A radiographic score for human donor lungs on ex vivo lung perfusion predicts transplant outcomes.

BACKGROUND: Ex vivo lung perfusion (EVLP) is an advanced platform for isolated lung assessment and treatment. Radiographs acquired during EVLP provide a unique opportunity to assess lung injury. The purpose of our study was to define and evaluate EVLP radiographic findings and their association with lung transplant outcomes. METHODS: We retrospectively evaluated 113 EVLP cases from 2020-21. Radiographs were scored by a thoracic radiologist blinded to outcome. Six lung regions were scored for 5 radiographic features (consolidation, infiltrates, atelectasis, nodules, and interstitial lines) on a scale of 0 to 3 to derive a score. Spearman's correlation was used to correlate radiographic scores to biomarkers of lung injury. Machine learning models were developed using radiographic features and EVLP functional data. Predictive performance was assessed using the area under the curve. RESULTS: Consolidation and infiltrates were the most frequent findings at 1 hour EVLP (radiographic lung score 2.6 (3.3) and 4.6 (4.3)). Consolidation (r = -0.536 and -0.608, p < 0.0001) and infiltrates (r = -0.492 and -0.616, p < 0.0001) were inversely correlated with oxygenation (∆pO2) at 1 hour and 3 hours of EVLP. First-hour consolidation and infiltrate lung scores predicted transplant suitability with an area under the curve of 87% and 88%, respectively. Prediction of transplant outcomes using a machine learning model yielded an area under the curve of 80% in the validation set. CONCLUSIONS: EVLP radiographs provide valuable insight into donor lungs being assessed for transplantation. Consolidation and infiltrates were the most common abnormalities observed in EVLP lungs, and radiographic lung scores predicted the suitability of donor lungs for transplant.

Airway pepsinogen A4 identifies lung transplant recipients with microaspiration and predicts chronic lung allograft dysfunction.

BACKGROUND: Aspiration is a known risk factor for adverse outcomes post-lung transplantation. Airway bile acids are the gold-standard biomarker of aspiration; however, they are released into the duodenum and likely reflect concurrent gastrointestinal dysmotility. Previous studies investigating total airway pepsin have found conflicting results on its relationship with adverse outcomes post-lung transplantation. These studies measured total pepsin and pepsinogen in the airways. Certain pepsinogens are constitutively expressed in the lungs, while others, such as pepsinogen A4 (PGA4), are not. We sought to evaluate the utility of measuring airway PGA4 as a biomarker of aspiration and predictor of adverse outcomes in lung transplant recipients (LTRs) early post-transplant. METHODS: Expression of PGA4 was compared to other pepsinogens in lung tissue. Total pepsin and PGA4 were measured in large airway bronchial washings and compared to preexisting markers of aspiration. Two independent cohorts of LTRs were used to assess the relationship between airway PGA4 and chronic lung allograft dysfunction (CLAD). Changes to airway PGA4 after antireflux surgery were assessed in a third cohort of LTRs. RESULTS: PGA4 was expressed in healthy human stomach but not lung. Airway PGA4, but not total pepsin, was associated with aspiration. Airway PGA4 was associated with an increased risk of CLAD in two independent cohorts of LTRs. Antireflux surgery was associated with reduced airway PGA4. CONCLUSIONS: Airway PGA4 is a marker of aspiration that predicts CLAD in LTRs. Measuring PGA4 at surveillance bronchoscopies can help triage high-risk LTRs for anti-reflux surgery.

A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization.

Ex vivo lung perfusion (EVLP) is a data-intensive platform used for the assessment of isolated lungs outside the body for transplantation; however, the integration of artificial intelligence to rapidly interpret the large constellation of clinical data generated during ex vivo assessment remains an unmet need. We developed a machine-learning model, termed InsighTx, to predict post-transplant outcomes using n = 725 EVLP cases. InsighTx model AUROC (area under the receiver operating characteristic curve) was 79 ± 3%, 75 ± 4%, and 85 ± 3% in training and independent test datasets, respectively. Excellent performance was observed in predicting unsuitable lungs for transplantation (AUROC: 90 ± 4%) and transplants with good outcomes (AUROC: 80 ± 4%). In a retrospective and blinded implementation study by EVLP specialists at our institution, InsighTx increased the likelihood of transplanting suitable donor lungs [odds ratio=13; 95% CI:4-45] and decreased the likelihood of transplanting unsuitable donor lungs [odds ratio=0.4; 95%CI:0.16-0.98]. Herein, we provide strong rationale for the adoption of machine-learning algorithms to optimize EVLP assessments and show that InsighTx could potentially lead to a safe increase in transplantation rates.

