HLA-II immunopeptidome profiling and deep learning reveal features of antigenicity to inform antigen discovery.

CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on antigen-presenting cells. Underrepresentation of diverse alleles in ligand databases and an incomplete understanding of factors affecting antigen presentation in vivo have limited progress in defining principles of peptide immunogenicity. Here, we employed monoallelic immunopeptidomics to identify 358,024 HLA-II binders, with a particular focus on HLA-DQ and HLA-DP. We uncovered peptide-binding patterns across a spectrum of binding affinities and enrichment of structural antigen features. These aspects underpinned the development of context-aware predictor of T cell antigens (CAPTAn), a deep learning model that predicts peptide antigens based on their affinity to HLA-II and full sequence of their source proteins. CAPTAn was instrumental in discovering prevalent T cell epitopes from bacteria in the human microbiome and a pan-variant epitope from SARS-CoV-2. Together CAPTAn and associated datasets present a resource for antigen discovery and the unraveling genetic associations of HLA alleles with immunopathologies.

Living Donor Liver transplantation in an alloimmunised patient: Immunological challenges and Management in Indian Settings.

Liver transplantation (LT) is often associated with hematological abnormalities with immune or non-immune etiologies and require timely diagnosis and interventions. We report a case of a patient suffering from non-alcoholic steato-hepatitis (NASH) related end stage liver disease (ESLD) with multiple red cell antibodies who underwent LT surgery. In postoperative phase, she developed immune hemolysis as well as acute antibody mediated rejection (AMR) which was managed with therapeutic plasma exchange and IVIG. The case highlights the need to develop an algorithm for red cell and HLA antibody screening in high-risk patients for timely detection and management.

HLA Variation and SARS-CoV-2 Specific Antibody Response.

Differences in SARS-CoV-2-specific immune responses have been observed between individuals following natural infection or vaccination. In addition to already known factors, such as age, sex, COVID-19 severity, comorbidity, vaccination status, hybrid immunity, and duration of infection, inter-individual variations in SARS-CoV-2 immune responses may, in part, be explained by structural differences brought about by genetic variation in the human leukocyte antigen (HLA) molecules responsible for the presentation of SARS-CoV-2 antigens to T effector cells. While dendritic cells present peptides with HLA class I molecules to CD8+ T cells to induce cytotoxic T lymphocyte responses (CTLs), they present peptides with HLA class II molecules to T follicular helper cells to induce B cell differentiation followed by memory B cell and plasma cell maturation. Plasma cells then produce SARS-CoV-2-specific antibodies. Here, we review published data linking HLA genetic variation or polymorphisms with differences in SARS-CoV-2-specific antibody responses. While there is evidence that heterogeneity in antibody response might be related to HLA variation, there are conflicting findings due in part to differences in study designs. We provide insight into why more research is needed in this area. Elucidating the genetic basis of variability in the SARS-CoV-2 immune response will help to optimize diagnostic tools and lead to the development of new vaccines and therapeutics against SARS-CoV-2 and other infectious diseases.

Targeted capture enrichment and sequencing identifies HLA variants associated with the severity of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is currently a global pandemic. The pathogenesis of severe COVID-19 has been widely investigated, but it is still unclear. Human leukocyte antigen (HLA) plays a central role in immune response, and its variants might be related to COVID-19 progression and severity. OBJECTIVE: To investigate the hypothesis that individual HLA variations could alter the course of COVID-19 and might be associated with the severity of COVID-19. METHODS: In this study, we conducted an HLA targeted capture enrichment and sequencing of severe COVID-19 patients matched to mild cases. A total of 16 COVID-19 patients, confirmed by SARS-CoV-2 viral RNA polymerase-chain-reaction (PCR) test and chest computed tomography (CT) scan, were enrolled in this study. The HLA targeted capture enrichment and sequencing were conducted. HLA typing was performed by comparing contigs with IPD-IMGT/HLA Database. RESULTS: In this study, 139 four-digit resolution HLA alleles were acquired. The results showed that HLA-DRB3*01:01 allele was significantly associated with the severity of COVID-19 (odds ratio [OR] = 27.64, 95% confidence interval [CI] = 1.35-560.50, P = 0.0064). And HLA-K*01:01 might be a potential risk factor for COVID-19 severity (OR = 0.11, 95% CI = 0.017-0.66, P = 0.019), but HLA-K*01:02 might be a protective factor (OR = 7.50, 95% CI = 1.48-37.92, P = 0.019). CONCLUSION: Three non-classical HLA alleles, including HLA-DRB3*01:01, HLA-K*01:01, HLA-K*01:02 were identified to be associated with the severity of COVID-19 by comparing mild and severe patients. The current findings would be helpful for exploring the influence of HLA gene polymorphisms on the development and severity of COVID-19.

