Combined effect of glutamine at position 70 of HLA-DRB1 and alanine at position 57 of HLA-DQB1 in type 1 diabetes: An epitope analysis

The Causal Relationship between Immune-Mediated Inflammatory Diseases and Aortic Aneurysm: A Bidirectional Two-Sample Mendelian Randomization Study

Methods

We sourced genetic association data from public genome-wide association study databases for populations of European ancestry. Adhering to MR principles, we identified valid instrumental variables from genetic variants. A range of statistical methods were applied for MR analysis, with the inverse variance weighted (IVW) method emerging as the most reliable estimator of causality in this context.

Results

The causal estimates obtained using the IVW method revealed a significant association between genetically predicted AA and rheumatoid arthritis (RA; OR = 1.06, 95% CI = 1.01-1.12, P=0.029). Conversely, genetically predicted RA showed nonsignificant causal estimates of AA (OR = 0.97, 95% CI = 0.92-1.02, P=0.204). Additionally, there was no evidence to suggest that AA may increase the risk of inflammatory bowel disease (IBD), Crohn's disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and psoriasis (PSO). The sensitivity analysis confirmed the absence of heterogeneity or horizontal pleiotropy effects.

Conclusion

Our findings shed light on the causal effects between genetically predisposed AA and RA. They also suggest the potential clinical utility of human leukocyte antigen (HLA) risk genetic markers for developing personalized treatment and prevention strategies.

Fifty years of HLA-associated type 1 diabetes risk: history, current knowledge, and future directions

More than 50 years have elapsed since the association of human leukocyte antigens (HLA) with type 1 diabetes (T1D) was first reported. Since then, methods for identification of HLA have progressed from cell based to DNA based, and the number of recognized HLA variants has grown from a few to tens of thousands. Current genotyping methodology allows for exact identification of all HLA-encoding genes in an individual's genome, with statistical analysis methods evolving to digest the enormous amount of data that can be produced at an astonishing rate. The HLA region of the genome has been repeatedly shown to be the most important genetic risk factor for T1D, and the original reported associations have been replicated, refined, and expanded. Even with the remarkable progress through 50 years and over 5,000 reports, a comprehensive understanding of all effects of HLA on T1D remains elusive. This report represents a summary of the field as it evolved and as it stands now, enumerating many past and present challenges, and suggests possible paradigm shifts for moving forward with future studies in hopes of finally understanding all the ways in which HLA influences the pathophysiology of T1D.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Association between alleles, haplotypes, and amino acid variations in HLA class II genes and type 1 diabetes in Kuwaiti children

Type 1 diabetes (T1D) is a complex autoimmune disorder that is highly prevalent globally. The interactions between genetic and environmental factors may trigger T1D in susceptible individuals. HLA genes play a significant role in T1D pathogenesis, and specific haplotypes are associated with an increased risk of developing the disease. Identifying risk haplotypes can greatly improve the genetic scoring for early diagnosis of T1D in difficult to rank subgroups. This study employed next-generation sequencing to evaluate the association between HLA class II alleles, haplotypes, and amino acids and T1D, by recruiting 95 children with T1D and 150 controls in the Kuwaiti population. Significant associations were identified for alleles at the HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci, including DRB1*03:01:01, DQA1*05:01:01, and DQB1*02:01:01, which conferred high risk, and DRB1*11:04:01, DQA1*05:05:01, and DQB1*03:01:01, which were protective. The DRB1*03:01:01~DQA1*05:01:01~DQB1*02:01:01 haplotype was most strongly associated with the risk of developing T1D, while DRB1*11:04-DQA1*05:05-DQB1*03:01 was the only haplotype that rendered protection against T1D. We also identified 66 amino acid positions across the HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes that were significantly associated with T1D, including novel associations. These results validate and extend our knowledge on the associations between HLA genes and T1D in Kuwaiti children. The identified risk alleles, haplotypes, and amino acid variations may influence disease development through effects on HLA structure and function and may allow early intervention via population-based screening efforts.

