Association studies between COVID-19 and SSc-ILD

Severe COVID-19 patients may develop pulmonary fibrosis, similar to SSc-ILD disease, suggesting a potential link between the two diseases. However, there are limited treatment options for SSc-ILD-type diseases. Therefore, investigating pathological markers of the two diseases can provide valuable insights for treating related conditions. RNA sequencing technology offers high throughput and precision. However, the bimodal nature of RNA-Seq data cannot be accurately captured by commonly used algorithms such as DESeq2. To address this issue, the Beta-Poisson model has been developed to identify differentially expressed genes. Unlike the classical DESeq2 algorithm, the Beta-Poisson model introduces a Beta distribution to construct a new hybrid distribution in place of the Gamma distribution of the Gamma-Poisson distribution, effectively characterizing the bimodal features of RNA-Seq data. The transcriptomes of SARS-CoV infection and SSc-ILD disease in the lung epithelial cell dataset were analyzed to identify common differentially expressed genes of SARS-CoV and SSc-ILD disease. Gene function and signaling pathway enrichment analysis and protein-protein interaction (PPI) network were used to identify common pathways and drug targets for SSc-ILD with COVID-19 infection. The results show that there are 50 differentially expressed genes in common between COVID-19 and SSC-ILD. The functions of these genes are mainly enriched in immune system response, interferon signaling pathway and other related signaling pathways, and enriched in biological processes such as cell defense response to virus and interferon regulation. Based on the detection of hub genes based on PPIs network, it is predicted that STAT1, ISG15, IRF7, MX1, EIF2AK2, DDX58, OAS1, OAS2, IFIT1 and IFIT3 are the key genes involved in the pathological phenotype of the two diseases. Based on the key genes, the interaction of transcription factor (TF) and miRNA with common differentially expressed genes is also identified. The possible pathological markers of the two diseases and related molecular regulatory mechanisms of disease treatment are revealed to provide theoretical basis for the treatment of the two diseases. © 2023 Editorial Office of Journal of Shenzhen University. All rights reserved.

Patients with interstitial lung disease are high-risk of COVID-19 morbidity with implications on access to early oral anti-viral treatments

Introduction/Aim: Patients with interstitial lung disease (ILD) are at higher risk of COVID-19 infection associated morbidity and mortality, and hence may benefit from early anti-viral therapy. The access criteria for early oral anti-viral therapies for COVID-19 varied in early 2022 due to limited supplies nationally. We created a live clinical database of ILD patients in a tertiary hospital setting, stratifying them by measurable risk factors and therefore accessibility by state or national criteria to anti-viral therapy. Method(s): A list of active ILD clinic patients was generated from the WEBPAS clinic database. Data on patient demographics, co-morbidities and immunosuppressive medications relevant to access to anti-viral medications via the PBS criteria and state-based criteria was gathered by medical records review. Demographic information included age, BMI, ethnicity, residential care living and rurality. Co-morbidity risk factors included congestive cardiac failure, neurological disease, diabetes mellitus, chronic kidney disease, liver cirrhosis, chronic lung disease and immunodeficiencies. Medications of relevance included glucocorticoids, steroid-sparing immunomodulators and chemotherapy. Combinations of the above risk factors equate to eligibility to treatment. Result(s): Between the data capture dates of 1 February 2021 and 31 January 2022, 526 patients were identified. Of these 457 fit the inclusion criteria. Median age was 71.4 years (range 20-92), ratio of F:M was 1.09. 11% of patients were on long term oxygen therapy. Commonest conditions were idiopathic pulmonary fibrosis (26.3%), connective-tissue disease ILD (18%) and sarcoidosis (13.4%). 92 (20%) of patients fit into 'moderate or severely immunocompromised' criteria. 346 (75%) of patients fit criteria for early anti-virals by the first iteration of PBS criteria. Using the second iteration of PBS criteria, 374 (82%) of the ILD patients fit criteria for early anti-viral treatment. Notably, some patients qualify for anti-virals on multiple eligibility PBS criteria. Conclusion(s): A large proportion of our ILD cohort is deemed 'high risk' for COVID-19 morbidity and would qualify for early anti-viral therapies (regardless of vaccination status).

