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Unravelling the role of secretory Immnuoglobulin-A in COVID-19: a multicentre study in nursing homes during the first wave

BMC Geriatrics volume 24, Article number: 804 (2024) Cite this article

Abstract

Background

The function of mucosal secretory IgA (SIgA) seems to be paramount in the immune response against SARS-CoV-2 however, there are few studies addressing this issue specifically in the institutionalized older population. This study aims to determine the levels of secretory IgA against the S1 domain of the SARS-CoV-2 spike (SIgA-S1) in older people living in nursing homes (NH) and to investigate the differences in baseline characteristics, severity of COVID-19, duration of symptoms, 30-day mortality, and reinfection according to the levels of SIgA-S1.

Methods

In this multicentre longitudinal study, conducted in two NHs attended in coordination with a hospital-based Geriatric team, 305 residents (87.3 years, 74.4% female) were included. A massive collection of nasopharyngeal samples was carried out after the first wave of COVID-19 in May 2020 and an ELISA analysis of SIgA-S1 was performed on frozen samples in May 2023. Values of SIgA-S1 ≥ 57.6 U/mL (“cut-off point”) were considered “induced”. Resident medical records were reviewed to assess symptoms, comprehensive geriatric assessment (CGA), reinfection, and overall 30-day mortality.

Results

At the time of sample collection, 274 residents (89.8%) exhibited “induced” SIgA-S1 levels (≥ 57.6 U/mL), 46 (15.1%) tested positive for PCR SARS-CoV-2, and 170 (57%) had experienced COVID-19 symptoms. “Induced” SIgA-S1 patients were more likely to be symptomatic (60.3% vs. 29%; p < 0.001) and exhibited upper respiratory tract symptoms more frequently (25.1% vs. 6.5%; p = 0.020) compared to “non-induced” patients. Patients with severe disease and duration of symptoms > 10 days had higher levels of SIgA-S1 than those with mild disease (252 vs.192.6 U/mL; p = 0.012) or duration ≤ 10 days (270.5 vs. 208.1 U/mL; p = 0.043), respectively. No significant differences were observed in age, sex, CGA, duration of symptoms, disease severity, overall 30-day-mortality, or reinfection between “induced” and “non-induced” residents.

Conclusions

Levels of SIgA-S1 are associated with the duration and type of COVID-19 symptoms, along with the severity of infection. While these findings shed light on the knowledge of SIgA-S1, further interdisciplinary studies are warranted to better understand the immune response to SARS-CoV-2 infection.

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Background

Impact of the COVID-19 on older people living in nursing homes (NH) has been particularly serious at national and international scales [1]. In this setting, some of the factors that contributed to the expansion and lethality of the virus were community living, lack of personal protective equipment for workers, restrictive access to the SARS-CoV-2 polymerase test reaction (PCR) test, the resident’s health vulnerability due to comorbidities or geriatric syndromes (i.e. frailty, dependence, dementia), and their low immune response [2]. In this regard, the initial interaction between the virus and the host respiratory mucosa triggers a cascade of innate and adaptive immune responses through diverse mechanisms [3, 4]. Within the realm of adaptive immunity, the humoral response, specially the production of neutralizing antibodies, plays a critical role in the protection against SARS-CoV-2 [5, 6]. Notably, immunoglobulin A (IgA) has emerged as a key player in mucosal immunity against SARS-CoV-2 infection [7]. IgA is the most abundant antibody isotype in the body and exists in various forms: monomeric, predominantly found in the systemic circulation, and polymeric, which forms a dimer of two IgA molecules linked by a J chain [8]. Dimeric IgA is secreted via the polymeric immunoglobulin receptor and is predominantly present in mucosal tissues [9], where it contributes to pathogen defense due to its enhanced neutralizing activity compared to monomeric IgA and IgG [10]. Additionally, IgA facilitates pathogen elimination through mechanisms such as mucociliary clearance and activation of the local immune system [11].

Previous studies have demonstrated the protective role of mucosal secretory IgA (SIgA) as well as the association between higher levels and severe cases of COVID-19 [12]. Neutralizing SIgA can be found in seronegative individuals, indicating a strong local mucosal response [13,14,15]. Also, it has been observed the predominant neutralization role that IgA has in the early response, albeit short-lived compared to IgG, especially in serum [15]. In mucosal fluids, specific IgA against SARS-CoV-2 can be detected even months after infection [16].

Whereas the function of SIgA seems to be paramount in the immune response against SARS-CoV-2, there are few studies addressing this issue specifically in the institutionalized older population.

