key: cord-1046483-b7gr379p
authors: Kumar, Nathella Pavan; Padmapriyadarsini, Chandrasekaran; Rajamanickam, Anuradha; Bhavani, Perumal Kannabiran; Nancy, Arul; Jayadeepa, Bharathi; Selvaraj, Nandhini; Ashokan, Dinesh; Renji, Rachel Mariam; Venkataramani, Vijayalakshmi; Tripathy, Srikanth; Babu, Subash
title: BCG vaccination induces enhanced frequencies of dendritic cells and altered plasma levels of type I and type III interferons in elderly individuals
date: 2021-07-22
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2021.07.041
sha: 548ba0c3164e38a1fcab2f70a506cf89c823e375
doc_id: 1046483
cord_uid: b7gr379p

OBJECTIVE: : BCG can improve the response to vaccines directed against viral infections and also BCG vaccination reduces all-cause mortality, most likely by protection against unrelated infections. However, the effect of BCG vaccination on the dendritic cells (DC) subsets is not well characterized. METHODS: : We investigated the impact of BCG vaccination on the frequencies of DC subsets and type I and III interferons (IFNs) using whole blood and plasma samples in a group of elderly individuals (age 60-80 years) at one month post vaccination as part of our clinical study to examine the effect of BCG on COVID-19. RESULTS: : Our results demonstrate that BCG vaccination induced enhanced frequencies of plasmacytoid DC (pDC) and myeloid DC (mDC). BCG vaccination also induced diminished plasma levels of type I IFNs like IFNα and IFNβ but increased levels of type III IFNs IL-28A and IL-29. CONCLUSIONS: : Thus, BCG vaccination was associated with enhanced DC subsets as well IL-29 in elderly individuals, suggesting its ability to induce non-specific innate immune responses.

Bacillus Calmette-Guérin (BCG) is a live-attenuated vaccine largely established to protect against childhood meningitis and disseminated tuberculosis (TB) (Foster et al., 2021) Several epidemiological findings suggest that BCG may increase the capacity of the immune system to fight against pathogens other than TB (Leentjens et al., 2015) and such non-specific responses augment both T cell-mediated adaptive and innate immune memory in a process called trained immunity and this could have important implications for improving vaccination strategies. (Netea and van Crevel, 2014) . Bearing in mind, the high morbidity and mortality due to COVID-19 in the elderly population, a feasible protective effect through BCG in this group would be of clinical significance (O'Neill and Netea, 2020) . However the effect of BCG vaccination in protecting against heterologous infections in elderly individuals is still unclear as not many biological studies have conducted so far to prove this hypothesis.

Dendritic cells (DC) are the most effective antigen-presenting cells (APC) and play important roles in bridging the innate and adaptive immune responses (Banchereau and Steinman, 1998) . DCs are more efficient than other APCs, B cells and monocytes, in inducing T-cell proliferation (Inaba et al., 1989 , Ludewig et al., 1999 . Furthermore, DCs also play a significant role in the establishment of immunologic memory (Ludewig et al., 1999) .

Type I interferons (IFN-α/β) have wide range of antiviral activities, which act by stimulating an antiviral response across a variety of cell types (Mantlo et al., 2020) Like type 1 interferons, type III IFNs, termed as IFN lambda-1(IL-29), IFN lambda-2 (IL-28A), IFN lambda-3 (IL-28B), also play important roles in antiviral immune activities (Zhou et al., 2018) . Studies have also shown that type I and type III IFNs are able to inhibit SARS-CoV-2 replication (Felgenhauer et al., 2020) but effect of BCG vaccination in inducing type I and III IFNs is not well studied.

Hence, we examined the induction of DC subsets in response to BCG vaccination in elderly individuals at baseline and one-month post-vaccination along with baseline frequencies in unvaccinated individuals. We also examined the circulating levels of type I and type III IFNs following vaccination. We demonstrate that BCG vaccination induces significantly enhanced frequencies of DC subsets and altered type I and type III IFNs, suggesting that BCG can potentially boost immune responses in a non -specific or off-target manner in these elderly individuals.

