Orthogonal Comparison of Molecular Signatures of Kidney Transplants With Subclinical and Clinical Acute Rejection: Equivalent Performance Is Agnostic to Both Technology and Platform

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm‐driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx...

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Veröffentlicht in:American journal of transplantation 2017-08, Vol.17 (8), p.2103-2116
Hauptverfasser: Kurian, S. M., Velazquez, E., Thompson, R., Whisenant, T., Rose, S., Riley, N., Harrison, F., Gelbart, T., Friedewald, J. J., charette, j., Brietigam, S., Peysakhovich, J., First, M. R., Abecassis, M. M., Salomon, D. R.
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Sprache:eng
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Zusammenfassung:We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm‐driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA‐seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation. Using orthogonal microarray and next‐generation sequencing technologies, the authors demonstrate the ability to discover and internally validate gene expression profiles for two clinical phenotypes.
ISSN:1600-6135
1600-6143
DOI:10.1111/ajt.14224