Dataset Information

Mass spectrometry-based proteomic techniques to identify cerebrospinal fluid biomarkers for diagnosing suspected central nervous system infections. A systematic review.

ABSTRACT:

Objectives

Central nervous system (CNS) infections account for considerable death and disability every year. An urgent research priority is scaling up diagnostic capacity, and introduction of point-of-care tests. We set out to assess current evidence for the application of mass spectrometry (MS) peptide sequencing in identification of diagnostic biomarkers for CNS infections.

Methods

We performed a systematic review (PROSPEROCRD42018104257) using PRISMA guidelines on use of MS to identify cerebrospinal fluid (CSF) biomarkers for diagnosing CNS infections. We searched PubMed, Embase, Web of Science, and Cochrane for articles published from 1 January 2000 to 1 February 2019, and contacted experts. Inclusion criteria involved primary research except case reports, on the diagnosis of infectious diseases except HIV, applying MS to human CSF samples, and English language.

Results

4,620 papers were identified, of which 11 were included, largely confined to pre-clinical biomarker discovery, and eight (73%) published in the last five years. 6 studies performed further work termed verification or validation. In 2 of these studies, it was possible to extract data on sensitivity and specificity of the biomarkers detected by ELISA, ranging from 89-94% and 58-92% respectively.

Conclusions

The findings demonstrate feasibility and potential of the methods in a variety of infectious diseases, but emphasise the need for strong interdisciplinary collaborations to ensure appropriate study design and biomarker validation.

SUBMITTER: Bharucha T

PROVIDER: S-EPMC6838782 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Publications

Mass spectrometry-based proteomic techniques to identify cerebrospinal fluid biomarkers for diagnosing suspected central nervous system infections. A systematic review.

Bharucha Tehmina T Gangadharan Bevin B Kumar Abhinav A de Lamballerie Xavier X Newton Paul N PN Winterberg Markus M Dubot-Pérès Audrey A Zitzmann Nicole N

The Journal of infection 20190809 5

<h4>Objectives</h4>Central nervous system (CNS) infections account for considerable death and disability every year. An urgent research priority is scaling up diagnostic capacity, and introduction of point-of-care tests. We set out to assess current evidence for the application of mass spectrometry (MS) peptide sequencing in identification of diagnostic biomarkers for CNS infections.<h4>Methods</h4>We performed a systematic review (PROSPEROCRD42018104257) using PRISMA guidelines on use of MS to ...[more]

PMID: 31404562

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Project description:BackgroundRecently, with the rapid progress of metagenomic next-generation sequencing (mNGS), inconsistency between mNGS results and clinical diagnoses has become more common. There is currently no reasonable explanation for this, and the interpretation of mNGS reports still needs to be standardised.MethodsA retrospective analysis was conducted on 47 inpatients with suspected central nervous system (CNS) infections, and clinical data were recorded. The final diagnosis was determined by an expert group based on the patient's clinical manifestation, laboratory examination, and response to treatment. mNGS results were compared with the final diagnosis, and any inconsistencies that occurred were investigated. Finally, the credibility of mNGS results was evaluated using the integral approach, which consists of three parts: typical clinical features, positive results with the traditional method, and cerebrospinal fluid cells ≥ 100 (× 106/L) or protein ≥ 500 mg/L, with one point for each item.ResultsForty-one patients with suspected CNS infection were assigned to infected (ID, 31/41, 75.61%) and non-infected groups (NID, 10/41, 24.39%) after assessment by a panel of experts according to the composite diagnostic criteria. For mNGS-positive results, 20 of the 24 pathogens were regarded as contaminants when the final score was ≤ 1. The remaining 11 pathogens detected by mNGS were all true positives, which was consistent with the clinical diagnosis when the score was ≥ 2. For mNGS negative results, when the score was ≥ 2, the likelihood of infection may be greater than when the score is ≤ 1.ConclusionThe integral method is effective for evaluating mNGS results. Regardless of whether the mNGS result was positive or negative, the possibility of infection was greater when the score was ≥ 2. A negative mNGS result does not necessarily indicate that the patient was not clinically infected, and, therefore, clinical features are more important.

Dataset Information

Mass spectrometry-based proteomic techniques to identify cerebrospinal fluid biomarkers for diagnosing suspected central nervous system infections. A systematic review.

Objectives

Methods

Results

Conclusions

Publications

Mass spectrometry-based proteomic techniques to identify cerebrospinal fluid biomarkers for diagnosing suspected central nervous system infections. A systematic review.

Similar Datasets

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