Potential Influence of Menstrual Status and Sex Hormones on Female Severe Acute Respiratory Syndrome Coronavirus 2 Infection: A Cross-sectional Multicenter Study in Wuhan, China

Abstract

Background: Recent studies have indicated that females with coronavirus disease 2019 (COVID-19) have a lower morbidity, severe case rate, and mortality and better outcome than those of male individuals. However, the reasons remained to be addressed.

Methods: To find the factors that potentially protect females from COVID-19, we recruited all confirmed patients hospitalized at 3 branches of Tongji Hospital (N = 1902), and analyzed the correlation between menstrual status (n = 509, including 68 from Mobile Cabin Hospital), female hormones (n = 78), and cytokines related to immunity and inflammation (n = 263), and the severity/clinical outcomes in female patients <60 years of age.

Results: Nonmenopausal female patients had milder severity and better outcome compared with age-matched men (P < .01 for both). Menopausal patients had longer hospitalization times than nonmenopausal patients (hazard ratio [HR], 1.91 [95% confidence interval {CI}, 1.06-3.46]; P = .033). Both anti-Müllerian hormone (AMH) and estradiol (E2) showed a negative correlation with severity of infection (adjusted HR, 0.146 [95% CI, .026-.824], P = .029 and 0.304 [95% CI, .092-1.001], P = .05, respectively). E2 levels were negatively correlated with interleukin (IL) 2R, IL-6, IL-8, and tumor necrosis factor alpha in the luteal phase (P = .033, P = .048, P = .054, and P = .023) and C3 in the follicular phase (P = .030).

Conclusions: Menopause is an independent risk factor for female COVID-19 patients. AMH and E2 are potential protective factors, negatively correlated with COVID-19 severity, among which E2 is attributed to its regulation of cytokines related to immunity and inflammation.

Keywords: E2; SARS-CoV-2; cross-sectional study; female hormones; menstrual status.

Figure 1.

Flowchart of patient recruitment procedure. Patients (N = 1902) from the 3 branches of Tongji Hospital were included to explore the sex differences in coronavirus disease 2019 (COVID-19) prognosis. Female patients (n = 509 [441 from Tongji Hospital and 68 from Mobile Cabin Hospital]) were surveyed by telephone follow-up regarding menstrual status and gynecologic history. A total of 435 patients with complete medical history were included. We then tested serum cytokines related to immunity and inflammation for 263 patients and sex hormone levels for 78 patients except those who denied our request. Finally, we determined the correlation between menstruation status/sex hormones and severity, and outcomes of COVID-19. Abbreviations: AMH, anti-Müllerian hormone; COVID-19, coronavirus disease 2019; E2, estradiol; FSH, follicle-stimulating hormone; LH, luteinizing hormone; P, progesterone; PRL, prolactin; T, testosterone.

Figure 2.

Cox analysis of age, menstrual status, and disease severity with probability of hospitalization. A, Univariate Cox regression of age with probability of hospitalization (hazard ratio [HR], 0.36 [95% confidence interval {CI}, .23–.57]; P < .0001). B, Univariate Cox regression of menstrual status with probability of hospitalization. Menstruation was divided into nonmenopause (regular or irregular menstruation) and menopause (HR, 0.67 [95% CI, .41–1.1]; P = .11). C, Univariate Cox regression of disease severity with probability of hospitalization (HR, 0.38 [95% CI, .2–.72]; P = .0029). D, In multivariate Cox analysis, the covariates age, menstruation, and severity were significant (P < .001, P = .033, and P = .007, respectively). However, the covariate comorbidities failed to be significant (P = .362, which is > .05). The HR for menstruation was 1.91, indicating a strong relationship between nonmenopause and reduced number of days in hospital. The HR for age and severity was 0.26 and 0.41, respectively, indicating that age and severity have a significant impact on risk of days in hospital. Abbreviation: AIC, Akaike information criterion

Figure 3.

Correlation between immunity/inflammation-related cytokines and severity, composite endpoint, and estradiol (E2) in different phases. A, Correlation between interleukin (IL) 6 with disease severity and composite endpoint. B, Correlation between IL-8 with disease severity and composite endpoint. C, Correlation between IL-2R with composite endpoint. In A–C, the mean value is marked as a solid line. Results of Mann-Whitney U test indicate that patients in the severe group showed higher levels of IL-6 and IL-8 (P = .040 and P = .033, respectively) and that patients who reached the composite endpoint presented higher levels of IL-6, IL-8, and IL-2R (P < .0001, P = .00017, and P = .0091, respectively). D, Correlation between C3 and E2 of patients with coronavirus disease 2019 (COVID-19) in the follicular phase (n = 11). Result of Pearson correlation analysis indicates a significant inverse correlation between E2 and C3 (R = −0.65, P = .030). E, Correlation between IL-6 and E2 of COVID-19 patients in the luteal phase (n = 13). F, Correlation between IL-8 and E2 of COVID-19 patients in the luteal phase (n = 13). G, Correlation between IL-2R and E2 of COVID-19 patients in the luteal phase (n = 13). H, Correlation between tumor necrosis factor alpha (TNF-α) and E2 of COVID-19 patients in the luteal phase (n = 13). Results of Pearson correlation analysis indicate a significant inverse correlation between the E2 level and IL-6 (R = −0.56, P = .048), IL-8 (R = −0.55, P = .054), IL-2R (R = −0.59, P = .033), and TNF-α (R = −0.62, P = .023).