HLA DNA sequence variation among human populations: molecular signatures of demographic and selective events

Genome‑wide association study and polygenic risk scores predict psoriasis and its shared phenotypes in Taiwan

Psoriasis is a chronic inflammatory dermatological disease, and there is a lack of understanding of the genetic factors involved in psoriasis in Taiwan. To establish associations between genetic variations and psoriasis, a genome‑wide association study was performed in a cohort of 2,248 individuals with psoriasis and 67,440 individuals without psoriasis. Using the ingenuity pathway analysis software, biological networks were constructed. Human leukocyte antigen (HLA) diplotypes and haplotypes were analyzed using Attribute Bagging (HIBAG)‑R software and chi‑square analysis. The present study aimed to assess the potential risks associated with psoriasis using a polygenic risk score (PRS) analysis. The genetic association between single nucleotide polymorphisms (SNPs) in psoriasis and various human diseases was assessed by phenome‑wide association study. METAL software was used to analyze datasets from China Medical University Hospital (CMUH) and BioBank Japan (BBJ). The results of the present study revealed 8,585 SNPs with a significance threshold of P<5x10‑8, located within 153 genes strongly associated with the psoriasis phenotype, particularly on chromosomes 5 and 6. This specific genomic region has been identified by analyzing the biological networks associated with numerous pathways, including immune responses and inflammatory signaling. HLA genotype analysis indicated a strong association between HLA‑A*02:07 and HLA‑C*06:02 in a Taiwanese population. Based on our PRS analysis, the risk of psoriasis associated with the SNPs identified in the present study was quantified. These SNPs are associated with various dermatological, circulatory, endocrine, metabolic, musculoskeletal, hematopoietic and infectious diseases. The meta‑analysis results indicated successful replication of a study conducted on psoriasis in the BBJ. Several genetic loci are significantly associated with susceptibility to psoriasis in Taiwanese individuals. The present study contributes to our understanding of the genetic determinants that play a role in susceptibility to psoriasis. Furthermore, it provides valuable insights into the underlying etiology of psoriasis in the Taiwanese community.

Association of HLA-C*07:359 with HLA-A, -B, and -DRB1 alleles in Taiwanese

Objectives

It is thought that Taiwanese indigenous people were the "first people" to populate Taiwan (Formosa) having been there for over 5000 years, preceding the Dutch colonization (from 1624 to 1662) and Spanish colonization (from 1626 to 1642). Taiwan's indigenes, represented by Austronesian language speakers, currently constitute approximately 2% of the total population in Taiwan. It is unknown whether they evolved from Taiwan's Paleolithic or Neolithic cultures, arrived during or after the Neolithic period from China or Southeast Asia or both. HLA studies on the Taiwanese indigenous population have found several intriguing genetic information showing one or two relatively frequently observed alleles and a small number of relatively less frequently observed ones. We report here a relatively frequently observed HLA-C*07:359 allele in the Taiwanese indigenous population, its linkage with HLA-B*39:01, and its probable associated HLA haplotype in two Taiwanese indigenous families. HLA-C*07:359 is a rarely observed allele in the HLA-C locus in the world populations. The objective of this study is to report the allele HLA-C*07:359 that is more frequently found in the Taiwanese population, especially in the Taiwanese indigenous people, to demonstrate that it has a close linkage with HLA-B*39:01 allele in the HLA-B locus and to show the plausible deduced HLA-A-C-B-DRB1-DQB1 haplotypes in association with HLA-C*07:359 in two families of Taiwanese indigenous unrelated individuals.

Materials and Methods

The samples were peripheral whole blood, with dipotassium ethylenediaminetetraacetic acid and/or acid citrate dextrose anticoagulation additives. The sequence-based typing method was employed to confirm the low incidence of the allele of HLA-C*07:359 observed in Taiwanese. Polymerase chain reaction was carried out to amplify exons 2, 3, and 4 of the HLA-A,-B,-C,-DRB1 and-DQB1 loci with group-specific primer sets. Amplicons were sequenced using the BigDye Terminator Cycle Sequencing Ready Reaction Kit in both directions according to the manufacturer's protocol.

Results

C*07:359 is an uncommon allele in the HLA-C locus in the world general population, according to our literature review. However, in this study, it is observed in the general Taiwanese population (frequency 0.41%), especially in the Taiwanese indigenous people at a frequency of 0.23%. In addition, we deduced two probable HLA haplotypes in association with C*07:359 in two indigenous families: A*24:02-C*07:359-B*39:01-DRB1*04:36 and A*24:02-C*07:359-B*39:01-DRB1*04:04.

