Comparison of multiplex meta analysis techniques for understanding the acute rejection of solid organ transplants

<p>Abstract</p> <p>Background</p> <p>Combining the results of studies using highly parallelized measurements of gene expression such as microarrays and RNAseq offer unique challenges in meta analysis. Motivated by a need for a deeper understanding of organ transplant rejection, we combine the data from five separate studies to compare acute rejection versus stability after solid organ transplantation, and use this data to examine approaches to multiplex meta analysis.</p> <p>Results</p> <p>We demonstrate that a commonly used parametric effect size estimate approach and a commonly used non-parametric method give very different results in prioritizing genes. The parametric method providing a meta effect estimate was superior at ranking genes based on our gold-standard of identifying immune response genes in the transplant rejection datasets.</p> <p>Conclusion</p> <p>Different methods of multiplex analysis can give substantially different results. The method which is best for any given application will likely depend on the particular domain, and it remains for future work to see if any one method is consistently better at identifying important biological signal across gene expression experiments.</p

In praise of arrays

Microarray technologies have both fascinated and frustrated the transplant community since their introduction roughly a decade ago. Fascination arose from the possibility offered by the technology to gain a profound insight into the cellular response to immunogenic injury and the potential that this genomic signature would be indicative of the biological mechanism by which that stress was induced. Frustrations have arisen primarily from technical factors such as data variance, the requirement for the application of advanced statistical and mathematical analyses, and difficulties associated with actually recognizing signature gene-expression patterns and discerning mechanisms. To aid the understanding of this powerful tool, its versatility, and how it is dramatically changing the molecular approach to biomedical and clinical research, this teaching review describes the technology and its applications, as well as the limitations and evolution of microarrays, in the field of organ transplantation. Finally, it calls upon the attention of the transplant community to integrate into multidisciplinary teams, to take advantage of this technology and its expanding applications in unraveling the complex injury circuits that currently limit transplant survival

Sequential broncho-alveolar lavages reflect distinct pulmonary compartments: clinical and research implications in lung transplantation

Abstract Background Bronchoalveolar lavage (BAL) has proven to be very useful to monitor the lung allograft after transplantation. In addition to allowing detection of infections, multiple BAL analytes have been proposed as potential biomarkers of lung allograft rejection or dysfunction. However, BAL collection is not well standardized and differences in BAL collection represent an important source of variation. We hypothesized that there are systematic differences between sequential BALs that are relevant to BAL analysis. Methods As part of 126 consecutive bronchoscopies in lung transplant recipients, two sequential BALs (BAL1 and BAL2) were performed in one location during each bronchoscopy by instilling and suctioning 50 ml of normal saline twice into separate containers. Cell concentration, viability and differentials, Surfactant Protein-D (SP-D), Club Cell Secretory Protein (CCSP), and levels of CXCL10, IL-10, CCL2, CCL5, VEGF-C, RAGE, CXCL9, CXCL1, IL-17A, IL-21, PDGF, and GCSF were compared between BAL1 and BAL2. Results Total cell concentration did not differ between BAL1 and BAL2; however, compared to BAL2, BAL1 had more dead cells, epithelial cells, neutrophils, and higher concentrations of airway epithelium-derived CCSP and inflammatory markers. BAL2 had a higher concentration of SP-D compared to BAL1. Conclusion In this study performed in lung transplant recipients, we show that sequential BALs represent different lung compartments and have distinct compositions. BAL1 represents the airway compartment with more epithelial cells, neutrophils, and epithelium-derived CCSP. Conversely, BAL2 samples preferentially the distal bronchoalveolar space with greater cell viability and higher SP-D. Our findings illustrate how the method of BAL collection can influence analyte concentrations and further emphasize the need for a standardized approach in translational research involving BAL samples

Plasma and bronchoalveolar lavage samples in acute lung allograft rejection: the potential role of cytokines as diagnostic markers

The role of differential cytology patterns in peripheral blood and bronchoalveolar lavage samples is increasingly investigated as a potential adjunct to diagnose acute and chronic allograft dysfunction after lung transplantation. While these profiles might facilitate the diagnosis of acute cellular rejection, low sensitivity and specificity of these patterns limit direct translation in a clinical setting. In this context, the identification of other biomarkers is needed. This review article gives an overview of cytokine profiles of plasma and bronchoalveolar lavage samples during acute cellular rejection. The value of these cytokines in supporting the diagnosis of acute cellular rejection is discussed. Current findings on the topic are highlighted and experimental settings for future research projects are identified

Gene Expression Profiling of Bronchoalveolar Lavage Cells Preceding a Clinical Diagnosis of Chronic Lung Allograft Dysfunction

BACKGROUND:Chronic Lung Allograft Dysfunction (CLAD) is the main limitation to long-term survival after lung transplantation. Although CLAD is usually not responsive to treatment, earlier identification may improve treatment prospects. METHODS:In a nested case control study, 1-year post transplant surveillance bronchoalveolar lavage (BAL) fluid samples were obtained from incipient CLAD (n = 9) and CLAD free (n = 8) lung transplant recipients. Incipient CLAD cases were diagnosed with CLAD within 2 years, while controls were free from CLAD for at least 4 years following bronchoscopy. Transcription profiles in the BAL cell pellets were assayed with the HG-U133 Plus 2.0 microarray (Affymetrix). Differential gene expression analysis, based on an absolute fold change (incipient CLAD vs no CLAD) >2.0 and an unadjusted p-value ≤0.05, generated a candidate list containing 55 differentially expressed probe sets (51 up-regulated, 4 down-regulated). RESULTS:The cell pellets in incipient CLAD cases were skewed toward immune response pathways, dominated by genes related to recruitment, retention, activation and proliferation of cytotoxic lymphocytes (CD8+ T-cells and natural killer cells). Both hierarchical clustering and a supervised machine learning tool were able to correctly categorize most samples (82.3% and 94.1% respectively) into incipient CLAD and CLAD-free categories. CONCLUSIONS:These findings suggest that a pathobiology, similar to AR, precedes a clinical diagnosis of CLAD. A larger prospective investigation of the BAL cell pellet transcriptome as a biomarker for CLAD risk stratification is warranted