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A rapid ecologic analysis, confirmed by a case–control study, identifies class I HLA alleles correlated to the risk of COVID-19

Journal of Translational Medicine volume 23, Article number: 303 (2025) Cite this article

Abstract

Background

Several studies suggest that the heterogeneous spread of SARS-CoV-2 pandemics started on December 2019 could be partially upheld by the prevalence of permissive class I HLA alleles in specific populations. Such HLA alleles are in fact unable to shape an efficient anti-viral immune-response in the hosts or sustain an exaggerated inflammatory T cell mediated response responsible for the COVID-19 disease. We previously reported an ecologic correlation between the risk of COVID-19 spreading across Italy and the germinal expression of permissive HLA-C*01 and -B*44 alleles in specific inter and intraregional populations along the first spreading wave.

Methods

Considering that SARS-CoV-2 has undergone multiple adaptative mutations since the beginning of pandemics related to a natural immunization and to the worldwide campaign of anti-SARS-CoV-2 vaccination, we have carried out further analyses to evaluate whether the predictive value of class I HLA-allele gene prevalence and COVID-19 incidence has changed with time along the first four pandemics spreading waves in Italy. To this purpose we carried out an ecologic study followed by a case–control study.

Results

| Our data revealed that the direct correlation of HLA-C*01, and HLA-B*44 gene expression and COVID-19 risk was completely lost just after the first pandemics wave in Italy. On the contrary, the expression of HLA-B*49 allele in specific populations emerged as inversely correlated to the risk of COVID-19 and could be considered as a protective factor. The statistical significance of this correlation was progressively enforced in each subsequent spreading wave until February 2022. The following case–control study in the two Regions of Campania and Calabria in Italy confirmed the protective value of HLA-B*49 allele gene expression (OR = 0.289; p = 0.041), although statistical significance is lost after adjustment by logistic regression model. The analysis also detected multiple class I HLA-alleles whose expression was strongly correlated with COVID-19 risk: HLA-B*08 (ORadj = 3.193; p = 0.015); -B*14:01 (ORadj = 3.596; p = 0.018); -B*15:01 (ORadj = 5.124; p = 0.001); -B*35 (ORadj = 2.972; p = 0.002).

Conclusions

Our study not only identifies specific HLA alleles related to COVID-19 risk but also exemplifies a rapid and inexpensive approach that can be used to identify individuals needing prioritization during vaccination campaigns.

Background

A new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA virus emerged, either as a zoonosis by spillover from wild bats or a leak from a research laboratory [1], and gave rise to the Coronavirus Infectious Disease-19 (COVID-19) in humans, which was declared as pandemic by the WHO on March,11th, 2020 [2] until 2023 [3]. Italy was one of the first countries to suffer the explosive evolution of the outbreak achieving one of the highest infection and mortality rates worldwide along the whole 2020 [4] with a large gradient of frequency decreasing from the northern to the southern part of the country [5]. This epidemic gradient was not modified along the first two years of pandemics even in the presence of a continuous unstoppable massive migratory flux of individuals escaping from the high-risk regions to return in their native landscapes [6]. The multiple socio-political as well as environmental hypotheses advocated to explain those inter- and intra-regional differences could never be confirmed in reliable experimental models; on the contrary, multiple immune-microbiological theories were formulated to explain this phenomenon. As expected for most RNA viruses mediated infections, it was hypothesized that both T cell and humoral response to COVID-19 infection are necessary for viral clearance from the host and to induce protective memory [4, 7]. At the beginning of the pandemics SARS-CoV-2 was mostly unknown to the human immunosurveillance system that reacted to its infection in unpredictable ways while attempting to mount an efficient T cell mediated and humoral response. Additionally, there was a minority of infected patients in which SARS-CoV-2 could easily spread from the oropharyngeal district to the lung and other tissues, triggering a systemic inflammatory reaction, intra-vessel disseminated coagulation and an exaggerated cell mediated response to the virus which led to interstitial pneumonitis and less frequently to a fatal acute respiratory distress syndrome (ARDS) [8,9,10,11].