Severe COVID-19 pneumonia leads to post-COVID-19 lung abnormalities on follow-up CT scans.

Purpose: To investigate the association of the maximal severity of pneumonia on CT scans obtained within 6-week of diagnosis with the subsequent development of post-COVID-19 lung abnormalities (Co-LA). Methods: COVID-19 patients diagnosed at our hospital between March 2020 and September 2021 were studied retrospectively. The patients were included if they had (1) at least one chest CT scan available within 6-week of diagnosis; and (2) at least one follow-up chest CT scan available ≥ 6 months after diagnosis, which were evaluated by two independent radiologists. Pneumonia Severity Categories were assigned on CT at diagnosis according to the CT patterns of pneumonia and extent as: 1) no pneumonia (Estimated Extent, 0%); 2) non-extensive pneumonia (GGO and OP, <40%); and 3) extensive pneumonia (extensive OP and DAD, >40%). Co-LA on follow-up CT scans, categorized using a 3-point Co-LA Score (0, No Co-LA; 1, Indeterminate Co-LA; and 2, Co-LA). Results: Out of 132 patients, 42 patients (32%) developed Co-LA on their follow-up CT scans 6-24 months post diagnosis. The severity of COVID-19 pneumonia was associated with Co-LA: In 47 patients with extensive pneumonia, 33 patients (70%) developed Co-LA, of whom 18 (55%) developed fibrotic Co-LA. In 52 with non-extensive pneumonia, 9 (17%) developed Co-LA: In 33 with no pneumonia, none (0%) developed Co-LA. Conclusions: Higher severity of pneumonia at diagnosis was associated with the increased risk of development of Co-LA after 6-24 months of SARS-CoV-2 infection.

Present and future perspectives in early diagnosis and monitoring for progressive fibrosing interstitial lung diseases.

Progressive fibrosing interstitial lung diseases (PF-ILDs) represent a group of conditions of both known and unknown origin which continue to worsen despite standard treatments, leading to respiratory failure and early mortality. Given the potential to slow down progression by initiating antifibrotic therapies where appropriate, there is ample opportunity to implement innovative strategies for early diagnosis and monitoring with the goal of improving clinical outcomes. Early diagnosis can be facilitated by standardizing ILD multidisciplinary team (MDT) discussions, implementing machine learning algorithms for chest computed-tomography quantitative analysis and novel magnetic-resonance imaging techniques, as well as measuring blood biomarker signatures and genetic testing for telomere length and identification of deleterious mutations in telomere-related genes and other single-nucleotide polymorphisms (SNPs) linked to pulmonary fibrosis such as rs35705950 in the MUC5B promoter region. Assessing disease progression in the post COVID-19 era also led to a number of advances in home monitoring using digitally-enabled home spirometers, pulse oximeters and other wearable devices. While validation for many of these innovations is still in progress, significant changes to current clinical practice for PF-ILDs can be expected in the near future.

Diagnosing interstitial lung disease by multidisciplinary discussion: A review.

The multidisciplinary meeting (MDM) has been endorsed in current international consensus guidelines as the gold standard method for diagnosis of interstitial lung disease (ILD). In the absence of an accurate and reliable diagnostic test, the agreement between multidisciplinary meetings has been used as a surrogate marker for diagnostic accuracy. Although the ILD MDM has been shown to improve inter-clinician agreement on ILD diagnosis, result in a change in diagnosis in a significant proportion of patients and reduce unclassifiable diagnoses, the ideal form for an ILD MDM remains unclear, with constitution and processes of ILD MDMs varying greatly around the world. It is likely that this variation of practice contributes to the lack of agreement seen between MDMs, as well as suboptimal diagnostic accuracy. A recent Delphi study has confirmed the essential components required for the operation of an ILD MDM. The ILD MDM is a changing entity, as it incorporates new diagnostic tests and genetic markers, while also adapting in its form in response to the obstacles of the COVID-19 pandemic. The aim of this review was to evaluate the current evidence regarding ILD MDM and their role in the diagnosis of ILD, the practice of ILD MDM around the world, approaches to ILD MDM standardization and future directions to improve diagnostic accuracy in ILD.

