Toscano‑Guerra et al. BMC Medicine (2022) 20:129 https://doi.org/10.1186/s12916-022-02345-w RESEARCH ARTICLE Open Access Recovery of serum testosterone levels is an accurate predictor of survival from COVID-19 in male patients Emily Toscano‑Guerra1,2,3, Mónica Martínez Gallo4,5,6*, Iria Arrese‑Muñoz4,5,6, Anna Giné1,2, Noelia Díaz‑Troyano1, Pablo Gabriel‑Medina1, Mar Riveiro‑Barciela7, Moisés Labrador‑Horrillo7, Fernando Martinez‑Valle7, Adrián Sánchez Montalvá8, Manuel Hernández‑González4,5,6, Ricardo Pujol Borrell4,5,6, Francisco Rodríguez‑Frias1, Roser Ferrer1, Timothy M. Thomson3,9,10,11* and Rosanna Paciucci1,2* Abstract Background: SARS-CoV-2 infection portends a broad range of outcomes, from a majority of asymptomatic cases to a lethal disease. Robust correlates of severe COVID-19 include old age, male sex, poverty, and co-morbidities such as obesity, diabetes, and cardiovascular disease. A precise knowledge of the molecular and biological mechanisms that may explain the association of severe disease with male sex is still lacking. Here, we analyzed the relationship of serum testosterone levels and the immune cell skewing with disease severity in male COVID-19 patients. Methods: Biochemical and hematological parameters of admission samples in 497 hospitalized male and female COVID-19 patients, analyzed for associations with outcome and sex. Longitudinal (in-hospital course) analyses of a subcohort of 114 male patients were analyzed for associations with outcome. Longitudinal analyses of immune popu‑ lations by flow cytometry in 24 male patients were studied for associations with outcome. Results: We have found quantitative differences in biochemical predictors of disease outcome in male vs. female patients. Longitudinal analyses in a subcohort of male COVID-19 patients identified serum testosterone trajectories as the strongest predictor of survival (AUC of ROC = 92.8%, p < 0.0001) in these patients among all biochemical param‑ eters studied, including single-point admission serum testosterone values. In lethal cases, longitudinal determinations of serum luteinizing hormone (LH) and androstenedione levels did not follow physiological feedback patterns. Failure to reinstate physiological testosterone levels was associated with evidence of impaired T helper differentiation and augmented circulating classical monocytes. Conclusions: Recovery or failure to reinstate testosterone levels is strongly associated with survival or death, respec‑ tively, from COVID-19 in male patients. Our data suggest an early inhibition of the central LH-androgen biosynthesis axis in a majority of patients, followed by full recovery in survivors or a peripheral failure in lethal cases. These obser‑ vations are suggestive of a significant role of testosterone status in the immune responses to COVID-19 and warrant *Correspondence: mmartinez@vhebron.net; titbmc@ibmb.csic.es; rpaciucci@vhebron.net 2 Cell Signaling and Cancer Progression Laboratory, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain 3 Universidad Peruana Cayetano Heredia, Lima, Perú 6 Department of Cell Biology, Physiology and Immunology, Autonomous University of Barcelona (UAB), Barcelona, Spain Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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Keywords: COVID-19, Survival, Longitudinal, Testosterone, Immune phenotype Background T regulatory cells, higher numbers of group 2 innate The COVID-19 pandemic, caused by SARS-CoV-2, is lymphoid cells (ILC2), and superior immune-mediated characterized by a diversity of clinical manifestations, tissue repair capacities as compared to men [22, 23]. In including exacerbated inflammatory states accompa- addition, sex hormones may differentially impact the fre- nied with tissue and organ destruction beyond direct quency and severity of many autoimmune and inflam- viral cytopathic effects. From the outset of the pan- matory diseases, generally more prevalent in women demic, it became clear that, while men and women than men [24, 25]. It should be noted that sex hormones present a similar prevalence of infection [1, 2], a higher may exert apparently contrasting effects. For example, an risk of severe disease and death is significantly associ- immunosuppressive role for testosterone was observed in ated with male sex [2, 3], similar to the other pathogenic response to influenza vaccination [26], while testosterone coronaviruses, SARS-CoV and MERS-CoV, and other supplementation following influenza infection in aged viral respiratory infections [4, 5]. Multiple factors have male mice, which caused decreased serum testosterone been considered to explain the sex disparity observed in levels, reduced mortality [27]. the development of severe COVID-19, including differ- In order to better understand the relationship between ential biological and pathophysiological impacts of age testosterone status and disease severity, we have analyzed and comorbidities such as cardiovascular disease, high serum biomarkers, including testosterone, and immune blood pressure, chronic obstructive pulmonary disease cell subpopulations in COVID-19 patients in associa- (COPD), diabetes, obesity, or active cancer [6]. Gender tion with disease outcome. We have found that the tra- differences in disease severity are also observed in racial jectories of serum testosterone levels are highly accurate and ethnic minority groups, disproportionately affected predictors of survival in male COVID-19 patients. Fur- by COVID-19 [6]. thermore, we establish that male COVID-19 patients The underlying mechanisms that may account for the with a fatal outcome display a late coordinated depletion differences between men and women in the development of circulating subsets of differentiated CD4+ T lympho- of severe COVID-19 are not completely understood. As cytes and monocytes, mirrored by a relative enrichment the main cellular receptor for SARS-CoV-2, ACE2, and of undifferentiated CD4+ T cells and monocytes. the major viral fusogenic membrane-associated protease, TMPRSS2, are under transcriptional regulation by andro- Methods gens [7], it had been predicted that men would present Study design a higher propensity of infection by SARS-CoV-2 and to With the aim of exploring factors that may underlie worse develop more severe disease than women [7, 8]. However, progression of COVID-19 in men, we have undertaken a men and women show comparable risks of infection [1, retrospective study with 497 (249 males and 248 females) 2] and observational studies of male COVID-19 patients patients admitted to the Vall d’Hebron Hospital (HVH) under androgen-deprivation therapy have yielded con- between May1st and June 30th 2020, with RT-PCR-con- trasting results with regard to risk of developing severe firmed diagnosis of SARS-CoV-2 infection. Patients were COVID-19 (ref. [9, 10]). Contrariwise, there is grow- first studied for serum biochemical and hematological ing evidence that severe COVID-19 in male patients is variables in samples collected at or near admission (first accompanied with diminished levels of circulating testos- time point or Sample 1), for baseline assessment. Sub- terone [11–13], suggesting a critical role for androgens sequently, a subcohort of 114 male patients was studied [11, 14] and androgen receptor, AR [15], in preventing for the progression of the disease by analyzing the same the innate and/or adaptive immune dysfunctions that variables longitudinally, and samples from this subcohort lead to the development of severe forms of the disease were further analyzed for serum luteinizing hormone [16–18]. A role on coagulation for