ArticleAnnals of laboratory medicine2014
Proteomic profiling of serum from patients with tuberculosis.
Article in Annals of laboratory medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
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.
Who cites it
16 citing papers in PubMed, 27 citations in OpenAlex.
- Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.Tuberculosis (Edinburgh, Scotland) · 2018Trial
- Article
- Acute phase proteins and IP-10 in plasma for tuberculosis diagnosis.Frontiers in tuberculosis · 2023Article
- Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature.International journal of molecular sciences · 2022Article
- Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases.Cancer cell international · 2022Review
- Identification of protein biomarkers in host cerebrospinal fluid for differential diagnosis of tuberculous meningitis and other meningitis.Frontiers in neurology · 2022Article
- Protein and Microbial Biomarkers in Sputum Discern Acute and Latent Tuberculosis in Investigation of Pastoral Ethiopian Cohort.Frontiers in cellular and infection microbiology · 2021Article
- Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis.JCI insight · 2020Article
- Changes in T-lymphocyte subsets and risk factors in human immunodeficiency virus-negative patients with active tuberculosis.Infection · 2020Article
- Determination of dehydroepiandrosterone and its biologically active oxygenated metabolites in human plasma evinces a hormonal imbalance during HIV-TB coinfection.Scientific reports · 2018Article
- Proteomic analysis of serum proteins from HIV/AIDS patients withClinical proteomics · 2018Article
- Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.Frontiers in microbiology · 2018Article
- Identification of a Novel Serum Biomarker for Tuberculosis Infection in Chinese HIV Patients by iTRAQ-Based Quantitative Proteomics.Frontiers in microbiology · 2018Article
- Diagnostic 'omics' for active tuberculosis.BMC medicine · 2016Review
- Host Protein Biomarkers Identify Active Tuberculosis in HIV Uninfected and Co-infected Individuals.EBioMedicine · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEffective treatment and monitoring of tuberculosis (TB) requires biomarkers that can be easily evaluated in blood samples. The aim of this study was to analyze the serum proteome of patients with TB and to identify protein biomarkers for TB.
methodsSerum samples from 26 TB patients and 31 controls were analyzed by using nano-flow ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in data-independent mode, and protein and peptide amounts were calculated by using a label-free quantitative approach. The generated data were analyzed by using principal component analysis and partial least squares discriminant analysis, a multivariate statistical method.
resultsOf more than 500 proteins identified, alpha-1-antitrypsin was the most discriminative, which was 4.4 times higher in TB patients than in controls. Peptides from alpha-1-antitrypsin and antithrombin III increased in TB patients and showed a high variable importance in the projection scores and coefficient in partial least square discriminant analysis.
conclusionsSera from patients with TB had higher alpha-1-antitrypsin levels than sera from control participants. Alpha-1-antitrypsin levels may aid in the diagnosis of TB.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.