Cellular localization of p-tau217 in brain and its association with p-tau217 plasma levels

Recent studies highlight phosphorylated tau (p-tau) at threonine tau 217 (p-tau217) as a new promising plasma biomarker for pathological changes implicated in Alzheimer’s disease (AD), but the specific brain pathological events related to the alteration in p-tau217 plasma levels are still largely unknown. Using immunostaining techniques of postmortem AD brain tissue, we show that p-tau217 is found in neurofibrillary tangles (NFTs) and neuropil threads that are also positive for p-tau181, 202, 202/205, 231, and 369/404. The p-tau217, but not the other five p-tau variants, was also prominently seen in vesicles structure positive for markers of granulovacuolar degeneration bodies and multi-vesicular bodies. Further, individuals with a high likelihood of AD showed significantly higher p-tau217 area fraction in 4 different brain areas (entorhinal cortex, inferior temporal gyrus, and superior frontal gyrus) compared to those with Primary age related tauopathy or other non-AD tauopathies. The p-tau217 area fraction correlated strongly with total amyloid-beta (Aβ) and NFT brain load when the whole group was analyzed. Finally, the mean p-tau217 area fraction correlated significantly with p-tau217 concentrations in antemortem collected plasma specifically in individuals with amyloid plaques and not in those without amyloid plaques. These studies highlight differences in cellular localization of different p-tau variants and suggest that plasma levels of p-tau217 reflect an accumulation of p-tau217 in presence of Aβ plaque load.

Predicting respiratory failure in patients infected by SARS-CoV-2 by admission sex-specific biomarkers

Background Several biomarkers have been identified to predict the outcome of COVID-19 severity, but few data are available regarding sex differences in their predictive role. Aim of this study was to identify sex-specific biomarkers of severity and progression of acute respiratory distress syndrome (ARDS) in COVID-19. Methods Plasma levels of sex hormones (testosterone and 17β-estradiol), sex-hormone dependent circulating molecules (ACE2 and Angiotensin1-7) and other known biomarkers for COVID-19 severity were measured in male and female COVID-19 patients at admission to hospital. The association of plasma biomarker levels with ARDS severity at admission and with the occurrence of respiratory deterioration during hospitalization was analysed in aggregated and sex disaggregated form. Results Our data show that some biomarkers could be predictive both for males and female patients and others only for one sex. Angiotensin1-7 plasma levels and neutrophil count predicted the outcome of ARDS only in females, whereas testosterone plasma levels and lymphocytes counts only in males. Conclusions Sex is a biological variable affecting the choice of the correct biomarker that might predict worsening of COVID-19 to severe respiratory failure. The definition of sex specific biomarkers can be useful to alert patients to be safely discharged versus those who need respiratory monitoring.

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area

The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancer. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2,732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the disease state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.