First use of imlifidase desensitization in a highly sensitized lung transplant candidate: a case report.

Lung transplant candidates who are highly sensitized against human leucocyte antigen present an ongoing challenge with regards to finding immunologically acceptable donors. Desensitization strategies aimed at reducing preformed donor-specific antibodies have a number of limitations. Imlifidase, an IgG-degrading enzyme derived from Streptococcus pyogenes, is a novel agent that has been used to convert positive crossmatches to negative in kidney transplant candidates, allowing transplantation to occur. We present the first case of imlifidase use for antibody depletion in a highly sensitized lung transplant candidate who went on to undergo a successful bilateral lung transplant.

COVID-19 infection and vaccination rarely impact HLA antibody profile in waitlisted renal transplant candidates- a multicenter cohort.

Although rare, infection and vaccination can result in antibodies to human leukocyte antigens (HLA). We analyzed the effect of SARS-CoV-2 infection or vaccination on HLA antibodies in waitlisted renal transplant candidates. Specificities were collected and adjudicated if the calculated panel reactive antibodies (cPRA) changed after exposure. Of 409 patients, 285 (69.7 %) had an initial cPRA of 0 %, and 56 (13.7 %) had an initial cPRA > 80 %. The cPRA changed in 26 patients (6.4 %), 16 (3.9 %) increased, and 10 (2.4 %) decreased. Based on cPRA adjudication, cPRA differences generally resulted from a small number of specificities with subtle fluctuations around the borderline of the participating centers' cutoff for unacceptable antigen listing. All five COVID recovered patients with an increased cPRA were female (p = 0.02). In summary, exposure to this virus or vaccine does not increase HLA antibody specificities and their MFI in approximately 99 % of cases and 97 % of sensitized patients. These results have implications for virtual crossmatching at the time of organ offer after SARS-CoV-2 infection or vaccination, and these events of unclear clinical significance should not influence vaccination programs.

Anti-human leukocyte antigen and anti-ABO antibodies after SARS-CoV-2 mRNA vaccination in kidney transplant recipients.

INTRODUCTION: In this study, we evaluated whether SARS-CoV-2 mRNA vaccines induce anti-human leukocyte antigen (HLA) antibodies and anti- ABO blood type antibodies (ABOAb) in kidney transplant recipients (KTRs). METHODS: Sixty-three adult KTRs with functioning grafts who received two doses of the SARS-CoV-2 mRNA vaccine were enrolled in this cohort. Changes in anti-ABO blood type immunoglobulin IgM and IgG antibody titers, flow panel reactive antibody (PRA), de novo donor-specific anti-human leukocyte antigen antibodies (DSA), and kidney allograft function before and after vaccination were evaluated. RESULTS: Only one patient experienced conversion from negative to positive flow PRA after vaccination. However, there was no DSA in single antigen flow-bead assays. The mean fluorescence intensity (MFI) in the eight DSA-positive recipients did not significantly change before and after vaccination (p = .383), and no additional DSA was produced after vaccination in those patients. No significant elevation of ABOAb titer was observed for either IgM (p = .438) or IgG (p = .526) after vaccination. There was no significant deterioration in estimated glomerular filtration rate (eGFR) after vaccination (p = .877) or elevation of the urine protein-to-creatinine ratio (p = .209) after vaccination. One episode of AMR was observed in addition to a preexisting acute cellular rejection. CONCLUSIONS: The SARS-CoV-2 mRNA vaccine did not induce anti-HLA antibody or ABOAb production in KTRs.

