Association between renin-angiotensin system and chronic lung allograft dysfunction

Urine Measurements of the Renin-Angiotensin System-Regulated Proteins Predict Death and Graft Loss in Kidney Transplant Recipients Enrolled in a Ramipril versus Placebo Randomized Controlled Trial

The renin-angiotensin system (RAS) is involved in kidney fibrosis. We previously identified six RAS-regulated proteins (RHOB, BST1, LYPA1, GLNA, TSP1, and LAMB2) that were increased in the urine of patients with kidney allograft fibrosis, compared to patients without fibrosis. We hypothesized that these urinary RAS-regulated proteins predicted primary outcomes in kidney transplant recipients enrolled in the largest RAS inhibitor randomized controlled trial. Urine excretion of 10 peptides corresponding to the six RAS-regulated proteins was quantified using parallel reaction monitoring mass spectrometry assays (normalized by urine creatinine) in a subset of patients in the trial. Machine learning models predicting outcomes based on urine peptide excretion rates were developed and evaluated. Urine samples (n = 111) from 56 patients were collected at 0, 6, 12, and 24 months. Twenty-four primary outcomes (doubling of serum creatinine, graft loss, or death) occurred in 17 patients. Logistic regression utilizing eight peptides of TSP1, BST1, LAMB2, LYPA1, and RHOB, from the last urine sample prior to outcomes, predicted a graft loss with an AUC of 0.78 (p = 0.00001). A random forest classifier utilizing BST1 and LYPA1 peptides predicted death with an AUC of 0.80 (p = 0.0016). Urine measurements of RAS-regulated proteins may predict outcomes in kidney transplant recipients, although further prospective studies are required.

A Rapid Human Lung Tissue Dissociation Protocol Maximizing Cell Yield and Minimizing Cellular Stress

The human lung is a complex organ that comprises diverse populations of epithelial, mesenchymal, vascular, and immune cells, which gains even greater complexity during disease states. To effectively study the lung at a single-cell level, a dissociation protocol that achieves the highest yield of viable cells of interest with minimal dissociation-associated protein or transcription changes is key. Here, we detail a rapid collagenase-based dissociation protocol (Col-Short) that provides a high-yield single-cell suspension that is suitable for a variety of downstream applications. Diseased human lung explants were obtained and dissociated through the Col-Short protocol and compared with four other dissociation protocols. Resulting single-cell suspensions were then assessed with flow cytometry, differential staining, and quantitative real-time PCR to identify major hematopoietic and nonhematopoietic cell populations, as well as their activation states. We observed that the Col-Short protocol provides the greatest number of cells per gram of lung tissue, with no reduction in viability when compared with previously described dissociation protocols. Col-Short had no observable surface protein marker cleavage as well as lower expression of protein activation markers and stress-related transcripts compared with four other protocols. The Col-Short dissociation protocol can be used as a rapid strategy to generate single cells for respiratory cell biology research.

Predicting Primary Graft Dysfunction in Lung Transplantation: Machine Learning-Guided Biomarker Discovery

BACKGROUND –

There is an urgent need to better understand the pathophysiology of primary graft dysfunction (PGD) so that point-of-care methods can be developed to predict those at risk. Here we utilize a multiplex multivariable approach to define cytokine, chemokines, and growth factors in patient-matched biospecimens from multiple biological sites to identify factors predictive of PGD.

METHODS –

Biospecimens were collected from patients undergoing bilateral LTx from three distinct sites: donor lung perfusate, post-transplant bronchoalveolar lavage (BAL) fluid (2h), and plasma (2h and 24h). A 71-multiplex panel was performed on each biospecimen. Cross-validated logistic regression (LR) and random forest (RF) machine learning models were used to determine whether analytes in each site or from combination of sites, with or without clinical data, could discriminate between PGD grade 0 (n = 9) and 3 (n = 8).

