Evidence map›Paper›PMID 28910318›Full record

Trial reportPloS one2017

Characterization of a novel panel of plasma microRNAs that discriminates between Mycobacterium tuberculosis infection and healthy individuals.

Jia-Yi Cui, Hong-Wei Liang, Xin-Ling Pan, Di Li, Na Jiao, Yan-Hong Liu, Jin Fu, Xiao-Yu He, Gao-Xiang Sun, Chun-Lei Zhang and 8 more

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  16. Key Macrophage Responses to Infection WithFrontiers in immunology · 2021
    Article
  17. Article
  18. The Roles of Host Noncoding RNAs inFrontiers in immunology · 2021
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 2 countries.

Jia-Yi CuiDepartment of Microbiology, Harbin Medical University, Harbin, China.
Hong-Wei LiangState Key Laboratory of Pharmaceutical Biotechnology, NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Xin-Ling PanDepartment of Microbiology, Harbin Medical University, Harbin, China.
Di LiDepartment of Microbiology, Harbin Medical University, Harbin, China.
Na JiaoHarbin Chest Hospital, Harbin, China.
Yan-Hong LiuDepartment of Laboratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Jin FuDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiao-Yu HeDepartment of Microbiology, Harbin Medical University, Harbin, China.
Gao-Xiang SunDepartment of Microbiology, Harbin Medical University, Harbin, China.
Chun-Lei ZhangHarbin Chest Hospital, Harbin, China.
Chi-Hao ZhaoState Key Laboratory of Pharmaceutical Biotechnology, NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Dong-Hai LiState Key Laboratory of Pharmaceutical Biotechnology, NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
En-Yu DaiDepartment of Microbiology, Harbin Medical University, Harbin, China.
Ke ZenState Key Laboratory of Pharmaceutical Biotechnology, NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Feng-Min ZhangDepartment of Microbiology, Harbin Medical University, Harbin, China.
Chen-Yu ZhangWu Lien-Teh Institute, Harbin Medical University, Harbin, China.
Xi ChenState Key Laboratory of Pharmaceutical Biotechnology, NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China.
Hong LingDepartment of Microbiology, Harbin Medical University, Harbin, China.
Nanjing University · CNHarbin Medical University · CNInstitute of Infection and Immunity · CASecond Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cavities are important in clinical diagnosis of pulmonary tuberculosis (TB) infected by Mycobacterium tuberculosis. Although microRNAs (miRNAs) play a vital role in the regulation of inflammation, the relation between plasma miRNA and pulmonary tuberculosis with cavity remains unknown. In this study, plasma samples were derived from 89 cavitary pulmonary tuberculosis (CP-TB) patients, 89 non-cavitary pulmonary tuberculosis (NCP-TB) patients and 95 healthy controls. Groups were matched for age and gender. In the screening phase, Illumina high-throughput sequencing technology was employed to analyze miRNA profiles in plasma samples pooled from CP-TB patients, NCP-TB patients and healthy controls. During the training and verification phases, quantitative RT-PCR (qRT-PCR) was conducted to verify the differential expression of selected miRNAs among groups. Illumina high-throughput sequencing identified 29 differentially expressed plasma miRNAs in TB patients when compared to healthy controls. Furthermore, qRT-PCR analysis validated miR-769-5p, miR-320a and miR-22-3p as miRNAs that were differently present between TB patients and healthy controls. ROC curve analysis revealed that the potential of these 3 miRNAs to distinguish TB patients from healthy controls was high, with the area under the ROC curve (AUC) ranged from 0.692 to 0.970. Moreover, miR-320a levels were decreased in drug-resistant TB patients than pan-susceptible TB patients (AUC = 0.882). In conclusion, we identified miR-769-5p, miR-320a and miR-22-3p as potential blood-based biomarkers for TB. In addition, miR-320a may represent a biomarker for drug-resistant TB.

Indexed as

AdolescentAdultBiomarkersFemaleHumansMaleMicroRNAsMiddle AgedReverse Transcriptase Polymerase Chain ReactionTuberculosis, Multidrug-ResistantTuberculosis, PulmonaryBiomarkersMicroRNAs

Identifiers

PMID28910318
PMCPMC5598944
OpenAlexW2754089886

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.