Comparative serum proteomic analysis of a selected protein panel in individuals with schizophrenia and bipolar disorder and the impact of genetic risk burden on serum proteomic profiles.

The diagnostic criteria for schizophrenia (SCZ) and bipolar disorder (BD) are based on clinical assessments of symptoms. In this pilot study, we applied high-throughput antibody-based protein profiling to serum samples of healthy controls and individuals with SCZ and BD with the aim of identifying differentially expressed proteins in these disorders. Moreover, we explored the influence of polygenic burden for SCZ and BD on the serum levels of these proteins. Serum samples from 113 individuals with SCZ and 125 with BD from the PsyCourse Study and from 44 healthy controls were analyzed by using a set of 155 antibodies in an antibody-based assay targeting a selected panel of 95 proteins. For the cases, genotyping and imputation were conducted for DNA samples and SCZ and BD polygenic risk scores (PRS) were calculated. Univariate linear and logistic models were used for association analyses. The comparison between SCZ and BD revealed two serum proteins that were significantly elevated in BD after multiple testing adjustment: "complement C9" and "Interleukin 1 Receptor Accessory Protein". Moreover, the first principal component of variance in the proteomics dataset differed significantly between SCZ and BD. After multiple testing correction, SCZ-PRS, BD-PRS, and SCZ-vs-BD-PRS were not significantly associated with the levels of the individual proteins or the values of the proteome principal components indicating no detectable genetic effects. Overall, our findings contribute to the evidence suggesting that the analysis of circulating proteins could lead to the identification of distinctive biomarkers for SCZ and BD. Our investigation warrants replication in large-scale studies to confirm these findings.

High Amounts of SARS-CoV-2 Precede Sickness Among Asymptomatic Health Care Workers.

BACKGROUND: Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity among asymptomatic subjects reflects past or future disease may be difficult to ascertain. METHODS: We tested 9449 employees at Karolinska University Hospital, Stockholm, Sweden for SARS-CoV-2 RNA and antibodies, linked the results to sick leave records, and determined associations with past or future sick leave using multinomial logistic regression. RESULTS: Subjects with high amounts of SARS-CoV-2 virus, indicated by polymerase chain reaction (PCR) cycle threshold (Ct) value, had the highest risk for sick leave in the 2 weeks after testing (odds ratio [OR], 11.97; 95% confidence interval [CI], 6.29-22.80) whereas subjects with low amounts of virus had the highest risk for sick leave in the 3 weeks before testing (OR, 6.31; 95% CI, 4.38-9.08). Only 2.5% of employees were SARS-CoV-2 positive while 10.5% were positive by serology and 1.2% were positive in both tests. Serology-positive subjects were not at excess risk for future sick leave (OR, 1.06; 95% CI, .71-1.57). CONCLUSIONS: High amounts of SARS-CoV-2 virus, as determined using PCR Ct values, was associated with development of sickness in the next few weeks. Results support the concept that PCR Ct may be informative when testing for SARS-CoV-2. Clinical Trials Registration. NCT04411576.