testosterone has also (LH) and androstenedione levels, as well as an extensive been suggested as a factor to consider in COVID-19 phenotyping of circulating immune cells. pathogenesis [19, 20]. The sexual dimorphism of immune responses to Patient selection pathogens has been long recognised [21], pointing to Patients included in the study were consecutive patients women having stronger antiviral mechanisms, stronger admitted to the HVH, with the following exclusion Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 3 of 18 criteria: previously hospitalized, recently transplanted, determined by chemiluminiscent immunoassays (CLIA) immunosuppressed, and hormonally depleted. One on an AtellicaTM IM Analyzer (Siemens Inc., NY), using hundred fourteen male patient subcohorts studied for testosterone TSTII (Siemens ref. 10995707) and luteiniz- longitudinal analyses were chosen on the basis of serum ing hormone (LH) (Siemens ref. 10995634) kits. Andros- sample availability. Within this subcohort, a group of tenedione was measured on a LIASON XL Analyzer 24 patients, for whom matched serum and peripheral (DiaSorin, Saluggia, Italy), using the LiasonR andros- blood mononuclear cells were available, was studied for tenedione (ref. 318870) assay. As references for healthy immune phenotyping. men, we used median total serum testosterone levels of 409.72 ng/dL (90% CI 197.44–669.58) for < 50-year-old Patient classification individuals and 377.46 ng/dL (90% CI 187.72–684.19) Patients were classified as mild, moderate, severe-survi- for ≥ 50-year-old individuals (FDA-approved proto- vor, and severe-deceased as per a 4-point scale adapted col, https://​www.​acces​sdata.​fda.​gov/​cdrh_​docs/​pdf19/​ from the 6-point ordinary scale used by Grein et al. [28] K1915​33.​pdf ). For luteinizing hormone (LH), the refer- as follows (Table ST3): Mild: symptomatic patients with ence median values were 2.8 mIU/mL (90% CI 1.5–9.3) PCR-diagnosed SARS-CoV-2 infection that were in for < 70-year-old individuals and 8.0 mIU/mL (90% CI emergency unit or required hospitalization for less than 3.1–34.6) for ≥ 70-year-old individuals. For androsten- 2 weeks; Moderate: hospitalized patients requiring low- edione, the reference median value was 1.80 ng/mL (90% flow oxygen (mask or nasal prongs) or high-flow oxygen, CI 0.5–3.5). Bioavailable-free testosterone was calcu- not requiring ICU admission; Severe-survivor: patients lated according to Vermeulen et al. [29]. admitted to the ICU requiring non-invasive or invasive mechanical ventilation, then discharged; and Severe- Immuno‑phenotyping deceased: ICU patients with a fatal outcome. Blood samples were collected in Vacutainer tubes con- taining ethylene-diamine-tetra-acetic acid (EDTA) as Data and sample collection anticoagulant (BD-Plymouth, PL6 7BP, UK) and pro- The final dataset was a compilation of data from the Vall cessed within 4 h after collection. Absolute counts d’Hebron Laboratory database and the Vall d’Hebron and relative numbers of peripheral blood lymphocytes prospective COVID-19 cohort database, which was col- were determined for all study participants using tetra lected prospectively from medical doctors during the CHROME Tube 1 (CD45-FITC/CD4-PE/CD8-ECD/ first and second wave of the pandemic using a case report CD3-PC5) and tetra CHROME Tube 2 (CD45-FITC/ form (CRF) designed by the Infection Disease Depart- CD56-PE/CD19-ECD/CD3-PC5) panels (Beckman Coul- ment in RedCAP web-based platform. Comorbidities ter). Samples were fixed in 1X lysing solution (BC) and considered were chronic lung disease, cardiovascular dis- acquired on a BC Navios EX instrument. ease, diabetes, chronic kidney disease, liver disease, HIV For multicolor staining and analysis, extended lympho- infection with good adherence, obesity (BMI ≥ 30), and cyte subpopulations were assessed with 5 different flow cancer. For single-point analyses, data were obtained on cytometry panels designed according to the HIPC pro- (or near) hospital admission date. For longitudinal analy- tocol [30]. Two additional panels were added to analyze ses, data were obtained throughout hospitalization with basic lymphocyte populations and RTE. Compensation serial time-point sample collection every 7 days in aver- controls were used in each panel to avoid overlapping age. For patients in the severe outcome groups, up to five of the different fluorochromes. Gating strategies were time-point samples were analyzed. Patients in the com- as described [31], and the antibody panels were summa- bined mild-moderate outcome groups were discharged in rized as follows and in Table ST4: average, after 2 weeks of admission, and a maximum of three time-point samples were procured from them. For • Panel 1: General immune phenotype for T, B, and immune phenotyping analyses, at least two independent natural killer (NK) lymphocyte subpopulations, gat- samples (Sample 1 and Sample 2) were collected, sepa- ing by CD45 versus SSC. rated by 5 to 20 days. ­ D4+ and • Panel 2: Gating strategy for differentiated C + ­CD8 T cell subsets, based on CD45RA and CCR7 Serological determinations expression defining: ­ CD45RA+/CCR7+ (naïve), Serum biochemical variables were measured by auto- − ­CD45RA /CCR7 + (central memory [TCM]), mated analyzers at the Biochemistry Service Core ­CD45RA−/CCR7− (effector memory [TEM]), and Laboratory Facility at HVH. All determinations were ­CD45RA+/CCR7− (terminal effector memory compared to internal controls used for reference [TEMRA]). ­CD4+ T helper (Th) populations (Th1, ranges at the Core Facility. Serum hormone levels were Th2, Th17, Th1–17), based on CCR6 and CXCR3 Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 4 of 18 expression, were analyzed by gating on CD45RA− patient and average values for each parameter calculated TCM and TEM cells. for each time-point, followed by linear regression. The • Panel 3: T regulatory (Treg) cell populations: resulting linear regression slope values were used in uni- ­CD3+CD4+CD25+, ­CD127−, ­CCR4+, and variate logistic regression analysis to assess the outcome + ­CD45RO . predictive power of the trajectories. P values ≤ 0.05 were • Panel 4: B cell populations (naïve, pre-switched, considered significant. For principal component analysis switched memory, and exhausted) depending on (PCA), the variables analyzed included all the biochemi- expression of IgD and CD27. The differing pattern of cal parameters and immune subpopulations, including ­CD24+ and ­CD38+ expression identified transitional numerical assignments for outcome (1, mild–moderate; cells and plasmablasts. CD27 and CD21 enabled 2, severe; 3, deceased) and selecting for ≥ 3 components, study of the CD21low population. of which the 2 summarizing the highest variance were • Panel 5: Dendritic cells (DC), natural killer (NK) used for the 2-dimensional representations. PCA, mul- cells, and monocyte populations were analyzed in the tivariate correlation analysis, and other calculations, as ­CD3−CD19−gate. NK subpopulations ­ (NKdim and well as graphic representations, were performed with bright ­NK ) were studied using CD56 and CD16 expres- GraphPad Prism 9.0.2. sion. CD16 and CD14 were used to identify classical monocytes ­(CD14+CD16−) and non-classical mono- Ethical considerations cytes ­(CD16+CD14−). DCs were studied selecting for The present study was performed with surplus serum populations negative for the following markers: CD3, samples from routinely tested hospitalized COVID-19 CD14, CD16, CD19, CD20, and CD56. High expres- patients, following protocols reviewed and approved by sion of HLA-DR and CD11c and CD123 was used to the HVH Institutional