Chapter 7 - Using Limited Memory Lung CT AI to Derive Advanced Quantitative CT Lung Metrics of COPD, ILD, and COVID-19 Pneumonia

In this chapter, we discuss the use of limited memory AI computer programs in lung CT AI for the assessment of normal and diseased lung tissue. Limited memory AI methods were discussed in Chapter 4 in the assessment of pulmonary nodules. Limited memory AI programs go beyond the reactive machine AI methods that were discussed in Chapters 5 and 6. Lung CT AI methods that use limited memory AI can detect and assess lung disease from COPD, ILD, and COVID-19 pneumonia in ways that reactive machine AI methods cannot. Lung CT AI using limited memory AI can detect and assess different lung CT texture patterns in patients with ILD including ground-glass opacities, reticulations, and honeycombing. Limited memory AI methods applied to lung CT AI can detect and distinguish different texture patterns of emphysema in COPD patients better than visual CT methods. Limited memory lung CT AI can detect, assess, and distinguish COVID-19 viral pneumonia from other forms of pneumonia.

Chapter 5 - Using Reactive Machine AI to Derive Quantitative Lung CT Metrics of COPD, ILD, and COVID-19 Pneumonia

This chapter will build on the lung CT AI approaches to lung nodules that were described in Chapter 4. In this chapter, we will describe the basic structure of the normal human lung and how emphysema from COPD decreases lung density that can be detected and assessed using reactive machine lung CT AI methods. Pulmonary fibrosis from ILD increases lung density as does acute viral pneumonia, such as COVID-19, and this increase in lung density can be detected and assessed using reactive machine-type lung CT AI methods. Four main steps in implementing lung CT AI to assess normal and abnormal structure in the human lung will be discussed;these include high-quality chest CT, segmenting the lung, extracting quantitative CT (QCT) features from the lung, using the QCT features to detect and assess diffuse lung disease. This chapter focuses on structural abnormalities of the lung that can be determined using a single chest CT scan of both lungs that is obtained at total lung capacity (TLC).

Automated Pneumonia Based Lung Diseases Classification with Robust Technique Based on a Customized Deep Learning Approach.

Many people have been affected by infectious lung diseases (ILD). With the outbreak of the COVID-19 disease in the last few years, many people have waited for weeks to recover in the intensive care wards of hospitals. Therefore, early diagnosis of ILD is of great importance to reduce the occupancy rates of health institutions and the treatment time of patients. Many artificial intelligence-based studies have been carried out in detecting and classifying diseases from medical images using imaging applications. The most important goal of these studies was to increase classification performance and model reliability. In this approach, a powerful algorithm based on a new customized deep learning model (ACL model), which trained synchronously with the attention and LSTM model with CNN models, was proposed to classify healthy, COVID-19 and Pneumonia. The important stains and traces in the chest X-ray (CX-R) image were emphasized with the marker-controlled watershed (MCW) segmentation algorithm. The ACL model was trained for different training-test ratios (90-10%, 80-20%, and 70-30%). For 90-10%, 80-20%, and 70-30% training-test ratios, accuracy scores were 100%, 96%, and 96%, respectively. The best performance results were obtained compared to the existing methods. In addition, the contribution of the strategies utilized in the proposed model to classification performance was analyzed in detail. Deep learning-based applications can be used as a useful decision support tool for physicians in the early diagnosis of ILD diseases. However, for the reliability of these applications, it is necessary to undertake verification with many datasets.

