The occurrence of fungal infection seriously affects the survival and life quality of transplanted patients. The accurate diagnosis is of particular importance in the early stage of infection. To develop a novel diagnostic method for this kind of patient, we established a post-transplant immunosuppressed mice model with fungus inoculation and collected their peripheral blood at specific time points after infection. After screening by microarray, differentially expressed miRNAs and lncRNAs were selected and homologously analyzed with those of human beings from the gene database. These miRNAs and lncRNAs candidates were validated by qRT-PCR in peripheral blood samples from transplanted patients. We found that, compared with normal transplanted patients, the levels of miR-215 and miR-let-7 c were up-regulated in the plasma of patients with fungal infection (P < 0.01), while levels of miR-154, miR-193a, NR_027669.1, and NR_036506.1 were down-regulated in their peripheral blood mononuclear cells (P < 0.01). Principal component analysis shows that the expression pattern of the above RNAs was different between the two groups. A 6-noncoding-RNA detection panel was established by the support vector machine analysis, whose area under the ROC curve was 0.927. The accuracy, precision, sensitivity, and specificity of this model were 0.928, 0.919, 0.944, and 0.910, respectively. Though our detection panel has excellent diagnostic efficacy, its clinical application value still needs to be further confirmed by multi-center prospective clinical trials.

The occurrence of fungal infection seriously affects the survival and life quality of transplanted patients. The accurate diagnosis is of particular importance in the early stage of infection. To develop a novel diagnostic method for this kind of patient, we established a post-transplant immunosuppressed mice model with fungus inoculation and collected their peripheral blood at specific time points after infection. After screening by microarray, differentially expressed miRNAs and lncRNAs were selected and homologously analyzed with those of human beings from the gene database. These miRNAs and lncRNAs candidates were validated by qRT-PCR in peripheral blood samples from transplanted patients. We found that, compared with normal transplanted patients, the levels of miR-215 and miR-let-7 c were up-regulated in the plasma of patients with fungal infection (P < 0.01), while levels of miR-154, miR-193a, NR_027669.1, and NR_036506.1 were down-regulated in their peripheral blood mononuclear cells (P < 0.01). Principal component analysis shows that the expression pattern of the above RNAs was different between the two groups. A 6-noncoding-RNA detection panel was established by the support vector machine analysis, whose area under the ROC curve was 0.927. The accuracy, precision, sensitivity, and specificity of this model were 0.928, 0.919, 0.944, and 0.910, respectively. Though our detection panel has excellent diagnostic efficacy, its clinical application value still needs to be further confirmed by multi-center prospective clinical trials.

Viral infection seriously affects the survival and life quality of transplanted patients without an accurate diagnosis during the early stage. Herein, we aimed to develop a novel diagnostic method based on non-coding RNAs expression in peripheral blood. An immunosuppressive mouse model of viral infection after transplantation was established. Differentially expressed non-coding RNAs were distinguished by microarray analyses in the virus-infected group. After homology analysis, 46 miRNAs and 24 lncRNAs were further verified by qRT-PCR in the peripheral blood samples of transplanted patients. Compared with normal transplanted patients, miR-29b, miR-185, and NR_073415.2 were significantly downregulated in the PBMC of post-transplant patients with viral infection. Based on the expression of the above three RNAs, principal component analysis (PCA) identified a slight overlap between the two groups. A 3-non-coding-RNA detection panel was constructed by the support vector machine analysis (SVM), whose loss rate was 14.71%. The area under the curve of it was 0.909. With the optimal cut-off value (Y = 0.328), the sensitivity was 0.929 and the specificity was 0.781. Therefore, based on non-coding RNAs expressions, a detection panel for viral infection after organ transplantation was formed with high diagnostic specificity and sensitivity.

Viral infection seriously affects the survival and life quality of transplanted patients without an accurate diagnosis during the early stage. Herein, we aimed to develop a novel diagnostic method based on non-coding RNAs expression in peripheral blood. An immunosuppressive mouse model of viral infection after transplantation was established. Differentially expressed non-coding RNAs were distinguished by microarray analyses in the virus-infected group. After homology analysis, 46 miRNAs and 24 lncRNAs were further verified by qRT-PCR in the peripheral blood samples of transplanted patients. Compared with normal transplanted patients, miR-29b, miR-185, and NR_073415.2 were significantly downregulated in the PBMC of post-transplant patients with viral infection. Based on the expression of the above three RNAs, principal component analysis (PCA) identified a slight overlap between the two groups. A 3-non-coding-RNA detection panel was constructed by the support vector machine analysis (SVM), whose loss rate was 14.71%. The area under the curve of it was 0.909. With the optimal cut-off value (Y = 0.328), the sensitivity was 0.929 and the specificity was 0.781. Therefore, based on non-coding RNAs expressions, a detection panel for viral infection after organ transplantation was formed with high diagnostic specificity and sensitivity.