Method

Study design

This is a longitudinal, retrospective, multicentre study conducted in two NH, which will be referred to hereafter as NH-1 and NH-2, supervised by the hospital-based Geriatric team of our Hospital during the first wave of COVID-19.

The primary objective of the study was to determine the levels of secretory IgA against the S1 domain of the SARS-CoV-2 spike protein (SIgA-S1) in this population. Secondary objectives were to evaluate differences between patients with “induced” or “non-induced” SIgA-S1 in general population characteristics, baseline status according to the Comprehensive Geriatric Assessment (CGA), clinical severity of COVID-19, symptom duration, 30-day mortality, and reinfection rate.

Population studied

The inclusion criteria of the study were being a NH resident and being alive after the first wave of the Covid-19. Those whose frozen specimen was not well preserved – or was insufficient for analysis – were excluded. As well, subjects with incomplete medical records regarding COVID-19 symptoms and/or vital signs throughout the study period, were also excluded.

Procedures

On May 11th in NH-1 and on May 17th, 2020 in NH-2, after the acute phase of the first wave of COVID-19, the hospital-based Geriatric team performed a mass screening by performing a PCR test for SARS-CoV-2 on all admitted residents, with the aim of early isolation of positive cases. Samples were frozen and stored at -80 °C in the laboratory freezers until analyzed for SIgA-S1 on May 2023. The freezers were continuously monitored to ensure that temperature variations did not exceed 1.5% throughout the storage period. In addition, sample stability was ensured through size assessment of protein integrity via electrophoresis with selected samples in the same rack. We developed and conducted a custom indirect ELISA to evaluate the levels of secretory IgA against SARS-CoV-2 spike S1 domain (SIgA-S1) in nasopharyngeal swabs obtained. Nunc 96-well ELISA plates (Thermo Fisher Scientific, Waltham, MA, USA, 439454) were coated with 0.5 µg of SARS-CoV-2 Spike Protein (Recombinant Human Novel Coronavirus Spike glycoprotein (S), Partial (Active)) supplied by Cusabio Technology LLC (Houston, TX, USA, CSB-YP3324GMY1) in 100 µL of 0.05 M carbonate-bicarbonate buffer, pH 9.6 (Sigma-Aldrich, St. Louis, MO, USA, C3041-50 CAP) per well. The plates were incubated overnight at 4 °C. Subsequently, four washes were performed using 100 µL of washing buffer containing 1x phosphate-buffered saline (PBS) (Fisher Scientific, Loughborough, UK, BP2944-100) and 0.05% Tween20 (PanReac Química S.L.U., Barcelona, Spain, 142312.1611). Following this, the wells were blocked with 200 µL of 1% bovine serum albumin (BSA) in Tris-buffered saline (50 mM Tris, 0.14 M NaCl, pH 8.0) (Sigma-Aldrich, T6789-10PAK) and incubated for 30 min at room temperature (RT). Four plate washes were performed using 300 µL of washing buffer per well. Duplicate samples (100 µL each), thawed and vortexed prior to use, were added to the corresponding wells and incubated for 1 h at RT. Human sera with known IgA activity (obtained from a commercial kit, AESKULISA® SARS-CoV-2 S1 IgA, AESKU.DIAGNOSTIC, Wendelsheim, Germany, 6124) were also added to the plates to generate a calibration curve. After the incubation with samples or standards, the plates were washed five times. Subsequently, 100 µL/well of a 0.01 µg/mL secondary antibody, Goat anti-human IgA HRP-conjugated (Fortis Life Sciences, 34021), was added to each well and incubated for 1 h at RT. The washing procedure was repeated, and to reveal the plates, 100 µL/well of TMB substrate solution (Thermo Fisher Scientific, 34021) was added and incubated for 5 min in the dark. The reaction was stopped by adding 100 µL/well of 1 M HCl (PanReac Química S.L.U, 131020.1612). The optical density (OD) at 450 nm with a reference wavelength of 620 nm was measured using an ELISA reader (SmartSpec ™ 3000, Bio Rad). The blank OD was subtracted from the sample readings, and the concentration was calculated using the equation of the standard curve fitted to a linear regression model.

