Age cohorts stratified according to age-distributions of COVID-19 morbidity statistics identify uniquely age-dependent CD3⁺CD8⁺ T-cell lymphocytopenia in COVID-19 patients without comorbidities on admission

Patient demographics and age- and COVID-19 incidence-specific subgroup characteristics of COVID-19

As of March 20, 2020, a total of 693 (323 women and 370 men) confirmed COVID-19 patients admitted to 10 hospitals in Wenzhou City, Zhejiang Province were enrolled in this study. Of 693 patients, 246 (35.5%) patients had previously been diagnosed with comorbidities, including cardiovascular and cerebrovascular diseases, respiratory system diseases, malignant tumor, chronic liver and kidney diseases, hypercholesterolemia, diabetes mellitus, and others. Out of 693 cases, approximately six percent (5.6%) of cases presented with a mild disease, 78.9% a moderate one, 12.3% a severe one, and 3.2% a critical ill one. By the data collection deadline, all patients have been discharged. The mean age at COVID-19 onset was 47 years (interquartile range [IQR] 37–56). Almost 53% (53.4%) of the cases were men. After the diagnosis of COVID-19 was confirmed, all patients received antiviral, herbal and supportive therapies.

To optimally understand how the clinical and immunological characteristics evolved in COVID-19 according to an age-dependence, the appropriate categorization of chronological ages was considered. In this study, we used the time interval of 1-year as the age interval to count the confirmed COVID-19 cases. A graphic plot of the number of COVID-19 cases per year vs age produced a bell-shaped curve (Figure 1A). There was a strong positive correlation between the number of confirmed COVID-19 cases and different year-cohorts in the age range of 2 to 57 years (r=0.919, p<0.001; Figure 1B). In contrast, a negative correlation between the number of confirmed COVID-19 cases and different year-cohorts in the age range of 58 to 93 years was observed (r= ‒0.739, p<0.002; Figure 1C).

To differentiate COVID-19 patients who were previously healthy from those with comorbidities, which showed strong interference in COVID-19 manifestations, data from 447 patients without comorbidities on admission were included in the analysis. Different age-cohorts were combined with their neighboring age cohorts with similar incidence counts/year together. Accordingly, five age-groups were formed as follows: 2‒25y (2.0±0.3 cases/year-cohort, n=34), 26‒38y (10.9±0.8 cases/year-cohort, n=121), 39‒57y (18.4±0.8 cases/year-cohort, n=235), 58‒68y (7.9±0.9 cases/year-cohort, n=41), and 69‒79y (2.8±0.7 cases/year-cohort, n=16) groups (Figure 1D). The COVID-19 incidences in the five age-groups indicated a triangle-shape trend as follows: 0‒25y (7.6%) <26‒38y (27.1%) <39‒57y (52.6%) >58‒68y (9.2%) >69‒79y (3.6%) (Figure 1E and Table 1, all p < 0.001 “<” or “>” p<0.001 between groups).

The age differences of the severity between children and older adults had been noticed at the early stages of the COVID-19 pandemic [1]. In the present study, Figure 1F shows an age dependence in severity and critical illness among the five age-groups of COVID-19 patients. Patients in the young age-group 2–25y experienced a mild infection more frequently (97.1%) than those in the older age-groups. The moderate form was found to be significantly associated with the middle age-groups 26–38y (90.1% cases) and 39–57y (86.8% cases). In contrast, more cases with a severe form were associated with the older age-groups 58–68y (31.7%) and 69–79y (25.0%). The critically ill cases in the age-groups 39–57y, 58–68y, and 69–79y accounted for 2.6%, 2.4% and 12.5% respectively.

