Determination of HLA-A, -B, -C, -DRB1 and -DQB1 allele and haplotype frequencies in heart failure patients

Construction and evaluation of immune-related diagnostic model in patients with heart failure caused by idiopathic dilated cardiomyopathy

OBJECTIVE

The purpose of the study was to construct the potential diagnostic model of immune-related genes during the development of heart failure caused by idiopathic dilated cardiomyopathy.

METHOD

GSE5406 and GSE57338 were downloaded from the GEO website ( https://www.ncbi.nlm.nih.gov/geo/ ). CIBERSORT was used for the evaluation of immune infiltration in idiopathic dilated cardiomyopathy (DCM) of GSE5406. Differently expressed genes were calculated by the limma R package and visualized by the volcano plot. The immune-related genes were downloaded from Immport, TISIDB, and InnateDB. Then the immune-related differential genes (IRDGs) were acquired from the intersection. Protein-protein interaction network (PPI) and Cytoscape were used to visualize the hub genes. Three machine learning methods such as random forest, logical regression, and elastic network regression model were adopted to construct the prediction model. The diagnostic value was also validated in GSE57338.

RESULTS

Our study demonstrated the obvious different ratio of T cell CD4 memory activated, T cell regulatory Tregs, and neutrophils between DCM and control donors. As many as 2139 differential genes and 274 immune-related different genes were identified. These genes were mainly enriched in lipid and atherosclerosis, human cytomegalovirus infection, and cytokine-cytokine receptor interaction. At the same time, as many as fifteen hub genes were identified as the IRDGs (IFITM3, IFITM2, IFITM1, IFIT3, IFIT1, HLA-A, HLA-B, HLA-C, ADAR, STAT1, SAMHD1, RSAD2, MX1, ISG20, IRF2). Moreover, we also discovered that the elastic network and logistic regression models had a higher diagnostic value than that of random forest models based on these hub genes.

CONCLUSION

Our study demonstrated the pivotal role of immune function during the development of heart failure caused by DCM. This study may offer new opportunities for the detection and intervention of immune-related DCM.

Expanding the MAPPs Assay to Accommodate MHC-II Pan Receptors for Improved Predictability of Potential T Cell Epitopes

A critical step in the immunogenicity cascade is attributed to human leukocyte antigen (HLA) II presentation triggering T cell immune responses. The liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based major histocompatibility complex (MHC) II-associated peptide proteomics (MAPPs) assay is implemented during preclinical risk assessments to identify biotherapeutic-derived T cell epitopes. Although studies indicate that HLA-DP and HLA-DQ alleles are linked to immunogenicity, most MAPPs studies are restricted to using HLA-DR as the dominant HLA II genotype due to the lack of well-characterized immunoprecipitating antibodies. Here, we address this issue by testing various commercially available clones of MHC-II pan (CR3/43, WR18, and Tü39), HLA-DP (B7/21), and HLA-DQ (SPV-L3 and 1a3) antibodies in the MAPPs assay, and characterizing identified peptides according to binding specificity. Our results reveal that HLA II receptor-precipitating reagents with similar reported specificities differ based on clonality and that MHC-II pan antibodies do not entirely exhibit pan-specific tendencies. Since no individual antibody clone is able to recover the complete HLA II peptide repertoire, we recommend a mixed strategy of clones L243, WR18, and SPV-L3 in a single immunoprecipitation step for more robust compound-specific peptide detection. Ultimately, our optimized MAPPs strategy improves the predictability and additional identification of T cell epitopes in immunogenicity risk assessments.

CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding.

METHODS

The SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed.

RESULTS

By using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs.

CONCLUSIONS

IGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.

High-risk genotypes for type 1 diabetes are associated with the imbalance of gut microbiome and serum metabolites

Background

The profile of gut microbiota, serum metabolites, and lipids of type 1 diabetes (T1D) patients with different human leukocyte antigen (HLA) genotypes remains unknown. We aimed to explore gut microbiota, serum metabolites, and lipids signatures in individuals with T1D typed by HLA genotypes.

