tissue may identify molecular subtypes of disease that could classify subtypes of IPF/UIP that have clinical implications.
We collected transcriptional profiles on lung tissue from 119 patients with IPF/UIP and 50 non-diseased controls. Differential expression of individual transcripts was identified using an analysis of covariance (ANCOVA) model incorporating the clinical diagnosis of each patient as well as age, gender and smoking status. Validation was performed in an independent cohort of 111 IPF/UIP and 39 non-diseased controls. Our analysis identified two subtypes of IPF/UIP based on a strong molecular signature associated with expression of genes previously associated with fibrosis (matrix metalloproteinases, osteopontin, keratins), cilium genes and genes with unknown function. We demonstrate that elevated expression of cilium genes is associated with more extensive microscopic honeycombing and higher expression of both the airway mucin gene MUC5B and the metalloproteinase MMP7, a gene recently implicated in attenuating ciliated cell differentiation during wound repair.
Expression of cilium genes appears to identify two unique molecular phenotypes of IPF/UIP. The different molecular profiles may be relevant to therapeutic responsiveness in patients with IPF/UIP.
The impact of modern treatments of pulmonary arterial hypertension (PAH) on pulmonary vascular pathology remains unknown.
To assess the spectrum of pulmonary vascular remodeling in the modern era of ...PAH medication.
Assessment of pulmonary vascular remodeling and inflammation in 62 PAH and 28 control explanted lungs systematically sampled.
Intima and intima plus media fractional thicknesses of pulmonary arteries were increased in the PAH group versus the control lungs and correlated with pulmonary hemodynamic measurements. Despite a high variability of morphological measurements within a given PAH lung and among all PAH lungs, distinct pathological subphenotypes were detected in cohorts of PAH lungs. These included a subset of lungs lacking intima or, most prominently, media remodeling, which had similar numbers of profiles of plexiform lesions as those in lungs with more pronounced remodeling. Marked perivascular inflammation was present in a high number of PAH lungs and correlated with intima plus media remodeling. The number of profiles of plexiform lesions was significantly lower in lungs of male patients and those never treated with prostacyclin or its analogs.
Our results indicate that multiple features of pulmonary vascular remodeling are present in patients treated with modern PAH therapies. Perivascular inflammation may have an important role in the processes of vascular remodeling, all of which may ultimately lead to increased pulmonary artery pressure. Moreover, our study provides a framework to interpret and design translational studies in PAH.
The pathobiology of idiopathic pulmonary fibrosis remains largely unknown. In this study, a variety of genetic techniques were used to implicate variants in the mucin-forming gene
MUC5B
as pivotal in ...a substantial proportion of patients with the disorder.
The evidence that there is a genetic basis for idiopathic interstitial pneumonia is substantial, with familial aggregation confirmed through studies in twins, siblings raised apart, and multigenerational families.
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Interstitial lung disease has been associated with several pleiotropic genetic disorders.
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The development of pulmonary fibrosis has been associated with private mutations in surfactant protein C,
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surfactant protein A2,
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and genes that maintain telomere length.
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However, collectively these mutations account for a small proportion of the population risk of idiopathic interstitial pneumonia.
In this article, we used a genomewide linkage scan to identify a risk locus for idiopathic interstitial pneumonia on the . . .
Usual interstitial pneumonia (UIP) is the defining morphology of idiopathic pulmonary fibrosis (IPF). Guidelines for IPF diagnosis conditionally recommend surgical lung biopsy for histopathology ...diagnosis of UIP when radiology and clinical context are not definitive. A "molecular diagnosis of UIP" in transbronchial lung biopsy, the Envisia Genomic Classifier, accurately predicted histopathologic UIP.
We evaluated the combined accuracy of the Envisia Genomic Classifier and local radiology in the detection of UIP pattern.
Ninety-six patients who had diagnostic lung pathology as well as a transbronchial lung biopsy for molecular testing with Envisia Genomic Classifier were included in this analysis. The classifier results were scored against reference pathology. UIP identified on high-resolution computed tomography (HRCT) as documented by features in local radiologists' reports was compared with histopathology.
In 96 patients, the Envisia Classifier achieved a specificity of 92.1% (confidence interval CI,78.6-98.3%) and a sensitivity of 60.3% (CI, 46.6-73.0%) for histology-proven UIP pattern. Local radiologists identified UIP in 18 of 53 patients with UIP histopathology, with a sensitivity of 34.0% (CI, 21.5-48.3%) and a specificity of 96.9% (CI, 83.8-100%). In conjunction with HRCT patterns of UIP, the Envisia Classifier results identified 24 additional patients with UIP (sensitivity 79.2%; specificity 90.6%).
In 96 patients with suspected interstitial lung disease, the Envisia Genomic Classifier identified UIP regardless of HRCT pattern. These results suggest that recognition of a UIP pattern by the Envisia Genomic Classifier combined with HRCT and clinical factors in a multidisciplinary discussion may assist clinicians in making an interstitial lung disease (especially IPF) diagnosis without the need for a surgical lung biopsy.
Cysts and cavities in the lung are commonly encountered on chest imaging. It is necessary to distinguish thin-walled lung cysts (≤2 mm) from cavities and characterize their distribution as focal or ...multifocal versus diffuse. Focal cavitary lesions are often caused by inflammatory, infectious, or neoplastic processes in contrast to diffuse cystic lung diseases. An algorithmic approach to diffuse cystic lung disease can help narrow the differential diagnosis, and additional testing such as skin biopsy, serum biomarkers, and genetic testing can be confirmatory. An accurate diagnosis is essential for the management and disease surveillance of extrapulmonary complications.
Usual interstitial pneumonia (UIP) is the histopathologic hallmark of idiopathic pulmonary fibrosis. Although UIP can be detected by high-resolution computed tomography of the chest, the results are ...frequently inconclusive, and pathology from transbronchial biopsy (TBB) has poor sensitivity. Surgical lung biopsy may be necessary for a definitive diagnosis.
To develop a genomic classifier in tissue obtained by TBB that distinguishes UIP from non-UIP, trained against central pathology as the reference standard.
Exome enriched RNA sequencing was performed on 283 TBBs from 84 subjects. Machine learning was used to train an algorithm with high rule-in (specificity) performance using specimens from 53 subjects. Performance was evaluated by cross-validation and on an independent test set of specimens from 31 subjects. We explored the feasibility of a single molecular test per subject by combining multiple TBBs from upper and lower lobes. To address whether classifier accuracy depends upon adequate alveolar sampling, we tested for correlation between classifier accuracy and expression of alveolar-specific genes.
The top-performing algorithm distinguishes UIP from non-UIP conditions in single TBB samples with an area under the receiver operator characteristic curve (AUC) of 0.86, with specificity of 86% (confidence interval = 71-95%) and sensitivity of 63% (confidence interval = 51-74%) (31 test subjects). Performance improves to an AUC of 0.92 when three to five TBB samples per subject are combined at the RNA level for testing. Although we observed a wide range of type I and II alveolar-specific gene expression in TBBs, expression of these transcripts did not correlate with classifier accuracy.
We demonstrate proof of principle that genomic analysis and machine learning improves the utility of TBB for the diagnosis of UIP, with greater sensitivity and specificity than pathology in TBB alone. Combining multiple individual subject samples results in increased test accuracy over single sample testing. This approach requires validation in an independent cohort of subjects before application in the clinic.
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