Time to extubation for lung transplant recipients represents a pragmatic end-point to guide the development of prognostic tests.

The field of transplantation would benefit from the integration of advanced precision medicine techniques. Although predictive tests for lung transplantation require a well-defined clinical end-point, there exists no consensus regarding which outcomes are optimal end-points for these purposes. While many possible candidate end-points exist, we propose that time-to-extubation is an optimal end-point for prognostic tests because of its: clinical relevance; objectiveness; stability over time; and association with healthcare expenditure. Herein, we describe the rationale for this selection and present the limitations of alternative outcomes for this purpose. Using a 72-hour cut-off, time to extubation correlated well with Primary Graft Dysfunction Grade 3, intensive care unit and hospital length of stay, and a greater than 2-fold increase in healthcare cost ratios. Given that time-to-extubation is an objective measure that is readily measured by all lung transplant centers, this metric represents a preferred primary end-point for prognostic tests developed for lung transplantation.

Identification of regional variation in gene expression and inflammatory proteins in donor lung tissue and ex vivo lung perfusate.

OBJECTIVE: Diagnosing lung injury is a challenge in lung transplantation. It has been unclear if a single biopsy specimen is truly representative of the entire organ. Our objective was to investigate lung inflammatory biomarkers using human lung tissue biopsies and ex vivo lung perfusion perfusate. METHODS: Eight human donor lungs declined for transplantation were air inflated, flash frozen, and partitioned from apex to base. Biopsies were then sampled throughout the lung. Perfusate was sampled from 4 lung lobes in 8 additional donor lungs subjected to ex vivo lung perfusion. The levels of interleukin-6, interleukin-8, interleukin-10, and interleukin-1ß were measured using quantitative reverse transcription polymerase chain reaction from lung biopsies and enzyme-linked immunosorbent assay from ex vivo lung perfusion perfusate. RESULTS: The median intra-biopsy equal-variance P value was .50 for messenger RNA biomarkers in tissue biopsies. The median intra-biopsy coefficient of variance was 18%. In donors with no apparent focal injuries, the biopsies in each donor showed no difference in various lung slices, with a coefficient of variance of 20%. The exception was biopsies from the lingula and injured focal areas that demonstrated larger differences. Cytokines in ex vivo lung perfusion perfusate showed minimal variation among different lobes (coefficient of variance = 4.9%). CONCLUSIONS: Cytokine gene expression in lung biopsies was consistent, and the biopsy analysis reflects the whole lung, except when specimens were collected from the lingula or an area of focal injury. Ex vivo lung perfusion perfusate also provides a representative measurement of lung inflammation from the draining lobe. These results will reassure clinicians that a lung biopsy or an ex vivo lung perfusion perfusate sample can be used to inform donor lung selection.

Triaging donor lungs based on a microaspiration signature that predicts adverse recipient outcome.