Post COVID-19 organizing pneumonia treated with mycophenolate mofetil.

Organizing pneumonia (OP) promptly responds to corticosteroids. However, a minority of patients demonstrate corticosteroid resistance or relapse on corticosteroid tapering. We describe post COVID-19 OP patients with clinically inadequate response to corticosteroids but that improved after the addition of Mycophenolate Mofetil (MMF). Case 1: A gentleman was diagnosed with post COVID-19 OP but had suboptimal clinico-physiologic-radiologic response and steroid toxicity during outpatient reviews. MMF was initiated resulting in marked clinical response and quick weaning from corticosteroids. Case 2: A gentleman with post COVID-19 OP relapsed during tapering of steroids. Clarithromycin and MMF were added to his regimen, which improved his clinico-physiologic parameters and allowed corticosteroid tapering. Unfortunately, he developed MMF-related colitis needing therapy cessation. Currently, no studies have reported on MMF utilization in difficult post COVID-19 OP patients. Nevertheless, we believe, similar as in non-COVID OPs, MMF or other immunomodulators, potentially have a role in treating difficult or steroid-resistant OPs.

A Delphi consensus statement for the management of post-COVID interstitial lung disease.

INTRODUCTION: As millions of people worldwide recover from COVID-19, a substantial proportion continue to have persistent symptoms, pulmonary function abnormalities, and radiological findings suggestive of post-COVID interstitial lung disease (ILD). To date, there is limited scientific evidence on the management of post-COVID ILD, necessitating a consensus-based approach. AREAS COVERED: A panel of experts in pulmonology and thoracic radiology was constituted. Key questions regarding the management of post-COVID ILD were identified. A search was performed on PubMed and EMBASE and updated till 1 March 2022. The relevant literature regarding the epidemiology, pathophysiology, diagnosis and treatment of post-COVID ILD was summarized. Subsequently, suggestions regarding the management of these patients were framed, and a consensus was obtained using the Delphi approach. Those suggestions which were approved by over 80% of the panelists were accepted. The final document was approved by all panel members. EXPERT OPINION: Dedicated facilities should be established for the care of patients with post-COVID ILD. Symptom screening, pulmonary function testing, and thoracic imaging have a role in the diagnosis. The pharmacologic and non-pharmacologic options for the management of post-COVID ILD are discussed. Further research into the pathophysiology and management of post-COVID ILD will improve our understanding of this condition.

MR Imaging for the Evaluation of Diffuse Lung Disease: Where Are We?

Patients with diffuse lung diseases require thorough medical and social history and physical examinations, coupled with a multitude of laboratory tests, pulmonary function tests, and radiologic imaging to discern and manage the specific disease. This review summarizes the current state of imaging of various diffuse lung diseases by hyperpolarized MR imaging. The potential of hyperpolarized MR imaging as a clinical tool is outlined as a novel imaging approach that enables further understanding of the cause of diffuse lung diseases, permits earlier detection of disease progression before that found with pulmonary function tests, and can delineate physiologic response to lung therapies.

Antisynthetase Syndrome Post Shingrix and Pneumovax Vaccinations, Possible Correlation.

This is a case report of a patient who developed acute progressive shortness of breath that started two days following the administration of Shingrix and Pneumovax vaccinations. Eight days after the onset of his symptoms he was diagnosed with acute interstitial pneumonitis based on CT scan of the chest which later appeared to be consistent with the diagnosis of antisynthetase syndrome in light of findings consistent with mechanic's hands on examination, elevated Anti-Jo-1 antibody titers and aldolase on laboratory studies.

Combination of acute exacerbation of idiopathic nonspecific interstitial pneumonia and pulmonary embolism after booster anti-COVID-19 vaccination.