The study was approved by the Ethics Committees of NIRT (NIRT-INo:2020010) . Informed written consent was obtained from all participants. The study is part of the clinical study entitled, Study to evaluate the effectiveness of the BCG vaccine in reducing morbidity and mortality in elderly individuals in COVID-19 hotspots in India (NCT04475302).

Elderly individuals, between 60 -80 years of age, residing in hotspots for SARS-Cov2 infection were included in the study between July 2020 and September 2020 in Chennai, India after obtaining informed written consent from the study participants. Elderly population positive for SARS-Cov2 infection by either antibody (serology) or PCR test; HIV infected or individuals with malignancy or on immunosuppressive drugs or transplant recipient and those on dialysis or anti-psychiatric medications or hypersensitivity to vaccinations were not included in the study. Also, those who were diagnosed with tuberculosis (TB) in the previous 6-months or were currently on anti-TB treatment were not included in the study. 54 participants received a single dose of BCG vaccine (Freeze-dried) manufactured by Serum Institute of India, Pune. The adult dose of BCG vaccine was 0.1 mL injected intradermally over the distal insertion of the deltoid muscle onto the left humerus (approximately one third down the left upper arm). In case of a previous vaccination scar, or presence of ulcer/injury or tattoo on the left upper arm, vaccination was given in the right upper arm. 32 elderly individuals from the same hotspot area were not vaccinated and were considered as controls. Blood was drawn from the vaccinated participants at baseline (before vaccination) and 1 month following vaccination. Blood was drawn from the controls only at baseline.

All antibodies used in the study were from BD Biosciences (San Jose, CA), BD Pharmingen (San Diego, CA), eBioscience (San Diego, CA), or R&D Systems (Minneapolis, MN). Whole blood was used for ex vivo phenotyping and it was performed on all 87 individuals. Briefly, to 250l aliquots of whole blood a cocktail of monoclonal antibodies specific for various immune cell types was added. Plasmacytoid DCs were classified as (Lin-HLA-DR + CD123 + ) and myeloid DCs (Lin-HLA-DR + CD11c + ). Monocyte phenotyping was performed using antibodies directed against CD45-PerCP, CD14-Pacific Blue, HLA-DR-PE-Cy7 (clone L243; BD), and CD16-APC-Cy7. Eight-color flow cytometry was performed on a FACS Canto II flow cytometer with FACSDIVA software, version 6 (Becton Dickinson). The gating was set by forward and side scatter, and 100 000 gated events were acquired. Data were collected and analyzed using FLOW JO software (TreeStar, Ashland, OR).

Circulating levels of IFN and IFNwere measured using Luminex Human Magnetic multiplex assay kit (R&D Systems). IL-28A, IL-28B and IL-29 was measured using the DuoSet ELISA kit (R&D Systems). The lowest detection limits were as follows: IFN 3.9 pg/mL; IFNpg/ml; IL-28A, 62.5 pg/mL; IL-28B, 62.5 pg/mL and IL-29, 62.5 pg/mL. The lowest standard value was assigned to the samples that were below the threshold of detection.

Geometric means (GM) were used for measurements of central tendency. Wilcoxon signedrank test was used to compare frequencies of immune subsets and type I and III interferons in the BCG vaccinated group at month 0 (M0) and month 1 (M1). Statistically significant differences between unvaccinated and BCG vaccinated M1 groups were analyzed using the Mann-Whitney test. Analyses were performed using Graph-Pad PRISM Version 9.0.

Correlation matrix analysis was done using statistical software JMP 14.0 (SAS, Cary, NC, USA).