BACKGROUND: Aspiration is a relative contraindication to accepting donor lungs for transplant and is currently assessed by visual inspection of the airways via bronchoscopy. However, this method is limited as it does not assess for microaspiration. Bile acids measured in large airway bronchial wash (LABW) samples have been shown to be a marker of aspiration in lung transplant recipients. Herein, we investigate the utility of measuring total bile acids (TBA) in donor LABW to predict performance of donor lungs and recipient outcomes. METHODS: TBA was measured in 605 consecutive lung donors at the Toronto Lung Transplant Program. TBA levels were compared in donor lungs deemed unsuitable for transplant, requiring further assessment on ex vivo lung perfusion (EVLP), and those suitable for direct transplantation using Mann-Whitney-U tests. Relationships between LABW TBA concentrations and recipient outcomes were evaluated using multivariable Cox-PH models and log-rank analysis. RESULTS: Donor TBA was highest in lungs deemed unsuitable for transplant and correlated with clinical assessment of aspiration. LABW TBA concentration correlated with calcium, decreased pH, and increased pro-inflammatory mediators in EVLP perfusate. TBA cut-off of 1245 nM was able to differentiate donor lungs directly declined from those suitable for direct transplantation with a 91% specificity (AUROC: 73%). High donor TBA status was associated with the increased rate of primary graft dysfunction, longer time to extubation, and shorter time to chronic lung allograft dysfunction. CONCLUSIONS: In a large retrospective cohort, we observed that donor LABW TBA was associated with suitability of donor lungs for transplant, performance of the organ on EVLP, and adverse recipient outcomes.

Testing the delivery of human organ transportation with drones in the real world.

Last-mile transportation of human donor lungs in a densely populated urban environment has been made possible with drones.

A biomarker assay to risk-stratify patients with symptoms of respiratory tract infection.

BACKGROUND: Patients who present to an emergency department (ED) with respiratory symptoms are often conservatively triaged in favour of hospitalisation. We sought to determine if an inflammatory biomarker panel that identifies the host response better predicts hospitalisation in order to improve the precision of clinical decision making in the ED. METHODS: From April 2020 to March 2021, plasma samples of 641 patients with symptoms of respiratory illness were collected from EDs in an international multicentre study: Canada (n=310), Italy (n=131) and Brazil (n=200). Patients were followed prospectively for 28 days. Subgroup analysis was conducted on confirmed coronavirus disease 2019 (COVID-19) patients (n=245). An inflammatory profile was determined using a rapid, 50-min, biomarker panel (RALI-Dx (Rapid Acute Lung Injury Diagnostic)), which measures interleukin (IL)-6, IL-8, IL-10, soluble tumour necrosis factor receptor 1 (sTNFR1) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1). RESULTS: RALI-Dx biomarkers were significantly elevated in patients who required hospitalisation across all three sites. A machine learning algorithm that was applied to predict hospitalisation using RALI-Dx biomarkers had a mean±sd area under the receiver operating characteristic curve of 76±6% (Canada), 84±4% (Italy) and 86±3% (Brazil). Model performance was 82±3% for COVID-19 patients and 87±7% for patients with a confirmed pneumonia diagnosis. CONCLUSIONS: The rapid diagnostic biomarker panel accurately identified the need for inpatient care in patients presenting with respiratory symptoms, including COVID-19. The RALI-Dx test is broadly and easily applicable across many jurisdictions, and represents an important diagnostic adjunct to advance ED decision-making protocols.

Utility of bile acids in large airway bronchial wash versus bronchoalveolar lavage as biomarkers of microaspiration in lung transplant recipients: a retrospective cohort study.

BACKGROUND: Bronchoalveolar lavage (BAL) is a key tool in respiratory medicine for sampling the distal airways. BAL bile acids are putative biomarkers of pulmonary microaspiration, which is associated with poor outcomes after lung transplantation. Compared to BAL, large airway bronchial wash (LABW) samples the tracheobronchial space where bile acids may be measurable at more clinically relevant levels. We assessed whether LABW bile acids, compared to BAL bile acids, are more strongly associated with poor clinical outcomes in lung transplant recipients. METHODS: Concurrently obtained BAL and LABW at 3 months post-transplant from a retrospective cohort of 61 lung transplant recipients were analyzed for taurocholic acid (TCA), glycocholic acid (GCA), and cholic acid by mass spectrometry and 10 inflammatory proteins by multiplex immunoassay. Associations between bile acids with inflammatory proteins and acute lung allograft dysfunction were assessed using Spearman correlation and logistic regression, respectively. Time to chronic lung allograft dysfunction and death were evaluated using multivariable Cox proportional hazards and Kaplan-Meier methods. RESULTS: Most bile acids and inflammatory proteins were higher in LABW than in BAL. LABW bile acids correlated with inflammatory proteins within and between sample type. LABW TCA and GCA were associated with acute lung allograft dysfunction (OR = 1.368; 95%CI = 1.036-1.806; P = 0.027, OR = 1.064; 95%CI = 1.009-1.122; P = 0.022, respectively). No bile acids were associated with chronic lung allograft dysfunction. Adjusted for risk factors, LABW TCA and GCA predicted death (HR = 1.513; 95%CI = 1.014-2.256; P = 0.042, HR = 1.597; 95%CI = 1.078-2.366; P = 0.020, respectively). Patients with LABW TCA in the highest tertile had worse survival compared to all others. CONCLUSIONS: LABW bile acids are more strongly associated than BAL bile acids with inflammation, acute lung allograft dysfunction, and death in lung transplant recipients. Collection of LABW may be useful in the evaluation of microaspiration in lung transplantation and other respiratory diseases.

