GWAS reveals genetic basis of a predisposition to severe COVID-19 through in silico modeling of the FYCO1 protein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is heavily reliant on its natural ability to "hack" the host's genetic and biological pathways. The genetic susceptibility of the host is a key factor underlying the severity of the disease. Polygenic risk scores are essential for risk assessment, risk stratification, and the prevention of adverse outcomes. In this study, we aimed to assess and analyze the genetic predisposition to severe COVID-19 in a large representative sample of the Russian population as well as to build a reliable but simple polygenic risk score model with a lower margin of error. Another important goal was to learn more about the pathogenesis of severe COVID-19. We examined the tertiary structure of the FYCO1 protein, the only gene with mutations in its coding region and discovered changes in the coiled-coil domain. Our findings suggest that FYCO1 may accelerate viral intracellular replication and excessive exocytosis and may contribute to an increased risk of severe COVID-19. We found significant associations between COVID-19 and LZTFL1, FYCO1, XCR1, CCR9, TMLHE-AS1, and SCYL2 at 3p21.31. Our findings further demonstrate the polymorphic nature of the severe COVID-19 phenotype.

Mortality and survival in nonagenarians during the COVID-19 pandemic: Unstable equilibrium of aging.

Introduction: Aging puts the human body under an immense stress and makes it extremely susceptible to many diseases, often leading to poor outcomes and even death. Long-living individuals represent a unique group of people who withstood the stress of time and offer an abundance of information on the body's ability to endure the pressure of aging. In this study, we sought to identify predictors of overall one-year mortality in 1641 long-living individuals. Additionally, we analyzed risk factors for COVID-19-related morality, since statistics demonstrated an extreme vulnerability of older adults. Methods: We conducted a two-stage evaluation, including a comprehensive geriatric assessment for major aging-associated: frailty, cognitive impairment, frontal lobe dysfunction, chronic pain, anxiety, risk of falls, sensory deficit, depression, sarcopenia, risk of malnutrition, fecal and urinary incontinence, dependence in Activities of Daily Living, dependence in Instrumental Activities of Daily Living, polypragmasia, and orthostatic hypotension; extensive blood testing, a survey, and a one-year follow-up interview. Results: The most reliable predictors of overall mortality were cognitive impairment, malnutrition, frailty, aging-associated diseases and blood markers indicating malnutrition-induced metabolic dysfunctions (decreased levels of protein fractions, iron, 25-hydroxyvitamin D, and HDL), and aging biomarkers, such as IGF-1 and N-terminal pro b-type natriuretic peptide. In post-COVID 19 participants, the most significant mortality predictors among geriatric syndromes were depression, frontal lobe dysfunction and frailty, and similar to overall mortality blood biomarkers - 25-hydroxyvitamin D, IGF-1, HDL as well as high white blood cell, neutrophils counts and proinflammatory markers. Based on the results, we built a predictive model of overall mortality in the long-living individuals with f-score=0.76. Conclusion: The most sensitive and reliable predictors of mortality were modifiable. This is another evidence of the critical importance of proper geriatric care and support for individuals in their "golden years". These results could facilitate geriatric institutions in their pursuit for providing improved care and could aid physicians in detecting early signs of potentially deadly outcomes. Additionally, our findings could be used in developing day-to-day care guidelines, which would greatly improve prevention statistics.

Analyzing Successful Aging and Longevity: Risk Factors and Health Promoters in 2020 Older Adults.

Geriatric syndromes (GSs) and aging-associated diseases (AADs) are common side effects of aging. They are affecting the lives of millions of older adults and placing immense pressure on healthcare systems and economies worldwide. It is imperative to study the factors causing these conditions and develop a holistic framework for their management. The so-called long-lived individuals-people over the age of 90 who managed to retain much of their health and functionality-could be holding the key to understanding these factors and their health implications. We analyzed the health status and lifestyle of the long-lived individuals and identified risk factors for GSs. Family history greatly contributes to the health and prevention of cognitive decline in older adults. Lifestyle and certain socioeconomic factors such as education, the age of starting to work and retiring, job type and income level, physical activity, and hobby were also associated with certain GSs. Moreover, the levels of total protein, albumin, alpha-1 globulins, high-density lipoprotein, free triiodothyronine, and 25-hydroxyvitamin D were direct indicators of the current health status. The proposed mathematical model allows the prediction of successful aging based on family history, social and economic factors, and life-long physical activity (f1 score = 0.72, AUC = 0.68, precision = 0.83 and recall = 0.64).