Background: COVID-19 pandemic has brought long-lasting social, emotional, and cognitive consequences. Long COVID is characterized by a myriad of symptoms and complications that persist long after the infection, including cognitive decline and mental health impairment. This study aims to investigate depressive symptoms and cognitive performance stratified by sex and group in adults with and without long COVID.
Method: Community-dwelling individuals from Porto Alegre, Brazil, were divided into control and long COVID groups. We recruited 49 individuals, aged >50 years. Individuals were evaluated with the mini mental state examination (MMSE), Clock Drawing Test, Trail Making Test (TMT-B), Wechsler Memory Scale (WMS-R) and PHQ-9 scale of depressive symptoms. A regression model was conducted stratified by sex, age and group. PHQ-9 was used as an interaction of the same variables. Data were analyzed using R, considering p-value < 0.05.
Result: A total of 49 individuals (59.8 ± 8.06 mean years of age, 63.3% females), having high education (>11 years of study) were included. The control group was comprised of 18 individuals (36.73%) and the long COVID group had 31 individuals (63.26%). The Long COVID group had a worse performance in WMS-A (p <0.011) and WMS-B (p <0.03) in the immediate test and WSM-B recall (p <0.02). The PHQ-9 test differed between groups, with long COVID individuals presenting depressive symptoms (p <0.003). We also found an interaction of long COVID and PHQ-9 impacting on the TMT- B test (p <0.03).
Conclusion: Preliminary results showed that long COVID induced impairment in executive functions, specifically in working memory and episodic memory scores. Additionally, there was an impact of depressive symptoms in the relationship between group and TMT-B scores. Participants with depressive symptoms had worsened cognitive performance on the regression analysis. A larger sample should corroborate these findings and provide further insights into the long COVID cognitive impact.
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http://dx.doi.org/10.1002/alz.093084 | DOI Listing |
Hum Immunol
January 2025
Medical University - Sofia, Medical Faculty, Department of Clinical Immunology, Bulgaria; University Hospital Alexandrovska, Clinic of Clinical Immunology and Stem Cell Bank, Bulgaria.
The SARS-CoV-2 outbreak represents a global health problem. The different infection rates are heavily influenced by host genetic factors, such as variability in the HLA region. The aim of our study was to investigate whether certain HLA alleles in the Bulgarian population contribute to COVID-19 progression and their role in anti-SARS-CoV-2 immunity.
View Article and Find Full Text PDFComput Biol Med
January 2025
LMA Laboratory, University of Bejaia, Bejaia 06000, Algeria. Electronic address:
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM)-based hybrid model for health monitoring and health crisis forecasting. It consists of efficiently retrieving safe content from multiple social media sources.
View Article and Find Full Text PDFNeuropsychopharmacol Rep
March 2025
Molecular Psychoneuroimmunology, Institute for Genetic Medicine, Hokkaido University, Sapporo, Hokkaido, Japan.
COVID-19 exhibits not only respiratory symptoms but also neurological/psychiatric symptoms rarely including delirium/psychosis. Pathological studies on COVID-19 provide evidence that the cytokine storm, in particular (epidermal growth factor) EGF receptor (EGFR, ErbB1, Her1) activation, plays a central role in the progression of viral replication and lung fibrosis. Of note, SARS-CoV-2 virus (specifically, S1 spike domain) mimics EGF and directly transactivates EGFR, preceding the inflammatory process.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Systems Engineering & Operations Research, George Mason University, Fairfax, VA, 22030, USA.
Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.
View Article and Find Full Text PDFNat Genet
January 2025
Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Aberrant immune responses to viral pathogens contribute to pathogenesis, but our understanding of pathological immune responses caused by viruses within the human virome, especially at a population scale, remains limited. We analyzed whole-genome sequencing datasets of 6,321 Japanese individuals, including patients with autoimmune diseases (psoriasis vulgaris, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), pulmonary alveolar proteinosis (PAP) or multiple sclerosis) and coronavirus disease 2019 (COVID-19), or healthy controls. We systematically quantified two constituents of the blood DNA virome, endogenous HHV-6 (eHHV-6) and anellovirus.
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