Prediction of donor related lung injury in clinical lung transplantation using a validated ex vivo lung perfusion inflammation score.

BACKGROUND: Ex vivo lung perfusion (EVLP) is an isolated organ assessment technique that has revolutionized the field of lung transplantation and enabled a safe increase in the number of organs transplanted. The objective of this study was to develop a protein-based assay that would provide a precision medicine approach to lung injury assessment during EVLP. METHODS: Perfusate samples collected from clinical EVLP cases performed from 2009 to 2019 were separated into development (n = 281) and validation (n = 57) sets to derive and validate an inflammation score based on IL-6 and IL-8 protein levels in perfusate. The ability of an inflammation score to predict lungs suitable for transplantation and likely to produce excellent recipient outcomes (time on ventilator ≤ 3 days) was assessed. Inflammation scores were compared to conventional clinical EVLP assessment parameters and associated with outcomes, including primary graft dysfunction and patient care in the ICU. RESULTS: An inflammation score accurately predicted the decision to transplant (AUROC 68% [95% CI 62-74]) at the end of EVLP and those transplants associated with short ventilator times (AUROC 73% [95% CI 66-80]). The score identified lungs more likely to develop primary graft dysfunction at 72-hours post-transplant (OR 4.0, p = 0.03). A model comprised of the inflammation score and ∆PO2 was able to determine EVLP transplants that were likely to have excellent recipient outcomes, with an accuracy of 87% [95% CI 83-92]. CONCLUSIONS: The adoption of an inflammation score will improve accuracy of EVLP decision-making and increase confidence of surgical teams to determine lungs that are suitable for transplantation, thereby improving organ utilization rates and patient outcomes.

Bronchoalveolar bile acid and inflammatory markers to identify high-risk lung transplant recipients with reflux and microaspiration.

BACKGROUND: Gastroesophageal reflux disease (GERD) is a risk factor for chronic lung allograft dysfunction. Bile acids-putative markers of gastric microaspiration-and inflammatory proteins in the bronchoalveolar lavage (BAL) have been associated with chronic lung allograft dysfunction, but their relationship with GERD remains unclear. Although GERD is thought to drive chronic microaspiration, the selection of patients for anti-reflux surgery lacks precision. This multicenter study aimed to test the association of BAL bile acids with GERD, lung inflammation, allograft function, and anti-reflux surgery. METHODS: We analyzed BAL obtained during the first post-transplant year from a retrospective cohort of patients with and without GERD, as well as BAL obtained before and after Nissen fundoplication anti-reflux surgery from a separate cohort. Levels of taurocholic acid (TCA), glycocholic acid, and cholic acid were measured using mass spectrometry. Protein markers of inflammation and injury were measured using multiplex assay and enzyme-linked immunosorbent assay. RESULTS: At 3 months after transplantation, TCA, IL-1ß, IL-12p70, and CCL5 were higher in the BAL of patients with GERD than in that of no-GERD controls. Elevated TCA and glycocholic acid were associated with concurrent acute lung allograft dysfunction and inflammatory proteins. The BAL obtained after anti-reflux surgery contained reduced TCA and inflammatory proteins compared with that obtained before anti-reflux surgery. CONCLUSIONS: Targeted monitoring of TCA and selected inflammatory proteins may be useful in lung transplant recipients with suspected reflux and microaspiration to support diagnosis and guide therapy. Patients with elevated biomarker levels may benefit most from anti-reflux surgery to reduce microaspiration and allograft inflammation.