The core mechanism triggering a virus-specific immune response is generally represented by the major histocompatibility complex (MHC) or human leukocyte antigen (HLA), an immunoglobulin-like structure, aimed to present virus-derived antigen peptides to the T cell precursors thus inducing an efficient antigen-specific cytotoxic T lymphocyte (CTL) response, promoting protective antibodies production by B cells and enhancing or inhibiting specific inflammatory responses. Considering the crucial role played by class I/II HLA molecules in triggering the anti-viral T and B cell mediated immune-response, it was hypothesized that the expression of different HLA alleles could define an individual susceptibility to COVID-19 infection as shown in different infections models [7]. In this context, several studies have been searching for selected HLAs with a very efficient ability to present viral-antigen-derived epitope peptides to CTLs. The identification of highly immunogenic peptide epitopes recognized by specific T Cell Receptors (TCRs) might, in fact, provide potential candidates for vaccine development [12, 13]. By triggering and sustaining the human host immune-defenses to the virus, specific class I HLA alleles may also be involved in the occurrence of other symptoms, morbidity or lethality [14]. There is a large heterogeneity and polymorphisms in class I -II HLA alleles whose genes present longitudinal parental transmission under continuous environmental pressure. Overall, the heterogeneous response of different populations to the same pathogens, chemical and physical agents, might be at least partially related to different clusters of HLA- alleles in the resident populations. Various studies suggest that the heterogeneous spread of SARS-CoV-2 pandemics could be at least partially sustained by the prevalence of permissive class I HLA alleles in specific populations, unable to shape an efficient anti-viral immune-response in the hosts or on the contrary sustain a exaggerate inflammatory T cell mediated response responsible for the COVID-19 disease. In our previous early ecologic analysis, we recorded a permissive role of HLA-C*01 and -B*44 towards SARS-CoV-2 infection incidence recorded at the pick of the first pandemic spreading wave. Our preliminary findings sustained the hypothesis that the regional prevalence of specific class I HLA alleles might shape the anti-viral immune-response in order to explain the differences in COVID-19 spreading across the country [15]. Since then, several case control studies worldwide continued to sustain the hypothesis that different HLA alleles are indeed involved in the susceptibility and development of the disease worldwide. Many of these studies however, identified different candidates owing to the highly polymorphic nature of the HLA system and the different study methodologies. HLA allele genes in fact present an extended rate of heterogeneity in term of frequency, family cluster and geographic prevalence that could affect the reliability of the reported results. Many other authors focused the attention on the infection measured as simple positivity to SARS-CoV-2 spike, to patients with symptomatic COVID-19 disease, or to patients with severe disease non homogenously managed worldwide. These studies become extremely complex requiring a very large statistical sample that can be reached in multi-centric studies only. Additionally, the occurrence of multiple SARS-CoV-2 variants, different geographic environments, life habits and the development of intense vaccination campaigns against the Coronavirus might have significantly affected the clinical exordium of the disease and the results in the health monitoring of the spreading.

On these bases, we decided to perform a long-term analysis in order to evaluate whether our ecological correlation was still valid after two full years of pandemic and the first four consecutive spreading waves and subsequently, confirming our findings in a case–control study analyzing hospitalized patients with severe COVID-19.

Materials and methods

Data source and population sample

The frequency of specific HLA alleles varies significantly among the different populations inhabiting the twenty geographic regions that compose the Italian Territory.

We retrieved the HLA allele frequency data, which were recorded within the different regions and relative intra-regional provinces, from the database of the Italian Bone Marrow Donor Registry (IBMDR). We referred to an IBMDR database analysis, published on 1 February 2010 [16] containing data that were collected in a twenty year interval from a cohort of 370,000 volunteer donors with known provincial and regional birthplace origin. These allele frequencies, expressed in % as calculated through the Arlequin Software, were also compared to those reported in a new version of the IBMDR database updated in 2019, including data collected on a further 120,926 volunteer donor cohort [17]. Samples from the more recent cohort were typed with a high-resolution method [17]; the same allele frequency distribution across Italy was confirmed; at the time of the analysis, all subjects were from 18 to 55 years old. The sample was composed of 45.6% males and 54.4% females. HLA frequency data (prevalence) available for all the HLA class I, A, B, C genes from these cohorts, distributed across provinces of all the 20 Italian regions, corresponded to a total of 357,711 volunteers and were used for the ecological analysis (Supplementary Table 1– “Ecological analysis”). HLA I alleles were reported using the updated nomenclature version available at the time of writing (according to the Immuno Polymorphism Database (IPD)-International ImMunoGeneTics project (IMGT/HLA) Database Release 3.54 https://www.ebi.ac.uk/ipd/imgt/hla/).

