While the seroprevalence of SARS-CoV-2 in healthy people does not differ significantly among age groups, those aged 65 years or older exhibit strikingly higher COVID-19 mortality compared to younger individuals. To further understand differing COVID-19 manifestations in patients of different ages, three age groups of ferrets are infected with SARS-CoV-2. Although SARS-CoV-2 is isolated from all ferrets regardless of age, aged ferrets (≥3 years old) show higher viral loads, longer nasal virus shedding, and more severe lung inflammatory cell infiltration, and clinical symptoms compared to juvenile (≤6 months) and young adult (1–2 years) groups. Furthermore, direct contact ferrets co-housed with the virus-infected aged group shed more virus than direct-contact ferrets co-housed with virus-infected juvenile or young adult ferrets. Transcriptome analysis of aged ferret lungs reveals strong enrichment of gene sets related to type I interferon, activated T cells, and M1 macrophage responses, mimicking the gene expression profile of severe COVID-19 patients. Thus, SARS-CoV-2-infected aged ferrets highly recapitulate COVID-19 patients with severe symptoms and are useful for understanding age-associated infection, transmission, and pathogenesis of SARS-CoV-2.

Abstract. This study investigated the effects of genetic polymorphisms in organic cation transporter (OCT) genes, such as OCT1-3, OCTN1, MATE1, and MATE2-K, on metformin pharmacokinetics. Of particular interest was the influence of genetic polymorphisms as covariates on the variability in the population pharmacokinetics (PPK) of metformin using nonlinear mixed effects modeling (NONMEM). In a retrospective data analysis, data on subjects from five independent metformin bioequivalence studies that used the same protocol were assembled and compared with 96 healthy control subjects who were administered a single oral 500 mg dose of metformin. Genetic polymorphisms of OCT2-808 G>T and OCTN1-917C>T had a significant (P<0.05) effect on metformin pharmacokinetics, yielding a higher peak concentration with a larger area under the serum time-concentration curve. The values obtained were 102± 34.5 L/h for apparent oral clearance (CL/F), 447±214 L for volume of distribution (V d /F), and 3.1±0.9 h for terminal half-life (mean±SD) by non-compartmental analysis. The NONMEM method gives similar results. The metformin serum levels were obtained by setting the one-compartment model to a first-order absorption and lag time. In the PPK model, the effects of OCT2-808 G>T and OCTN1-917C>T variants on the CL/F were significant (P<0.001 and P<0.05, respectively). Thus, genetic variants of OCTN1-917C>T, along with OCT2-808 G>T genetic polymorphisms, could be useful in titrating the optimal metformin dose.

Given the current COVID-19 pandemic, coinfection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and influenza A virus (IAV) is a major concern for public health. However, the immunopathogenic events occurring with coinfections of SARS-CoV-2 and IAV remain unclear. Here, we report the pathogenic and immunological consequences of SARS-CoV-2 and IAV H1N1 coinfection in the K18-hACE2 transgenic mouse model. Compared to a single infection with SARS-CoV-2 or IAV, coinfections not only prolonged the primary virus infection period but also increased immune cell infiltration and inflammatory cytokine levels in bronchoalveolar lavage fluid leading to severe pneumonia and lung damage. Moreover, coinfections caused severe lymphopenia in peripheral blood, resulting in reduced total IgG, neutralizing antibody titers, and CD4 + T cell responses against each virus. This study sheds light on the immunopathogenesis of SARS-CoV-2 and IAV coinfection, which may guide the development of effective therapeutic strategies for the treatment of patients coinfected with these viruses. Importance The co-circulation of influenza virus merging with the COVID-19 pandemic raises a potentially severe threat to public health. Recently, increasing numbers of SARS-CoV-2 and influenza virus coinfection have been reported from many countries. It is a worrisome issue that SARS-CoV-2 coinfection with other pathogens may worsen the clinical outcome and severity of COVID-19 and increase fatality. Here, we evaluated SARS-CoV-2 and IAV coinfection using the K18-hACE2 mouse model. Coinfected mice exhibited increased mortality with a prolonged IAV shedding. Furthermore, coinfected mice showed a higher level of cytokines and chemokines compared to a single infection condition. Interestingly, our data show that coinfected mice showed significantly less amount of virus-specific and neutralizing antibodies than the mice with a single infection. Overall, this study suggests that coinfection aggravates viral pathology by impaired neutralizing antibody response.

Few studies have used a longitudinal approach to describe the immune response to SARS-CoV-2 infection. Here, we perform single-cell RNA sequencing of bronchoalveolar lavage fluid cells longitudinally obtained from SARS-CoV-2-infected ferrets. Landscape analysis of the lung immune microenvironment shows distinct changes in cell proportions and characteristics compared to uninfected control, at 2 and 5 days post-infection (dpi). Macrophages are classified into 10 distinct subpopulations with transcriptome changes among monocyte-derived infiltrating macrophages and differentiated M1/M2 macrophages, notably at 2 dpi. Moreover, trajectory analysis reveals gene expression changes from monocyte-derived infiltrating macrophages toward M1 or M2 macrophages and identifies a macrophage subpopulation that has rapidly undergone SARS-CoV-2-mediated activation of inflammatory responses. Finally, we find that M1 or M2 macrophages show distinct patterns of gene modules downregulated by immune-modulatory drugs. Overall, these results elucidate fundamental aspects of the immune response dynamics provoked by SARS-CoV-2 infection.