Evidence map›Paper›PMID 39340659›Full record

ArticleInflammation research : official journal of the European Histamine Research Society ... [et al.]2024

Olink proteomics and lipidomics analysis of serum from patients infected with non-tuberculous mycobacteria and Mycobacterium tuberculosis.

Li Wang, Guoling Yang, Liang Guo, Lan Yao, Yidian Liu, Wei Sha

Abstract read
In one paragraph

Article in Inflammation research : official journal of the European Histamine Research Society ... [et al.], 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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  4. Rapid discrimination ofBMJ health & care informatics · 2025
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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

6 authors.

Li Wang *Department of Tuberculosis, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Guoling Yang *Department of Tuberculosis, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Liang Guo *Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Lan YaoDepartment of Tuberculosis, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Yidian LiuDepartment of Tuberculosis, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Wei ShaDepartment of Tuberculosis, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China. 13671758200@126.com.

Funding

National Key R&D Program of China 2023YFC2307300National Natural Science Foundation of China 82102251Shanghai 2020 "science and technology innovation action plan" technological innovation fund: Clinical Study on New Short-Course treatment regimens and Host-Directed Therapy for MDR-TB 20Z11900500Shanghai's 2023 "Science and Technology Innovation Action Plan", special general project of medical innovation research 23Y11900300Shanghai three-year (2023-2025) action plan to strengthen the public health system GWVI-11.1-05
6 · The paper itself

Abstract

backgroundNon-tuberculous mycobacterial (NTM) and Mycobacterium tuberculosis (MTB) infections are difficult to diagnose and treat, significantly burdening global health. The host immune status is generally believed to be associated with the onset and progression of NTM and MTB infections, but its specific impact remains unclear.

methodsIn the present study, proteomics and lipidomics analysis of serum from normal controls (n = 26) and patients with MTB (n = 26), rapidly growing NTM (RGM, n = 15), and slowly growing NTM (SGM, n = 21) were conducted using the Olink technique based on a highly sensitive and specific neighborhood extension assay and the lipidomics technique.

resultsIFN-γ, CXCL9, CXCL10, CXCL11, and CXCL13, etc. were simultaneously upregulated in MTB, RGM, and SGM, while lipids FAHFA 22:3, FAHFA 26:4, FAHFA 24:4, FAHFA 20:5, FAHFA 18:2 simultaneously downregulated. IL8, CCL3, CXCL5, and MCP-2, etc. were simultaneously upregulated in RGM and SGM compared to MTB, as well as PCs, LPCs, PEs, and LPEs. Compared with RGM, IL7, CD27, CCL17, CXCL12, and LPC 28:7-SN2 were downregulated in SGM. Pathway analyses revealed that tuberculosis, sphingolipid signaling pathway, and adipocytokine signaling pathway were regulated at the protein level and metabolite level. Diagnostic panels comprising immune-associated proteins and lipids greatly enhance diagnostic specificity and sensitivity.

conclusionThis integrated multi-omics analysis provides a more comprehensive understanding of the molecular landscape of NTM and MTB, which may provide molecular targets for specialized therapies.

Indexed as

LipidomicsMycobacterium Infections, NontuberculousMycobacterium tuberculosisProteomicsTuberculosisAdultAgedFemaleHumansLipidsMaleMiddle AgedNontuberculous MycobacteriaLipidsBiomarkersLipidomicsMetabolomicsMycobacterium tuberculosisNon-tuberculous mycobacteriaOlinkProteomics

Identifiers

PMID39340659
PMCPMC11541342

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.