We used the positive and negative controls supplied in the kit as positive and negative controls and applied the cut-off formula, defined as the mean plus three times the standard deviation [17]. Therefore, the negative control was set at 2.76 U/mL, while the positive cut-off point at 57.6 U/mL. Thereby, we classified samples equal to or above 57.6 U/mL as “induced”, while those below this threshold as “non-induced”. Furthermore, we additionally calculated cut-off values to divide the samples into different SIgA-S1 levels due to the wide range of values. We obtained these cut-off values by Change-Point detection analysis, using the R package “changepoint“ [18]. This method has been validated for identifying cut-off points in ELISAs in the absence of controls [19]. Following the protocol described by Lardeux et al. 2016, we sorted the SIgA-S1 values in ascending order and in the R package we employed the Binary Segmentation algorithm with the CUSUM method as a detection option [20]. In this regard, we further classified the “induced” SIgA-S1 values into four degrees of induced positivity according to the three change points detected and the threshold of the positive control as shown in Fig. 1.

Fig. 1
figure 1

Flow chart of the study

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Data collection

To obtain data regarding patient’s baseline characteristics, clinical manifestations and severity of symptoms, a comprehensive and systematic review of each individual’s electronic medical records was carried out by the research team, comprised by physicians and nurses specialized in geriatrics (in collaboration with the NH care staff). Demographic characteristics, CGA information, and comorbidities present 2 weeks before the first case of Covid-19 (March 15th) were registered. From March 15th onwards, the presence of COVID-19 symptomatology –according to WHO criteria – was registered until 14 days after the PCR was performed in both NH, as this period of time was considered to respect the incubation period of the disease [21, 22] (Figure S1). The variables included in the study are described in detail in the Supplement 1. Finally, positive/negative PCR results for SARS-CoV-2 and their cycle threshold (Ct) were recorded.

Based on positive SARS-CoV-2 PCR test, COVID-19 reinfection diagnosis was assessed within three months of IgA sampling at both NH. Additionally, 30-day mortality analyzed, as well as the setting in which it occurred (hospital vs. NH).

Statistical analysis

In light of previous studies, which reported the proportion of SARS-CoV-2 positive patients during the first wave of the COVID-19 pandemic to be between 70% and 80% [23], we determined that a sample size of 345 residents would be necessary. This calculation aimed to ensure a precision error of less than 5% and a confidence interval of 95%, while also considering an expected loss rate of 15%.

For descriptive analysis, absolute (n) and relative (%) frequencies were used to express categorical variables. Confidence intervals at 95% were calculated for these proportions. To analyse quantitative variables, mean and standard deviation or median and interquartile range were used and interquartile range according to the results obtained from the Shapiro Wilk or Kolmogorov-Smirnov normality test. In order to analyse the existence or not of statistically significant differences with respect to the variables of interest between “induced” and “non-induced” residents as well as between severe and non-severe cases, and those with symptoms lasting form more or less than 10 days, Chi-square tests or Fisher’s Exact Tests were used for qualitative variables, and the Student’s T-test or the Mann Whitney U-test for quantitative variables according to the normality of the variables analysed.

Finally, to discriminate the ability of SIgA-S1 values to predict the severity and duration of symptoms > 10 days, ROC curves were analyzed, calculating the AUC and its 95% confidence interval (CI). In this regard, SIgA-S1 values were considered as continuous variables. For each ROC curve, a score above 0.7 was considered acceptable predictive ability and below 0.6 as unacceptable [24]. In addition, the SIgA-S1 cutoff point of maximum likelihood between sensitivity and specificity was calculated to predict severity and duration of symptoms > 10 days. All statistical calculations were performed using SPSS statistical software (version 23.0 IBM Corp; USA).

Ethical issues

The study complied with good clinical practice standards set forth in the Declaration of Helsinki of 1975 and was approved by the relevant institutional review boards: the Ethics and Drug Research Committee of our reference, the Research Committee of the Hospital and by the Ethics Committee of the University.

Results

Demographics and baseline clinical characteristics

Among the 345 patients in both NH at the time of the extraction of the nasopharyngeal samples, 305 complied with the criteria for inclusion in the study (Fig. 1). Moreover 274 residents (89.8%) presented “induced” SIgA-S1 levels (≥ 57.6 U/ml), whereas 31 (11.2%) had basal SIgA-S1 values (< 57.6 U/ml). Regarding PCR SARS-CoV-2 test, 46 (15.1%) of them were positive, with a Ct median of 37.1 (Table 1).