Conclusion

The two deduced HLA haplotypes associated with the uncommon C*07:359 allele that we report here are valuable for HLA tissue typing laboratories for reference purposes and for stem cell transplantation donor search coordinators to determine the likelihood of finding compatible donors in unrelated bone marrow donor registries for patients bearing the uncommon HLA allele. Since C*07:359 was found mostly in the Taiwanese indigenous population, we think the allele and its haplotypes we report here are important in population and anthropological studies.

Associative role of HLA-DRB1 as a protective factor for susceptibility and progression of Parkinson's disease: a Chinese cross-sectional and longitudinal study

Background

Previous genome-wide association studies investigating the relationship between the HLA-DRB1 and the risk of Parkinson's disease (PD) have shown limited racial diversity and have not explored clinical heterogeneity extensively.

Methods

The study consisted of three parts: a case-control study, a cross-sectional study, and a longitudinal cohort study. The case-control study included 477 PD patients and 477 healthy controls to explore the relationship between rs660895 and PD susceptibility. The cross-sectional study utilized baseline data from 429 PD patients to examine the correlation between rs660895 and PD features. The longitudinal study included 388 PD patients who completed a 3-year follow-up to investigate the effects of rs660895 on PD progression.

Results

In the case-control study, HLA-DRB1 rs660895-G allele was associated with a decreased risk of PD in allele model (adjusted OR=0.72, p = 0.003) and dominant model (AG + GG vs. AA: adjusted OR = 0.67, p = 0.003). In the cross-sectional analysis, there was no association between rs660895 and the onset age, motor phenotype, or initial motor symptoms. In the longitudinal analysis, PD patients with the G allele exhibited a slower progression of motor symptoms (MDS-UPDRS-III total score: β = -5.42, p < 0.001, interaction ptime × genotype < 0.001) and non-motor symptoms (NMSS score: β = -4.78, p = 0.030, interaction ptime × genotype < 0.001).

Conclusion

Our findings support HLA-DRB1 rs660895-G allele is a protective genetic factor for PD risk in Chinese population. Furthermore, we also provide new evidence for the protective effect of rs660895-G allele in PD progression.

The Association of Class I and II Human Leukocyte Antigen Serotypes With End-Stage Kidney Disease Due to Membranoproliferative Glomerulonephritis and Dense Deposit Disease

RATIONALE & OBJECTIVE

Membranoproliferative glomerulonephritis (MPGN), encompassing several distinct diseases, is a rare but significant cause of kidney failure in the United States. The potential etiologies of MPGN are unclear, but prior studies have suggested dysregulation of the alternative complement pathway and, recently, autoimmunity as potential mechanisms driving MPGN pathogenesis. In this study, we examined HLA associations with end-stage kidney disease (ESKD) due to MPGN and dense deposit disease (DDD) in a large racially and ethnically diverse US-based cohort.

STUDY DESIGN

Case-control study.

SETTING & PARTICIPANTS

Using US Renal Data System (USRDS) and United Network for Organ Sharing (UNOS) data, we identified 3,424 patients with kidney failure due to MPGN and 263 due to DDD. We matched patients to kidney donor controls on designated race and ethnicity in a 1:15 ratio.

EXPOSURE

58 class I and II HLA serotypes.

OUTCOME

Case-control status.

ANALYTICAL APPROACH

For each disease cohort, univariable and multivariable logistic regression analyses were used to investigate associations between the disease and 58 HLA serotypes. In subgroup analyses, we investigated HLA associations in White and Black patients. We also studied antiglomerular basement membrane (anti-GBM) nephritis as a positive-control outcome. We applied a Bonferroni correction to account for multiple comparisons.

RESULTS

Eighteen serotypes were significantly associated with the odds of having MPGN in univariable analyses, with DR17 having the strongest association (odds ratio [OR], 1.55 [95% CI, 1.44-1.68], P=4.33e-28). No significant associations were found between any HLA serotype and DDD. Designated race-specific analyses showed comparable findings. We recapitulated known HLA associations in anti-GBM nephritis.

LIMITATIONS

Reliance on HLA serotypes (rather than genotype), lack of biopsy-confirmed diagnoses.

CONCLUSIONS

HLA-DR17 is associated with ESKD due to MPGN in a racially and ethnically diverse cohort. The strength of association was similar in White and Black patients, suggesting a role in the pathogenesis of MPGN. No HLA associations were observed in patients with DDD.