Non-classical HLA class I molecules and their potential role in viral infections.

Human Leukocyte Antigens (HLA) are classified in three different classes I, II and III, and represent the key mediators of immune responses, self-tolerance development and pathogen recognition. Among them, non-classical subtypes (HLA-Ib), e.g. HLA-E and HLA-G, are characterize by tolerogenic functions that are often exploited by viruses to evade the host immune responses. In this perspective, we will review the main current data referred to HLA-G and HLA-E and viral infections, as well as the impact on immune response. Data were selected following eligibility criteria accordingly to the reviewed topic. We used a set of electronic databases (Medline/PubMed, Scopus, Web of Sciences (WOS), Cochrane library) for a systematic search until November 2022 using MeSH keywords/terms (i.e. HLA, HLA-G, HLA-E, viral infection, SARS-CoV-2, etc.…). Recent studies support the involvement of non-classical molecules, such as HLA-E and HLA-G, in the control of viral infection. On one side, viruses exploit HLA-G and HLA-E molecule to control host immune activation. On the other side, the expression of these molecules might control the inflammatory condition generated by viral infections. Hence, this review has the aim to summarize the state of art of literature about the modulation of these non-classical HLA-I molecules, to provide a general overview of the new strategies of viral immune system regulation to counteract immune defenses.

Association between PIRCHE-II scores and de novo allosensitization after reduction of immunosuppression during SARS-CoV-2 infection in kidney transplant recipients.

BACKGROUND: Before the availability of mRNA vaccines, many transplant centers chose to significantly reduce maintenance immunosuppression in kidney transplant recipients (KTRs) with SARS-CoV-2 infection. The extent to which this increases the risk of allosensitization is unclear. METHODS: In this observational cohort study, we analyzed 47 KTRs from March 2020 to February 2021 who underwent substantial reduction of maintenance immunosuppression during SARS-CoV-2 infection. KTRs were followed at 6 and 18 months concerning the development of de novo donor-specific anti-HLA (human leukocyte antigen) antibodies (DSA). The HLA-derived epitope mismatches were calculated using the predicted indirectly recognizable HLA-epitopes (PIRCHE-II) algorithm. RESULTS: In total, 14 of 47 KTRs (30%) developed de novo HLA antibodies after the reduction of maintenance immunosuppression. KTRs with higher total PIRCHE-II scores and higher PIRCHE-II scores for the HLA-DR locus were more likely to develop de novo HLA antibodies (p = .023, p = .009). Furthermore, 4 of the 47 KTRs (9%) developed de novo DSA after reduction of maintenance immunosuppression, which were exclusively directed against HLA-class II antigens and also showed higher PIRCHE-II scores for HLA-class II. The cumulative mean fluorescence intensity of 40 KTRs with preexisting anti-HLA antibodies and 13 KTRs with preexisting DSA at the time of SARS-CoV-2 infection remained stable after the reduction of maintenance immunosuppression (p = .141; p = .529). CONCLUSIONS: Our data show that the HLA-derived epitope mismatch load between donor and recipient influences the risk of de novo DSA development when immunosuppression is temporarily reduced. Our data further suggest that reduction in immunosuppression should be made more cautiously in KTRs with high PIRCHE-II scores for HLA-class II antigens.

Differences in Presentation of SARS-CoV-2 Omicron Strain Variant BA.1-BA.5 Peptides by HLA Molecules.