Table 1 Characteristics of the population according to SIgA-S1 (“induced” vs.“non-induced” SIgA-S1)
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Overall, the median age was 87.3 [84.0–93.0] and 227 were women (74.4%). The median of comorbidities per patient was 1.2 [1,2,3] and the most frequent were hypertension (N = 189, 62.5%), chronic neurological disease (N = 77, 25.6%), diabetes (N = 69, 22.8%), heart failure (N = 47, 15.5%), chronic renal disease (N = 33, 10.9%) and solid neoplasm (N = 64, 10.2%, Table 1). A total of 170 (57%) patients were symptomatic, the median number of days with symptoms was 6.1 and the most frequent were cough (N = 75, 25.1%), upper respiratory symptoms (N = 69, 23.5%), fever (N = 40, 13.4%), headache (N = 40, 13.4%), dyspnoea (N = 39, 13%) and vomiting (N = 39, 13%). Finally, 81 (33.9%) patients suffered a severe case, the overall 30-day mortality was 2.6% and the 90-day reinfection rate was 5.6%.

Characteristics of the population according to SIgA-S1 (“induced” vs. “non-induced” SIgA-S1)

The distribution of patients according to the different levels of “induced” SIgA-S1 is shown in Fig. 1. Moreover, Table 2 shows that those with “induced” SIgA-S1 presented more symptoms of upper respiratory tract (25.1vs.6.5, percentage) and were more frequently symptomatic (60.3vs.29, percentage) than those with “non-induced” SIgA-S1. However, there were no differences in age, sex, comprehensive geriatric assessment, number of days with symptoms, severity of the disease, overall 30-day mortality or reinfection between SIgA “induced” and “non-induced” residents.

Table 2 Characteristics of the population and SIgA-S1 levels according to the severity of the symptoms
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Characteristics of the population and SIgA-S1 levels according to the severity of the symptoms

Eighty-one patients (26.5%) presented a severe form of the disease. This form of the disease was more common in men (38.3 vs. 21, percentage). In these cases, comorbidities (2.2vs.1.9, median), Chronic Renal Disease (18.5vs.8.1, percentage), and COPD (14.8 Vs 6.3, percentage), were significantly more frequent. There were no differences regarding age, Barthel Index or Clinical Frailty Scale. Symptoms of upper respiratory tract (54.1 vs. 31.4, percentage) and cough (58.8 vs. 34.3, percentage) were more frequent in severe forms. Furthermore, patients with these forms presented significantly more number of symptoms (3.6 vs. 2.5, median) and a longer duration of symptoms (10.8 vs. 3.8, median). We did not observe significant differences in the percentage of patients with “induced” SIgA between those with severe and non-severe cases (88.8% vs. 92.6%; p = 0.338). However, the median of SIgA-S1 value (U/ml) was significantly higher (252 vs. 192.6 U/mL, median) in severe cases than in non-severe (Table and Fig. 2). Nevertheless, in the ROC curve, we did not find a SIgA-S1 cut-off point with adequate sensitivity and specificity to predict COVID-19 severity (Figure S2).

Fig. 2
figure 2

SIgSA-S1, (a) severity and (b) duration of symptoms

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Characteristics of the population and SIgA-S1 levels according to duration of symptoms

Symptoms lasted more than 10 days in 56 (19.4%) and ≤ 10 days in 249 patients (81.6%), as presented in Table 3. Compared to patients with symptoms of long duration, patients whose symptoms lasted ≤ 10 days showed more comorbidities (2.4vs.1.9, median). There were no differences in any of the comorbidities, age or comprehensive geriatric assessment composites between the groups. Patients with symptoms of long duration (> 10 days) more frequently presented with fever (63.5vs.35.6, percentage), cough (65.4 vs. 34.7, percentage) and upper respiratory symptoms (55.8 vs. 33.9, percentage). As expected, severe cases (66.1vs.17.6) were more frequent in patients with symptoms of long duration. However, there were no statistically significant differences in the other variables evaluated. Finally, although an equal percentage of patients with “induced” SIgA-S1 were observed in patients with symptoms lasting > or ≤ 10 days (92.9% vs. 92.9%; p = 0.566), SIgA-S1 was higher in patients with symptoms lasting > 10 days (270.5vs.208.1 U/mL); however, on the ROC curve, we did not find a SIgA-S1 cut-off point with adequate sensitivity and specificity to predict a duration of symptoms > 10 days (Figure S3).

Table 3 Characteristics of the population and SIgA-S1 levels according to the duration of the symptoms
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Discussion

The results of this study conducted on institutionalized older adults during the first wave of COVID-19 show a high percentage of patients with positive SIgA-S1, with this group being more frequently symptomatic. Additionally, we observed that patients with severe disease and duration of symptoms longer than 10 days had median higher levels of SIgA-S1 than those with mild disease or a duration ≤ 10 days, respectively. Nevertheless, we failed to detect a SIgA-S1 cut-off point with adequate sensitivity and specificity to predict severity or disease duration > 10 days. Finally, we did not observe a significant relation between SIgA-S1 values and 30-day mortality or 90-day reinfection.