Common Risk Variants in AHI1 Are Associated With Childhood Steroid Sensitive Nephrotic Syndrome

Introduction

Steroid-sensitive nephrotic syndrome (SSNS) is the most common form of kidney disease in children worldwide. Genome-wide association studies (GWAS) have demonstrated the association of SSNS with genetic variation at HLA-DQ/DR and have identified several non-HLA loci that aid in further understanding of disease pathophysiology. We sought to identify additional genetic loci associated with SSNS in children of Sri Lankan and European ancestry.

Methods

We conducted a GWAS in a cohort of Sri Lankan individuals comprising 420 pediatric patients with SSNS and 2339 genetic ancestry matched controls obtained from the UK Biobank. We then performed a transethnic meta-analysis with a previously reported European cohort of 422 pediatric patients and 5642 controls.

Results

Our GWAS confirmed the previously reported association of SSNS with HLA-DR/DQ (rs9271602, P = 1.12 × 10-27, odds ratio [OR] = 2.75). Transethnic meta-analysis replicated these findings and identified a novel association at AHI1 (rs2746432, P = 2.79 × 10-8, OR = 1.37), which was also replicated in an independent South Asian cohort. AHI1 is implicated in ciliary protein transport and immune dysregulation, with rare variation in this gene contributing to Joubert syndrome type 3.

Conclusions

Common variation in AHI1 confers risk of the development of SSNS in both Sri Lankan and European populations. The association with common variation in AHI1 further supports the role of immune dysregulation in the pathogenesis of SSNS and demonstrates that variation across the allele frequency spectrum in a gene can contribute to disparate monogenic and polygenic diseases.

Development of antidrug antibodies against adalimumab maps to variation within the HLA-DR peptide-binding groove

Targeted biologic therapies can elicit an undesirable host immune response characterized by the development of antidrug antibodies (ADA), an important cause of treatment failure. The most widely used biologic across immune-mediated diseases is adalimumab, a tumor necrosis factor inhibitor. This study aimed to identify genetic variants that contribute to the development of ADA against adalimumab, thereby influencing treatment failure. In patients with psoriasis on their first course of adalimumab, in whom serum ADA had been evaluated 6-36 months after starting treatment, we observed a genome-wide association with ADA against adalimumab within the major histocompatibility complex (MHC). The association signal mapped to the presence of tryptophan at position 9 and lysine at position 71 of the HLA-DR peptide-binding groove, with both residues conferring protection against ADA. Underscoring their clinical relevance, these residues were also protective against treatment failure. Our findings highlight antigenic peptide presentation via MHC class II as a critical mechanism in the development of ADA against biologic therapies and downstream treatment response.

DR4/DQ2 haplotype confers susceptibility to T1DM with early clinical disease onset: A retrospective analysis in a tertiary-care hospital in Italy

INTRODUCTION

T1DM is the most frequent form of diabetes in children. It has a multifactorial pathogenesis in which genetic, environmental and immunological factors are involved. Among genetic explanations a major role is attributed to second class HLA genes, with the greatest risk associated with the simultaneous presence of the haplotypes DR3DQ2 and DR4DQ8. Based on results obtained in other countries, the aim of this research is to verify a possible association between the haplotype DRB1 * 04: 05-DQA1 * 03-DQB1 * 02 and the onset of T1DM among Italian children with possible genotype-phenotype correlations. Greater knowledge of genes which increase or decrease susceptibility is important for genome analysis.

MATERIALS AND METHODS

165 patients with type 1 diabetes treated at the Diabetology Unit of the Meyer Children's University Hospital, were clinically analyzed. Data relating to age at diagnosis, pancreatic anti-beta cell autoimmunity, comorbidities with date of diagnosis and family history were retrospectively collected from medical data. A case-control study was conducted to investigate the HLA types of the patients compared to a control group of 819 Tuscan donors enrolled in the National Bone Marrow Donor Register. Typing was carried out using the Eurospital "DIABEGEN" kit, currently in use at the immunology laboratory of the Meyer Children's University Hospital.

RESULTS

Mean age at diagnosis was 9.3 years; most children (97%) had anti-pancreatic beta cell autoimmunity; the anti-insulin antibody (IAA) was more frequent among children with early clinical disease onset (0-5 years of age). From the case control comparison performed on HLA typing, it emerged that the greatest risk for the development of type 1 diabetes is conferred by the haplotypes DR3DQ2 and DR4DQ8, but in addition to these haplotypes, already known in other countries, we identified another haplotype, DR4DQ2 (DRB1 * 04: 05-DQA1 * 03-DQB1 * 02) which appears to predispose children to type 1 diabetes (p value 2.80E-08) and it is associated with early clinical disease onset (p-value = 0.002).