Laboratory findings of age- and COVID-19 incidence-specific cohorts on admission

From our retrospective analysis of 447 patients on admission, 443 patients had their lymphocyte counts recorded. Laboratory parameters, including leukocyte and neutrophil counts, and plasma C-reactive protein (CRP) and interleukin-6 (IL-6) levels were above the normal reference ranges, in contrast to lymphocyte counts as well as lymphocyte subset counts, which were within the lower part of their ranges (Table 1). Compared with the normal reference ranges for the total lymphocyte count (1.1– 3.2 ×10⁹/L), B cell count (90–560 n/μl), NK cell count (150–1100 n/μl), T cell count (955–2860 n/μl), CD4⁺ T cell count (550–1440 n/μl), CD8⁺ T cell count (320–1250 n/μl), and CD4⁺/CD8⁺ T cell ratio (1.5–2.0), there were 9.1% cases with low lymphocyte counts (<1.1×10⁹/L) and 80% cases with low CD4⁺/CD8⁺ T cell ratio (<1.5) with no significant changes in other cell counts of lymphocyte subsets, in the SARS-CoV-2 infected age-group 2–25y. In the age-group 26–38y, SARS-CoV-2 infection further increased cases with a low lymphocyte count (25.0%, p<0.05) and decreased the CD8⁺ T lymphocyte count (385 cells/μl) when compared with the age-group 2–25y (520 cells/μl, p<0.05). From the age-group 39–57y onwards, the number of cases with lymphopenia (<1.1×10⁹/L) and lower CD8⁺ T cell counts (<200 cells/μl) further linearly increased (Figure 2A) (refer to Table 1 for p values). The decrease in the lymphocytes was not due to B cell and NK cell counts, but due to the T cell counts, as the B cell and NK cell counts did not differ among the age-groups (Figure 2B, 2C); however, T cell counts reduced linearly (Figure 2D). In T cell subpopulations, the CD4⁺ T cell counts did not differ among age-groups (Figure 2E). In contrast, the CD8⁺ T cell counts (n/μl) dropped linearly and sharply from the age-group 26–38y onwards (age-group 2–25y [520 (IQR: 372–663)], 26–38y [385 (IQR:283–497)], 39–57y [320 (IQR: 208–429)], 58–68y [172 (IQR: 94–313)] and 69–79y [139 (IQR: 112–229)], p<0.05, p<0.05, p<0.001 and p<0.001 respectively, Figure 2F). A negative correlation between age and CD8⁺ T cell counts was observed in COVID-19 patients (r=‒0.435, n=193, p<0.0001, Figure 2G), indicating that SARS-CoV-2 infection age-dependently reduces the number of CD8⁺ T cells.

Virus infection is usually associated with systemic inflammatory responses [11]. SARS-CoV-2 infection increased cases of hyper leukemia (>10×10⁹) or high plasma CRP levels (>10 mg/L) both from the age-group 39–57y onwards (Table 1 and Figure 2H). Compared with the age-group 26–38y, plasma IL-6 levels were significantly higher in both the 56–68y and 69–79y groups (Figure 2I, both p<0.05). These results suggest that systemic inflammatory response to SARS-CoV-2 infection are also age-dependent.

Study design and participants

We performed a retrospective review of the medical records of 693 COVID-19 patients admitted to 10 hospitals in Wenzhou City, Zhejiang Province, China as of March 20, 2020. The diagnosis of COVID-19 was made according to the interim guidance of the World Health Organization [21] and confirmed by RNA detection of the 2019-nCoV in the clinical laboratories of hospitals as described previously [11]. Based on the guidelines for diagnosis and management of COVID-19 (7th edition, in Chinese) released by the National Health Commission of China [22], the COVID-19 patients were stratified into mild (with mild symptoms and no sign of pneumonia), moderate (with pneumonia and arterial oxygen partial pressure/fractional inspired oxygen [PaO2/FIO2] >300 mmHg), severe (with pneumonia and respiratory distress, respiratory rate >30 breaths/min; oxygen saturation <93% at rest; and PaO2/FIO2 <300 mmHg) and critically ill (with respiratory failure and a requirement for mechanical ventilation, shock, and complications from other organ failures that required monitoring and treatment in the intensive care unit) groups.