Methods

We did a cross-sectional study that included 73 T1D adult patients. Patients were categorized into two groups according to the HLA haplotypes they carried: those with any two of three susceptibility haplotypes (DR3, DR4, DR9) and without any of the protective haplotypes (DR8, DR11, DR12, DR15, DR16) were defined as high-risk HLA genotypes group (HR, n=30); those with just one or without susceptibility haplotypes as the non-high-risk HLA genotypes group (NHR, n=43). We characterized the gut microbiome profile with 16S rRNA gene amplicon sequencing and analyzed serum metabolites with liquid chromatography-mass spectrometry.

Results

Study individuals were 32.5 (8.18) years old, and 60.3% were female. Compared to NHR, the gut microbiota of HR patients were characterized by elevated abundances of Prevotella copri and lowered abundances of Parabacteroides distasonis. Differential serum metabolites (hypoxanthine, inosine, and guanine) which increased in HR were involved in purine metabolism. Different lipids, phosphatidylcholines and phosphatidylethanolamines, decreased in HR group. Notably, Parabacteroides distasonis was negatively associated (p ≤ 0.01) with hypoxanthine involved in purine metabolic pathways.

Conclusions

The present findings enabled a better understanding of the changes in gut microbiome and serum metabolome in T1D patients with HLA risk genotypes. Alterations of the gut microbiota and serum metabolites may provide some information for distinguishing T1D patients with different HLA risk genotypes.

HLA-DRB1∗16:01 and HLA-DQB1∗05:02 Alleles Influence the Susceptibility and Progression of Cutaneous Malignant Melanoma

Background

The influence of HLA class I and II loci on the susceptibility to melanoma remains an area of intense debate. This study aimed to examine whether the HLA system was related to melanoma susceptibility and prognosis in a southern Spanish population.

Methods

In this study, HLA class I and class II genotyping were performed using polymerase chain reaction sequence-specific oligonucleotides (PCR-SSO) in 237 Spanish melanoma patients and 636 ethnically matched controls. Data were analyzed according to the clinical characteristics of the defined subgroups.

Results

Compared to the control group, DRB1∗16:01 (4% vs. 1.3%, p=0.001, Pc = 0.035, OR = 3.28) and DQB1∗05:02 (4.9% vs. 2%, p=0.001, Pc = 0.017, OR = 2.54) were positivity associated with the susceptibility to melanoma. Both DRB1∗16:01 (5.4% vs. 1.3%, p=0.001, Pc = 0.035, OR = 4.46) and DQB1∗05:02 (6.5% vs. 2%, p=0.001, Pc = 0.017, OR = 3.44) also showed a positive correlation with Breslow thickness >1.5 mm, most notably at an early age of diagnosis (≤58 years), DRB1∗16:01 (4.2% vs. 1.3%, p=0.001, Pc = 0.035, OR = 3.41) and DQB1∗05:02 (5.4% vs. 2%, p=0.002, Pc = 0.034, OR = 2.86).

Conclusion

These findings established HLA-DRB1∗16:01 and HLA-DQB1∗05:02 loci as melanoma risk factors in the southern Spanish population.

Bioinformatic HLA Studies in the Context of SARS-CoV-2 Pandemic and Review on Association of HLA Alleles with Preexisting Medical Conditions

After the announcement of a new coronavirus in China in December 2019, which was then called SARS-CoV-2, this virus changed to a global concern and it was then declared as a pandemic by WHO. Human leukocyte antigen (HLA) alleles, which are one of the most polymorphic genes, play a pivotal role in both resistance and vulnerability of the body against viruses and other infections as well as chronic diseases. The association between HLA alleles and preexisting medical conditions such as cardiovascular diseases and diabetes mellitus is reported in various studies. In this review, we focused on the bioinformatic HLA studies to summarize the HLA alleles which responded to SARS-CoV-2 peptides and have been used to design vaccines. We also reviewed HLA alleles that are associated with comorbidities and might be related to the high mortality rate among COVID-19 patients. Since both genes and patients' medical conditions play a key role in both severity of the disease and the mortality rate in COVID-19 patients, a better understanding of the connection between HLA alleles and SARS-CoV-2 can provide a wider perspective on the behavior of the virus. Such understanding can help scientists, especially in terms of protecting healthcare workers and designing effective vaccines.