Data concerning the total number of individuals infected by SARS-CoV-2 (updated to February 8th 2022) were provided by the Italian Department of Civil Protection, the institution under the Presidency of the Council of Ministers that manages the emergency at national level. Data were provided as aggregate numbers, in an anonymized manner. The COVID-19 incidence data were obtained by dividing the total number of infected individuals by the total number of residents in each specific Italian province (data are provided in Supplementary Table 1 – “Ecological analysis”).

Statistical analysis

The relationship between SARS-CoV-2 infection and the frequency of HLA alleles was explored as part of an ecologic approach aimed at assessing the degree of correlation between the incidence of COVID-19 and the prevalence of HLA alleles, both measured on a geographical basis (taking each Italian province as the unit of observation, see Supplementary Table 1– “Ecological analysis”) as shown in a previous study of our group [15]. For each allele, values were preliminarily plotted in a scatter diagram and the curve with the best fit (corresponding to exponential curve) was selected using the least squares method, which is the most widely used procedure for developing estimates of the model parameters. The estimated regression equations are indicated at the top of each graph. Consistent with the exponential model, Pearson’s coefficient (r) was calculated as a measure of the correlation between the logarithm of the COVID-19 incidence and the prevalence of different HLA alleles. For each value of r, the corresponding p-value was also considered, in order to assess the statistical significance of the correlation (with respect to the null hypothesis of no log-linear correlation).

Finally, the association between the logarithm of the COVID-19 incidence (considered as dependent variable) and HLA alleles independently of each other was tested using a multivariable regression analysis. The choice to use an “exponential” model for the analysis of ecological data was based on a statistical evaluation of goodness of fit (using the least squares method), as previously reported [15]. Furthermore, the Italian regions were included as covariates in the model (which is an alternative approach to stratified analysis), in order to control for the confounding of geographical context and, at the same time, to verify the association of interest regardless of the North–South gradient.

All statistical analyses were conducted using STATA software 11.0 version (StataCorp LLC, College Station, Texas, TX 77845–4512, USA). Microsoft Excel was used to draw maps.

Case–control study

To perform the case–control analysis, 39 and 36 cases were collected from patients hospitalized for COVID-19 at the Azienda Ospedaliera Specialistica dei Colli, Cotugno Hospital, Naples, Campania and the Grand Metropolitan Hospital 'Bianchi Melacrino Morelli', GOM of Reggio Calabria, Calabria, respectively. Patients’ inclusion criteria were the following: age above 18 years; positivity for SARS-CoV-2 infection (assessed by oropharyngeal swab); asymptomatic, pauci-symptomatic or with documented pneumonia or COVID-19-related pathology; ability to provide informed consent. Exclusion criteria were the following: age below 18 years and inability to provide informed consent. The study was approved by the local ethical committee of both institutions (Protocol NA, number eudract NA, Date of approval by south etic local committee 10/02/2021; GOM deliberation n. 634, 29/09/2021). Patients had a median age of 64.5 years and were mostly men 69%. For each enrolled patient (case), DNA was extracted by whole peripheral blood samples through automatic extractor EZ1 Advanced XL—Qiagen, amplified by locus specific PCR and typing performed on HLA class I and II by reverse SSO DNA typing assay added of eRES kits to obtain an enhanced resolution analysis (Luminex technology, MatchIt Software, Lifecodes-Immucor). For each Italian region, 191 and 206 controls (from Campania and Calabria respectively), were randomly sampled from the IBMDR Regional Registry data from which class I HLA typing were obtained as representative of the population from which the cases were drawn (supplementary Table 2 – “Case–control analysis”). In this type of case–control study, controls were selected as to be a sample of the whole population (and not just the non-cases), with respect to HLA class I prevalence. In this situation, the odds ratio is an estimate of the relative risk of having COVID-19 for exposed people compared with those unexposed to expression of different HLA alleles. Moreover, controls were matched (frequency matching) by regions of residence to reproduce the same distribution observed for the cases. Logistic regression was used to assess the association between COVID-19 hospitalization and HLA alleles independently of each other, and to account for matching by including the variable “region of residence” in the model. STATA software 11.0 version (StataCorp LLC, College Station, Texas, TX 77845–4512, USA) was used to conduct statistical analyses.