CONCLUSIONS

We report a new haplotype which increases susceptibility to type 1 diabetes among Italian children and which is associated with early clinical disease onset. Given the central role attributed to genetic factors in the pathogenesis of T1DM and to the II class HLA genes, this new haplotype ought to be recognized as a risk factor and included in tests routinely carried out to identify patients with a genetic predisposition to type I diabetes in Italy. These findings could have practical implications in research and prevention programs.

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes by using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA-DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top 10 DEGs. These genes were enriched in aerobic respiration, T-cell antigen receptor pathway, tricarboxylic acid metabolic process, vitamin D receptor pathway, toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for machine learning (ML) analysis. The decision tree, extra-tree regressor and random forest algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. Machine learning algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes.

HLA-DRB1: A new potential prognostic factor and therapeutic target of cutaneous melanoma and an indicator of tumor microenvironment remodeling

Cutaneous melanoma (CM) is the most common skin cancer and one of the most aggressive cancers and its incidence has risen dramatically over the past few decades. The tumor microenvironment (TME) plays a crucial role in the occurrence and development of cutaneous melanoma. Nevertheless, the dynamics modulation of the immune and stromal components in the TME is not fully understood. In this study, 471 CM samples were obtained from TCGA database, and the ratio of tumor-infiltrating immune cells (TICs) in the TME were estimated using the ESTIMATE algorithms and CIBERSORT computational method. The differently expressed genes (DEGs) were applied to GO and KEGG function enrichment analysis, establishment of protein-protein interaction (PPI) network and univariate Cox regression analysis. Subsequently, we identified a predictive factor: HLA-DRB1 (major histocompatibility complex, class II, DR beta 1) by the intersection analysis of the hub genes of PPI network and the genes associated with the prognosis of the CM patients obtained by univariate Cox regression analysis. Correlation analysis and survival analysis showed that the expression level of HLA-DRB1 was negatively correlated with the Stage of the patients while positively correlated with the survival, prognosis and TME of melanoma. The GEPIA web server and the representative immunohistochemical images of HLA-DRB1 in the normal skin tissue and melanoma tissue from the Human Protein Atlas (HPA) database were applied to validate the expression level of HLA-DRB1. CIBERSORT analysis for the ratio of TICs indicated that 9 types of TICs were positively correlated with the expression level of HLA-DRB1 and only 4 types of TICs were negatively correlated with the expression level of HLA-DRB1. These results suggested that the expression level of HLA-DRB1 may be related to the immune activity of the TME and may affect the prognosis of CM patients by changing the status of the TME.

Association Between BoLA-DRB3.2 Polymorphism and Bovine Papillomavirus Infection for Bladder Tumor Risk in Podolica Cattle

Blood samples from 260 unrelated cattle (132 animals affected by papillomavirus-associated bladder tumors and 128 healthy) were genotyped using the classic polymerase chain reaction/restriction fragment length polymorphism method to screen MHC class II bovine leukocyte antigen-DRB3. 2 polymorphism. The DRB3^*22 allele was significantly (p ≤ 0.01) detected in healthy cattle, thus appearing to have a negative association (protective effect) with virus infection of the urinary bladder known to represent a bladder tumor risk for cattle living free at pasture. Considering the two sequence alleles identified in animals carrying DRB3^*22, DRB3^*011:01 allele from samples of animals harboring the unexpressed bovine papillomaviruses (BPV)-2 E5 gene was characterized by amino acid residues believed to have a protective effect against BPV infection such as arginine at position 71 (R⁷¹) in pocket 4, histidine at position 11 (H¹¹) in pocket 6, and both glutamine at position 9 (Q⁹) and serine at position 57 (S⁵⁷) in pocket 9 of the antigen-binding groove. The DRB3^*011:02v allele from affected animals was characterized by amino acids believed to be susceptibility residues such as lysine (K⁷¹), tyrosine (Y¹¹), glutamic acid (E⁹), and aspartic acid (D⁵⁷) in these pockets. These results suggest that animals harboring the DRB3^*011:01 allele may have a lower risk of BPV infection and, consequently, a reduced risk of bladder tumors.