RESULTS –

Using optimal AUROC, BAL fluid at 2h was the most predictive of PGD (LR, 0.825; RF, 0.919), followed by multi-timepoint plasma (LR, 0.841; RF, 0.653), then perfusate (LR, 0.565; RF, 0.448). Combined clinical, BAL, and plasma data yielded strongest performance (LR, 1.000; RF, 1.000). Using a LASSO of the predictors obtained using LR, we selected IL-1RA, BCA-1, and Fractalkine, as most predictive of severe PGD.

CONCLUSIONS –

BAL samples collected 2h post-transplant were the strongest predictors of severe PGD. Our machine learning approach not only identified novel cytokines not previously associated with PGD, but identified analytes that could be used as a point-of-care cytokine panel aimed at identifying those at risk for developing severe PGD.

Identification of novel pQTL-SNPs associated with lung adenocarcinoma risk: A multi-stage study

BACKGROUND AND OBJECTIVE

To explore the association between protein quantitative trait loci (pQTL-SNPs) and the risk of LUAD.

METHODS

"Blood +" high depth blood proteomics analysis was performed on plasma from female LUAD patients and female healthy controls, and combined with proteomics data from tumors and adjacent non-tumor tissues of female LUAD patients to screen proteins uniformly expressed in plasma and tissues. pQTL-SNPs were then screened through multiple databases and subjected to multilevel screening. The associations between selected pQTL-SNPs and LUAD risk were evaluated by Female Lung Cancer Consortium in Asia GWAS (FLCCA GWAS). Enzyme linked immunosorbent assay (ELISA) is used to determine the levels of candidate protein.

RESULTS

A total of 7 pQTL-SNPs were significantly associated with altered LUAD risk (p < 0.05). Meanwhile, the expression of their corresponding target proteins were all decreased in both plasma and tumor tissues of LUAD cases, which may play a role of tumor suppressor proteins. After mutation of 3 pQTL-SNPs (rs7683000, rs73224660, and rs2776937), the expression of corresponding target proteins BST1 and NRP1 decreased, and as potential tumor suppressor proteins, which may promote tumorigenesis and further increasing the risk of developing LUAD (OR >1, p < 0.05); while after mutation the other pQTL-SNP rs62069916, the corresponding target protein APOH expression was increased, while as a potential tumor suppressor protein, which may inhibit tumorigenesis and further reduced the risk of developing LUAD (OR <1, p < 0.05). In addition, the expression of NRP1 and APOH were significant decreased in LUAD cell lines and validated in plasma of LUAD patients.

CONCLUSION

A total of 4 pQTL-SNPs (rs7683000, rs73224660, rs2776937, and rs62069916) may associate with altered LUAD risk by regulating the expression of target proteins (BST1, NRP1, and APOH) after mutation.

Angiotensin II as a Vasopressor for Perioperative Hypotension in Solid Organ Transplant

During the perioperative period of transplantation, patients experience hypotension secondary to the side effects of anesthesia, surgical stress, inflammatory triggering, and intraoperative fluid shifts, among others causes. Vasopressor support, in this context, must reverse systemic hypotension, but ideally, the agents used should benefit allograft function and avoid the adverse events commonly seen after transplantation. Traditional therapies to reverse hypotension include catecholamine vasopressors (norepinephrine, epinephrine, dopamine, and phenylephrine), but their utility is limited when considering allograft complications and adverse events such as arrhythmias with agents with beta-adrenergic properties. Synthetic angiotensin II (AT2S-[Giapreza]) is a novel vasopressor indicated for distributive shock with a unique mechanism of action as an angiotensin receptor agonist restoring balance to an often-disrupted renin angiotensin aldosterone system. Additionally, AT2S provides a balanced afferent and efferent arteriole vasoconstriction at the level of the kidney and could avoid the arrhythmic complications of a beta-adrenergic agonist. While the data, to date, are limited, AT2S has demonstrated safety in case reports, pilot studies, and small series in the kidney, liver, heart, and lung transplant populations. There are physiologic and hemodynamic reasons why AT2S could be a more utilized agent in these populations, but further investigation is warranted.