Results

Ecologic study

We performed a dynamic correlation among the stable prevalence of class I HLA alleles in the different regions of Italy and the evolved incidence of severe COVID-19 through the national territory since the beginning of the pandemics. The incidence of COVID-19 was calculated on the data recorded at the pick of each one of the four subsequent spreading waves recorded on April, 9th, 2020; December, 27th, 2020; March, 25th, 2021, and February, 8th, 2022 (Supplementary Table 1 – “Ecological analysis”). In line with the first study, COVID-19 data were provided by the National Civil Protection Department, whereas HLA allele prevalence was retrieved through the (IBMDR).

In line with the results of the previous analysis performed on the pick of the first spreading wave (April, 9th, 2020) we studied the relationship between HLA class I allele frequency and COVID-19 incidence using a scatter plot by interpolating a line of best fit and confirmed a positive log-linear correlation among the prevalence of HLA-A*25, -B*08, -B*44, -B*15:01, -B*51, -C*01, and -C*03 allele with COVID-19 incidence rate. However, the statistical significance (at the 5% level) of -B*44 and -C*01 correlations was progressively lost along the subsequent pandemics waves (Table 1).

Table 1 Association between HLA allele prevalence and COVID-19 incidence assessed at different time points corresponding to four epidemic waves in Italy (years 2020–2022)
Full size table

In the present analysis we also observed that the prevalence of HLA-B*49, which did not show any correlation with COVID-19 incidence during the first spreading waves, acquired an inverse log-linear correlation with SARS-CoV-2 spreading along Italy in the subsequent spreading waves, Fig. 1 (regression coefficient − 0.143, − 0.123, − 0.107 and − 0.091, p-value < 0.05) (Table 1). When the prevalence of the above-mentioned HLA alleles was examined simultaneously in the consecutive COVID-19 spreading waves using a multiple regression model to avoid confounding factors, only HLA-B*49 resulted as an independent variable predictive of low risk of COVID-19 (Table 1).

Fig. 1
figure 1

Association between B*49 prevalence and COVID-19 incidence. The graphs show the association between the prevalence of HLA-B*49 expressed as percentage, for all the available Italian provinces and COVID-19 incidence during four waves of the pandemics in Italy (a April 9th 2020; b December 27th 2020; c March 25th 2021; d February 8th 2022). For each graph, the R-squared value is provided, which represents a measure of the goodness of fit of the exponential model

Full size image

Case–control study

The hypothesis that the prevalence of the specific class I HLA alleles, identified through the ecologic study, might be of permissive or protective value to COVID-19 spread was subsequently tested in a case–control study where we examined the correlation among the expression of specific HLA alleles in the resident population and patients with severe COVID-19 hospitalized in the two Specialized Hospitals respectively located in the two South Italian regions of Campania and Calabria between December 2021 and April 2022. The study was designed with a control group in order to estimate the actual expression frequency of the investigated HLA allele genes in a representative sample of the resident population. The control group was represented by bone marrow healthy donors who underwent HLA genetic typing in the same interval of time, with the same methodology in the same areas of residence; Campania and Calabria respectively (Supplementary Table 2–“Case–control study)”. In particular, our study involved 75 patients with severe COVID-19 respectively hospitalized within the Cotugno Hospital of Naples (39 Cases) and the GOM of Reggio Calabria (36 cases) and 397 donors in anonymous form (191 from the Campania registry and 206 from the Calabria registry, respectively). Patients and donors features are represented in Table 2. Our analysis showed a strong positive association between the expression of HLA-B*08 (OR = 2.384; p = 0.051), HLA-B*15:01 (OR = 5.012; p < 0.001) and HLA-B*35 (OR = 2.584; p = 0.001) and COVID-19 hospitalization. On the contrary, the expression of HLA-B*49 allele showed an inverse correlation with COVID-19 (OR = 0.289; p < 0.041) thus confirming its protective value found in the epidemiologic study (Table 3). When a multivariate regression logistic model was applied to eliminate the reciprocal confounding by the other variables considered in the model, the expression of HLA-B*08, HLA-B*14:01 (not shown in the univariate analysis), HLA-B*15:01 and HLA-B*35, maintained their statistically significant association with COVID-19. On the contrary, in the multivariate analysis the COVID-19 protective effect of HLA-B*49 expression maintained its magnitude levels but lost the statistical significance at the 5% level (Table 4).

