Dysnatremia is a predictor for morbidity and mortality in hospitalized patients with COVID-19

Context: Dysnatremia is an independent predictor of mortality in patients with bacterial pneumonia. There is paucity of data about the incidence and prognostic impact of abnormal sodium concentration in patients with coronavirus disease 2019 (COVID-19). Objective: This work aimed to examine the association of serum sodium during hospitalization with key clinical outcomes, including mortality, need for advanced respiratory support and acute kidney injury (AKI), and to explore the role of serum sodium as a marker of inflammatory response in COVID-19. Methods: This retrospective longitudinal cohort study, including all adult patients who presented with COVID-19 to 2 hospitals in London over an 8-week period, evaluated the association of dysnatremia (serum sodium  145 mmol/L, hyponatremia, and hypernatremia, respectively) at several time points with inpatient mortality, need for advanced ventilatory support, and AKI. Results: The study included 488 patients (median age, 68 years). At presentation, 24.6% of patients were hyponatremic, mainly due to hypovolemia, and 5.3% hypernatremic. Hypernatremia 2 days after admission and exposure to hypernatremia at any time point during hospitalization were associated with a 2.34-fold (95% CI, 1.08-5.05; P = .0014) and 3.05-fold (95% CI, 1.69-5.49; P < .0001) increased risk of death, respectively, compared to normonatremia. Hyponatremia at admission was linked with a 2.18-fold increase in the likelihood of needing ventilatory support (95% CI, 1.34-3.45, P = .0011). Hyponatremia was not a risk factor for in-hospital mortality, except for the subgroup of patients with hypovolemic hyponatremia. Sodium values were not associated with the risk for AKI and length of hospital stay. Conclusion: Abnormal sodium levels during hospitalization are risk factors for poor prognosis, with hypernatremia and hyponatremia being associated with a greater risk of death and respiratory failure, respectively. Serum sodium values could be used for risk stratification in patients with COVID-19

In Silico Whole Genome Association Scan for Murine Prepulse Inhibition

Background The complex trait of prepulse inhibition (PPI) is a sensory gating measure related to schizophrenia and can be measured in mice. Large-scale public repositories of inbred mouse strain genotypes and phenotypes such as PPI can be used to detect Quantitative Trait Loci (QTLs) in silico. However, the method has been criticized for issues including insufficient number of strains, not controlling for false discoveries, the complex haplotype structure of inbred mice, and failing to account for genotypic and phenotypic subgroups. Methodology/Principal Findings We have implemented a method that addresses these issues by incorporating phylogenetic analyses, multilevel regression with mixed effects, and false discovery rate (FDR) control. A genome-wide scan for PPI was conducted using over 17,000 single nucleotide polymorphisms (SNPs) in 37 strains phenotyped. Eighty-nine SNPs were significant at a false discovery rate (FDR) of 5%. After accounting for long-range linkage disequilibrium, we found 3 independent QTLs located on murine chromosomes 1 and 13. One of the PPI positives corresponds to a region of human chromosome 6p which includes DTNBP1, a gene implicated in schizophrenia. Another region includes the gene Tsn which alters PPI when knocked out. These genes also appear to have correlated expression with PPI. Conclusions/Significance These results support the usefulness of using an improved in silico mapping method to identify QTLs for complex traits such as PPI which can be then be used for to help identify loci influencing schizophrenia in humans