Using the inherent chemistry of the endothelin-1 peptide to develop a rapid assay for pre-transplant donor lung assessment.

Endothelin-1 is a potent vasoconstrictive peptide that plays an important role in ex vivo lung perfusion. ET-1 expression levels are predictive of lung transplant outcomes and represent a valuable monitoring tool for surgeons; however, traditional techniques that measure [ET-1] are not suitable for the transplant setting. Herein, we demonstrate a new assay that rapidly measures ET-1 peptide levels in lung perfusate.

Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

Biomarker profiling is being rapidly incorporated in many areas of modern medical practice to improve the precision of clinical decision-making. This potential improvement, however, has not been transferred to the practice of organ assessment and transplantation because previously developed gene-profiling techniques require an extended period of time to perform, making them unsuitable in the time-sensitive organ assessment process. We sought to develop a novel class of chip-based sensors that would enable rapid analysis of tissue levels of preimplantation mRNA markers that correlate with the development of primary graft dysfunction (PGD) in recipients after transplant. Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies. A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung. Thus, the FraCS-based approach delivers a key predictive value test that could be applied to enhance transplant patient outcomes. This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

Effect of microelectrode structure on electrocatalysis at nucleic acid-modified sensors.

The electrochemical detection of nucleic acids using an electrocatalytic reporter system and nanostructured microelectrodes is a powerful approach to ultrasensitive biosensing. In this report we systematically study for the first time the behavior of an electrocatalytic reporter system at nucleic acid-modified electrodes with varying structures and sizes. [Ru(NH3)6](3+) is used as a primary electron acceptor that is electrostatically attracted to nucleic acid-modified electrodes, and [Fe(CN)6](3-) is introduced into the redox system as a secondary electron acceptor to regenerate Ru(3+) after electrochemical reduction. We found that the electrode structure has strong impact on mass transport and electron-transfer kinetics, with structures of specific dimensions yielding much higher electrochemical signals and catalytic efficiencies. The electrocatalytic signals obtained when gold sensors were electrodeposited in both circular and linear apertures were studied, and the smallest structures plated in linear apertures were found to exhibit the best performance with high current densities and turnover rates. This study provides important information for optimal assay performance and insights for the future design and fabrication of high performance biomolecular assays.

Ultrasensitive electrochemical biomolecular detection using nanostructured microelectrodes.

Electrochemical sensors have the potential to achieve sensitive, specific, and low-cost detection of biomolecules--a capability that is ever more relevant to the diagnosis and monitored treatment of disease. The development of devices for clinical diagnostics based on electrochemical detection could provide a powerful solution for the routine use of biomarkers in patient treatment and monitoring and may overcome the many issues created by current methods, including the long sample-to-answer times, high cost, and limited prospects for lab-free use of traditional polymerase chain reaction, microarrays, and gene-sequencing technologies. In this Account, we summarize the advances in electrochemical biomolecular detection, focusing on a new and integrated platform that exploits the bottom-up fabrication of multiplexed electrochemical sensors composed of electrodeposited noble metals. We trace the evolution of these sensors from gold nanoelectrode ensembles to nanostructured microelectrodes (NMEs) and discuss the effects of surface morphology and size on assay performance. The development of a novel electrocatalytic assay based on Ru(3+) adsorption and Fe(3+) amplification at the electrode surface as a means to enable ultrasensitive analyte detection is discussed. Electrochemical measurements of changes in hybridization events at the electrode surface are performed using a simple potentiostat, which enables integration into a portable, cost-effective device. We summarize the strategies for proximal sample processing and detection in addition to those that enable high degrees of sensor multiplexing capable of measuring 100 different analytes on a single chip. By evaluating the cost and performance of various sensor substrates, we explore the development of practical lab-on-a-chip prototype devices. By functionalizing the NMEs with capture probes specific to nucleic acid, small molecule, and protein targets, we can successfully detect a wide variety of analytes at clinically relevant concentrations and speeds. Using this platform, we have achieved attomolar detection levels of nucleic acids with overall assay times as short as 2 min. We also describe the adaptation of the sensing platform to allow for the measurement of uncharged analytes--a challenge for reporter systems that rely on the charge of an analyte. Furthermore, the capabilities of this system have been applied to address the many current and important clinical challenges involving the detection of pathogenic species, including both bacterial and viral infections and cancer biomarkers. This novel electrochemical platform, which achieves large molecular-to-electrical amplification by means of its unique redox-cycling readout strategy combined with rapid and efficient analyte capture that is aided by nanostructured microelectrodes, achieves excellent specificity and sensitivity in clinical samples in which analytes are present at low concentrations in complex matrices.