PLAIN-LANGUAGE SUMMARY

Prior studies have suggested dysregulation of the alternative complement pathway as a potential etiology of membranoproliferative glomerulonephritis (MPGN), but recent evidence from a British White population has implicated an autoimmune mechanism in MPGN pathogenesis. We investigated HLA associations between MPGN and dense deposit disease (DDD) in a large racially and ethnically diverse cohort of patients. We found that HLA-DR17 is associated with end-stage kidney disease (ESKD) due to MPGN in both White and Black patients. By contrast, no significant HLA associations with ESKD due to DDD were identified. These results suggest a role for autoimmunity in some cases of MPGN and highlight differences in the disease etiology of MPGN compared with DDD.

A registry-based population study of the HLA in Québec, Canada

As part of the worldwide effort to better characterize HLA diversity in populations, we have studied the population of Québec in Canada. This province has been defined by a complex history with multiple founder effects and migration patterns. We analyzed the typing data of 3806 individuals registered in Héma-Québec's Registry, which covered most administrative regions in Québec. Typing information was resolved at the second field level of resolution by next-generation sequencing (NGS) or by Sanger sequencing. We used the HLA-net.eu GENE[RATE] tools to estimate allele and two-locus haplotype frequencies for HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1, as well as Hardy-Weinberg equilibrium (HWE), selective neutrality, and linkage disequilibrium. The chord genetic distance was also calculated between administrative regions and was visualized using non-metric multidimensional scaling (NMDS) analysis. While most individual regions were in HWE, HWE was rejected for the province considered as a whole. Some regions exhibited signatures of selection, mostly toward an excess of heterozygotes. Allele and haplotype frequencies revealed outlier regions that strongly differed from the other regions. NMDS plots also showed differences between regions. The administrative regions of the province of Québec displayed heterogeneity in their HLA profiles. This heterogeneity was attributable to differing allele and haplotype specificities by region. In particular, regions 02-Saguenay-Lac-Saint-Jean and 01-Bas-St-Laurent diverged from the rest of the regions. The urban regions 06-Montréal and 13-Laval were very diversified in their HLA profiles. Together, these results will help optimize donor recruitment strategies in Québec.

Emerging therapeutic options in the management of diabetes: recent trends, challenges and future directions

Diabetes is a serious health issue that causes a progressive dysregulation of carbohydrate metabolism due to insufficient insulin hormone, leading to consistently high blood glucose levels. According to the epidemiological data, the prevalence of diabetes has been increasing globally, affecting millions of individuals. It is a long-term condition that increases the risk of various diseases caused by damage to small and large blood vessels. There are two main subtypes of diabetes: type 1 and type 2, with type 2 being the most prevalent. Genetic and molecular studies have identified several genetic variants and metabolic pathways that contribute to the development and progression of diabetes. Current treatments include gene therapy, stem cell therapy, statin therapy, and other drugs. Moreover, recent advancements in therapeutics have also focused on developing novel drugs targeting these pathways, including incretin mimetics, SGLT2 inhibitors, and GLP-1 receptor agonists, which have shown promising results in improving glycemic control and reducing the risk of complications. However, these treatments are often expensive, inaccessible to patients in underdeveloped countries, and can have severe side effects. Peptides, such as glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), are being explored as a potential therapy for diabetes. These peptides are postprandial glucose-dependent pancreatic beta-cell insulin secretagogues and have received much attention as a possible treatment option. Despite these advances, diabetes remains a major health challenge, and further research is needed to develop effective treatments and prevent its complications. This review covers various aspects of diabetes, including epidemiology, genetic and molecular basis, and recent advancements in therapeutics including herbal and synthetic peptides.

Paroxysmal Nocturnal Hemoglobinuria: Biology and Treatment

Paroxysmal nocturnal hemoglobinuria (PNH) is a nonmalignant clonal hematopoietic disorder characterized by the lack of glycosylphosphatidylinositol-anchored proteins (GPI-APs) as a consequence of somatic mutations in the phosphatidylinositol glycan anchor biosynthesis class A (PIGA) gene. Clinical manifestations of PNH are intravascular hemolysis, thrombophilia, and bone marrow failure. Treatment of PNH mainly relies on the use of complement-targeted therapy (C5 inhibitors), with the newest agents being explored against other factors involved in the complement cascade to alleviate unresolved intravascular hemolysis and extravascular hemolysis. This review summarizes the biology and current treatment strategies for PNH with the aim of reaching a general audience with an interest in hematologic disorders.