Table 2 Study population
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Table 3 Association between hospitalization for COVID-19 and HLA alleles: case–control study
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Table 4 Association between hospitalization for COVID-19 and HLA alleles: logistic regression analysis
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Sex and age data relative to the controls were not available, which limited the possibility to study their impact in these cohorts. However, neither sex nor age are associated to HLA class I genotype (whose genes are located on chromosome 6) and therefore it fails the assumption to be considered as possible confounders in the association between HLA I frequency and COVID-19 analysis [18], although both factors (sex and age in particular) can affect hospitalization.

Discussion

Our previous epidemiologic analysis by means of a geographical ecologic approach, identified putative class I HLA alleles permissive of SARS-Cov-2 infection at the pick of the first pandemic wave. In particular, our study identified HLA-A*25, HLA-B*08, HLA-B*15:01, HLA-B*44, HLA-B*51, and HLA-C*03 as directly correlated with the incidence of SARS CoV-2 infection. When a multivariate analysis was performed only the expression of HLA-B*44 and HLA-C*01 resulted positively correlated with inter-regional and intra-regional incidence of COVID-19. On the basis of those findings we formulated the hypothesis that individuals expressing the above mentioned HLA alleles were unable to mount an efficient immune-defense against the newborn Coronavirus and were thus unable to prevent the occurrence of COVID-19 [15].

This hypothesis was consistent with previous clinical studies and experimental models supporting HLA alleles role in infectious diseases, tumors and inflammatory autoimmune disease [19,20,21,22,23,24,25,26,27,28,29]. HLA-B*44 and C*01 alleles, in particular, have been respectively associated to known inflammatory autoimmune diseases [30] and susceptibility to recurrent sinopulmonary infections [31] a fact that highlights their ability to trigger an inappropriate immune-reaction in response to possible immune-attack. This hypothesis was largely confirmed in worldwide large studies of other groups in different patients settings and experimental conditions [32].

More recently, Boquett et al. performed a further ecological study aimed to investigate the correlation between HLA haplotypes and the different regional distribution of COVID-19 mortality in Brazil that showed large variability among the different 26 states and the Federal District since the beginning of the pandemic. HLA data were obtained from the Brazilian Voluntary Bone Marrow Donors Registry while COVID-19 records were retrieved from the State Health Secretariats via Brazil’s Ministry of Health from February/2020 to July/2022. These authors found a direct correlation between the ancestral HLA-A*01 ~ B*08 ~ DRB1*03 haplotype and COVID-19 mortality rates suggesting that this particular HLA haplotype might be considered as a potential risk factor of COVID-19 related death [33].

On these bases, we have therefore, decided to continue our investigation after three years of pandemics in Italy, by taking in consideration the infection spreading of SARS-CoV-2 associated with a decreased morbidity and mortality in humans worldwide. In the present analysis we observed that the statistical positive correlation between HLA-B*44 and C*01 and SARS-CoV-2 infection spreading was completely lost just after the second epidemic waves on March, 25th, 2021. Our analysis however, recorded an inverse correlation between HLA-B*49 expression and SARS-CoV-2 infection in Italy occurring between the second and the fourth spreading waves of the outbreak. HLA-B*49 was therefore considered as a potential protective factor form SARS-CoV-2 spreading. This finding recorded in the present study could have multiple explanations including: (1) different epidemiologic data retrieved from the Italian authorities since the beginning of the pandemic; in fact along the first wave SARS-CoV-2 was mainly tested on heavily symptomatic patients with COVID-19, while in the subsequent waves all individuals positive to the SARS-CoV-2 test were collected independently from the presence or absence of symptoms of disease; (2) the rise of multiple variants of SARS-CoV-2 due to the natural selective pressure on the native virus when more the 80% of the worldwide population has had contact with it with progressive occurrence of SARS-CoV-2 homoplasy in the humans leading to much less aggressive forms of COVID-19; and (3) the intensive SARS-CoV-2 vaccination programme that covered 80% of Italian population started on December 2020.

