Molecular and Biological Mechanisms Underlying Gender Differences in COVID-19 Severity and Mortality

Wehbe, Zena; Hammoud, Safaa Hisham; Yassine, Hadi M.; Fardoun, Manal; El‐Yazbi, Ahmed F.; Eid, Ali H.

doi:10.3389/fimmu.2021.659339

Cited by 45 publications

(48 citation statements)

References 159 publications

(215 reference statements)

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“…Recent evidence points to the possible contributions of triggering and persistence of autoimmune activation in SARS-CoV-2-infected COVID-19 patients [ 2 , 3 ]. Intriguingly, despite classic autoimmune diseases being more prevalent in females, emerging studies have revealed a paradoxical male predominance of autoimmune activation in the setting of severe COVID-19 illness [ 4 ]. The extent to which such paradoxical sex differences in triggered autoimmunity may exist and persist across the broader clinical spectrum of SARS-CoV-2 infection is unclear.…”

Section: Introductionmentioning

confidence: 99%

Paradoxical sex-specific patterns of autoantibody response to SARS-CoV-2 infection

et al. 2021

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Background Pronounced sex differences in the susceptibility and response to SARS-CoV-2 infection remain poorly understood. Emerging evidence has highlighted the potential importance of autoimmune activation in modulating the acute response and recovery trajectories following SARS-CoV-2 exposure. Given that immune-inflammatory activity can be sex-biased in the setting of severe COVID-19 illness, the aim of the study was to examine sex-specific autoimmune reactivity to SARS-CoV-2 in the absence of extreme clinical disease. Methods In this study, we assessed autoantibody (AAB) reactivity to 91 autoantigens previously linked to a range of classic autoimmune diseases in a cohort of 177 participants (65% women, 35% men, mean age of 35) with confirmed evidence of prior SARS-CoV-2 infection based on presence of antibody to the nucleocapsid protein of SARS-CoV-2. Data were compared to 53 pre-pandemic healthy controls (49% women, 51% men). For each participant, socio-demographic data, serological analyses, SARS-CoV-2 infection status and COVID-19 related symptoms were collected by an electronic survey of questions. The symptoms burden score was constructed based on the total number of reported symptoms (N = 21) experienced within 6 months prior to the blood draw, wherein a greater number of symptoms corresponded to a higher score and assigned as more severe burden. Results In multivariable analyses, we observed sex-specific patterns of autoreactivity associated with the presence or absence (as well as timing and clustering of symptoms) associated with prior COVID-19 illness. Whereas the overall AAB response was more prominent in women following asymptomatic infection, the breadth and extent of AAB reactivity was more prominent in men following at least mildly symptomatic infection. Notably, the observed reactivity included distinct antigens with molecular homology with SARS-CoV-2. Conclusion Our results reveal that prior SARS-CoV-2 infection, even in the absence of severe clinical disease, can lead to a broad AAB response that exhibits sex-specific patterns of prevalence and antigen selectivity. Further understanding of the nature of triggered AAB activation among men and women exposed to SARS-CoV-2 will be essential for developing effective interventions against immune-mediated sequelae of COVID-19.

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Section: Introductionmentioning

confidence: 99%

Paradoxical sex-specific patterns of autoantibody response to SARS-CoV-2 infection

et al. 2021

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“…A third branch of research invests risk factors for specific groups: pregnant women [12], the elderly population [13,14], or specific regions [15][16][17], to name a few examples. While in the beginning, identifying risk factors was of primary interest, there are now also some attempts to understand possible mechanisms [18][19][20]. Unsurprisingly, the vast amount of research has led to an equally high number of systematic reviews and meta-analyses on risk factors [21][22][23][24][25][26][27][28][29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study

Meintrup

Borgmann

Seidl

et al. 2021

JCM

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(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06–1.10), cardiovascular disease (OR 1.64, CI 1.06–2.55), pulmonary disease (OR 1.87, CI 1.16–3.03), baseline Statin treatment (0.54, CI 0.33–0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92–0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01–1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94–0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62–0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05–1.18), kidney failure (OR 1.68, CI 1.05–2.70), congestive heart failure (OR 2.62, CI 1.11–6.21), severe liver failure (OR 4.93, CI 1.94–12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14–2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.

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“…This exposes them to considerably greater risks of critical COVID-19 outcomes [34][35][36][37]. Alongside this, various studies provide complementary explanations based on sexual dimorphisms [38]. Some in vivo experiments have shown the possible role of sex hormones in regulating ACE2 activity, essential for SARS-CoV-2 to enter the host cells in upper and lower respiratory tracts [39].…”

Section: Main Findingsmentioning

confidence: 99%

Dying From COVID-19 or With COVID-19: A Definitive Answer Through a Retrospective Analysis of Mortality in Italy

Rovetta¹,

Bhagavathula

2021

Preprint

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Background: COVID-19 mortality was associated with several reasons, including conspiracy theories and infodemic phenomena. However, little is known about the potential endogenous reasons for the increase in COVID-19 associated mortality in Italy. Objective: This study aimed to search the potential endogenous reasons for the increase in COVID-19 mortality recorded in Italy during the year 2020 and evaluate the statistical significance of the latter. Methods: We analyzed all the trends in the timelapse 2011-2019 related to deaths by age, sex, region, and cause of death in Italy and compared them with those of 2020. Ordinary least squares (OLS) linear regressions and ARIMA (p, d, q) models were applied to investigate the predictions of death in the year 2020 as compared to death reported in 2020. Grubbs and Iglewicz-Hoaglin tests were used to identify the statistical differences between the predictors and observed death during the year 2020. The relationship between mortality and predictive variables was assessed using OLS multiple regression models. Results: Both ARIMA and OLS linear regression models predicted the number of deaths in Italy during the year 2020 is between 640,000 and 660,000 (95% confidence intervals range: 620,000 - 695,000) and these values were far from the observed deaths reported (n = 750,000). Significant difference in deaths at national level (P = 0.003), and higher male mortality than women (+18% versus +14%, P < 0.001 versus P = 0.01) was observed. Finally, higher mortality was strongly and positively correlated with latitude (R = 0.82, P < 0.001) Conclusions: Our findings suggest that the absence of historical endogenous reasons capable of justifying the increase in deaths and mortality observed in Italy in 2020. Together with the current knowledge on the novel coronavirus 2019, these findings provide decisive evidence on the devastating impact of COVID-19 in Italy. We suggest that this research be leveraged by government, health, and information authorities to furnish proof against conspiracy theorists. Moreover, given the marked concordance between the predictions of the ARIMA and OLS regression models, we suggest that these models be exploited to predict mortality trends.

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Molecular and Biological Mechanisms Underlying Gender Differences in COVID-19 Severity and Mortality

Cited by 45 publications

References 159 publications

Paradoxical sex-specific patterns of autoantibody response to SARS-CoV-2 infection

Paradoxical sex-specific patterns of autoantibody response to SARS-CoV-2 infection

Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study

Dying From COVID-19 or With COVID-19: A Definitive Answer Through a Retrospective Analysis of Mortality in Italy

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