MicroRNAs are ideal candidates as blood-based biomarkers. Comprehensive profiling of microRNAs is challenging. We overcame the existing challenges by developing robust protocols for isolation of extracellular RNA, and for sequencing of barcoded cDNA libraries of small RNAs. We also developed microRNA-specific stem-loop PCR assays for absolute quantification of candidate biomarkers. Armed with these tools, we investigated the hypothesis that circulating extracellular microRNA profiles are predictive of human liver allograft status.

We characterized the circulating extracellular microRNAs in 31 sera collected at the time of 31 allograft biopsies from 28 liver allograft recipients; acute rejection (AR, 14 sera from 12 recipients); normal allograft histology (Normal, 17 sera from 16 recipients). We used EdgeR statistic to identify microRNAs that discriminated AR from Normal. We used area under the ROC curve (AUC) to assess the performance of individual microRNAs, and used linear discriminant analysis to generate a parsimonious model diagnostic of AR.

Sixteen microRNAs with greater than 2 fold change between AR vs. Normal, among the top 90%, were identified by sequencing (Figure-1).

Absolute quantification of microRNA abundance by quantitative RT-PCR assays verified differential expression. The top candidate microRNA had an AUC of 0.93 for discriminating AR from Normal. A linear combination of 3 of the 16 microRNAs yielded higher AUC (0.98, 95%CI: 0.94-1.00, P<0.001) (Figure-2).

To our knowledge, this is the first characterization of circulating, extracellular microRNA transcriptome in serum of liver allograft recipients.

The discovered diagnostic signature, in addition to reducing the need for invasive biopsies, may help personalize immunosuppression.

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