Evaluation of the Spanish population coverage of a prospective HLA haplobank of induced pluripotent stem cells

Background

iPSC (induced pluripotent stem cells) banks of iPSC lines with homozygous HLA (human leukocyte antigen) haplotypes (haplobanks) are proposed as an affordable and off-the-shelf approach to allogeneic transplantation of iPSC derived cell therapies. Cord blood banks offer an extensive source of HLA-typed cells suitable for reprogramming to iPSC. Several initiatives worldwide have been undertaken to create national and international iPSC haplobanks that match a significant part of a population.

Methods

To create an iPSC haplobank that serves the Spanish population (IPS-PANIA), we have searched the Spanish Bone Marrow Donor Registry (REDMO) to identify the most frequently estimated haplotypes. From the top ten donors identified, we estimated the population coverage using the criteria of zero mismatches in HLA-A, HLA-B, and HLA-DRB1 with different stringencies: high resolution, low resolution, and beneficial mismatch.

Results

We have calculated that ten cord blood units from homozygous donors stored at the Spanish cord blood banks can provide HLA-A, HLA-B, and HLA-DRB1 matching for 28.23% of the population.

Conclusion

We confirm the feasibility of using banked cord blood units to create an iPSC haplobank that will cover a significant percentage of the Spanish and international population for future advanced therapy replacement strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-021-02301-0.

Investigation of hub genes and immune status in heart transplant rejection using endomyocardial biopsies

T cell‒mediated rejection (TCMR) and antibody‐mediated rejection (ABMR) are severe post‐transplantation complications for heart transplantation (HTx), whose molecular and immunological pathogenesis remains unclear. In the present study, the mRNA microarray data set GSE124897 containing 645 stable, 52 TCMR and 144 ABMR endomyocardial biopsies was obtained to screen for differentially expressed genes (DEGs) between rejected and stable HTx samples and to investigate immune cell infiltration. Functional enrichment analyses indicated roles of the DEGs primarily in immune‐related mechanisms. Protein‐protein interaction networks were then constructed, and ICAM1, CD44, HLA‐A and HLA‐B were identified as hub genes using the maximal clique centrality method. Immune cell infiltration analysis revealed differences in adaptive and innate immune cell populations between TCMR, ABMR and stable HTx samples. Additionally, hub gene expression levels significantly correlated with the degree and composition of immune cell infiltration in HTx rejection samples. Furthermore, drug‐gene interactions were constructed, and 12 FDA‐approved drugs were predicted to target hub genes. Finally, an external GSE2596 data set was used to validate the expression of the hub genes, and ROC curves indicated all four hub genes had promising diagnostic value for HTx rejection. This study provides a comprehensive perspective of molecular and immunological regulatory mechanisms underlying HTx rejection.

Determination of HLA-A, -B, -C, -DRB1 and -DQB1 allele and haplotype frequencies in heart failure patients

Aims

Cell therapy can be used to repair functionally impaired organs and tissues in humans. Although autologous cells have an immunological advantage, it is difficult to obtain high cell numbers for therapy. Well‐characterized banks of cells with human leukocyte antigens (HLA) that are representative of a given population are thus needed. The present study investigates the HLA allele and haplotype frequencies in a cohort of heart failure (HF) patients.

Methods and results

We carried out the HLA typing and the allele and haplotype frequency analysis in 247 ambulatory HF patients. We determined HLA class I (A, B, and C) and class II (DRB1 and DQB1) using next‐generation sequencing technology. The allele frequencies were obtained using Python for Population Genomics (PyPop) software, and HLA haplotypes were estimated using HaploStats. A total of 30 HLA‐A, 56 HLA‐B, 23 HLA‐C, 36 HLA‐DRB1, and 15 HLA‐DQB1 distinct alleles were identified within the studied cohort. The genotype frequencies of all five HLA loci were in Hardy–Weinberg equilibrium. We detected differences in HLA allele frequencies among patients when the etiological cause of HF was considered. There were a total of 494 five‐loci haplotypes, five of which were present six or more times. Moreover, the most common estimated HLA haplotype was HLA‐A*01:01, HLA‐B*08:01, HLA‐C*07:01, HLA‐DRB1*03:01, and HLA‐DQB1*02:01 (6.07% haplotype frequency per patient). Remarkably, the 11 most frequent haplotypes would cover 31.17% of the patients of the cohort in need of allogeneic cell therapy.

Conclusions

Our findings could be useful for improving allogeneic cell administration outcomes without concomitant immunosuppression.