In this work, we analyzed the binding affinities of mutated peptides of Omicron strain variants BA.1-BA.5 and the worldwide prevalent HLA alleles. Bioinformatics analysis was conducted with the use of T-CoV web portal. We showed that, for all five viral variants, mutations cause a significant reduction in the number of tightly binding peptides for HLA-B*07:02 and HLA-C*01:02 molecules. At the same time, there were novel potential mutant epitopes (binding affinity less than 50 nM) in case of HLA-A*32:01 allele. Interestingly, mutations caused multidirectional effect on the binding affinities of the viral peptides and HLA-DRB1*03:01. Specifically, Spike protein mutations in the BA.1 variant caused more than 100-fold decrease in PINLVRDLPQGFSAL binding affinity, 10-fold decrease in affinity in the case of BA.2, BA.4, and BA.5 variants, and 30% increase in affinity for the BA.3 variant.

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown that immunotherapy based on non-classical HLA has essential applications in cancer, COVID-19, and allergic diseases. However, there are few deep learning methods to predict non-classical HLA alleles. In this work, an adaptive dual-attention network named DapNet-HLA is established based on existing datasets. Firstly, amino acid sequences are transformed into digital vectors by looking up the table. To overcome the feature sparsity problem caused by unique one-hot encoding, the fused word embedding method is used to map each amino acid to a low-dimensional word vector optimized with the training of the classifier. Then, we use the GCB (group convolution block), SENet attention (squeeze-and-excitation networks), BiLSTM (bidirectional long short-term memory network), and Bahdanau attention mechanism to construct the classifier. The use of SENet can make the weight of the effective feature map high, so that the model can be trained to achieve better results. Attention mechanism is an Encoder-Decoder model used to improve the effectiveness of RNN, LSTM or GRU (gated recurrent neural network). The ablation experiment shows that DapNet-HLA has the best adaptability for five datasets. On the five test datasets, the ACC index and MCC index of DapNet-HLA are 4.89% and 0.0933 higher than the comparison method, respectively. According to the ROC curve and PR curve verified by the 5-fold cross-validation, the AUC value of each fold has a slight fluctuation, which proves the robustness of the DapNet-HLA. The codes and datasets are accessible at https://github.com/JYY625/DapNet-HLA.

SARS-CoV-2 accessory proteins ORF7a and ORF3a use distinct mechanisms to down-regulate MHC-I surface expression.

Major histocompatibility complex class I (MHC-I) molecules, which are dimers of a glycosylated polymorphic transmembrane heavy chain and the small-protein ß2-microglobulin (ß2m), bind peptides in the endoplasmic reticulum that are generated by the cytosolic turnover of cellular proteins. In virus-infected cells, these peptides may include those derived from viral proteins. Peptide-MHC-I complexes then traffic through the secretory pathway and are displayed at the cell surface where those containing viral peptides can be detected by CD8+ T lymphocytes that kill infected cells. Many viruses enhance their in vivo survival by encoding genes that down-regulate MHC-I expression to avoid CD8+ T cell recognition. Here, we report that two accessory proteins encoded by SARS-CoV-2, the causative agent of the ongoing COVID-19 pandemic, down-regulate MHC-I expression using distinct mechanisms. First, ORF3a, a viroporin, reduces the global trafficking of proteins, including MHC-I, through the secretory pathway. The second, ORF7a, interacts specifically with the MHC-I heavy chain, acting as a molecular mimic of ß2m to inhibit its association. This slows the exit of properly assembled MHC-I molecules from the endoplasmic reticulum. We demonstrate that ORF7a reduces antigen presentation by the human MHC-I allele HLA-A*02:01. Thus, both ORF3a and ORF7a act post-translationally in the secretory pathway to lower surface MHC-I expression, with ORF7a exhibiting a specific mechanism that allows immune evasion by SARS-CoV-2.

The role of the HLA allelic repertoire on the clinical severity of COVID-19 in Canadians, living in the Saskatchewan province.