This type of ecologic approach has intrinsic limits, but it also has the advantage of considering a large number of cases which are readily available through public-access datasets and can be easily repeated in order to monitor possible changes along the time. Indeed, geographical ecological studies are often the first to identify risk factors for a variety of diseases, which deserve to be verified through subsequent studies [34]. On this basis, we carried out the present case–control study, where the expression of specific class I HLA alleles in the resident population of Calabria and Campania in the southern of Italy was correlated with the risk of hospitalization due to COVID-19. Our analyses revealed a strong positive association among the expression of HLA-B*08, HLA-B*14:01, HLA-B*15:01 and HLA-B*35 and severe COVID-19 hospitalization. Individuals expressing one of these alleles, compared to the controls, showed a 2.5 to 5 times higher risk of developing a severe COVID-19 upon infection by SARS-COV-2 confirming the results of the ecologic study by Boquett et al.

Our case–control analysis also confirmed the results of our ecologic analysis where the expression of HLA-B*49 allele showed an inverse correlation with COVID-19 thus validating its protective value firstly found in our ecologic study. In fact, individuals expressing this allele compared to the controls showed an almost four-time lower risk of developing a severe COVID-19 upon infection by SARS-CoV-2. In multivariate analysis the COVID-19 protective effect of HLA-B*49 expression maintained its magnitude levels but lost the statistical significance at the 5% level, suggesting that either the statistical power is not sufficient, or the effect is conditioned by other parameters.

The hypothesis of a strong correlation between HLA haplotypes and SARS-CoV-2 spreading and disease were not surprising considering that their gene products, hence class I-II HLA molecules bind and present virus antigen-derived epitope peptides to the T cell receptor of T cells. Class I-II HLA molecules are critically involved in both T cells replication and ability to recognize and destroy virus-infected target cells [35]. In this context the binding of antigen-derived peptides to HLA molecules is allele-specific and is restricted by specific amino-acidic consensus motifs that allow their anchorage to different HLA molecules; the HLA-binding consensus motifs are expressed in a single antigenic protein/peptide recognizable by using specific algorithm programs [36]. Thus, two individuals carrying the same antigen but expressing different class I-II HLA profile may give rise to a completely different T-cell-mediated immune-response, since they may have completely different amounts of HLA-specific antigen-derived epitopes aimed to direct the immune-response. This phenomenon has been confirmed in several studies concerning a number of pathogens, tumor antigens, autoimmune models and viruses, including SARS-CoV-2 [12, 19,20,21,22,23,24,25].

It is consequential that SARS-CoV-2 variants present new antigen peptides, thus changing the spectrum of the derivative antigen peptide binding to class I and II HLA molecules, a hypothesis, that could easily explain the change in the predictive COVID-19 risk correlation in the ecologic study concerning HLA-B*44 and HLA-C*01 and subsequently, HLA-B*49 between the first and the subsequent outbreak waves in Italy. Indeed, various evolutionary trajectories have led to SARS-CoV-2 diversification into variants with distinct phenotypic characteristics that affect transmissibility, severity and evasion of both innate and adaptive immune responses (for a recent detailed review see [37].

Consistently, the changing relationship between B*14:01 and COVID-19 risk from the early stages of the pandemic to those of the case–control study could be related to mutations in the SARS-CoV-2 virus affecting epitope presentation or shifts in the population's immune landscape due to vaccination and natural infections over time.