In our study, we highlight firstly that 89.8% of the residents had an “induced” SIgA-S1, a slightly higher incidence than in other research conducted in younger healthcare workers at NH [15, 16]. However, these younger patients more frequently presented with mild COVID-19 infection and tended to have higher mucosal SIgA-S1 titers. These elevated titers have been reported even in the absence of serum antibodies to SARS-CoV-2, indicating a possible superior immune response to the virus compared to older patients [13].

We present a very old population with high comorbidity, dependency, and cognitive impairment, which is common in this setting [25]. However, this sample is not comparable to any previous study that evaluated the role of secretory IgA. For example, the study by Cervia et al. [13] had a median age of 59.7, or the one by Zervou et al. that had a median age of 61 [26].

To our knowledge, most studies prior to ours had evaluated the relation between severity of infection and serum IgA specific for SARS-CoV-2, such as the study by Zervou et al. which demonstrated that serum IgA levels were higher in patients with severe disease, even after adjusting for age, sex, and duration of symptoms [26]. In this regard, the study by Santos et al., investigated specific SIgA levels for SARS and cytokines in the respiratory mucosa of patients with suspected COVID-19, demonstrating that SIgA levels in the mucosa are strongly associated with the severity of COVID-19 infection [12]. Additionally, as we expected and in line with previous studies, patients with symptoms lasting > 10 days had higher SIgA-S1 titers compared to those with shorter illness durations [16]. Whereas further studies demonstrating the predictive value of secretory IgA are needed, these results may have substantial implications for clinical decision-making. Understanding the relationship between SIgA-S1 positivity and disease severity and duration might guide personalized interventions for older patients, aiding prognostication and resource allocation. Furthermore, comprehending the role of SIgA-S1 could contribute to the development of targeted therapeutic strategies that take advantage of mucosal immunity to mitigate the impact of COVID-19 in susceptible populations.

On the other hand, it has been described that patients with negative or low serum IgA have a higher risk of COVID-19 reinfection [27]. However, the low reinfection rate recorded in our sample possibly prevented us from demonstrating this in SIgA-S1 patients. Similarly, we can say the same about 30-day mortality, which was also very low, as most deaths occurred in the weeks prior to sample collection.

Regarding the action of SIgA, it is known to be 15 times more powerful than serum IgA monomers and has the ability to neutralize viruses within intracellular tissue, preventing the uptake of pathogens by agglutination, providing a first line of defense against SARS-CoV-2 infection [10]. Despite these and other important functions, most studies have focused on studying the role of serum immunoglobulins in COVID-19 infection [23, 28]. In this way, one of the strengths of our study is the comprehensive evaluation of the role of SIgA-S1 in SARS-CoV-2 infection in a unique clinical context, the institutionalized older population, one of the most affected by COVID-19 during the pre-vaccination first wave. Another notable aspect is the detailed clinical analysis, not only of the infection but also of the baseline patient characteristics through comprehensive geriatric assessment, at a time when obtaining such data was challenging. However, the study also presents some limitations: firstly, we lack pre-pandemic controls for COVID-19, which would have allowed us to establish an exact cut-off point for determining secretory SIgA-S1 positivity. Secondly, we did not evaluate the co-detection of other respiratory viruses in the samples, such as rotavirus, poliovirus, or influenza although due to patient isolation in the facilities and strict measures during the early pandemic period, we assume a low risk of incidence of co-infection by other common respiratory viruses. Additionally, it should be noted that the nasopharyngeal samples were extracted from all residents on the same day, so the times from exposure to infection varied. However, the low rate of residents with positive PCR for SARS-CoV-2 and their high cycle threshold levels indicate that the majority had been in contact with and/or developed the infection in the weeks prior to sample collection. For this reason, and because it has been described that mucosal IgA can last up to nine months [15, 29], we consider the recorded SIgA-S1 values to be valid. Finally, the lack of access to plasma IgG against SARS-CoV-2 at that time prevented us from having a gold-standard test to determine which patients truly developed the infection. Without a doubt, this study adds a crucial piece to the puzzle of COVID-19 immunopathogenesis, but many questions remain. The interaction between systemic and mucosal immune responses, the mechanistic basis of SIgA influence, and the longevity of SIgA mediated protection deserve further exploration. Collaborative efforts between disciplines such as immunology, geriatrics, and epidemiology will be essential to advance our understanding of the broader role of mucosal immunity in infectious diseases, beyond COVID-19.