Coronavirus disease-2019 (COVID-19) is a systemic disorder with the lung and the vasculature being the preferred targets. Patients with interstitial lung diseases represent a category at high risk of progression in the case of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 infection, and as such deserve special attention. We first describe the combination of acute exacerbation and pulmonary embolism in an elderly ILD patient after booster anti-COVID-19 mRNA vaccination. Vaccines availability had significantly and safety impacted COVID-19 morbidity and mortality worldwide. Immunization against COVID-19 is indisputable but must not be separated from the awareness of potential adverse effects in fragile patients.

Exploring the common pathophysiological links between IPF, SSc-ILD and post-COVID fibrosis.

In coronavirus disease 2019 (COVID-19) patients, dysregulated release of matrix metalloproteinases occurs during the inflammatory phase of acute respiratory distress syndrome (ARDS), resulting in epithelial and endothelial injury with excessive fibroproliferation. COVID-19 resembles idiopathic pulmonary fibrosis (IPF) in several aspects. The fibrotic response in IPF is driven primarily by an abnormally activated alveolar epithelial cells (AECs) which release cytokines to activate fibroblasts. Endoplasmic reticulum (ER) stress is postulated to be one of the early triggers in both diseases. Systemic sclerosis (SSc) is a heterogeneous autoimmune rare connective tissue characterised by fibrosis of the skin and internal organs. Interstitial lung disease (ILD) is a common complication and the leading cause of SSc-related death. Several corollaries have been discussed in this paper for new drug development based on the pathogenic events in these three disorders associated with pulmonary fibrosis. A careful consideration of the similarities and differences in the pathogenic events associated with the development of lung fibrosis in post-COVID patients, IPF patients and patients with SSc-ILD may pave the way for precision medicine. Several questions need to be answered through research, which include the potential role of antifibrotics in managing IPF, SSc-ILD and post-COVID fibrosis. Many trials that are underway will ultimately shed light on their potency and place in therapy.

Importance of Vaccination against SARS-CoV-2 in Patients with Interstitial Lung Disease Associated with Systemic Autoimmune Disease.

OBJECTIVES: To describe the frequency of COVID-19 and the effect of vaccination in patients with interstitial lung disease and systemic autoimmune disease (ILD-SAD) and to identify factors associated with infection and severity of COVID-19. METHODS: We performed a cross-sectional multicenter study of patients with ILD-SAD followed between June and October 2021. The main variable was COVID-19 infection confirmed by a positive polymerase chain reaction (PCR) result for SARS-CoV-2. The secondary variables included severity of COVID-19, if the patient had to be admitted to hospital or died of the disease, and vaccination status. Other variables included clinical and treatment characteristics, pulmonary function and high-resolution computed tomography. Two logistic regression was performed to explore factors associated with "COVID-19" and "severe COVID-19". RESULTS: We included 176 patients with ILD-SAD: 105 (59.7%) had rheumatoid arthritis, 49 (27.8%) systemic sclerosis, and 22 (12.54%) inflammatory myopathies. We recorded 22/179 (12.5%) SARS-CoV-2 infections, 7/22 (31.8%) of them were severe and 3/22 (13.22%) died. As to the vaccination, 163/176 (92.6%) patients received the complete doses. The factors associated with SARS-CoV-2 infection were FVC (OR (95% CI), 0.971 (0.946-0.989); p = 0.040), vaccination (OR (95% CI), 0.169 (0.030-0.570); p = 0.004), and rituximab (OR (95% CI), 3.490 (1.129-6.100); p = 0.029). The factors associated with severe COVID-19 were the protective effect of the vaccine (OR (95% CI), 0.024 (0.004-0.170); p < 0.001) and diabetes mellitus (OR (95% CI), 4.923 (1.508-19.097); p = 0.018). CONCLUSIONS: Around 13% of patients with ILD-SAD had SARS-CoV-2 infection, which was severe in approximately one-third. Most patients with severe infection were not fully vaccinated.

Lung Ultrasound as a First-Line Test in the Evaluation of Post-COVID-19 Pulmonary Sequelae.