The demographics of the study population are shown in Table I . From July 2020 through September 2020, 86 individuals were enrolled in the study with 54 in the vaccinated arm and 32 in the unvaccinated arm. All the vaccinated individuals were followed up at month 1 post-vaccination with no loss to follow-up. Median age was 65 (Range: 60-78) years in BCG vaccinated group and 63 years (Range: 60-80) in the unvaccinated group. There were 34 males and 20 females in the BCG vaccinated and 15 males and 17 females in unvaccinated group. In the enrolled population, 26% of BCG vaccinated and 15% of unvaccinated individuals had diabetes mellitus while 15% and 9% had cardiovascular disease respectively.

In our cohort, 4%-6% were current smokers and there were 6% were alcoholics. Other baseline characteristics were similar between the two arms.

To assess the ex vivo phenotype of DC subsets following BCG vaccination, we compared the subsets at baseline or before BCG vaccination (M0) and at month 1 (M1) postvaccination. As shown in Fig 1A, 

To study the plasma levels of type I IFNs following BCG vaccination, we compared the plasma levels of IFN and IFN at baseline or before BCG vaccination (M0) and at month 1 (M1) post-vaccination. As shown in Figure 

To study the plasma levels of type III IFNs following BCG vaccination, we compared the plasma levels of IL-28A, IL-28B and IL-29 at baseline or before BCG vaccination (M0) and at month 1 (M1) post-vaccination. As shown in Figure 3A , IL-28A (pand IL-29 (p showed significantly increased levels at M1 compared to M0. Next, we compared the plasma levels of type III IFNs in post-vaccinated individuals to unvaccinated controls. As shown in Fig 3B, 

We wanted to identify correlations between frequencies of DC subsets (pDC and mDC) and type I (IFN and IFN) and III IFNs (IL-28A, IL-28 B and IL-29) in BCG vaccinated individuals. As shown in the Fig. 4 , a multiparametric matrix correlation plot showed no significant correlation between the DC subsets and type I IFNs. However, a strong positive correlation between plasma levels of IL-29 with the frequencies of pDC was observed. No significant correlation was seen between IL-28A and IL-28B and DC subsets.

Our results overall indicate partial association between the DC subsets and type I and III

IFNs.

Naturally, elderly population are at a larger risk for infection against new infectious episodes. We have chosen to investigate the elderly population residing in the COVID-19 hotspots as it is known that this population is at a high risk to develop infections. Various clinical trials have shown that BCG vaccination limits number of infections of all causes, and especially respiratory tract infections, reasoning for a protective effect (Giamarellos-Bourboulis et al., 2020 , Madsen et al., 2020 . Few other studies have determined the protective effect of BCG vaccination against SARS-CoV2 in elderly individuals (Ten Doesschate et al., 2020). Various findings over the years have reported that BCG vaccines can induce a dominant nonspecific immune response, but it is still unclear if the BCG vaccine can offer meaningful protection against diseases like COVID-19. (Aspatwar et al., 2021) .

Actually, numerous clinical trials are ongoing to estimate the capacity of the BCG vaccine to modulate immunity against COVID-19. The main goal of these clinical trials is to determine if BCG vaccination lessens the incidence and severity of the SARS-CoV-2 infection. These studies will eventually help us to understand whether and to what extent BCG offers protection against SARS-CoV-2 (Aspatwar et al., 2021) . In addition, studies have also reported that upon BCG vaccination in the elderly population resulted in decreased risk of pneumonia in tuberculin positive individuals, indicating that administering BCG is one of the effective strategies for the prevention of pneumonia (Ohrui et al., 2005) . In this current study, we wanted to evaluate the impact of BCG on DC subsets, type I and III interferons in elderly individuals residing in COVID-19 hotspots. As part of the study protocol, we studied the dendritic cells, Type 1 and III immune responses generated by BCG vaccination in a group of elderly individuals.