Critical Amino Acid Variants in HLA-DRB1 and -DQB1 Allotypes in the Development of Classical Type 1 Diabetes and Latent Autoimmune Diabetes in Adults in the Japanese Population

The effects of amino acid variants encoded by the human leukocyte antigen (HLA) class II on the development of classical type 1 diabetes (T1D) and latent autoimmune diabetes in adults (LADA) have not been fully elucidated. We retrospectively investigated the HLA-DRB1 and -DQB1 genes of 72 patients with classical T1D and 102 patients with LADA in the Japanese population and compared the frequencies of HLA-DRB1 and -DQB1 alleles between these patients and the Japanese populations previously reported by another institution. We also performed a blind association analysis with all amino acid positions in classical T1D and LADA, and compared the associations of HLA-DRB1 and -DQB1 amino acid positions in classical T1D and LADA. The frequency of DRß-Phe-13 was significantly higher and those of DRß-Arg-13 and DQß-Gly-70 were significantly lower in patients with classical T1D and LADA than in controls. The frequencies of DRß-His-13 and DQß-Glu-70 were significantly higher in classical T1D patients than in controls. The frequency of DRß-Ser-13 was significantly lower and that of DQß-Arg-70 was significantly higher in LADA patients than in controls. HLA-DRß1 position 13 and HLA-DQß1 position 70 could be critical amino acid positions in the development of classical T1D and LADA.

Association of HLA-DR-DQ alleles, haplotypes, and diplotypes with type 1 diabetes in Saudis

AIMS

Type 1 diabetes (T1D) is an autoimmune disease that affects many children worldwide. Genetic factors and environmental triggers play crucial interacting roles in the aetiology. This study aimed to assess the contribution of HLA-DRB1-DQA1-DQB1 alleles, haplotypes, and genotypes to the risk of T1D among Saudis.

METHODS

A total of 222 children with T1D and 342 controls were genotyped for HLA-DRB1, -DQA1, and -DQB1 using reverse sequence-specific oligonucleotide (rSSO) Lab Type high definition (HD) kits. Alleles, haplotypes, and diplotypes were compared between cases and controls using the SAS statistical package.

RESULTS

DRB1*03:01-DQA1*05:01-DQB1*02:01 (32.4%; OR = 3.68; P_c < .0001), DRB1*04:05-DQA1*03:02-DQB1*03:02 (6.6%; OR = 6.76; P_c < .0001), DRB1*04:02-DQA1*03:01-DQB1*03:02 (6.0%; OR = 3.10; P_c = .0194), DRB1*04:01-DQA1*03:01-DQB1*03:02 (3.7%; OR = 4.22; P_c = .0335), and DRB1*04:05-DQA1*03:02-DQB1*02:02 (2.7%; OR = 6.31; P_c = .0326) haplotypes were significantly increased in cases compared to controls, whereas DRB1*07:01-DQA1*02:01-DQB1*02:02 (OR = 0.41; P_c = .0001), DRB1*13:01-DQA1*01:03-DQB1*06:03 (OR = 0.05; P_c < .0001), DRB1*15:01-DQA1*01:02-DQB1*06:02 (OR = 0.03; P_c < .0001), and DRB1*11:01-DQA1*05:05-DQB1*03:01 (OR = 0.07; P_c = .0291) were significantly decreased. Homozygous DRB1*03:01-DQA1*05:01-DQB1*02:01 genotypes and combinations of DRB1*03:01-DQA1*05:01-DQB1*02:01 with DRB1*04:05-DQA1*03:02-DQB1*03:02, DRB1*04:02-DQA1*03:01-DQB1*03:02, and DRB1*04:01-DQA1*03:01-DQB1*03:02 were significantly increased in cases than controls. Combinations of DRB1*03:01-DQA1*05:01-DQB1*02:01 with DRB1*07:01-DQA1*02:01-DQB1*02:02 and DRB1*13:02-DQA1*01:02-DQB1*06:04 showed low OR values but did not remain significantly decreased after Bonferroni correction.

CONCLUSIONS

HLA-DRB1-DQA1-DQB1 alleles, haplotypes, and diplotypes in Saudis with T1D are not markedly different from those observed in Western and Middle-Eastern populations but are quite different than those of East Asians.

