key: cord-0775652-msq37o1b
authors: Gao, Shu‐Hui; Chen, Chun‐Guang; Zhuang, Chun‐Bo; Zeng, Yu‐Ling; Zeng, Zhen‐Zhen; Wen, Pei‐Hao; Yu, Yong‐Min; Ming, Liang; Zhao, Jun‐Wei
title: Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis
date: 2021-06-09
journal: J Clin Lab Anal
DOI: 10.1002/jcla.23871
sha: 31c97488d754582eaeabf3d654f3db0e3f7c23aa
doc_id: 775652
cord_uid: msq37o1b

BACKGROUND: To verify the differential expression of miR‐30c and miR‐142‐3p between tuberculosis patients and healthy controls and to investigate the performance of microRNA (miRNA) and subsequently models for the diagnosis of tuberculosis (TB). METHODS: We followed up 460 subjects suspected of TB, and finally enrolled 132 patients, including 60 TB patients, 24 non‐TB disease controls (TB‐DCs), and 48 healthy controls (HCs). The differential expression of miR‐30c and miR‐142‐3p in serum samples of the TB patients, TB‐DCs, and HCs were identified by reverse transcription–quantitative real‐time PCR. Diagnostic models were developed by analyzing the characteristics of miRNA and electronic health records (EHRs). These models evaluated by the area under the curves (AUC) and calibration curves were presented as nomograms. RESULTS: There were differential expression of miR‐30c and miR‐142‐3p between TB patients and HCs (p < 0.05). Individual miRNA has a limited diagnostic value for TB. However, diagnostic performance has been both significantly improved when we integrated miR‐142‐3p and ordinary EHRs to develop two models for the diagnosis of tuberculosis. The AUC of the model for distinguishing tuberculosis patients from healthy controls has increased from 0.75 (95% CI: 0.66–0.84) to 0.96 (95% CI: 0.92–0.99) and the model for distinguishing tuberculosis patients from non‐TB disease controls has increased from 0.67 (95% CI: 0.55–0.79) to 0.94 (95% CI: 0.89–0.99). CONCLUSIONS: Integrating serum miR‐142‐3p and EHRs is a good strategy for improving TB diagnosis.

diagnosis and appropriate treatment. Early diagnosis of active tuberculosis is beneficial to reduce its death toll and prevent onward transmission of infection. 3, 4 But so far, the common clinical diagnostic tools for tuberculosis exist with various deficiencies: smear microscopy suffers from poor sensitivity, mycobacterial culture has a long turn around time, GeneXpert Mtb/RIF test is not available in all laboratories, etc. 5, 6 To develop TB diagnostic tools or biomarkers for patients with sputum-scarce samples and extrapulmonary tuberculosis is one of the top 10 priorities for tuberculosis diagnostics development. 3 More and more different types of biomarkers have been discovered, 7 such as noncoding RNAs, [8] [9] [10] proteins, 11 and metabolites. 12 MicroRNAs are small endogenous noncoding RNAs that regulate gene expression posttranscriptionally. 13 And serum miRNAs are stable and detectable, 14 which is a dominant characteristic of widely used biomarkers. In recent years, the development of transcriptome sequencing has allowed a surge of differential expression of miRNAs between TB subjects and healthy controls to be observed, including miR-30c 15, 16 and miR-142-3p. 17, 18 But the absence of validation limits the applicability of the sequencing findings. Moreover, recent evidence suggested that integrating miRNAs and EHRs could improve the diagnosis for TB patients, 19, 20 but there are a few reports on this yet. Therefore, this study was performed to validate above miRNAs which were selected from miRNAs expression profiles and investigate the diagnostic potential of miRNAs and diagnostic models incorporating miRNA and EHRs data to identify TB cases. 

The sample size was calculated by the HyLown Power and Sample Size Calculators (http://power andsa mples ize.com/Calcu lator s/).

Based on our pre-experiment, it was calculated that at least 22 subjects were needed in each group when the standard error α was 0.05 and the test efficiency β was 80%.

Total RNA was extracted using the BIOG cfRNA Easy Kit (Baidai). follows:pre-denaturation at 95°C for 3 min, followed by 45 cycles at 95°C for 5 s, 60°C for 30 s, and 72°C for 30 s. Each sample was run in triplicate as well as the ddH 2 O negative control and blank control. RT-qPCR data were analyzed by the 2 −ΔΔCt method, normalized against external controls (cel-miR-39-3p).

Continuous variables are expressed as mean ± SD or mean (minimum-maximum) and compared using an unpaired, two-tailed t-test or Mann-Whitney U test. Categorical variables were reported as whole numbers and proportions and compared using the chisquare test or Fisher's exact test. A 10% missing value threshold was applied to remove incomplete features, and mean imputation was performed to supplement missing data. The significance of each variable was assessed by univariate logistic regression analysis. All variables associated with TB at a significant level were candidates for stepwise multivariate analysis. Then, adding some variables linked with clinical symptoms based on clinical importance and scientific knowledge. Selected variables were used to create the models and incorporated in the nomograms to predict the probability of TB by using the rms package of R, version 4.0 (http://www.r-proje ct.org/).