Review Board (Medical Research identify plasmacytoid DCs (HLA-DR+CD123+) and Ethics Committee, protocol number PR(AG)329-2020). myeloid DCs (HLA-DR+CD11c+). Immunophenotyping studies of the peripheral blood • Panel 6: Recent thymic emigrant cells (RTEs) were cells underwent a separate review and approval process studied using CD3, CD4, CD27, CD31, CD45RA, (protocol number PR(AG)242/2020). For the final dataset and CD62L expression. from the Vall d’Hebron prospective COVID-19 cohort database, clearance from the Institutional Review Board Data were acquired on a NAVIOS EX (BC) flow cytom- was obtained. To minimize risks of infection to the health eter. At least 100,000 events were acquired for each sam- staff, a written informed consent was waved, although all ple. Flow cytometry data were analyzed with Kaluza patients received proper study information and gave oral Software. Absolute values were calculated from the abso- consent. lute number of leucocytes and lymphocytes as deter- mined on a hematological analyzer (XN-2000; Sysmex, Results Japan). Biochemical and hematological predictors of outcome in male and female COVID‑19 patients Statistical analysis Biochemical and hematological parameters were ana- Continuous variables were expressed as mean ± SD or lyzed at admission for 497 male and female COVID-19 median and interquartile range (IQR). Simple and multi- patients. Demographics, background information, and ple comparisons were performed using parametric (two- treatments are shown in Tables 1 and 2 and Additional sided Student’s t test or ANOVA) and non-parametric file: Table ST1-ST2. Age-stratified patients (Additional (Mann-Whitney U test or Kruskal–Wallis) statistical file: Figure SF1) were grouped according to their even- tests with Dunn’s and Tukey’s post hoc tests. Categori- tual outcomes at discharge/death into mild, moderate, cal variables were presented as numbers and percent- severe-survivor, and severe-deceased (Tables 1 and 2). ages and compared using the 2-sided Fisher’s exact A higher proportion of female patients (56%) vs. males test as appropriate. Correlation between variables were (44%) fell into the mild and moderate than severe-survi- assessed using simple linear regression. ROC curves vor outcome groups (Additional file: Figure SF1a. Fisher were calculated with the univariate logistic regression exact test p = 0.0183). Conversely, a higher proportion of model implemented in GraphPad and the EasyROC male (58%) vs. female (41%) patients fell into the severe- web tool (http://​www.​bioso​ft.​hacet​tepe.​edu.​tr/​easyR​ deceased outcome group, albeit without reaching statis- OC/). The groups classified by the model were used in tical significance (p = 0.0511). In both male and female 2 × 2 contingency analysis to calculate odds ratios (OR) patients, the median age in severe-deceased outcome and significance determined by Fisher’s exact test. For groups was significantly older than those in mild or longitudinal analyses, trajectories were plotted for each moderate outcome groups, as expected [32]. However, Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 5 of 18 Table 1 Baseline clinical characteristics of the male study population Mild-moderate Severe-recovered Severe-deceased p-value1–2 p-value1-3 p-value2–3 N=114 N=97 N=38 Age (years), median (IQR) 59 (56–63) 56 (53–59) 68 (67–71) 0.1096 0.0001 <0.0001 Length of stay (days), median (IQR) 8 (7–9) 30.5 (27–34) 19 (9–26) <0.0001 <0.0001 0.0009 Comorbidity, n° (%) 54 (47.36) 57 (58.76) 28 (73.68) 0.1279 0.0051 0.1175 Hypertension 35 (30.70) 31 (31.96) 21 (55.26) 0.8822 0.0109 0.0178 Diabetes 20 (17.54) 15 (16.46) 11 (28.95) 0.7143 0.1630 0.0908 Cancer 6 (5.26) 3 (3.09) 3 (7.89) 0.5115 0.6915 0.3497 Cardiovascular diseases 9 (7.89) 12 (12.37) 3 (7.89) 0.3573 0.9999 0.5560 Chronic Lung diseases 10 (8.77) 6 (6.19) 5 (13.16) 0.6046 0.5297 0.2912 Obesity-Dyslipidaemia 16 (14.03) 33 (34.02) 11 (28.95) 0.0009 0.0497 0.6842 Chronic Kidney disease 6 (5.26) 2 (2.06) 1 (2.63) 0.2927 0.6808 0.6727 Others 9 (7.89) 13 (13.4) 7 (18.42) 0.2586 0.1220 0.5903 Biochemical parameters, median (IQR) Testosterone 144.3 (112.3–189.3) 52.91 (45.03–66.73) 58.48 (46.83–81.94) <0.0001 <0.0001 0.9999 Leucocytes n° 6.32 (5.78–6.88) 7.80 (6.83–8.80) 8.70 (7.20–9.65) <0.0001 0.0051 0.9999 Lymphocytes n° 1.20 (1.0–1.4) 0.77 (0.70–0.82) 0.8 (0.65–0.90) <0.0001 0.0001 0.9999 Lymphocytes % 18.55 (16.15–1.57) 9.20 (8.18–11.28) 10.89 (7.95–13.38) <0.0001 <0.0001 0.9999 Neutrophils 4.57 (3.92–4.90) 6.26 (5.53–7.38) 6.39 (5.53–8.34) <0.0001 0.0007 0.9999 Interleukine-6 42.30 (25.33–53.46) 130.8 (112.10–160.6) 215.30 (117.6–996.4) <0.0001 <0.0001 0.9999 C-reactive protein 9.57 (6.76–10.88) 17.47 (12.17–0.72) 14.56 (9.84–24.019) <0.0001 0.0069 0.9999 LDH 324 (296.0–369.0) 472.5 (440.0–506.0) 493.0 (429.0–583.0) <0.0001 <0.0001 0.9999 D-Dimer 236 (213.0–311.0) 529.0 (361.0–711.0) 421.5 (260.0–684.0) <0.0001 0.0210 0.9999 Ferritin 934 (679.0–1089.0) 1289 (1100.0–1574.0) 1443.0 (554.9–1919.0) 0.0022 0.7403 0.6783 The Fisher’s exact test was used to compare comorbidities. The Kruskal-Wallis test with Dunn’s multiple comparison was used to analyze the length of stay and biochemical parameters 1 Mild-moderate group, 2Severe-recovered group, 3Severe-deceased group women in the severe-deceased group were significantly than biochemical parameters predictive of poor outcome, older than males in the same outcome group (Additional such as D-dimer, ferritin, LDH, or IL-6 (Fig. 1A). file: Figure SF1c). In female patients, PCA and multivariate analysis also As an approach to capture global patterns of associa- highlight significant differences between mild-mod- tion between biochemical parameters and outcomes, we erate and severe outcomes (Fig. 1B, D). Similar to male applied principal component analysis (PCA), followed patients, the mild outcome group of female patients by Spearman multivariate correlation analysis (Fig. 1A, showed strong correlations to lymphocyte counts and B). In male patients (Fig. 1A), both PCA and multivari- hemoglobin levels, while the severe outcome groups are ate analysis showed a clear correlation between mild or correlated with high IL-6, CRP, D-dimer, ferritin, and moderate outcomes with known predictors of good out- LDH (Fig. 1B, D). Like in male patients, older age showed come, such as higher lymphocyte counts or hemoglobin the strongest correlation to a severe-deceased group in levels, while severe outcome groups correlated with high female patients (Fig. 1B; Additional file: Figure SF1c). neutrophil counts, and high IL-6, CRP, D-dimer, ferritin, Age, platelet counts, and fibrinogen levels significantly or LDH levels, confirming prior evidence [1, 32, 33]. In discriminated severe-survivor from severe-deceased contrast, patients with moderate or severe outcomes had female patients (Fig. 1B, D). significantly lower serum testosterone levels (p < 0.0001) The risk of ICU admission for patients with mild-mod- compared to those with mild outcomes (Table 1, Fig. 1C), erate outcomes was assessed by odds ratio (OR) esti- in agreement with other studies [12, 13]. Interestingly, the mates and logistic regression analysis. In male patients, low testosterone levels found in the admission time-point the most significant OR of ICU admission were found determinations for both severe outcome groups were not for IL-6 (OR 10.53, 95% CI 5.42 to 20.67), LDH (OR 6.62, significantly different between survivor and deceased 95% CI 3.62 to 11.79), lymphocyte fraction of WBC (OR patients (Table 1). Furthermore, older age presented a 0.14, 95% CI 0.08 to 0.25) and neutrophilia (OR 3.95, 95% stronger correlation