Animal and translational models of SARS-CoV-2 infection and COVID-19

COVID-19 is causing a major once-in-a-century global pandemic. The scientific and clinical community is in a race to define and develop effective preventions and treatments. The major features of disease are described but clinical trials have been hampered by competing interests, small scale, lack of defined patient cohorts and defined readouts. What is needed now is head-to-head comparison of existing drugs, testing of safety including in the background of predisposing chronic diseases, and the development of new and targeted preventions and treatments. This is most efficiently achieved using representative animal models of primary infection including in the background of chronic disease with validation of findings in primary human cells and tissues. We explore and discuss the diverse animal, cell and tissue models that are being used and developed and collectively recapitulate many critical aspects of disease manifestation in humans to develop and test new preventions and treatments.

Sheep and cattle exposed to Mycobacterium avium subspecies paratuberculosis exhibit altered total serum cholesterol profiles during the early stages of infection

Pathogenic mycobacteria such as Mycobacterium tuberculosis are capable of utilising cholesterol as a primary carbon-based energy source in vitro but there has been little research examining the significance of cholesterol in vivo. Johne's disease is a chronic enteric disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). This study sought to evaluate the levels of total serum cholesterol in the host following exposure to MAP. Blood samples were collected from both sheep and cattle prior to experimental challenge with MAP and at monthly intervals post-challenge. Total serum cholesterol levels in sheep challenged with MAP were significantly elevated at 9 weeks post-inoculation (wpi) in comparison to controls. When stratified based on disease outcome, there was no significant difference in serum cholesterol at the timepoints examined between MAP exposed sheep that were susceptible and those that were resistant to Johne's disease. There was a similar elevation in serum cholesterol at 9 wpi in cattle with histopathological gut lesions associated with disease or those with an early high IFN-γ response. Total serum cholesterol in exposed cattle was significantly lower when compared to controls at 13 wpi. Taken together, these results demonstrate changes in serum cholesterol following MAP exposure and disease progression which could reflect novel aspects of the pathogenesis and immune response associated with MAP infection in both sheep and cattle.

Toxicity and efficacy of lomustine and bevacizumab in recurrent glioblastoma patients

The combination of lomustine and bevacizumab is a commonly used salvage treatment for recurrent glioblastoma (GBM). We investigated the toxicity and efficacy of lomustine plus bevacizumab (lom-bev) in a community-based patient cohort and made a comparison to another frequently used combination therapy consisting of irinotecan plus bevacizumab (iri-bev). Seventy patients with recurrent GBM were treated with lomustine 90 mg/m² every 6 weeks and bevacizumab 10 mg/kg every 2 weeks. Toxicity was registered and compared to the toxicity observed in 219 recurrent GBM patients who had previously been treated with irinotecan 125 mg/m² and bevacizumab 10 mg/kg every 2 weeks. The response rate was 37.1% for lom-bev and 30.1% for iri-bev. Median progression-free survival (PFS) was 23 weeks for lom-bev and 21 weeks for iri-bev (p = 0.9). Overall survival (OS) was 37 weeks for lom-bev and 32 weeks for iri-bev (p = 0.5). Lom-bev caused a significantly higher frequency of thrombocytopenia (11.4% grade 3-4) compared to iri-bev (3.5% grade 3-4). Iri-bev patients had more gastrointestinal toxicity with regard to nausea, vomiting, diarrhea, constipation and stomatitis. Within the limitations of the study lom-bev is a well-tolerated treatment for recurrent GBM, although hematological toxicity may be a dose limiting factor. No significant differences between lom-bev and iri-bev were observed with regard to PFS or OS. The differences in toxicity profiles between lom-bev and iri-bev could guide treatment decision in recurrent GBM therapy as efficacy is equal and no predictive factors for efficacy exist.

Prediction of excessive weight gain in insulin treated patients with type 2 diabetes

BACKGROUND

Weight gain is an ongoing challenge when initiating insulin therapy in patients with type 2 diabetes mellitus (T2DM). However, if prediction of insulin-associated weight gain was possible on an individual level, targeted initiatives could be implemented to reduce weight gain. The aim of the present study was to identify predictors of weight gain in insulin-treated patients with T2DM.

METHODS

In all, 412 individuals with T2DM were, in addition to metformin or placebo, randomized into 18-month treatment groups with three different insulin analog treatment regimens (biphasic, aspart, detemir). Participants with excessive weight gain were defined as the group with weight gain in the 4th quartile (>6.2 kg).We developed a pattern classification method to predict individuals prone to excessive weight gain.

RESULTS

Over the 18-month treatment period, median weight gain among all 412 patients was 2.4 kg (95% prediction interval [PI] -5.6, 12.4 kg), whereas median weight gain for those in the upper 4th quartile (n = 103) was 8.9 kg (95% PI 6.3, 15.2 kg). No clinical baseline data were strong predictors of excessive weight gain. However, the weight gain during the first 3 months of the trial and the subsequent dose of insulin yielded a useful predictor for weight gain at the 18-month follow-up. Combining these two predictors into a prediction model with other clinical available information produced a receiver operating characteristic area under the curve of 0.80.

CONCLUSIONS

We have developed a prediction model that could help identify a substantial proportion of individuals with T2DM prone to large weight gain during insulin therapy.