For clinical use, the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic value of miRNAs and the performance of the models. The calibration curves were generated to explore the performance characteristics of the nomograms.

In all analyses, p < 0.05 was considered to indicate statistical significance. All analyses were performed using SPSS Statistics 19.0 and R, version 4.0. Scatter diagrams and ROC were generated with GraphPad Prism 5.

The characteristics of all participants are given in Table 1 . There were no significant differences between patients with TB and HCs in age and gender, but TB patients were younger than their TB-DCs (p < 0.0001). All clinical signs distinguished poorly between patients with TB and TB-DCs, which puts more pressure on doctors.

However, for hematological outcomes, there were some significant differences among the three groups, such as urea and mean platelet volume, which gives doctors insights into diagnosis.

The expression level of two candidate miRNAs was measured by RT-qPCR. Comparison between TB patients and healthy subjects, the expression levels of miR-30c and miR-142-3p were both decreased 

The results of the univariate logistic analysis are presented in the Table 3 ).

The diagnostic models that incorporated the features based on stepwise multivariate analysis were developed and presented as the nomograms (Figure 4 ).

The Hosmer-Lemeshow test yielded a nonsignificant statistic 

Several previous studies have noted the importance of miRNAs in TB about its roles in the disease pathogenesis, 21,22 diagnosis, 23, 24 and treatment. 25, 26 In this study, the differential expression of miR-30c and miR-142-3p between TB patients and healthy subjects was validated by RT-qPCR. Then, the models incorporating miRNA signatures and clinically available EHRs indicators were created, which vastly improved the diagnostic power.

We searched PubMed and "web of science" with "tuberculosis," "serum," and "miRNA" as the keywords, and the results showed that a total of 38 literature were retrieved. Then, we screened out nine articles whose purpose was to clarify the miRNAs with differential expression between active tuberculosis and health controls. Intersecting the available miRNA expression profiles in these literature, we harvested miR-30c and miR-142-3p finally (data not shown). Spinelli et al 27 found that miR-30c is strongly downregulated in mononuclear cells of pulmonary TB patients compared to tuberculous pleurisy cases and identified miR-30c as a specific correlate of pulmonary manifestations of TB. And miR-142-3p interacted with a functional SNP (rs13120371) in the 3′ untranslated region of the xCT gene which increases susceptibility to TB. 28 However, these miRNAs for the TB diagnostic value were not evaluated in the above studies until now. Therefore, we selected miR-30c and miR-142-3p

to assess whether these serum miRNAs could act as putative candidate biomarkers in TB patients.

We found that the level of miR-30c in serum from patients with tuberculosis was lower than that in the healthy group, and the same is true for miR-142-3p ( Figure 2) . Surprisingly, the expression tendency of miR-30c is inconsistent with the original profiles, which implied that there was a higher expression in TB patients. 15 Figures 3 and 5) . The results illustrated that integrating miRNAs and EHRs could indeed improve the diagnosis for TB patients as proposed by prior findings. 19 One unanticipated finding was that the feature of MPV included in the both of models was paid a little attention to the diagnosis of tuberculosis in the previous reports. Huang et al 35 showed that patients with active intestinal tuberculosis had decreased MPV (p = 0.002), but red cell distribution width had better diagnostic value than MPV. However, MPV has been confirmed to be related to tuberculosis and inflammation. 36 More specifically, MPV

can be an inflammatory marker to determine the disease activity in TB patients, 37 and platelet abnormalities in patients with tuberculous meningitis contribute to infarct and are associated with poor clinical outcomes. 38 Besides, there was significantly higher MPV level in the active tuberculosis group and that decreased with anti-TB therapy.

And MPV correlations with radiological extent of TB was also significant but weaker, which indicated MPV may be related to the severity of the TB. 39 Similarly, Dong et al 40 also showed that activation of the coagulation pathway, shown by increased platelet distribution width, decreased MPV, and shortened prothrombin time, was risk factor for severe lung lesions in patients with TB. Therefore, more interests should be given to MPV in the diagnosis of TB. As nomogram for individualized prediction of incident tuberculosis and multidrugresistant tuberculosis is convenient, 20,41,42 two nomograms were produced subsequently, with good discrimination (through AUC) and calibration (via Hosmer-Lemeshow and test calibration curve) ( Figure 6 ). However, these results were not very encouraging due to the limitation of sample size, and further study should verify the nomograms and confirm its universality.

Overall, our results suggested that miR-30c and miR-142-3p are potential biomarkers for TB diagnosis. The proposed nomograms were able to promote the diagnosis and differential diagnosis of TB and required further validation with large sample size in multicenter.

The authors declare that they have no conflict of interest. 

The data that support the findings of this study are available in the Table S1 of this article. 

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