with a severe-deceased outcome CI 2.30 to 6.78) (Fig. 2A), in agreement with previous Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 6 of 18 Table 2 Baseline clinical characteristics of the female study population Mild-moderate Severe-recovered Severe-deceased p-value1–2 p-value1–3 p-value2–3 N=145 N=76 N=27 Age (years) median (IQR) 57 (54–60) 55 (53–62) 74 (68–81) 0.9999 <0.0001 <0.0001 Length of stay (days), median (IQR) 7 (6–7) 25 (20.0–33.0) 15 (8–19) <0.0001 0.0033 0.0003 Comorbidity, n° (%) 89 (61.38) 47 (61.84) 22 (81.48) 0.9999 0.0503 0.0942 Hypertension 43 (29.65) 20 (26.31) 14 (51.85) 0.6408 0.0431 0.0190 Diabetes 20 (13.79) 6 (7.89) 2 (7.41) 0.2719 0.5343 >0.9999 Cancer 9 (6.21) 5 (6.58) 4 (14.81) 0.9999 0.1259 0.2366 Cardiovascular diseases 11 (7.58) 5 (6.58) 3 (11.11) 0.9999 0.4637 0.4290 Chronic Lung diseases 12 (8.27) 8 (10.53) 6 (22.22) 0.6249 0.0413 0.1877 Obesity-Dyslipidaemia 43 (29.65) 28 (36.84) 8 (29.63) 0.2916 0.9999 0.6396 Chronic Kidney disease 5 (3.49) 2 (2.63) 2 (7.41) 0.9999 0.3024 0.2805 Others 20 (13.79) 11 (14.47) 5 (18.52) 0.9999 0.5453 0.5461 Biochemical parameters, median (IQR) Leucocytes n° 5.95 (5.40–6.81) 6.28 (5.46–7.02) 7.29 (5.74–9.07) 0.9999 0.2849 0.6427 Lymphocytes n° 1.18 (1.04–1.27) 1.00 (0.84–1.12) 0.89 (0.74–1.21) 0.0008 0.0349 0.9999 Lymphocytes % 19.76 (17.96–22.16) 15.65 (16.62–18.58) 13.40 (9.59–19.18) 0.0009 0.0025 0.9999 Neutrophils n° 4.02 (3.6–4.78) 4.88 (4.23–5.43) 5.83 (4.37–7.66) 0.2125 0.0649 0.9426 Interleukine-6 34.21 (26.81–38.60) 75.30 (50.26–86.23) 65.36 (45.03–154.6) <0.0001 <0.0001 0.9999 C-reactive protein 8.38 (4.78–10.44) 12.67 (10.44–14.99) 14.47 (6.43–21.89) 0.0042 0.0846 0.9999 LDH 304 (289.0–345.0) 420.0 (380.0–486.0) 415.0 (283.0–539.0) <0.0001 0.0855 0.9999 D-Dimer 258.0 (228.0–275.0) 334.0 (258.0–422.0) 269.0 (207.0–424.0) 0.0379 0.7287 0.9999 Ferritin 378.0 (284.0–437.0) 528.0 (445.0–729.0) 445.0 (387.0–730.0) 0.0023 0.3007 0.9999 The Fisher’s exact test was used to compare comorbidities. The Kruskal-Wallis test with Dunn’s multiple comparison was used to analyze the length of stay and biochemical parameters 1 Mild-moderate group, 2Severe-recovered group, 3Severe-deceased group studies [32, 34]. A significant OR was also found for tes- for males; and females had OR 4.21 and AUC of ROC tosterone (0.17, 95% CI 0.09 to 0.31) also in line with 0.7123, p = 0.0014) (Fig. 2B, D). other studies [12–14]. In female patients, the most signif- A significant correlation was observed between serum icant OR of ICU admission were for IL-6 (OR 7.77, 95% testosterone levels and lymphocyte counts (absolute CI 3.48 to 16.9), LDH (OR 6.26, 95% CI 2.88 to 13.34), counts, r = 0.3122; fraction of WBC, r = 0.4187) and ferritin (OR 3.17, 95% CI 1.50 to 6.74), and lymphocyte neutrophil counts (r = −0.3586), suggesting that these fraction of WBC (OR 0.33, 95% CI 0.20 to 0.57) (Fig. 2A). three parameters may be mutually coupled (Fig. 2E). Interestingly, testosterone levels on admission were not significantly associated with the occurrence of comorbid- Recovery of serum testosterone levels accurately predicts ities in older men (Additional file: Figure SF2). survival in male COVID‑19 patients The power of these parameters to predict severe dis- In order to explore whether determinations in longitu- ease was corroborated by logistic regression analysis. The dinal samples could yield additional or improved predic- resulting receiver operating characteristic (ROC) curves tors of lethal disease, we evaluated the trajectories for yielded areas under the curve (AUC), which, in male all clinical biochemical and hematological parameters patients, were > 0.7 (p < 0.0001) for IL-6, LDH, and neu- and plotted for all patients grouped into mild-moderate, trophilia, and < 0.23 for lymphopenia and testosterone. severe survivor, and severe deceased outcomes (Fig. 3A In females, AUC of ROC curves were > 0.7 (p < 0.0001) and Additional file: Figure SF3). The trajectories of only for IL-6 and LDH (Fig. 2B). three parameters, namely testosterone (p = 0.0038), lym- The same parameters showed a weaker power to pre- phocyte counts (or fractions of WBC) (p = 0.01), and dict the risk of death from COVID-19 when compar- neutrophil counts (p = 0.0023), were significantly dif- ing all survivors, including severe survivors, versus ferent, as analyzed by two-way ANOVA, in comparisons deceased patients, with the exception of serum IL-6 of trajectories between the severe survivor and severe levels, in both male and female patients (OR 4.45, 95% deceased groups (Fig. 3A). No significant differences CI 2.14 to 10.71 and AUC of ROC 0.7189, p = 0.0002 for any of these variables were observed between severe Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 7 of 18 Fig. 1 Clinical biochemistry features of male (A, C) and female (B, D) COVID-19 patients, associated with outcomes. Clinical biochemistry values were determined for samples collected at patient admission. A, B Left panels: Principal component analysis (PCA) illustrating correlations between elevated levels of the indicated parameters and mild, moderate, severe survivor or severe deceased outcomes in male (A) or female (B) patients. Right panels: Heatmap of correlation coefficients between elevated levels of biochemical parameters and outcomes. Spearman multivariant correlation analyses were performed for all parameters vs. outcomes, the resulting coefficients normalized for each column (range, 0 to 1) and used to build heatmaps. C, D Values of relevant clinical biochemistry parameters assessed for admission samples and grouped by eventual outcome for male (C) and female (D) patients. Asterisks denote significance of pairwise comparisons between samples grouped by outcome: *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001. Non-significant comparisons (p > 0.05) are not shown survivor and mild-moderate outcomes (Fig. 3A). None counts (numbers per dL or fractions of WBCs) were of the other parameters showed statistically significant also highly accurate predictors of outcome, as were different trajectories in comparisons between severe neutrophil counts (Fig. 3B). Interestingly, the tra- survivor vs. severe deceased outcomes (Additional file: jectories of IL-6 or LDH, whose values on admission Figure SF3). were predictive of severity and death from COVID- The resulting ROC curves and AUC values, calcu- 19 in male patients, were not significantly different in lated from the slopes of the trajectories, indicated these longitudinal comparisons (Additional file: Fig- that serum testosterone trajectories are remarkably ure SF3). These results suggest a role for testosterone accurate predictors of survival from COVID-19, both in deregulation of the immune response in deceased in all-survivor vs. deceased (AUC = 0.9281, 95% CI patients, in particular for the observed lymphopenia 0.8801 to 0.9761, p < 0.0001) and severe survivor vs. and neutrophilia. deceased (AUC = 0.9205, 95% CI 0.8664 to 0.9747, p Age is a predictor of COVID-19 severity [32]. In our < 0.0001) outcome comparisons (Fig. 3B). Lymphocyte cohort of male patients, the testosterone trajectory Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 8 of 18 Fig. 2 Assessment of clinical biochemistry parameters as predictors of risk of severe disease or death from COVID-19. A, B Odds ratios (OR) of clinical biochemistry parameters and risk of severe disease (A) or death (B) in male and female patients. C, D Receiver operating characteristic (ROC) curves and area under the curve (AUC) values of risk of severe disease (C) or death (D). Shown are only those parameters with significant AUC values (p ≤ 0.05). E Correlations of testosterone serum levels with lymphocytes (percentage of WBC and counts) and neutrophil counts slopes significantly and inversely correlated with age (r However, and interestingly, the median age of patients = −0.3801, p < 0.0001) (Fig. 3C). Consistently, a major- with severe deceased outcomes was not significantly dif- ity of patients with severe deceased outcomes had low ferent from the median age of patients with mild-mod- or negative testosterone trajectory slopes (Fig. 3C). erate outcomes, and a substantial proportion of patients Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 9 of 18 with severe survivor outcomes were aged older than 60 survivor group, although without reaching the statisti- (Fig. 3C). Likewise, while the frequency of comorbidities cal significance. On the other hand, although androsten- was higher among patients with fatal outcomes as com- edione levels fell within normal ranges in the majority of pared with those who survived severe disease, it was not patients in all outcome groups and throughout the lon- significantly different from the frequency of the moder- gitudinal analysis (Fig. 4A, B), deceased patients showed ate outcome group (Additional file: Table 1, Figure SF1). increased levels as compared to the survivor outcome Similar to total circulating testosterone, free testoster- groups, without a concomitant increase in testosterone one levels were significantly decreased in severe patients levels (Fig. 4A). As such, the failure to recover physi- in comparison to the mild-moderate group (Additional ological levels of testosterone in patients with fatal out- file 1: Figure SF4). In addition, serum levels of sex hor- comes, in spite of LH and androstenedione levels within mone-binding globulin (SHBG), the most abundant normal ranges, and the lack of rise in LH expected with circulating testosterone binding protein, showed a sig- low circulating testosterone, suggest the development of nificant association of with older age in mild-moderate a combined central and peripheral (Leydig cell failure) patients (p = 0.0237), but not in severe patients. malfunction in the biosynthesis of testosterone in these These observations suggests that old age, with or with- patients. out accompanying comorbidities, may impact the ability of a subset of COVID-19 patients to reinstate testoster- Lethal male COVID‑19 is associated with a depletion one production, coupled to a failure to recover from the of circulating T helper cells disease. A number of studies have found substantial differences in immune responses to SARS-CoV-2 between male The LH‑androstenedione axis is not significantly perturbed and female patients [16, 18], although the mechanisms in male COVID‑19 patients underlying these differences are still unclear. In order to Testosterone is synthesized from androstenedione in the address the relationship between testosterone trajecto- Leydig cells of the testis under the stimulus of luteinizing ries, outcome, and immune status in male patients, we hormone (LH), secreted from the anterior portion of the analyzed circulating immune subpopulation repertoires pituitary gland. The observed critical decline in circulat- in a subset of our patient cohort, in at least two inde- ing testosterone levels in male COVID-19 patients sug- pendent determinations, separated by 5–20 days. These gests the occurrence of a transient (survivor outcomes) analyses point to a correlation between immune subpop- or sustained (fatal outcomes) hypogonadism following ulations, outcome, and testosterone levels both in a first the onset of COVID-19. To address potential mecha- determination of samples near admission date (Sample nisms explaining the observed failure to recover circulat- 1) and a subsequent analysis of samples near discharge ing testosterone levels in fatal COVID-19, we determined or death (Sample 2), with some subpopulations show- circulating LH and androstenedione levels in a longitudi- ing remarkable shifts between Sample 1 and Sample 2 in nal series of samples in a patient subcohort for which the their correlations with outcome (Fig. 5A, B; Additional testosterone trajectories had been concomitantly deter- file: Figure SF5). As such, Sample 1 determinations dem- mined. The median levels of LH fell within normal ranges, onstrated relatively few changes in immune cell reper- independent of patient outcome (Fig. 4A). Similarly, lon- toires between surviving and deceased patients. In stark gitudinal LH trajectories were not significantly different contrast, a subsequent determination (Sample 2) showed between patients in the survivor vs. deceased outcomes, a coordinated depletion of T helper subpopulations in stark contrast with the strongly divergent testosterone in association with death, along with changes in natu- trajectories (Fig. 4B). Nevertheless, LH levels determined ral killer (­CD56+brightCD16- and C­ D56+dimCD16+) and in the last of the longitudinal samples showed a decline in monocyte subpopulations (Fig. 5A). The subpopulations the deceased outcome group as compared to the severe with the most significant changes in relative abundance (See figure on next page.) Fig. 3 Recovery of serum testosterone levels and blood lymphocyte counts predict survival in male COVID-19 patients. A Longitudinal determinations (≥ 3 samples per patient collected on separate dates) of clinical biochemistry parameters were performed, and trajectories for individual patients (grey lines) and average values (red lines) plotted. A given time-point corresponds to a cluster of days post-admission (± 3 days). Linear regression was applied to average trajectories and the resulting slopes compared for significance between outcome groups by means of two-way ANOVA. B ROC curves and AUC values for longitudinal trajectories (linear regression slopes) of serum testosterone, blood lymphocyte counts (number per mL and % of white blood cells), and blood neutrophils as predictors of survival in comparisons of all surviving vs. deceased patients (left two panels) or surviving patients with severe disease vs. deceased patients (right two panels). Longitudinal analyses for additional clinical biochemistry parameters are shown in Additional file 1: Figure SF4. C Correlations of age with testosterone trajectory slopes in all patients with longitudinal analyses (leftmost panel) and in different outcome groups Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 10 of 18 Fig. 3 (See legend on previous page.) Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 11 of 18 Fig. 4 The luteinizing hormone (LH)-androstenedione axis is not significantly perturbed in male COVID-19 patients. A Determinations of serum LH and androstenedione levels in samples collected at admission, grouped by eventual outcomes. Pair-way between-group comparisons were performed by t test. B Longitudinal determinations (≥ 3 samples) of serum LH, androstenedione, and testosterone levels, analyzed as in Fig. 3. Comparisons of trajectories (linear regression slopes) were performed by two-way ANOVA Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 12 of 18 as a function of outcome tended to correlate with serum and the strength of their predictive power, are consist- testosterone levels sampled in the same period (1–3 days ently higher in male patients as compared to female from sampling for immune repertoire analyses) (Fig. 5A). patients. This becomes more evident when evaluating These correlations were more evident in multivariate predictive markers of lethal COVID-19, which yields correlation analyses, particularly for Sample 2 (Fig. 5B). IL-6 and lymphocyte (percentage of total WBC) as the These analyses show a generalized loss of representa- only two significantly predictive markers shared in both tion of circulating differentiated and polarized T helper male and female patients. Other significant markers subpopulations in deceased patients (Th1, Th17, Th1- predictive of lethal COVID-19 in male but not female Th17, Th2, central memory C ­ D4+, effector memory patients are LDH levels, neutrophilia, and absolute lym- + + ­CD4 , ­CD4 TEMRA) compared to surviving patients, phocyte counts, in addition to testosterone levels, which accompanied with a reciprocal increased representation are exclusively masculine in our patient cohorts. Fur- of undifferentiated CD4+ cells (recent thymus emigrant thermore, we found significant and direct correlations ­CD4+, naïve ­CD4+) (Fig. 5B–D). They also point to an between testosterone levels, lymphocytes, and neu- association of monocyte differentiation with outcome, trophils, suggesting a role for testosterone in aberrant with a predominant correlation with non-classical mono- immune responses in deceased patients. cytes in moderate and severe survivor patients and, con- These observations suggest that male COVID-19 versely, with significantly more pro-inflammatory [35] patients with severe and lethal disease suffer from more classical monocytes in deceased patients (Fig. 5B–D). deleterious underlying pathogenic and inflammatory There are additional associations of cytotoxic T cell or B processes than female patients with comparable clinical cell subpopulations with lethal COVID-19 (Fig. 5D–F), severity [2], a situation also observed in other respiratory albeit without reaching statistical significance. These cor- viral infections [4, 5]. Our baseline analysis reveals that relations were made more evident when comparing all critically low serum testosterone levels in male patients surviving patients (moderate and severe survivor) with are a risk factor for severe COVID-19, along with other deceased patients (Fig. 5G) and further illustrated by flow factors predictive of severity that are in line with prior cytometry histograms of representative cases (Additional evidence [32, 34]. We have also found that male COVID- file: Figure SF5). 19 patients with a higher risk of progression to a severe- Together, these observations indicate that male critical disease present higher levels of inflammatory COVID-19 patients with a lethal outcome suffer from a markers (serum IL-6, blood neutrophil counts) and tissue decline in circulating differentiated T helper cells accom- damage (LDH), and more marked lymphopenia [2], as panied with a relative enrichment in circulating undiffer- compared to age-matched female patients. entiated ­CD4+ T cells. Interestingly, markers of inflammation (IL-6, CRP) or tissue damage (LDH), with good outcome predic- Discussion tive power in admission sample determinations, lost Numerous studies have identified prognostic mark- their predictive power in longitudinal analyses in male ers able to discern severe COVID-19 patients, includ- patients, collected up to the time of discharge or death. ing older age, male sex, co-morbidities such as obesity, In contrast, testosterone levels, whose determinations on diabetes, or cardiovascular disease, elevated circulating admission provided a relatively modest outcome predic- markers of inflammation, lymphopenia, neutrophilila [2, tive power, corroborating other studies [11, 13], gained 12, 17, 32–34, 36], or the presence of autoantibodies to remarkable levels of significance when analyzed longitu- class-I interferons [37]. Nomograms or scores that com- dinally. The AUC values of ROC curves in logistic regres- bine several independent parameters have been proposed sion analyses (mild-moderate vs. severe: 0.9281, 95% CI as predictors of COVID-19 outcome [2, 12, 32]. However, 0.7216 to 0.9252, p < 0.0001; severe survivor vs. deceased: relatively few studies have addressed sex differences in 0.9205, 95% CI 0.8664 to 0.9747, p < 0.0001) indicate that predictive markers of disease outcome [2, 12, 32, 38–40]. serum testosterone trajectories in longitudinal determi- Interestingly, inflammation markers, but not co-morbid- nations constitute, to the best of our knowledge, the most ities, BMI, or age, have been found to be associated with accurate independent predictors of disease outcome in outcome differences between male and female COVID- male COVID-19 patients described thus far. Further- 19 patients [40]. more, longitudinal trajectories of lymphocyte and neu- Our comparative analysis of biochemical and hema- trophil counts also yield highly significant predictions of tological parameters has revealed that both sexes share disease outcome. markers with significant predictive power of disease out- Other biochemical parameters indicative of pathologi- come, including IL-6, LDH, D-dimer, lymphopenia, and cal inflammatory or pro-coagulant states, such as ele- neutrophilia. Nevertheless, the levels of these markers, vated IL-6, CRP or D-dimer levels, eventually return to Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 13 of 18 near-physiological levels in both survivors and patients testosterone, combined with normal androstenedione with fatal outcomes. This has been observed in other levels and a lack of rise in LH, suggests a malfunction studies [40, 41] and suggests that the normalization of of the testosterone-LH feedback loop. As such, an irre- these factors is insufficient, per se, to abate the patho- versible damage of Leydig cells [48] in patients with fatal logical hyperinflammation and hypercoagulation accom- outcomes could explain these observations, while a reso- panying severe COVID-19 with a fatal outcome, which lution of viral infection would explain the recovery of a might require the concomitant alleviation of lympho- normal production of testosterone in survivors. penia and neutrophilia. On the other hand, although Another relevant factor associated with late-onset different stimuli and conditions such as mechanical hypogonadism [49], as well as with an irreversible fail- ventilation, muscle immobilization, severe sepsis, and ure to reinstate testosterone production after critical multiple organ dysfunction as well as neuro/myotoxic situations that may compromise the LH-androstenedione agents may contribute to a critical status among patients axis, is old age [50], which has been linked to senescent admitted to ICU [42], all severe patients in our study, dysfunction of Leydig cells [51]. The fact that a major- with either survivor or deceased outcomes, were under ity of non-survivor patients in our study who failed to comparable pharmacological and physical management reinstate testosterone levels are older than 60 years of (Additional file 1: Tables ST1 and ST2), and thus, these age would be consistent with the senescence hypoth- factors are unlikely to contribute to the differential out- esis. However, our cohort has more patients older than comes in this study. 