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

<p><strong>Objectives:</strong> Central nervous system (CNS) infections account for a large number of disability-adjusted life years worldwide every year. An urgent research priority is scaling up diagnostic capacity, and introduction of point-of-care tests. We set out to assess cu...

Descrizione completa

Dettagli Bibliografici
Autori principali: Bharucha, T, Gangadharan, B, Kumar, A, De Lamballerie, X, Newton, P, Winterberg, M, Dubot-Pérès, A, Zitzmann, N
Natura: Journal article
Lingua:English
Pubblicazione: Elsevier 2019
Descrizione
Riassunto:<p><strong>Objectives:</strong> Central nervous system (CNS) infections account for a large number of disability-adjusted life years worldwide 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.</p> <p><strong>Methods:</strong> We performed a systematic review (PROSPERO-CRD42018104257) usingPRISMA 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.</p> <p><strong>Results:</strong> 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. 6studies 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.</p> <p><strong>Conclusions:</strong> The findings demonstrate feasibility and significant 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.</p>