Background: Interstitial lung sequelae are increasingly being reported in survivors of COVID-19 pneumonia. An early detection of these lesions may help prevent the development of irreversible lung fibrosis. Lung ultrasound (LUS) has shown high diagnostic accuracy in interstitial lung disease (ILD) and could likely be used as a first-line test for post-COVID-19 lung sequelae. Methods: Single-center observational prospective study. Follow-up assessments of consecutive patients hospitalized for COVID-19 pneumonia were conducted 2-5 months after the hospitalization. All patients underwent pulmonary function tests (PFTs), high-resolution computed tomography (HRCT), and LUS. Radiological alterations in HRCT were quantified using the Warrick score. The LUS score was obtained by evaluating the presence of pathological B-lines in 12 thoracic areas (range, 0-12). The correlation between the LUS and Warrick scores was analyzed. Results: Three hundred and fifty-two patients who recovered from COVID-19 pneumonia were recruited between July and September 2020. At follow-up, dyspnea was the most frequent symptom (69.3%). FVC and DLCO alterations were present in 79 (22.4%) and 234 (66.5%) patients, respectively. HRCT showed relevant interstitial lung sequelae (RILS) in 154 (43.8%) patients (Warrick score ≥ 7). The LUS score was strongly correlated with the HRCT Warrick score (r = 0.77) and showed a moderate inverse correlation with DLCO (r = -0.55). The ROC curve analysis revealed that a LUS score ≥ 3 indicated an excellent ability to discriminate patients with RILS (sensitivity, 94.2%; specificity, 81.8%; negative predictive value, 94.7%). Conclusions: LUS could be implemented as a first-line procedure in the evaluation of Post-COVID-19 interstitial lung sequelae. A normal LUS examination rules out the presence of these sequelae in COVID-19 survivors, avoiding the need for additional diagnostic tests such as HRCT.

[Clinical, radiological, and histopathological features of pulmonary post-COVID syndrome : A form of autoimmune-mediated interstitial lung disease?] / Klinische, radiologische und histopathologische Merkmale des pulmonalen Post-COVID-Syndroms : Eine Form der autoimmunvermittelten interstitiellen Lungenerkrankung?

BACKGROUND: About 10% of patients develop persistent symptoms after mild/moderate COVID-19. We have previously reported detection of antinuclear autoantibodies/extractable nuclear antigens (ANA/ENA) in patients with severe COVID-19. OBJECTIVES: The aim of this small pilot study was to characterize long-/post-COVID and to evaluate possible similarities between lung involvement in long-/post-COVID and connective tissue disease (CTD). METHODS: We prospectively enrolled 33 previously healthy patients with persistent pulmonal symptoms after mild/moderate COVID-19 without hospitalization (median age, 39 years). We performed clinical evaluation including pulmonary function tests, computed tomography (CT), and serology for ANA/ENA. In 29 of 33 patients, transbronchial biopsies (TBBs) were taken for histopathological assessment. RESULTS: Most patients presented with disturbed oxygen pulse in spiroergometry and slight lymphocytosis in bronchoalveolar lavage (BAL) fluid. The CT pattern showed bronchial wall thickening and increased low-attenuation volume. Autoantibodies were detected in 13 of 33 patients (39.4%). Histopathological assessment showed interstitial lymphocytosis with alveolar fibrin and organizing pneumonia. Ultrastructural analyses revealed interstitial collagen deposition. CONCLUSION: While histopathology of pulmonary long-/post-COVID alone is unspecific, the combination with clinical and radiological features together with detection of autoantibodies would allow for a diagnosis of interstitial pneumonia with autoimmune features (IPAF). Since we observe interstitial collagen deposition and since IPAF/CTD-ILD might progress to fibrosis, the persistence of autoantibodies and possible fibrotic change should be closely monitored in autoantibody-positive long-/post-COVID patients.