60 who reinstated their testosterone levels and survived We have found that testosterone trajectories are not severe COVID-19. Therefore, either Leydig cell senes- paralleled by changes in circulating LH or androstenedi- cence only affects a small subset of older patients or other one trajectories expected in the presence of functioning mechanisms may be invoked to explain failure to restore physiological feedback loops. This could be explained by testosterone production. an inhibition of the LH-androstenedione axis, which has Conversely, these observations also suggest that while been associated with non-specific critical illness [43] and the reinstatement of physiological testosterone levels the deleterious action on the hypophysis of inflamma- may be mechanistically linked to a return to lymphocyte tory cytokines [44]. A second possible mechanism may and neutrophil homeostasis, it may not be required for involve infection and damage by SARS-CoV-2 of ACE2- the relative normalization of other inflammatory path- expressing testicular cells, mainly Leydig cells [45, 46]. In ways, arguably driven by an unmitigated production of the first scenario, acute declines in LH and adrostenedi- IL-6 and other pro-inflammatory cytokines triggered by one levels would be expected, while in the latter scenario, acute viral infection [52]. Our observations suggest that they would be either unaffected or increased for LH due sufficient and timely resolution of pathogenic hyper- to a negative feedback loop with testosterone [43]. How- inflammation to prevent a lethal outcome may require ever, we observed that LH levels showed a slight decline the additional return to homeostasis of innate and/or in deceased patients, while androstenedione levels were adaptive immune cell dynamics and function, possibly increased. It should be noted that circulating androsten- assisted in male patients by the reinstatement of testos- edione is produced mostly by adrenal glands [47] and terone production. its synthesis might be affected by the corticosteroids There is now a wealth of studies describing the dynam- used to treat these patients (Additional file: Table ST1B), ics of immune responses to acute and subacute infection which may block the endogenous production of corti- with SARS-CoV-2, including multiparameter and func- sol, corticosterone, and aldosterone [47]. Therefore, a tional analyses of circulating and tissue-associated innate likely mechanism to explain the failure of patients with and adaptive immune subpopulations [53, 54]. Some fatal outcomes to recover their physiological levels of of these studies have addressed sex differences in such (See figure on next page.) Fig. 5 Immune switch during the course of disease in severe and deceased patients, as determined by multiparameter profiling of circulating immune cells. A PCA of samples analyzed near admission (Sample 1, left panel) and near discharge or death (Sample 2, right panel). Mild, moderate, severe survivor, and severe deceased outcomes were assigned values 1, 2, 3, and 4, respectively. Serum testosterone values of samples collected in the same or nearby dates (± 3 days) were included in the analysis. The indicated immune subpopulations are defined by cell-surface markers and determined by spectral flow cytometry (Materials and methods). B Heatmap of correlation coefficients between immune subpopulation values and outcomes, for near-admission (Sample 1, left Heatmap) and near-discharge/death (Sample 2, right Heatmap) samples. Spearman multivariant correlation analyses were performed for all parameters vs. outcomes, the resulting coefficients normalized for each column (range, 0 to 1) and used to build heatmaps. C–F Between-outcome comparisons of immune cell subpopulation: CD4+ (C); natural killer, dendritic, and monocyte (D); CD8+ (E); and B (F) cell subpopulations. G Survivor (mild, moderate, severe survivor) vs. deceased patient comparisons for T cell (CD4+ and CD8+) and dendritic cells and monocytes. Such comparisons were not significant for other immune subpopulations (B cells, NK cells) Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 14 of 18 Fig. 5 (See legend on previous page.) Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 15 of 18 responses [11, 14]. Our analysis in male patients indi- of circulating differentiated and polarized cells may be cates an association of specific immune subpopulations an enhanced clearance or migration from circulation with COVID-19 outcome and a shift of such associations to peripheral tissues [57]. Finally, specific subpopula- from early (Sample 1) to late (Sample 2) time-points in tions may become exhausted in late stages of the dis- the course of the disease. For example, the relative rep- ease [58–60]. These three putative mechanisms are not resentation of differentiated (­CD8+ TEMRA, C ­D4+ mutually exclusive and may take place either simulta- + + TEMRA) and activated (HLA-DR on ­ CD4 and on neously or dynamically at different time points along ­CD8+) T cell subpopulations and differentiating B cells the clinical course of the patients. Notably, very recent modestly correlated with all outcomes except mild dis- studies recognize T cell apoptosis and depletion as a ease in Sample 1. This indicates an ongoing early immune feature defining severe COVID-19 [60]. response of similar nature and magnitude, regardless of The observed concordance of lethal outcome in male final outcome, as reported by others [53]. In this phase, COVID-19 patients with (i) persistent lymphopenia and non-classical monocytes are more prevalent than clas- neutrophilia, (ii) depletion of circulating differentiated sical monocytes in patients with a moderate outcome, T helper and T cytotoxic cells and non-classical mono- while patients with severe survivor and severe deceased cytes, (iii) accumulation of undifferentiated immune outcomes show a predominance of more inflammatory counterparts, and (iv) failure to reinstate physiological [55] classical monocytes, in support of a more inflamma- levels of testosterone, mirrored by converse pheno- tory state of these patients, as also evidenced by the clini- types in severe survivor patients who have undergone cal biochemical and hematological parameters discussed equivalent critical illness and management, makes it above. appealing to hypothesize a mechanistic relationship However, later in the course of disease (Sample 2), a bonding these coincident phenotypes. Relevantly, sex remarkable shift takes place, in particular with regard hormones have a profound influence on innate and to correlations with severe survivor as compared to adaptive immune system development, differentia- severe deceased patients. As such, while patients with tion, and response to challenge [14, 18] More specifi- severe survivor outcomes show positive correlations cally, androgens have a global anti-inflammatory effect with differentiated ­(CD4+ TEMRA, ­C D8+ TEMRA), [26, 61], reflected in higher frequencies of autoimmune activated (HLA-DR+ on ­ C D4+ and on ­ C D8+), and diseases in women or in acquired or genetically deter- + + memory ­(CD4 central memory, ­C D8 central mem- mined hypogonadism [21], as compared to men with ory) T cell subpopulations, patients with eventual a normal XY chromosome complement. On the other fatal outcomes evidence a depletion of these subpop- hand, testosterone replacement therapy in hypogonadal ulations, along with an accumulation of undifferenti- men attenuates inflammation [62] and androgens sup- ated T helper cells (recent thymic emigrant C ­ D4+ and press thymic precursor development [63] and promote + naïve ­C D4 ). This late shift also affects innate immune the terminal differentiation of T cell subpopulations populations, as severe survivor patients correlate [64] and monocyte precursors [65]. Conversely, andro- with non-classical monocytes over classical mono- gen deprivation through surgical or pharmacological cytes, while the reverse is the case for severe deceased castration in animal models prompts the regeneration patients. Similar observations have been made by oth- of the thymus in aged mice, leading to a relative accu- ers in studies correlating innate [53] and adaptive [17] mulation of undifferentiated T cell