This study was reviewed and approved by the Ethics Committee of Wenzhou Medical University (Ref 2020002). Written informed consent was waived due to the rapid emergence of COVID-19.

Accurate patient age-subgrouping is an important prerequisite for the generation of accurate age-dependent results. If the age boundaries are arbitrarily or roughly defined, the age-related analysis could result in questionable findings. As medical interventions can influence many parameters giving rise to conflicting data, the parameters were assessed only at pre-hospitalization. To further differentiate COVID-19 patients who were previously healthy from those with comorbidities, which showed strong interference in COVID-19 manifestations, data from 447 patients without comorbidities on admission were included in the analysis. Therefore, different age-cohorts were combined with their neighboring age cohorts with similar incidence counts/year together. Accordingly, the five age-groups, 2‒25y, 26‒38y, 39‒57y, 58‒68y, and 69–93y were formed.

Collection of clinical and laboratory data

We collected epidemiological, demographic, clinical, laboratory, treatment, and outcome data from the electronic medical records. Data were obtained and curated with a customized data collection form. Three physicians (CC, BY, and TL) and a third researcher (SJ) checked all the data and adjudicated any differences in interpretation among the three primary reviewers. Routine blood examinations in patients on admission included complete blood counts (white blood cells, neutrophils, lymphocytes, and platelets), serum biochemical tests (for renal and liver function, creatine kinase, lactate dehydrogenase, myocardial enzymes, CRP, IL-6, IL-2, IL-4, IL-5, IL-10, TNF-α, and IFN-γ). The coagulation tests, prothrombin time, activated partial thromboplastin time, fibrinogen test, and d-dimer test were also performed.

Flow cytometry analysis

To detect the phenotypic characteristics of the lymphocytes (CD4⁺ and CD8⁺ T-cells, and B-cells and NK cells), samples of ethylenediaminetetraacetic acid anticoagulated peripheral blood (2 mL) were collected from COVID-19 patients before initial treatment and a second sample was collected after 12 days of treatment. Measurements were performed as previously described [6]. Briefly, CD4⁺ and CD8⁺ T-cell, CD19⁺ B-cell, and CD16⁺ CD56⁺ NK-cell staining was performed with the following antibodies: Peridin chlorophyll protein-conjugated anti-human CD3 mAb (BD Biosciences, California, USA), allophycocyanin (APC)-conjugated anti-human CD4 mAb (BD Biosciences), APC/Cy7-conjugated anti-human CD8 mAb (Biolegend, USA), APC-conjugated anti-human CD19 mAb (BD Biosciences), APC-conjugated anti-human CD16, and Brilliant™ Violet 510 (BV-510)-conjugated anti-human CD56 mAb (Biolegend). The gate strategy of CD4⁺ T-cells, CD8⁺ T-cells, B-cells, and NK cells was executed as CD3⁺CD4⁺, CD3⁺CD8⁺, CD3⁻CD19⁺, and CD3⁻CD16⁺/CD56⁺, respectively, and the cells were analyzed using multiple-color flow cytometry on a BD FACS Canto II flow cytometry system (BD Biosciences).

Statistical analyses

Where appropriate according to the data distribution, the results were reported as means±standard deviations, medians (IQRs), or as categorical variables as numbers and percentages. The distributions were compared using the D'Agostino and Pearson omnibus normality, Shapiro-Wilk normality, and Kolmogorov-Smirnov tests. Categorical variables were shown as frequencies (%). The Mann-Whitney U test, Kruskal-Wallis test, χ² test, Chi-square with a Yates' correction, or Fisher’s exact test was used for nonparametric data where appropriate. Spearman correlation coefficients were performed to determine the associations between variables. A p-value of <0.05 was considered statistically significant. GraphPad Prism 8.0 software (GraphPad Software, Inc., San Diego, CA, USA) was used for the statistical analyses.

Ethical approval

This study conformed to the ethical guidelines of the 1975 Declaration of Helsinki. The ethics approval has been issued by the Ethics Committee of Wenzhou Medical University (Ref 2020002).