AIMS: The HLA system has been implicated as an underlying determinant for modulating the immune response to SARS-CoV-2. In this study, we aimed to determine the association of patients' HLA genetic profiles with the disease severity of COVID-19 infection. METHODS: Prospective study was conducted on COVID-19 patients (n = 40) admitted to hospitals in Saskatoon, Canada, between March and December 2020. Next-generation sequencing was performed on the patient samples to obtain high-resolution HLA typing profiles. The statistical association between HLA allelic frequency and disease severity was examined. The disease severity was categorized based on the length of hospital stay and intensive care needs or demise during the hospital stay. RESULTS: HLA allelic frequencies of the high and low-severity cohorts were normalized against corresponding background allelic frequencies. In the high-severity cohort, A*02:06 (11.8-fold), B*51:01 (2.4-fold), B*15:01(3.1-fold), C*01:02 (3.3-fold), DRB1*08:02 (31.2-fold), DQ*06:09 (11-fold), and DPB1*04:02(4-fold) were significantly overrepresented (p < 0.05) making these deleterious alleles. In the low-severity cohort, A*24:02 (2.8-fold), B*35:01 (2.8-fold), DRB1*04:07 (5.3-fold), and DRB1*08:11 (22-fold) were found to be significantly overrepresented (p < 0.05) making these protective alleles. These above alleles interact with NK cell antiviral activity via the killer immunoglobulin-like receptors (KIR). The high-severity cohort had a higher predilection for HLA alleles associated with KIR subgroups; Bw4-80I (1.1-fold), and C1 (1.6-fold) which promotes NK cell inhibition, while the low-severity cohort had a higher predilection for Bw4-80T (1.6-fold), and C2 (1.6-fold) which promote NK cell activation. CONCLUSION: In this study, the HLA allelic repository with the distribution of deleterious and protective alleles was found to correlate with the severity of the clinical course in COVID-19. Moreover, the interaction of specific HLA alleles with the KIR-associated subfamily modulates the NK cell-mediated surveillance of SARS-CoV-2. Both deleterious HLA alleles and inhibitory KIR appear prominently in the severe COVID-19 group focusing on the importance of NK cells in the convalescence of COVID-19.

Ancestral origins are associated with SARS-CoV-2 susceptibility and protection in a Florida patient population.

COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. The widespread clinical symptoms encompass a large group of asymptomatic COVID-19 patients, raising a crucial question regarding genetic susceptibility, e.g., whether individual differences in immunity play a role in patient symptomatology and how much human leukocyte antigen (HLA) contributes to this. To reveal genetic determinants of susceptibility to COVID-19 severity in the population and further explore potential immune-related factors, we performed a genome-wide association study on 284 confirmed COVID-19 patients (cases) and 95 healthy individuals (controls). We compared cases and controls of European (EUR) ancestry and African American (AFR) ancestry separately. We identified two loci on chromosomes 5q32 and 11p12, which reach the significance threshold of suggestive association (p<1x10-5 threshold adjusted for multiple trait testing) and are associated with the COVID-19 susceptibility in the European ancestry (index rs17448496: odds ratio[OR] = 0.173; 95% confidence interval[CI], 0.08-0.36 for G allele; p = 5.15× 10-5 and index rs768632395: OR = 0.166; 95% CI, 0.07-0.35 for A allele; p = 4.25×10-6, respectively), which were associated with two genes, PPP2R2B at 5q32, and LRRC4C at 11p12, respectively. To explore the linkage between HLA and COVID-19 severity, we applied fine-mapping analysis to dissect the HLA association with mild and severe cases. Using In-silico binding predictions to map the binding of risk/protective HLA to the viral structural proteins, we found the differential presentation of viral peptides in both ancestries. Lastly, extrapolation of the identified HLA from the cohort to the worldwide population revealed notable correlations. The study uncovers possible differences in susceptibility to COVID-19 in different ancestral origins in the genetic background, which may provide new insights into the pathogenesis and clinical treatment of the disease.

Improved predictions of antigen presentation and TCR recognition with MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8+ T-cell epitopes.

