A systematic review on global RSV genetic data: Identification of knowledge gaps. (20th September 2021)

• Record Type: Journal Article
• Authors: Langedijk, Annefleur C.; Harding, Eline R.; Konya, Burak; Vrancken, Bram; Lebbink, Robert Jan; Evers, Anouk; Willemsen, Joukje; Lemey, Philippe; Bont, Louis J.
• Is Part Of: Reviews in medical virology. Volume 32:Number 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-20
• Subjects: molecular epidemiology -- monoclonal antibodies -- respiratory syncytial virus -- RSV -- systematic review; Medical virology -- Periodicals; Review Literature -- Periodicals; Virus Diseases -- Periodicals; Viruses -- Periodicals; 616.0194
• DOI: 10.1002/rmv.2284
• Languages: English
• ISSNs: 1052-9276

Abstract

Abstract: Respiratory syncytial virus (RSV) is a major health problem. A better understanding of the geographical and temporal dynamics of RSV circulation will assist in tracking resistance against therapeutics currently under development. Since 2015, the field of RSV molecular epidemiology has evolved rapidly with around 20–30 published articles per year. The objective of this systematic review is to identify knowledge gaps in recent RSV genetic literature to guide global molecular epidemiology research. We included 78 studies published between 2015 and 2020 describing 12, 998 RSV sequences of which 8, 233 (63%) have been uploaded to GenBank. Seventeen (22%) studies were performed in low‐ and middle‐income countries (LMICs), and seven (9%) studies sequenced whole‐genomes. Although most reported polymorphisms for monoclonal antibodies in clinical development (nirsevimab, MK‐1654) have not been tested for resistance in neutralisation essays, known resistance was detected at low levels for the nirsevimab and palivizumab binding site. High resistance was found for the suptavumab binding site. We present the first literature review of an enormous amount of RSV genetic data. The need for global monitoring of RSV molecular epidemiology becomes increasingly important in evaluating the effectiveness of monoclonal antibody candidates as they reach their final stages of clinical development. We have identified the following three knowledge gaps: whole‐genome data to study global RSV evolution, data from LMICs and data from global surveillance programs.