Molecular mimicry and autoimmunity in the time of COVID-19

Infectious diseases are commonly implicated as potential initiators of autoimmune diseases (ADs) and represent the most commonly known factor in the development of autoimmunity in susceptible individuals. Epidemiological data and animal studies on multiple ADs suggest that molecular mimicry is one of the likely mechanisms for the loss of peripheral tolerance and the development of clinical disease. Besides molecular mimicry, other mechanisms such as defects in central tolerance, nonspecific bystander activation, epitope-determinant spreading, and/or constant antigenic stimuli, may also contribute for breach of tolerance and to the development of ADs. Linear peptide homology is not the only mechanism by which molecular mimicry is established. Peptide modeling (i.e., 3D structure), molecular docking analyses, and affinity estimation for HLAs are emerging as critical strategies when studying the links of molecular mimicry in the development of autoimmunity. In the current pandemic, several reports have confirmed an influence of SARS-CoV-2 on subsequent autoimmunity. Bioinformatic and experimental evidence support the potential role of molecular mimicry. Peptide dimensional analysis requires more research and will be increasingly important for designing and distributing vaccines and better understanding the role of environmental factors related to autoimmunity.

Distinct mutational processes shape selection of MHC class I and class II mutations across primary and metastatic tumors

Disruption of antigen presentation via loss of major histocompatibility complex (MHC) expression is a strategy whereby cancer cells escape immune surveillance and develop resistance to immunotherapy. Here, we develop the personalized genomics algorithm Hapster and accurately call somatic mutations within the MHC genes of 10,001 primary and 2,199 metastatic tumors, creating a catalog of 1,663 non-synonymous mutations that provide key insights into MHC mutagenesis. We find that MHC class I genes are among the most frequently mutated genes in both primary and metastatic tumors, while MHC class II mutations are more restricted. Recurrent deleterious mutations are found within haplotype- and cancer-type-specific hotspots associated with distinct mutational processes. Functional classification of MHC residues reveals significant positive selection for mutations disruptive to the B2M, peptide, and T cell binding interfaces, as well as to MHC chaperones.

In silico formulation of a next-generation multiepitope vaccine for use as a prophylactic candidate against Crimean-Congo hemorrhagic fever

BACKGROUND

Crimean-Congo hemorrhagic fever (CCHF) is a widespread disease transmitted to humans and livestock animals through the bite of infected ticks or close contact with infected persons' blood, organs, or other bodily fluids. The virus is responsible for severe viral hemorrhagic fever outbreaks, with a case fatality rate of up to 40%. Despite having the highest fatality rate of the virus, a suitable treatment option or vaccination has not been developed yet. Therefore, this study aimed to formulate a multiepitope vaccine against CCHF through computational vaccine design approaches.

METHODS

The glycoprotein, nucleoprotein, and RNA-dependent RNA polymerase of CCHF were utilized to determine immunodominant T- and B-cell epitopes. Subsequently, an integrative computational vaccinology approach was used to formulate a multi-epitopes vaccine candidate against the virus.

RESULTS

After rigorous assessment, a multiepitope vaccine was constructed, which was antigenic, immunogenic, and non-allergenic with desired physicochemical properties. Molecular dynamics (MD) simulations of the vaccine-receptor complex show strong stability of the vaccine candidates to the targeted immune receptor. Additionally, the immune simulation of the vaccine candidates found that the vaccine could trigger real-life-like immune responses upon administration to humans.

CONCLUSIONS

Finally, we concluded that the formulated multiepitope vaccine candidates would provide excellent prophylactic properties against CCHF.

An HLA map of the world: A comparison of HLA frequencies in 200 worldwide populations reveals diverse patterns for class I and class II