The recognition of pathogen or cancer-specific epitopes by CD8+ T cells is crucial for the clearance of infections and the response to cancer immunotherapy. This process requires epitopes to be presented on class I human leukocyte antigen (HLA-I) molecules and recognized by the T-cell receptor (TCR). Machine learning models capturing these two aspects of immune recognition are key to improve epitope predictions. Here, we assembled a high-quality dataset of naturally presented HLA-I ligands and experimentally verified neo-epitopes. We then integrated these data in a refined computational framework to predict antigen presentation (MixMHCpred2.2) and TCR recognition (PRIME2.0). The depth of our training data and the algorithmic developments resulted in improved predictions of HLA-I ligands and neo-epitopes. Prospectively applying our tools to SARS-CoV-2 proteins revealed several epitopes. TCR sequencing identified a monoclonal response in effector/memory CD8+ T cells against one of these epitopes and cross-reactivity with the homologous peptides from other coronaviruses.

A systemic review of T-cell epitopes defined from the proteome of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains in a global pandemic, and no eradicative therapy is currently available. Host T cells have been shown to play a crucial role in the antiviral immune protection and pathology in Coronavirus disease 2019 (COVID-19) patients; thus, identifying sufficient T-cell epitopes from the SARS-CoV-2 proteome can contribute greatly to the development of T-cell epitope vaccines and the precise evaluation of host SARS-CoV-2-specific cellular immunity. This review presents a comprehensive map of T-cell epitopes functionally validated from SARS-CoV-2 antigens, the human leukocyte antigen (HLA) supertypes to present these epitopes, and the strategies to screen and identify T-cell epitopes. To the best of our knowledge, a total of 1349 CD8+ T-cell epitopes and 790 CD4+ T-cell epitopes have been defined by functional experiments thus far, but most are presented by approximately twenty common HLA supertypes, such as HLA-A0201, A2402, B0702, DR15, DR7 and DR11 molecules, and 74-80% of the T-cell epitopes are derived from S protein and nonstructural protein. These data provide useful insight into the development of vaccines and specific T-cell detection systems. However, the currently defined T-cell epitope repertoire cannot cover the HLA polymorphism of major populations in an indicated geographic region. More research is needed to depict an overall landscape of T-cell epitopes, which covers the overall SARS-CoV-2 proteome and global patients.

Human genetic basis of severe or critical illness in COVID-19.

Coronavirus Disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable morbidity and mortality worldwide. The clinical manifestation of COVID-19 ranges from asymptomatic or mild infection to severe or critical illness, such as respiratory failure, multi-organ dysfunction or even death. Large-scale genetic association studies have indicated that genetic variations affecting SARS-CoV-2 receptors (angiotensin-converting enzymes, transmembrane serine protease-2) and immune components (Interferons, Interleukins, Toll-like receptors and Human leukocyte antigen) are critical host determinants related to the severity of COVID-19. Genetic background, such as 3p21.31 and 9q34.2 loci were also identified to influence outcomes of COVID-19. In this review, we aimed to summarize the current literature focusing on human genetic factors that may contribute to the observed diversified severity of COVID-19. Enhanced understanding of host genetic factors and viral interactions of SARS-CoV-2 could provide scientific bases for personalized preventive measures and precision medicine strategies.

A Mendelian randomization study of genetic predisposition to autoimmune diseases and COVID-19.

Autoimmune diseases and coronavirus disease 2019 (COVID-19) share many similarities. Concerns have arisen that autoimmune diseases may increase the susceptibility and severity of COVID-19. We used Mendelian randomization to investigate whether liability to autoimmune diseases is related to COVID-19 susceptibility and severity. Genetic instruments for 8 autoimmune diseases, including type 1 diabetes mellitus, rheumatoid arthritis, systemic lupus erythematosus, psoriasis, multiple sclerosis, primary sclerosing cholangitis, primary biliary cirrhosis and juvenile idiopathic arthritis, were obtained from published genome-wide association studies. Two-sample Mendelian randomization analyses of the associations of liability to each autoimmune disease with COVID-19 infection, hospitalized COVID-19, and very severe COVID-19 were performed using the latest publicly available genome-wide association study for COVID-19. Genetic liability to each of the autoimmune diseases was largely not associated with COVID-19 infection, hospitalized COVID-19, or very severe COVID-19 after accounting for multiple comparison. Sensitivity analysis excluding genetic variants in the human leukocyte antigen gene, which has an important role in the immune response, showed similar results. The autoimmune diseases examined were largely not genetically associated with the susceptibility or severity of COVID-19. Further investigations are warranted.