Conclusions

In summary, SIgA-S1 levels are associated with the duration and type of COVID-19 symptoms, as well as infection severity. Investigating the role of anti-spike SIgA in institutionalized older patients during the first wave of the COVID-19 pandemic adds a valuable layer of knowledge to the intricate immunological landscape of this global health crisis. This study sheds light on the potential clinical and public health implications, while stimulating further multidisciplinary research.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

NH:

Nursing homes

IgA:

Immunoglobulin A

SigA:

Secretory IgA

SIgA-S1:

IgA against the S1 domain of the SARS-CoV-2 spike

Ct:

Cycle threshold

CI:

Confidence interval

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Acknowledgements

We thank Dr. Beatriz Romero and Dr. Sergio González from VISAVET Centre (Complutense University of Madrid) and Susana Pérez-Benavente for the management and storage of the samples used in this study. We would also like to thank Álvaro Leal from the European University of Madrid and all the staff of the two Nursing Home who collaborated with the data collection work. Finally, we would like to thank all the staff working in the nursing homes for their hard daily work with the older patients during the pandemic period.

Funding

This research has been funded by the Complutense University of Madrid through a REACT-UE grant from the Community of Madrid to the ANTICIPA-REACT project of the Complutense University of Madrid and by the European University of Madrid through a grant awarded for internal projects in the year 2021.

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Authors and Affiliations

  1. Department of Geriatric Medicine, Hospital Universitario Infanta Sofía, Paseo de Europa 37, San Sebastián de los Reyes, 28007, Spain

    Rafael Bielza, Patricia Pérez, Nuria García, Rosa María Martínez, Clara Hernando & María Victoria Rodríguez

  2. Complutense University of Madrid, Madrid, Spain

    Laura Ballesteros-Sanabria, Azam Ghazi & José Manuel Bautista

  3. Faculty of Biomedical and Health Sciences, Department of Medicine, European University of Madrid, Madrid, Spain

    Rafael Bielza, Patricia Pérez, Israel J. Thuissard & Cristina Andreu-Vázquez

Authors
  1. Rafael Bielza
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  2. Patricia Pérez
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  3. Nuria García
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  4. Laura Ballesteros-Sanabria
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  5. Rosa María Martínez
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  6. Azam Ghazi
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  7. Clara Hernando
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  8. María Victoria Rodríguez
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  9. Israel J. Thuissard
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  10. Cristina Andreu-Vázquez
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  11. José Manuel Bautista
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Contributions

- Study concept and design: Rafael Bielza, Patricia Pérez, José Manuel Bautista- Acquisition of data: Patricia Pérez, Nuria García, Rosa María Martínez, Clara Hernando, María Victoria Rodríguez - Analysis and interpretation of data: Israel J. Thuissard, Cristina Andreu-Vázquez,- Drafting of the manuscript: Rafael Bielza, Patricia Pérez, José Manuel Bautista, Laura Ballesteros-Sanabria, Azam Ghazi - Critical revision of the manuscript for important intellectual content: Rafael Bielza, Patricia Pérez, José Manuel Bautista, Israel J. Thuissard, Cristina Andreu-Vázquez, Laura Ballesteros-Sanabria, Azam Ghazi.

Corresponding author

Correspondence to Rafael Bielza.

Ethics declarations

Ethics approval and consent to participate

The study complied with good clinical practice standards set forth in the Declaration of Helsinki of 1975 and was approved by the relevant institutional review boards: the Ethics and Drug Research Committee of our reference, the Research Committee of the Hospital and by the Ethics Committee of the University. All participants in this study signed a written informed consent to freeze their samples for research purposes.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Supplementary Material 1

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Supplementary Material 2

: Figure S1. Dates of sample collection and periods of clinical and morbi-mortality assessment.

Supplementary Material 3

: Figure S2. ROC curve and AUC: Severity and SIgSA-S1

Supplementary Material 4

: Figure S3. ROC curve and AUC: Duration of symptoms and SIgSA-S1

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Bielza, R., Pérez, P., García, N. et al. Unravelling the role of secretory Immnuoglobulin-A in COVID-19: a multicentre study in nursing homes during the first wave. BMC Geriatr 24, 804 (2024). https://doi.org/10.1186/s12877-024-05402-6

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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