populations (RTE immune cell subpopulations to COVID-19 outcome. and naïve T cells) [66] and classical monocytes [67]. A Importantly, our study additionally correlates rela- similar effect of androgen deprivation on T cell devel- tive representations of immune subpopulations to opment and differentiation has been observed in pros- testosterone levels. Thus, higher testosterone levels tate cancer patients, with an expansion of RTE and in Sample 1 are correlated to polarized (Th1, Th17, naive T cells, particularly among ­C D4+ cells [66, 68]. Th1-17, Th2) and differentiated (effector memory ­C D4+, central memory ­C D4+, ­C D8+ TEMRA) T cell Conclusions subpopulations. In Sample 2, testosterone levels cor- The tight association observed between reinstate- relate to a similar range of subpopulations, along with ment of testosterone and survival from COVID-19 in plasmablasts and mature NK cells (­CD16+dimCD16+). male patients, along with a reversal of signs of exces- These temporal switches in the differentiation profiles sive inflammation and immune dysfunction, suggests of distinct immune subpopulations may suggest that in a potential functional role for testosterone, beyond patients with lethal outcomes, there may be a defective being a mere biomarker of outcome, in such recov- differentiation of T helper cells [56] and monocytes. A ery. Further explorations of mechanistic relation- second possible explanation of the apparent depletion ships between testosterone status and SARS-CoV-2 Toscano‑Guerra et al. BMC Medicine (2022) 20:129 Page 16 of 18 infection outcomes may lead to potential prophylac- distribution by outcome, age, and comorbidities. Figure SF2. Distribution tic or therapeutic interventions to tackle severe and of male patients with comorbidities according to age and testosterone lethal COVID-19 in men. levels. Figure SF3. Longitudinal analysis of serum levels of IL-6, C-reactive protein (CRP), ferritin and lactate dehydrogenase (LDH) in male patients. Figure SF4. Bioavailable testosterone serum levels and correlation Study limitations between age and sex-hormone binding globulin (SHBG). Figure SF5. The limitations of our study include its observational Flow cytometry analysis of circulating immune subpopulations in three illustrative cases with moderate, severe survivor and severe deceased nature on retrospective patients and samples, which has outcomes. hampered the collection of samples at precisely equiva- lent time points after symptom onset for all patients. Acknowledgements Notably, the retrospective analyses impacted our lon- The authors wish to thank the Vall d’Hebron Biochemical Service for technical gitudinal studies of immune populations which, in the support. present study, were limited to a relative small number Authors’ contributions and two temporally separate determinations per male Contributors RP, TMT, ETG, and MMG conceived and designed the study, ana‑ patient studied. Similarly, the retrospective nature of our lyzed the data, generated the figures and tables, and wrote the manuscript. study has precluded assessing the potential impact of ETG, AG, NDT, PGM, MLH, FMV, and MRB collected clinical samples and data. ETG, MMG, IAM, and AG performed the experiments, analyzed the data, and the circadian rhythm of testosterone production in our generated the figures and tables. MLH, FMV, and MRB participated in patient patients. A further limitation was the determination of care. RP, TMT, ETG, MMG, PG, MH, RPB, FRF, ASM, and RF contributed to the testosterone by immunoassay and not by gold-standard data interpretation and critically reviewed the manuscript. The authors read and approved the final manuscript for submission. mass spectrometry (not available in the clinical setting). On the other hand, several hypotheses laid out here Funding would require formal testing by means of approaches This study was funded by grants from the Ministerio de Ciencia e Innovación (RTI2018-096055-B-I00), Consejo Superior de Investigaciones Científicas’ that are not addressed in the present study. For exam- COVID-19 Research Fund (CSIC-COV19-006, CSIC-COV19-201), Agència de ple, the various mechanisms postulated to explain the Gestió d’Ajuts Universitaris i de Recerca (2020PANDE00048 and 2017SGR 1411 depletion of circulating differentiated T cells in lethal GRC), and Plan Nacional de I+D (PID-107139RB-C21) and Instituto Nacional de la Salud Carlos III (PI18/00346 and COVID-19_00416). COVID-19 patients would benefit from additional analy- ses of senescent and activation states of such populations Availability of data and materials with appropriate markers, as well as detailed analyses The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. of viral infection and immune cell populations infiltrat- ing key tissues, mainly the lung and testis. Finally, pre- Declarations clinical animal models would be required for a robust experimental demonstration of mechanistic relation- Ethics approval and consent to participate ships between testosterone status (e.g., deprivation and The study was reviewed and approved by the Hospital Vall d’Hebron Institutional Review Board (Medical Research Ethics Committee, protocol replacement) and SARS-CoV-2 infection outcomes, number PR(AG)329-2020). Immunophenotyping studies of peripheral blood which should also contemplate factors such as age. cells underwent a separate review and approval process (protocol number PR(AG)242/2020). Abbreviations Consent for publication ACE2: Angiotensin-converting enzyme 2; AR: Androgen receptor; AUC​: Area Not applicable. under the curve; BMI: Body mass index; COPD: Chronic obstructive pulmonary disease; DC: Dendritic cells; FDA: Food and Drug Administration; ICU: Intensive Competing interests care unit; IL-6: Interleukin-6; ILC2: Group 2 innate lymphoid cells; LDH: Lactate The authors declare that they have no competing interests. dehydrogenase; LH: Luteinizing hormone; MERS-CoV: Middle East respiratory syndrome; NK: Natural killer cells; PCA: Principal component analysis; PCR: Author details 1 C-reactive protein; RTEs: Recent thymic emigrant cells; ROC: Receiver operat‑ Biochemistry Service, Vall d’Hebron Hospital, Autonomous University ing characteristic; SARS-CoV: Severe acute respiratory syndrome-coronavirus; of Barcelona (UAB), Barcelona, Spain. 2 Cell Signaling and Cancer Progres‑ TEM: T cells effector memory; TEMRA: T cell terminal effector memory; Th: T sion Laboratory, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain. 3 helper cells; TMPRSS2: Transmembrane protease serine 2; Treg: T regulatory Universidad Peruana Cayetano Heredia, Lima, Perú. 4 Immunology Division, cells; WBC: White blood cells. Vall d’Hebron Hospital, Barcelona, Spain. 5 Translational Immunology Research Group, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain. 6 Depart‑ ment of Cell Biology, Physiology and Immunology, Autonomous University Supplementary Information of Barcelona (UAB), Barcelona, Spain. 7 Internal Medicine Service, Vall d’Hebron The online version contains supplementary material available at https://​doi.​ Hospital, Barcelona, Spain. 8 Infectious Diseases Department, International org/​10.​1186/​s12916-​022-​02345-w. Health and Tuberculosis Unit National Referral Centre for Tropical Diseases, Vall d’Hebron University Hospital, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain. 9 Barcelona Institute for Molecular Biology, National Sci‑ Additional file 1: Table ST1. Treatments comparison by outcome in ence Council (IBMB-CSIC), Barcelona, Spain. 10 Networked Center for Hepatic male patients. Table ST2. 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