DCs encompass a diverse population of cells that play an important role in initiating, directing and regulating adaptive immune response (Soto et al., 2020) . Activating the adaptive immune response requires the presentation of antigens to T cells by DC and macrophages (Hilligan and Ronchese, 2020) Delays in activation of DC could often result in a delay in the induction of the adaptive immune response to pathogens. Thus, methods to either increase the frequencies of DCs or to activate DCs would improve the protective efficacy of vaccines (Fucikova et al., 2019) . Our data showing elevated frequencies of both mDC and pDC thus clearly illustrate an important effect of BCG vaccination in enhancing the innate immune response to both specific and non-specific pathogens (possibly) in elderly individuals. Moreover, while mDC is mainly involved in the process of antigenpresentation (Macri et al., 2018) , pDC is the main source of Type 1 interferons in the host (Leylek and Idoyaga, 2019) Thus, it is potentially likely that increased frequencies of pDC might heighten the propensity of pDC to mount Type I IFN responses against pathogens encountered.

Interferons constitute the first line of defense against microbial infections particularly against viruses (Sa Ribero et al., 2020) . Type I interferons and DCs share an overlying history, studies have been well reported that expression of type 1 IFNs by DC and their interface are the one of the important components of the innate and adaptive immune responses (Fitzgerald-Bocarsly and Feng, 2007) . It also known that cross-talk between pDC and mDC via type I IFNs has been involved in some pathological situations (Fitzgerald-Bocarsly and Feng, 2007) . Even in our study we do observe a significant increase in the frequencies of DC subsets, whereas there was a significant decrease in the circulating level of IFN and IFN upon one month of post BCG vaccination indicating that this inverse relationship may be involved in the containment of the infection.

Type III IFNs typically act on epithelial cells in response to viral infection (Sommereyns et al., 2008) . Plasmacytoid dendritic cells are the foremost producers of Type III IFNs (Yin et al., 2012 , Zhang et al., 2013 . Published data suggest that the impact of Type III IFNs on host immunity extends beyond its effect at the mucosal level to effects on systemic immune responses, specifically the innate, and adaptive arms of the immune response (Zanoni et al., 2017) . Thus, Type III IFNs are known play a key role in adaptive immune responses to viral and bacterial infection, alter anti-tumor responses and affect immunity (Lasfar et al., 2016 , Lazear et al., 2015 , Wack et al., 2015 . Some studies have reported that Type III IFNs are the prominent IFNs produced after viral infection (Andreakos et al., 2017) . In our study we observe elevated circulating levels of IL-28A and IL-29 after one month of BCG vaccination, which in turn it was correlated with the elevated levels of dendritic cells. However, their role in SAR-CoV-2 infections has not, to our knowledge, been explored.

In summary, our study highlights the effect of BCG vaccination in modulating the frequencies of DC subsets. Study limitations are that samples were collected only during the baseline visit and not at follow up in control individuals and that all the measured data are reported only in percentages but not absolute numbers. Our study also reveals an effect of BCG in inducing positive correlation with type III IFNs and DC subsets. The possible cellular mechanism is that type I or III IFNs may contribute to DC maturation, which is promoted by BCG vaccination. Although our study did not examine the mechanistic changes in the immune system, our data however reveal a vital role for BCG vaccination in boosting immune responses in the elderly population. 

Multiparametric matrix correlation plot of DC subsets, and type I and III interferons in all individuals with BCG pre-vaccinated and month 1 following vaccination. Spearman's correlation coefficients are visualized. Blue line represents the x-axis parameter and red line represents the y-axis parameter. 

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☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work

We thank the staff of the Department of Clinical Research, NIRT. We thank the data entry operators Mr. Jaiganesh and Mr. Vigneshwaran, and also all the staff members of the ICER department and Greater Chennai Corporation for the timely help. responsible for the enrolment of the participants and also contributed to acquisition and interpretation of clinical data (C.P., B.P.K., B.J., D.K., S.T); wrote the manuscript (S.B., N.P.K., C.P). All authors read and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.Data and materials availability. All the reported data are available within the manuscript