Evidence map›Paper›PMID 41102509›Full record

ArticleScientific reports2025

Distinguishing tuberculosis from non-tuberculous mycobacteria and other respiratory conditions by microbiome patterns.

Jee Youn Oh, Young Kyung Ko, Min Ha Jeon, Hyun Myung Doo, Sanghyun Roh, Jeong-An Gim

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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

6 authors.

Jee Youn OhDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, 08308, South Korea.
Young Kyung KoDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, 08308, South Korea.
Min Ha JeonDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, 08308, South Korea.
Hyun Myung DooDivision of Medical Oncology, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, 08308, South Korea.
Sanghyun RohDepartment of Medical Science, Soonchunhyang University, 31538, Asan, South Korea.
Jeong-An GimDepartment of Medical Science, Soonchunhyang University, 31538, Asan, South Korea. vitastar@sch.ac.kr.

Funding

National Research Foundation of Korea 2022R1C1C1009250
6 · The paper itself

Abstract

Tuberculosis (TB) and non-tuberculous mycobacterial (NTM) infections, both caused by acid-fast bacteria, exhibit overlapping clinical presentations and radiological findings, making accurate and swift differentiation imperative for appropriate patient management. The ability to promptly distinguish between TB and NTM is pivotal, particularly in healthcare settings where TB patients require isolation. So, there is a pressing need to identify reliable biomarkers capable of delineating these conditions. In this study, we carefully analyzed a group of 108 patients, including 38 with TB, 29 with NTM, and 41 with other respiratory diseases. We used bacterial 16 S rRNA sequencing to examine the relative amounts of different microbial species in each patient group. We also used advanced methods like co-occurrence analysis, mutually exclusive analysis, and decision tree analysis to explore the complex patterns within the microbial communities. Our investigation revealed intriguing associations between microbial taxa and disease entities. In TB patients, prominent species were Enterococcus faecalis, Streptococcus mutans, and Snodgrassella alvi, while in NTM, prominent species were Cariobacterium hominis and Prevotella nigrescens. The absence of Mobiluncus curtisii indicated a higher probability of NTM, especially if Olsenella phocaeensis was also absent. This comprehensive analysis unveiled distinct microbial signatures that serve as discerning markers for discriminating TB, NTM infections, and other respiratory ailments. By elucidating microbial patterns unique to each condition, our findings offer valuable insights into the development of diagnostic strategies and therapeutic interventions tailored to specific respiratory infections.

Indexed as

MicrobiotaMycobacterium Infections, NontuberculousNontuberculous MycobacteriaTuberculosisAdultAgedDiagnosis, DifferentialFemaleHumansMaleMiddle AgedRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID41102509
PMCPMC12533053

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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.