Genomic surveillance tracks RSV evolution, identifies mutations in Minnesota

RSV

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A new study shows that the addition of respiratory syncytial virus (RSV) to Minnesotas viral genomic surveillance program demonstrates that prospective monitoring of the respiratory pathogen can identify the emergence of important mutations and clades.

Minnesota Department of Health (MDH) investigators, who published the findings yesterday in Emerging Infectious Diseases, conducted whole-genome sequencing of 575 respiratory specimens collected from hospitalized and nonhospitalized RSV patients at 11 state healthcare facilities from July 2023 to February 2024. The median patient age was 2 years, 91.8% were adults, 53.4% were female, and 5% were 65 years or older.

Investigators have applied whole-genome sequencing (WGS) for retrospective RSV surveillance and outbreak investigation in the United States, but WGS has not yet been documented as a tool for prospective surveillance,” they wrote.

One clade has resistance gene 

Sequencing classified 287 (49.9%) genomes as subgroup A and 288 (50.1%) as subgroup B. Most RSV-A genomes (98.9%) were distributed in four whole-genome lineages (A.D.1, 10.8%; A.D.3, 18.5%; A.D.5, 38.0%; and A.D.5.2, (31.7%), while 95.1% of RSV-B genomes belonged to the B.D.E.1 lineage.

The detection of clusters within the viral population shows the potential use of WGS for detection and investigation of RSV outbreaks at state or local levels.

Comparisons of diagrams representing evolutionary relationships showed greater diversity among all RSV-A genomes than among RSV-B genomes. Time-scaled phylogenetic analyses specific to the genomes sequenced estimated that the divergence of lineages occurred 2 to 8 years before their earliest specimen collections.

The team identified single-nucleotide polymorphisms (SNPs; a type of mutation), with pairwise comparisons showing that 32.3% of genomes were identical to at least one other genome, while 53% had one SNP. Twenty-three clusters of three or more genomes were identical, including 19.5% of all genomes. 

One clade of eight RSV-B genomes had a mutation tied to resistance to the RSV monoclonal antibody nirsevimab (Beyfortus). The most recent common ancestor of this clade likely circulated in fall 2023.

To evaluate their ability to link RSV genomes to known severe infections, the researchers cross-referenced the names and birthdates of RSV patients with sequenced specimens with the Centers for Disease Control and Prevention’s Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). 

Of 531 genomes collected from October 2023 to January 2024, the peak months of specimen collection, 22% were found in RSV-NET cases, representing 6.3% of all hospitalizations for RSV during that period. Nine (39.1%) of the 23 clusters included one or more RSV-NET cases, and 13.4% of clustered cases were in RSV-NET. 

Two RSV-NET case-patients with sequenced RSV from A.D.5.2 infections had received nirsevimab. Of the eight RSV-B patients whose genomes carried the nirsevimab-resistance gene, one was found in RSV-NET.

Potential role in outbreak investigation 

The findings “show that applying WGS for RSV surveillance can yield insights into viral circulation and population dynamics,” the authors wrote. “The detection of clusters within the viral population shows the potential use of WGS for detection and investigation of RSV outbreaks at state or local levels. Our study also provided novel cross-referencing of viral genomic data against sentinel clinical surveillance of severe RSV infections.”

The team cautioned that their “skewed and localized convenience sampling limited the analytical potential of our findings. The limited geographic and temporal scope of our study also potentially introduced variability in our time-scaled analyses and location-specific discrepancies between RSV evolution in Minnesota and in other regions.”

The researchers said they will expand their genomic and epidemiologic data with more targeted collection of specimens and perform sufficiently powered epidemiologic analyses on the emergence of mutations associated with vaccine escape, virulence, and transmissibility.

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