Metabolic syndrome and acute hyperglycemia are associated with endoplasmic reticulum stress in human mononuclear cells.

Endoplasmic reticulum (ER) stress and the activation of the unfolded protein response (UPR) have been implicated in a number of complications associated with diabetes mellitus including micro- and macrovascular dysfunction. In this study we examine ER stress levels in blood cells isolated from human subjects with metabolic syndrome and in healthy controls. Total RNA and protein were isolated from leukocytes and the levels of specific ER stress markers were quantified by real-time-PCR and immunoblot analysis. Our results indicate that, compared to healthy controls, individuals with metabolic syndrome have elevated mRNA levels of genes indicative of ER stress; including spliced XBP-1 (sXBP-1), Grp78, and CHOP. Induced ER stress levels correlate with blood glucose but not plasma lipid concentration. Furthermore, in healthy individuals, a standard 75 g oral glucose challenge produced a significant elevation in spliced XBP-1 (1.3 fold), Grp78 (2.0 fold), and calreticulin (3.5 fold) mRNA 60 min post challenge and a significant increase in Grp78 (2.0 fold), calreticulin (2.7 fold) protein levels 2 h postchallenge, relative to fasting levels. The UPR was also activated ex vivo, in human leukocytes cultured in the presence of 15 mmol/l glucose, supporting a specific role for glucose. The oral glucose challenge was associated with a significant increase in the expression of inflammatory cytokines, including interleukin (IL)-1α/ß, IL-6, and IL-8, that may result from ER stress. These findings suggest that there is an association between both acute and chronic dysglycemia and ER stress in humans.

Hexosamine biosynthesis pathway flux promotes endoplasmic reticulum stress, lipid accumulation, and inflammatory gene expression in hepatic cells.

There is increasing evidence that endoplasmic reticulum (ER) stress contributes to the development of atherosclerosis in diabetes mellitus. The purpose of this study was to determine the effects of increased hexosamine biosynthesis pathway (HBP) flux on ER stress levels and the complications of ER stress associated with diabetes and atherosclerosis in hepatic cells. Glutamine:fructose-6-phosphate amidotransferase (GFAT), the rate-limiting enzyme of the HBP, was overexpressed in HepG2 cells by use of an adenoviral expression system. The ER stress response and downstream effects, including activation of lipid and inflammatory pathways, were determined using real-time PCR, immunoblot analysis, and cell staining techniques. GFAT overexpression resulted in increased expression of ER stress markers, including Grp78, Grp94, calreticulin, and GADD153, relative to cells infected with an empty adenoviral vector. In addition, GFAT overexpression promoted lipid, but not cholesterol, accumulation in hepatic cells as well as inflammatory pathway activation. Treatment with 6-diazo-5-oxo-norleucine, a GFAT antagonist, blocked the effects of GFAT overexpression. Consistent with our in vitro data, hyperglycemic mice presented with elevated markers of hepatic ER stress, glucosamine and lipid accumulation. Together, these data suggest that HBP flux-induced ER stress plays a role in the development of hepatic steatosis and atherosclerosis under conditions of hyperglycemia.