Mass spectrometry-based proteomics for advancing solid organ transplantation research

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Metformin attenuates chronic lung allograft dysfunction: evidence in rat models

BACKGROUND

Chronic lung allograft dysfunction (CLAD) directly causes an abysmal long-term prognosis after lung transplantation (LTx), but effective and safe drugs are not available. Metformin exhibits high therapeutic potential due to its antifibrotic and immunomodulatory effects; however, it is unclear whether metformin exerts a therapeutic effect in CLAD. We sought to investigate the effect of metformin on CLAD based on rat models.

METHODS

Allogeneic LTx rats were treated with Cyclosporin A (CsA) in the first week, followed by metformin, CsA, or vehicle treatment. Syngeneic LTx rats received only vehicles. All rats were sacrificed on post-transplant week 4. Pathology of lung graft, spleen, and thymus, extent of lung fibrosis, activity of profibrotic cytokines and signaling pathway, adaptive immunity, and AMPK activity were then studied.

RESULTS

Allogeneic recipients without maintenance CsA treatment manifested CLAD pathological characteristics, but these changes were not observed in rats treated with metformin. For the antifibrotic effect, metformin suppressed the fibrosis extent and profibrotic cytokine expression in lung grafts. Regarding immunomodulatory effect, metformin reduced T- and B-cell infiltration in lung grafts, spleen and thymus weights, the T- and B-cell zone areas in the spleen, and the thymic medullary area. In addition, metformin activated AMPK in lung allografts and in α-SMA⁺ cells and T cells in the lung grafts.

CONCLUSIONS

Metformin attenuates CLAD in rat models, which could be attributed to the antifibrotic and immunomodulatory effects. AMPK activation suggests the potential molecular mechanism. Our study provides an experimental rationale for further clinical trials.

Biomarkers for Chronic Lung Allograft Dysfunction: Ready for Prime Time?

Chronic lung allograft dysfunction (CLAD) remains a major hurdle impairing lung transplant outcome. Parallel to the better clinical identification and characterization of CLAD and CLAD phenotypes, there is an increasing urge to find adequate biomarkers that could assist in the earlier detection and differential diagnosis of CLAD phenotypes, as well as disease prognostication. The current status and state-of-the-art of biomarker research in CLAD will be discussed with a particular focus on radiological biomarkers or biomarkers found in peripheral tissue, bronchoalveolar lavage' and circulating blood' in which significant progress has been made over the last years. Ultimately, although a growing number of biomarkers are currently being embedded in the follow-up of lung transplant patients, it is clear that one size does not fit all. The future of biomarker research probably lies in the rigorous combination of clinical information with findings in tissue, bronchoalveolar lavage' or blood. Only by doing so, the ultimate goal of biomarker research can be achieved, which is the earlier identification of CLAD before its clinical manifestation. This is desperately needed to improve the prognosis of patients with CLAD after lung transplantation.

Novel biomarkers of chronic lung allograft dysfunction: is there anything reliable?

PURPOSE OF REVIEW

Chronic lung allograft dysfunction (CLAD) remains a major barrier preventing long-term survival following lung transplantation. As our clinical knowledge regarding its definition and presentation has significantly improved over the last years, adequate biomarkers to predict development of CLAD, phenotype of CLAD or prognosis post-CLAD diagnosis are definitely needed.

RECENT FINDINGS

Radiological and physiological markers are gradually entering routine clinical practice. In-depth investigation of biological samples including broncho-alveolar lavage, biopsy and serum has generated potential biomarkers involved in fibrogenesis, airway injury and inflammation but none of these are universally accepted or implemented although progress has been made, specifically regarding donor-derived cell-free DNA and donor-specific antibodies.

SUMMARY

Although a lot of promising biomarkers have been put forward, a very limited number has made it to routine clinical practice. Nevertheless, a biomarker that leads to earlier detection or more adequate disease phenotyping would advance the field enormously.