HLA frequencies show widespread variation across human populations. Demographic factors as well as selection are thought to have shaped HLA variation across continents. In this study, a worldwide comparison of HLA class I and class II diversity was carried out. Multidimensional scaling techniques were applied to 50 HLA-A and HLA-B (class I) as well as 13 HLA-DRB1 (class II) first-field frequencies in 200 populations from all continents. Our results confirm a strong effect of geography on the distribution of HLA class I allele groups, with principal coordinates analysis closely resembling geographical location of populations, especially those of Africa-Eurasia. Conversely, class II frequencies stratify populations along a continuum of differentiation less clearly correlated to actual geographic location. Double clustering analysis revealed finer intra-continental sub-clusters (e.g., Northern and Western Europe vs. South East Europe, North Africa and Southwest Asia; South and East Africa vs. West Africa), and HLA allele group patterns characteristic of these clusters. Ancient (Austronesian expansion) and more recent (Romani people in Europe) migrations, as well as extreme differentiation (Taiwan indigenous peoples, Native Americans), and interregional gene flow (Sámi, Egyptians) are also reflected by the results. Barrier analysis comparing D_ST and geographic location identified genetic discontinuities caused by natural barriers or human behavior explaining inter and intra-continental HLA borders for class I and class II. Overall, a progressive reduction in HLA diversity from African to Oceanian and Native American populations is noted. This analysis of HLA frequencies in a unique set of worldwide populations confirms previous findings on the remarkable similarity of class I frequencies to geography, but also shows a more complex development for class II, with implications for both human evolutionary studies and biomedical research.

Human Leukocyte Antigen (HLA) Modulates the Dependence on Age of the Variability of Synchronous Neural Interactions

Recent evidence documented a protective effect of Class II human leukocyte antigen (HLA) DRB1*13 on brain health across the lifespan including evidence of reduced neural network variability relative to non-carriers. Here, in an extension of those findings, we evaluated the influence of a large number of Class I and Class II HLA alleles on aging-related changes in neural network variability. Cognitively healthy women (N = 178) ranging in age from 28 to 99 years old underwent a magnetoencephalography scan from which neural network variability was calculated and provided a blood sample from which HLA and apolipoprotein E (ApoE) genotype were determined. The primary analyses assessed the dependence of network variability on age in carriers of a specific HLA allele compared to non-carriers. Effects were considered protective if there was a significant increase of network variability with age in the absence of a given HLA allele but not in its presence, and were considered to confer susceptibility if the converse was documented; HLA alleles that did not influence the dependence of network variability on age in their presence or absence were considered neutral. Of 50 alleles investigated, 22 were found to be protective, 7 were found to confer susceptibility, and 21 were neutral. The frequencies of those 50 alleles were not associated significantly with ApoE genotype. The findings, which document the influence of HLA on age-related brain changes and highlight the role of HLA in healthy brain function, are discussed in terms of the role of HLA in the human immune response to foreign antigens.

Immunoinformatics Analysis of Citrullinated Antigen as Potential Multi-peptide Lung Cancer Vaccine Candidates for Indonesian Population

Non-small-cell lung cancer (NSCLC) is the most common lung cancer which has the highest mortality rate in Indonesia. One of the trends in treating cancer is by utilizing peptide vaccines, an immunotherapeutic approach that aims to stimulate the cell-mediated adaptive immune system to recognize cancer-associated peptides. Currently, no peptide vaccines are available in the market for NSCLC treatment. Therefore, this project aims to develop a multi-epitope peptide-based vaccine for NSCLC utilizing citrullinated peptides. Citrullination is a post-translational modification that occurs in cancer cells during autophagy that functions to induce immune responses towards modified self-epitopes such as tumor cells, through activation of PAD enzymes within the APC and target cells. It was found that introducing a common citrullinated neo-antigen peptide such as vimentin and enolase to the immune system could stimulate a higher specific CD4⁺ T cell response against NSCLC. Moreover, carcinoembryonic antigen (CEA), an antigen that is highly expressed in cancer cells, is also added to increase the vaccine’s specificity and to mobilize both CD4⁺ and CD8⁺ T cells. These antigens bind strongly to the MHC Class II alleles such as HLA-DRB1*07:01 and HLA-DRB*11:01, which are predominant alleles in Indonesian populations. Through in silico approach, the peptides generated from CEA, citrullinated vimentin and enolase, were analyzed for their MHC binding strength, immunogenicity, ability to induce IFNγ response, and population coverage. It is expected that the immunodominant antigens presentation is able to induce a potent immune response in NSCLC patients in Indonesia, resulting in tumor eradication.

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.

Clinical and Genetic Analysis in Pediatric Patients with Multiple Sclerosis and Related Conditions: Focus on DR Genes of the Major Histocompatibility Complex

Introduction:

There are several diseases recognized as variants of MS: post-infectious acute disseminated encephalitis, multiple sclerosis (MS), Rasmussen leukoencephalitis and Schilder's leukoencephalitis and related, but separate neuroimmune condition – Neuromyelitis Devic’s. In Kazakhstan diagnosis of such diseases was rare and immune modified treatment was only admitted after the age of 18. Clinical and immunogenetic study of MS spectrum diseases in Kazakhstan would allow to justify early targeted treatment.