Our model suggests that the expression of specific class I HLA alleles in healthy individuals could make them more or less susceptible to SARS-CoV-2 infection and severity of the derivative disease (COVID-19) due to the ability of specific HLA haplotype to present a sufficient amount of immune-dominant virus derived antigen peptides to the T cells able to mount a fast and efficient anti-viral immune response; to avoid an inappropriate reaction with occurrence of inflammatory mediated damage of healthy tissues as shown in multiple studies. The expression of several alleles such as HLA-B*08, HLA-B*15.01, HLA-B*35 that have shown a direct correlation with COVID-19 were also strongly correlated to other viral infection susceptibility [22, 35, 36, 38,39,40] and to severe inflammatory mediated autoimmune diseases and immune-related adverse events upon immune-oncological treatments [25,26,27,28,29,30,31, 35, 41, 42]. Indeed, it has been recently shown that class I and II HLA allele profiling could be predictive of treatment response and prolonged survival in non small cell lung cancer (NSCLC) patients receiving PD-1/PD-L1 immune checkpoint blockade, an immune-oncological treatment acting by restoring the activity of CTLs infiltrating the tumor made anergic throughout this specific immunosuppressive immune checkpoint [25, 41, 42]. In line with the results of other immunological studies, the occurrence of immune-related Adverse Events (irAEs) in these patients is consequential to the cross-priming of antigens released from the tumor site in an immunological context of CTL-mediated immune-rejection, whose cross-priming may be facilitated and redirected to the B cell compartment by the germline expression of specific and multiple class II HLA alleles [43,44,45]. In a previous study of our group we also showed that the germinal expression of HLA-B*35 and/or DRB1*11 alleles is associated with a high risk of immune-related pneumonitis in cancer patients addressed to immune-oncological therapy with immune checkpoint inhibitor mAbs to Programmed cell death receptor 1 (PD-1) or PD-1 ligand 1 (PD-L1) [46]. This is similar to what reported in the present paper, where individuals presenting germinal expression of pro-inflammatory HLA alleles directly correlated with the risk of severe COVID-19. In this context haplotypes HLA-B*08, HLA-B*15.01 or HLA-B*35 allele have all been clearly correlated with autoimmune disease and to high risk of Chlamydia pneumoniae-associated pneumonitis in patients with chronic diseases and to severe primary pulmonary hypertension in patients with scleroderma and nephritis associated to hyper-leukocytosis disease [47, 48]. Similarly, B*35 expression has also been associated to high-risk juvenile idiopathic arthritis [49]. To this purpose, it appears of great interest the finding that individuals harboring HLA-A*11:01, A*24:02, B*08:01, and B*27:05 in the Southeast Asia, East Asia, and Oceania undergone to T cell sensitization with SARS-CoV-2 vaccination also showed the highest incidence of adverse events [50].

A further consideration deserves the property of several class I HLA alleles to modulate the activity of natural killer (NK) cells, which represent the first line of host defense to the infection before the occurrence of a more specific T cell response with memory. Class I HLA-alleles locus C, represent the specific ligands for killer cell immunoglobulin like receptors (KIRs), KIR2DL1, KIR2DL2 and KIR2DL3, and locus B alleles containing the serologically defined Bw4 epitope are ligands for KIR3DL1. These receptors are able to transmit an inhibitory message to NK cells, as shown in multiple experimental models [51,52,53,54,55], blocking the response of these important immune system effectors. It will be interesting to study how specific class I HLA-alleles affect the NK anti SARS-CoV-2 response.

Also, it will be interesting to evaluate the SARS-CoV-2 peptide-binding ability of the class I HLA alleles related to COVID-19 susceptibility. To this purpose HLA typing will have to be performed in high resolution then tested through different immunopeptidomic softwares and possibly in vitro [56].

Overall, our study provides a method, rapid and costless, to identify HLA alleles potentially predictive of severe COVID-19 risk and also identifies specific subsets of individuals who deserve priority in HLA haplotype-driven SARS-Cov-2 vaccination programs.

Availability of data and materials

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

Abbreviations

ARDS:

Acute respiratory distress syndrome

COVID-19:

Coronavirus infectious disease-19

CTL:

Cytotoxic T lymphocyte

HLA:

Human leukocyte antigen

IBMDR:

Italian Bone Marrow Donor Registry

irAEs:

Immune-related Adverse Events

IPD-IMGT/HLA:

Immuno Polymorphism Database-ImMunoGeneTics/HLA project

KIRs:

Killer cell immunoglobulin like receptors

MHC:

Major histocompatibility complex

NK:

Natural killer

NSCLC:

Non small cell lung cancer

SARS-CoV-2:

Severe acute respiratory syndrome coronavirus 2

TCRs:

T Cell Receptors

Th :

T helper lymphocyte

Tregs :

Regulatory T lymphocyte

WHO:

World health organization

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Acknowledgements

We are very grateful to anonymous bone marrow donors for their generosity and to anonymized COVID-19 patients. We are thankful to: Natale Imbesi and Valentina Arcati for technical assistance and Daniela Barone and Antonella Salvea for their bureaucratic assistance in submitting the research proposal to the Ethical committees.

