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PLOS Papers on Hainan Province Hantavirus, ACE2 Modifiers, Lipidomic Risk Scores

A Nanjing Medical University-led team describes hantavirus and related rodent host patterns in China's Hainan province. As they report in PLOS One, the researchers used PCR to screen for hantavirus in 60 rodents trapped at half a dozen port sites in the province from 2016 to 2019. After detecting hantaviruses in seven Rattus norvegicus rats, they used sequencing and phylogenetic analyses to uncover closer genetic ties between Hainan and Guangdong province strains than between strains in Hainan and those reported on the Xisha Islands. From these and other results, the authors suggest that hantaviruses from Guangdong's ports and trading sites may have made their way to rodents in Hainan province. "[I]t is of great significance to strengthen the surveillance of rodents in port areas, especially [to] capture and eliminate rodents on ship," they write. "Timely elimination of host animals of hantavirus in port areas is necessary to prevent an outbreak of [hantavirus] disease."

For a paper in PLOS Pathogens, researchers at the University of Michigan present findings from a CRISPR gene editing-based screen for genetic factors affecting the cell surface expression of the ACE2 protein that SARS-CoV-2 uses to enter hosts cells. The team detected nearly three dozen potential ACE2-modifier genes with high-throughput screening in a human liver cell line, prompting follow-up gene knockout experiments and additional screening to find still other ACE2 modifiers specific to lung cells. "[A]side from ACE2 itself, we identified distinct sets of ACE2 modifiers in either cell line," the authors note, adding that the findings "demonstrate the important influence of cell type on investigations of SARS-CoV-2 infection and nominate candidate pathways for ACE2-targeted therapeutic development."

Finally, a team from Germany and Sweden outlines its search for lipidomic risk scores linked to diabetes or cardiovascular disease for a paper appearing in PLOS Biology. Using machine learning and data for nearly 4,100 individuals in the Malmö Diet and Cancer-Cardiovascular Cohort, the investigators found that quantifying blood plasma levels for 184 lipids could identify individuals at enhanced or reduced risk of type 2 diabetes (T2D) and cardiovascular disease (CVD) in a manner that appeared distinct from risk gleaned from genetics-based polygenic risk scores. "Our results demonstrate that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence," they report. "The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays."

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