Objective:

The aim of the study was to investigate genes of the main complex of human histocompatibility (MHC) associated with diseases of MS spectrum in Kazakhstani population.

Methods:

Complex clinical, neuroimaging and immunogenetic studies were performed in 34 children (24 girls, 10 boys) aged 4 to 18 years. 21 children were diagnosed with MS (11 Kazakh origin and 10 – Russian; 4 boys, 17 girls), 7 with leucoencephalitis (all Kazakh, 5 boys, 2 girls) and 6 with Devic neuromyelitis optica (all Kazakh, 1 boy, 5 girls). Genotyping of HLA DRB1, DQA1, DQB1 genes was performed for all patients.

Results:

MS group was characterized by classical relapsing-remitting MS. Predominant haplotype as a linkage complex was DRB1*15:01~DQA1*01:02~DQB1*06:02 in 20 (47.6%) of 42 DR-alleles, in 16 (76.2%) patients. MS relative risk (RR) was 13,36 for ethnic Kazakhs and RR=5,55 in Russians.

Leukoencephalitis had 7 children, with 28.6% mortality rate. The haplotype DRB1*15:01~DQA1*01:02~DQB1*06:02 as a linkage complex was detected 3 patients (4 alleles), RR=5,88.

Devic’s neuromyelitis optica (NMO) clinical course was characterized by fast and prolonged progression. There was predominance of DRB1*14 allele with RR=3,38.

Conclusion:

Summarizing, in the Kazakh population the haplotype DRB1*15:01∼DQA1*01:02∼DQB1*06:02 as a linkage complex was associated with prediction to MS and leukoencephalitis, but not to Devic’s NMO. Our study highlights the importance of awareness of MS and related disorders diagnosis which allows to implement early admission of disease-modified treatment in pediatric MS in Kazakhstan.

Challenges and opportunities associated with rare-variant pharmacogenomics

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

The False Dawn of Polygenic Risk Scores for Human Disease Prediction

Polygenic risk scores (PRSs) are being constructed for many diseases and are presented today as a promising avenue in the field of human genetics. These scores aim at predicting the risk of developing a disease by leveraging the many genome-wide association studies (GWAS) conducted during the two last decades. Important investments are being made to improve score estimates by increasing GWAS sample sizes, by developing more sophisticated methods, and by proposing different corrections for potential biases. PRSs have entered the market with direct-to-consumer companies proposing to compute them from saliva samples and even recently to help parents select the healthiest embryos. In this paper, we recall how PRSs arose and question the credit they are given by revisiting underlying assumptions in light of the history of human genetics and by comparing them with estimated breeding values (EBVs) used for selection in livestock.

RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data

The usage of expressed somatic mutations may have a unique advantage in identifying active cancer driver mutations. However, accurately calling mutations from RNA-seq data is difficult due to confounding factors such as RNA-editing, reverse transcription, and gap alignment. In the present study, we proposed a framework (named RNA-SSNV, https://github.com/pmglab/RNA-SSNV) to call somatic single nucleotide variants (SSNV) from tumor bulk RNA-seq data. Based on a comprehensive multi-filtering strategy and a machine-learning classification model trained with comprehensively curated features, RNA-SSNV achieved the best precision–recall rate (0.880–0.884) in a testing dataset and robustly retained 0.94 AUC for the precision–recall curve in three validation adult-based TCGA (The Cancer Genome Atlas) datasets. We further showed that the somatic mutations called by RNA-SSNV tended to have a higher functional impact and therapeutic power in known driver genes. Furthermore, VAF (variant allele fraction) analysis revealed that subclonal harboring expressed mutations had evolutional selection advantage and RNA had higher detection power to rescue DNA-omitted mutations. In sum, RNA-SSNV will be a useful approach to accurately call expressed somatic mutations for a more insightful analysis of cancer drive genes and carcinogenic mechanisms.

High Resolution HLA ∼A, ∼B, ∼C, ∼DRB1, ∼DQA1, and ∼DQB1 Diversity in South African Populations

Background: Lack of HLA data in southern African populations hampers disease association studies and our understanding of genetic diversity in these populations. We aimed to determine HLA diversity in South African populations using high resolution HLA ∼A, ∼B, ∼C, ∼DRB1, ∼DQA1 and ∼DQB1 data, from 3005 previously typed individuals.

Methods: We determined allele and haplotype frequencies, deviations from Hardy-Weinberg equilibrium (HWE), linkage disequilibrium (LD) and neutrality test. South African HLA class I data was additionally compared to other global populations using non-metrical multidimensional scaling (NMDS), genetic distances and principal component analysis (PCA).