Funding

This research was possible thanks to the fundraising campaign entitled “EMERGENZA DEL CORONAVIRUS (COVID-19)” by Mr Sal Da Vinci and Prof. Antonio Giordano Raccolta fondi di Sal Da Vinci: Sal Da Vinci e SbarroInstitute contro #CORONAVIRUS (gofundme.com).

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Authors and Affiliations

  1. Unit of Medical Oncology, Grand Metropolitan Hospital ‘Bianchi Melacrino Morelli’, I-89124, Reggio Calabria, Italy

    Pierpaolo Correale

  2. Research Unit of AGENAS, Italian National Agency for Regional Healthcare Services, Rome, Italy

    Giovanni Baglio

  3. Unit of Respiratory Infectious Diseases, “Azienda Ospedaliera Specialistica Dei Colli”, Naples, Italy

    Roberto Parrella & Francesco Scarano

  4. Link Campus University, Rome, Italy

    Roberto Parrella

  5. Tissue Typing Unit Grand Metropolitan Hospital ‘Bianchi Melacrino Morelli’, 89124, Reggio Calabria, Italy

    Rita Emilena Saladino, Marina Francone & Maria Cuzzola

  6. Unit of Microbiology and Virology “Azienda Ospedaliera Specialistica Dei Colli”, Naples, Italy

    Nunzia Cuomo

  7. Unit of Infectious Diseases, Grand Metropolitan Hospital ‘Bianchi Melacrino Morelli’, 89124, Reggio Calabria, Italy

    Giuseppe Foti

  8. Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, BioLife Science Bldg. Suite 333, 1900 North 12th Street, Philadelphia, PA, 19122, USA

    Luciano Mutti & Antonio Giordano

  9. Department of Applied Sciences and Biotechnology, Università Dell’Aquila, L’Aquila, Italy

    Luciano Mutti

  10. Department of Medicine and Surgery, LUM University, S.S. 100 Km. 18, 70010, Casamassima, BA, Italy

    Francesca Pentimalli

  11. Department of Medical Biotechnologies, University of Siena, Siena, Italy

    Antonio Giordano

Authors
  1. Pierpaolo Correale
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  2. Giovanni Baglio
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  3. Roberto Parrella
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  4. Rita Emilena Saladino
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  6. Francesco Scarano
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  7. Marina Francone
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  8. Maria Cuzzola
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  9. Giuseppe Foti
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  11. Francesca Pentimalli
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  12. Antonio Giordano
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Contributions

PC conceived and planned the study with FP, GB, RES, RP, LM, AG; RES and GB collected HLA and COVID-19 data, respectively; GF selected Calabria patients; RES, MF, MC collected patients specimens and data and performed HLA typing on the whole cohort samples; RP, FS selected Campania patients and collected patients specimens and data; NC extracted DNA from Campania patients’ specimens; GB performed the statistical analysis; PC, FP, GB, RES analyzed the data; AG acquired funding and supervised the study; PC, wrote the first manuscript draft; FP, GB, RES contributed to manuscript writing and editing; all authors revised the final manuscript.

Corresponding authors

Correspondence to Francesca Pentimalli or Antonio Giordano.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the local ethical committee of both participating institutions: Azienda Ospedaliera Specialistica dei Colli, Cotugno Hospital, Naples, Campania and the Grand Metropolitan Hospital 'Bianchi Melacrino Morelli', GOM of Reggio Calabria, Calabria (Protocol NA, number eudract NA, Date of approval by south etic local committee 10/02/2021; GOM deliberation n. 634, 29/09/2021.

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The authors declare that they have no conflict of interest.

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Correale, P., Baglio, G., Parrella, R. et al. A rapid ecologic analysis, confirmed by a case–control study, identifies class I HLA alleles correlated to the risk of COVID-19. J Transl Med 23, 303 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12967-025-06285-w

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Journal of Translational Medicine

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