Distinct responses of newly identified monocyte subsets to advanced gastrointestinal cancer and COVID-19.

Monocytes are critical cells of the immune system but their role as effectors is relatively poorly understood, as they have long been considered only as precursors of tissue macrophages or dendritic cells. Moreover, it is known that this cell type is heterogeneous, but our understanding of this aspect is limited to the broad classification in classical/intermediate/non-classical monocytes, commonly based on their expression of only two markers, i.e. CD14 and CD16. We deeply dissected the heterogeneity of human circulating monocytes in healthy donors by transcriptomic analysis at single-cell level and identified 9 distinct monocyte populations characterized each by a profile suggestive of specialized functions. The classical monocyte subset in fact included five distinct populations, each enriched for transcriptomic gene sets related to either inflammatory, neutrophil-like, interferon-related, and platelet-related pathways. Non-classical monocytes included two distinct populations, one of which marked specifically by elevated expression levels of complement components. Intermediate monocytes were not further divided in our analysis and were characterized by high levels of human leukocyte antigen (HLA) genes. Finally, we identified one cluster included in both classical and non-classical monocytes, characterized by a strong cytotoxic signature. These findings provided the rationale to exploit the relevance of newly identified monocyte populations in disease evolution. A machine learning approach was developed and applied to two single-cell transcriptome public datasets, from gastrointestinal cancer and Coronavirus disease 2019 (COVID-19) patients. The dissection of these datasets through our classification revealed that patients with advanced cancers showed a selective increase in monocytes enriched in platelet-related pathways. Of note, the signature associated with this population correlated with worse prognosis in gastric cancer patients. Conversely, after immunotherapy, the most activated population was composed of interferon-related monocytes, consistent with an upregulation in interferon-related genes in responder patients compared to non-responders. In COVID-19 patients we confirmed a global activated phenotype of the entire monocyte compartment, but our classification revealed that only cytotoxic monocytes are expanded during the disease progression. Collectively, this study unravels an unexpected complexity among human circulating monocytes and highlights the existence of specialized populations differently engaged depending on the pathological context.

In-silico study of influence of HLA heterogeneity on CTL responses across ethnicities to SARS-CoV-2.

Differences in outcome to COVID-19 infection in different individuals is largely attributed to genetic heterogeneity leading to differential immune responses across individuals and populations. HLA is one such genetic factor that varies across individuals leading to differences in how T-cell responses are triggered against SARS-CoV-2, directly influencing disease susceptibility. HLA alleles that influence COVID-19 outcome, by virtue of epitope binding and presentation, have been identified in cohorts worldwide. However, the heterogeneity in HLA distribution across ethnic groups limits the generality of such association. In this study, we address this limitation by comparing the recognition of CTL epitopes across HLA genotypes and ethnic groups. Using HLA allele frequency data for ethnic groups from Allele Frequency Net Database (AFND), we construct synthetic populations for each ethnic group and show that CTL epitope strength varies across HLA genotypes and populations. We also observe that HLA genotypes, in certain cases, can have high CTL epitope strengths in the absence of top-responsive HLA alleles. Finally, we show that the theoretical estimate of responsiveness and hence protection offered by a HLA allele is bound to vary across ethnic groups, due to the influence of other HLA alleles within the HLA genotype on CTL epitope recognition. This emphasizes the need for studying HLA-disease associations at the genotype level rather than at a single allele level.