Results: All loci strongly (p < 0.0001) deviated from HWE, coupled with excessive heterozygosity in most loci. Two of the three most frequent alleles, HLA ∼DQA1*05:02 (0.2584) and HLA ∼C*17:01 (0.1488) were previously reported in South African populations at lower frequencies. NMDS showed genetic distinctness of South African populations. Phylogenetic analysis and PCA clustered our current dataset with previous South African studies. Additionally, South Africans seem to be related to other sub-Saharan populations using HLA class I allele frequencies.

Discussion and Conclusion: Despite the retrospective nature of the study, data missingness, the imbalance of sample sizes for each locus and haplotype pairs, and induced methodological difficulties, this study provides a unique and large HLA dataset of South Africans, which might be a useful resource to support anthropological studies, disease association studies, population based vaccine development and donor recruitment programs. We additionally provide simulated high resolution HLA class I data to augment the mixed resolution typing results generated from this study.

HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed abstracts

Extreme complexity in the Human Leukocyte Antigens (HLA) system and its nomenclature makes it difficult to interpret and integrate relevant information for HLA associations with diseases, Adverse Drug Reactions (ADR) and Transplantation. PubMed search displays ~ 146,000 studies on HLA reported from diverse locations. Currently, IPD-IMGT/HLA (Robinson et al., Nucleic Acids Research 48:D948-D955, 2019) database houses data on 28,320 HLA alleles. We developed an automated pipeline with a unified graphical user interface HLA-SPREAD that provides a structured information on SNPs, Populations, REsources, ADRs and Diseases information. Information on HLA was extracted from ~ 28 million PubMed abstracts extracted using Natural Language Processing (NLP). Python scripts were used to mine and curate information on diseases, filter false positives and categorize to 24 tree hierarchical groups and named Entity Recognition (NER) algorithms followed by semantic analysis to infer HLA association(s). This resource from 109 countries and 40 ethnic groups provides interesting insights on: markers associated with allelic/haplotypic association in autoimmune, cancer, viral and skin diseases, transplantation outcome and ADRs for hypersensitivity. Summary information on clinically relevant biomarkers related to HLA disease associations with mapped susceptible/risk alleles are readily retrievable from HLASPREAD. The resource is available at URL http://hla-spread.igib.res.in/ . This resource is first of its kind that can help uncover novel patterns in HLA gene-disease associations.

Sexual dimorphism of the immune system predicts clinical outcomes in glioblastoma immunotherapy: A systematic review and meta-analysis

Background

Biological differences based on sex have been documented throughout the scientific literature. Glioblastoma (GBM), the most common primary malignant brain tumor in adults, has a male sex incidence bias, however, no clinical trial data examining differential effects of treatment between sexes currently exists.

Method

We analyzed genomic data, as well as clinical trials, to delineate the effect of sex on the immune system and GBM outcome following immunotherapy.

Results

We found that in general females possess enriched immunological signatures on gene set enrichment analysis, which also stratified patient survival when delineated by sex. Female GBM patients treated with immunotherapy had a statistically significant survival advantage at the 1-year compared to males (relative risk [RR] = 1.15; P = .0241). This effect was even more pronounced in vaccine-based immunotherapy (RR = 1.29; P = .0158).

Conclusions

Our study shows a meaningful difference in the immunobiology between males and females that also influences the overall response to immunotherapy in the setting of GBM.

Comparative Analysis of Susceptibility and Severity of COVID-19 in Countries from the Eastern and the Western World Till March '21

Majority of the world’s human population today is affected by Covid-19. The disease has not only exhibited differences in susceptibility among people of different countries, but also the mortality rate. In general, Western world has been reporting a greater number of infected cases than eastern countries. Even the mortality rates are quite high there. The aim of this study was to analyse the data available on the infectivity and mortality rates of Covid-19 in different countries till March’21 and then reviewed the literature to find reasons for the differences in susceptibility and severity in eastern and western countries. The reasons for the observed differences may be: (i) Eastern countries followed stricter modalities and got grace period to create better healthcare facilities to tackle COVID-19. This probably also slowed the transmission of virus and its evolution, (ii) Vaccination policies in the east may have provided some immunity due to cross reactivity, (iii) Frequent exposure to infections at young age in eastern countries might be helping in better immunity, (iv) Mutations in viral genome may be geography based and (v) Genetic differences in the immune system of the hosts with respect to ACE receptors and MHC may be playing an important role. In this article, an attempt has been made to put forth and discuss these plausible reasons along with suitable evidences. These findings may help in future research on the diagnosis, treatment and prevention of Covid-19.