The complex pattern of genetic associations of leprosy with HLA class I and class II alleles can be reduced to four amino acid positions

Leprosy is a chronic disease caused by Mycobacterium leprae. Worldwide, more than 200,000 new patients are affected by leprosy annually, making it the second most common mycobacterial disease after tuberculosis. The MHC/HLA region has been consistently identified as carrying major leprosy susceptibility variants in different populations at times with inconsistent results. To establish the unambiguous molecular identity of classical HLA class I and class II leprosy susceptibility factors, we applied next-generation sequencing to genotype with high-resolution 11 HLA class I and class II genes in 1,155 individuals from a Vietnamese leprosy case-control sample. HLA alleles belonging to an extended haplotype from HLA-A to HLA-DPB1 were associated with risk to leprosy. This susceptibility signal could be reduced to the HLA-DRB1*10:01~ HLA-DQA1*01:05 alleles which were in complete linkage disequilibrium (LD). In addition, haplotypes containing HLA-DRB3~ HLA-DRB1*12:02 and HLA-C*07:06~ HLA-B*44:03~ HLA-DRB1*07:01 alleles were found as two independent protective factors for leprosy. Moreover, we replicated the previously associated HLA-DRB1*15:01 as leprosy risk factor and HLA-DRB1*04:05~HLA-DQA1*03:03 as protective alleles. When we narrowed the analysis to the single amino acid level, we found that the associations of the HLA alleles were largely captured by four independent amino acids at HLA-DRβ1 positions 57 (D) and 13 (F), HLA-B position 63 (E) and HLA-A position 19 (K). Hence, analyses at the amino acid level circumvented the ambiguity caused by strong LD of leprosy susceptibility HLA alleles and identified four distinct leprosy susceptibility factors.

Despite global efforts to eliminate leprosy over the past 25 years, more than 200,000 new cases are reported annually, and leprosy still represents a major public health problem in endemic regions. Leprosy presents a strong link with the host genetic background. The most significant susceptibility factors are located in the MHC region and likely involve classical HLA genes. However, the molecular identity of the HLA class I/II-leprosy risk factor(s) has been a matter of longstanding scientific dispute. By conducting a comprehensive sequenced-based analysis of HLA class I and class II genes, we are able to provide a unifying view of the complex relationship of leprosy susceptibility and HLA alleles. In addition, we show that four amino acid polymorphisms in HLA-DRβ1, HLA-B and HLA-A are sufficient to explain the majority of leprosy-HLA associations which opens the way for select protein-HLA peptide binding studies.

Effect of photobiomodulation therapy on oxidative stress markers of gastrocnemius muscle of diabetic rats subjected to high-intensity exercise

This study aimed to determine whether photobiomodulation therapy (PBMT) in diabetic rats subjected to high-intensity exercise interferes with the expression of the oxidative stress marker in the gastrocnemius muscle. Twenty-four male Wistar rats were included in this study comprising 16 diabetic and eight control rats. The animals were allocated into three groups-control, diabetic fatigue, and diabetic PBMT fatigue groups. Diabetes was induced via the intraperitoneal administration of streptozotocin (50 mg/kg). We subsequently assessed blood lactate levels and PBMT. The animals of the diabetic fatigue group PBMT were irradiated before the beginning of the exercises, with dose of 4 J and 808 nm, were submitted to treadmill running with speed and gradual slope until exhaustion, as observed by the maximum volume of oxygen and lactate level. The animals were euthanized and muscle tissue was removed for analysis of SOD markers, including catalase (CAT), glutathione peroxidase (GPx), and 2-thiobarbituric acid (TBARS) reactive substances. CAT, SOD, and GPx activities were significantly higher in the diabetic PBMT fatigue group (p < 0.05) than in the diabetic fatigue group. Outcomes for the diabetic PBMT fatigue group were similar to those of the control group (p > 0.05), while their antioxidant enzymes were significantly higher than those of the diabetic fatigue group. PBMT mitigated the TBARS concentration (p > 0.05). PBMT may reduce oxidative stress and be an alternative method of maintaining physical fitness when subjects are unable to perform exercise. However, this finding requires further testing in clinical studies.