Loss of the sense of smell (anosmia) has been included as a COVID-19 symptom by the World Health Organization. The majority of patients recover the sense of smell within a few weeks postinfection (short-term anosmia), while others report persistent anosmia. Several studies have investigated the mechanisms leading to anosmia in COVID-19; however, the evidence is scattered, and the mechanisms remain poorly understood. Based on a comprehensive review of the literature, we aim here to evaluate the current knowledge and uncertainties regarding the mechanisms leading to short-term anosmia following SARS-CoV-2 infection. We applied an adverse outcome pathway (AOP) framework, well established in toxicology, to propose a sequence of measurable key events (KEs) leading to short-term anosmia in COVID-19. Those KEs are (1) SARS-CoV-2 Spike proteins binding to ACE-2 expressed by the sustentacular (SUS) cells in the olfactory epithelium (OE); (2) viral entry into SUS cells; (3) viral replication in the SUS cells; (4) SUS cell death; (5) damage to the olfactory sensory neurons and the olfactory epithelium (OE). This AOP-aligned approach allows for the identification of gaps where more research should be conducted and where therapeutic intervention could act. Finally, this AOP gives a frame to explain several disease features and can be linked to specific factors that lead to interindividual differences in response to SARS-CoV-2 infection.
Global emphasis on enhancing prevention and treatment strategies necessitates increased understanding of biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the "general psychopathology factor", is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography-tandem mass spectrometry, 14 proteins with a significant connection with the p-factor were identified, 9 of which were linked to epidermal growth factor receptor (EGFR) signalling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.
Adolescence is often a challenging time in which psychiatric issues have a strong connection to mental health disorders later in life. The early identification of the problems can reduce the burden of disease. To date, the effective identification of adolescents at risk of developing mental health problems remains understudied. Altogether, the interaction between circulating cell-free mtDNA (ccf-mtDNA) and inflammatory cytokines in adolescents is insufficiently understood regarding experienced mental health difficulties. Our study selected the participants based on the Strength and Difficulty Questionnaire (SDQ) score using the cut-off points of 3 and 18 for the low and the high score groups, respectively. The answers of the SDQ at the age of 12.2–15.7 years contributed to the investigation of (i) whether ccf-mtDNA units are associated with cytokines, and (ii) if an interaction model for predicting risk of mental health issues is observed. We discovered a sex-specific correlation between the screened markers associated with mental health problems in the low and high SDQ score groups among the male participants and in the low SDQ score group among the female participants. The mitochondrial MT-ND4 and MT-CO1 genes correlated significantly with interleukin-12p70 (IL-12p70) in males and with monocyte chemoattractant protein-1 (MCP-1) in females. Due to the nature of the explorative study, the studied markers alone did not indicate statistical significance for the prediction of mental health problems. Our analysis provided new insight into potential plasma-based biomarkers to predict mental health issues.
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