Advances of genomic science and systems biology in renal transplantation: a review
作者： David Perkins , Meenakshi Verma , Ken J. Park
DOI: 10.1007/S00281-011-0243-2
关键词: Personalized medicine 、 Pathology 、 Systems biology 、 Omics technologies 、 Biopsy 、 Kidney transplantation 、 Transplantation 、 Genomics 、 Medicine 、 Predictive value 、 Bioinformatics
摘要: The diagnosis of rejection in kidney transplant patients is based on histologic classification a graft biopsy. current “gold standard” the Banff 97 criteria; however, there are several limitations classifying biopsy samples. First, involves an invasive procedure. Second, significant variance among blinded pathologists interpretation And third, also between histology and molecular profiles To increase positive predictive value classifiers rejection, committee developing criteria that integrate data into unified classifier could diagnose prognose rejection. develop most appropriate criteria, have been studies by multiple groups applying omics technologies attempts to identify biomarkers In this review, we discuss using genome-wide sets transcriptome proteome investigate acute chronic allograft dysfunction, tolerance. We which focus genetic urine peripheral blood, will provide clinicians with minimally methods for monitoring patients. emerging technologies, including whole-exome sequencing RNA-Seq new bioinformatic systems biology approaches, should ability both mechanistic understanding process.
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