Major Insights in Dynamics of Host Response to SARS-CoV-2: Impacts and Challenges

The coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization on March 11, 2020, is caused by the infection of highly transmissible species of a novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of July 25, 2021, there are 194,372,584 cases and 4,167,937 deaths with high variability in clinical manifestations, disease burden, and post-disease complications among different people around the globe. Overall, COVID-19 is manifested as mild to moderate in almost 90% of the cases and only the rest 10% of the cases need hospitalization. However, patients with older age and those having different comorbidities have made worst the pandemic scenario. The variability of pathological consequences and clinical manifestations of COVID-19 is associated with differential host-SARS-CoV-2 interactions, which are influenced by the factors that originated from the SARS-CoV-2 and the host. These factors usually include the genomic attributes and virulent factors of the SARS-CoV-2, the burden of coinfection with other viruses and bacteria, age and gender of the individuals, different comorbidities, immune suppressions/deficiency, genotypes of major histocompatibility complex, and blood group antigens and antibodies. We herein retrieved and reviewed literatures from PubMed, Scopus, and Google relevant to clinical complications and pathogenesis of COVID-19 among people of different age, sex, and geographical locations; genomic characteristics of SARS-CoV-2 including its variants, host response under different variables, and comorbidities to summarize the dynamics of the host response to SARS-CoV-2 infection; and host response toward approved vaccines and treatment strategies against COVID-19. After reviewing a large number of published articles covering different aspects of host response to SARS-CoV-2, it is clear that one aspect from one region is not working with the scenario same to others, as studies have been done separately with a very small number of cases from a particular area/region of a country. Importantly, to combat such a pandemic as COVID-19, a conclusive understanding of the disease dynamics is required. This review emphasizes on the identification of the factors influencing the dynamics of host responses to SARS-CoV-2 and offers a future perspective to explore the molecular insights of COVID-19.

Analysis of HLA gene polymorphisms in East Africans reveals evidence of gene flow in two Semitic populations from Sudan

Sudan, a northeastern African country, is characterized by high levels of cultural, linguistic, and genetic diversity, which is believed to be affected by continuous migration from neighboring countries. Consistent with such demographic effect, genome-wide SNP data revealed a shared ancestral component among Sudanese Afro-Asiatic speaking groups and non-African populations, mainly from West Asia. Although this component is shared among all Afro-Asiatic speaking groups, the extent of this sharing in Semitic groups, such as Sudanese Arab, is still unknown. Using genotypes of six polymorphic human leukocyte antigen (HLA) genes (i.e., HLA-A, -C, -B, -DRB1, -DQB1, and -DPB1), we examined the genetic structure of eight East African ethnic groups with origins in Sudan, South Sudan, and Ethiopia. We identified informative HLA alleles using principal component analysis, which revealed that the two Semitic groups (Gaalien and Shokrya) constituted a distinct cluster from the other Afro-Asiatic speaking groups in this study. The HLA alleles that distinguished Semitic Arabs co-exist in the same extended HLA haplotype, and those alleles are in strong linkage disequilibrium. Interestingly, we find the four-locus haplotype "C*12:02-B*52:01-DRB1*15:02-DQB1*06:01" exclusively in non-African populations and it is widely spread across Asia. The identification of this haplotype suggests a gene flow from Asia, and likely these haplotypes were brought to Africa through back migration from the Near East. These findings will be of interest to biomedical and anthropological studies that examine the demographic history of northeast Africa.

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Like Wings of a Bird: Functional Divergence and Complementarity between HLA-A and HLA-B Molecules

Human leukocyte antigen (HLA) genes are among the most polymorphic of our genome, as a likely consequence of balancing selection related to their central role in adaptive immunity. HLA-A and HLA-B genes were recently suggested to evolve through a model of joint divergent asymmetric selection conferring all human populations, including those with severe loss of diversity, an equivalent immune potential. However, the mechanisms by which these two genes might undergo joint evolution while displaying very distinct allelic profiles in populations are still unknown. To address this issue, we carried out extensive data analyses (among which factorial correspondence analysis and linear modeling) on 2,909 common and rare HLA-A, HLA-B, and HLA-C alleles and 200,000 simulated pathogenic peptides by taking into account sequence variation, predicted peptide-binding affinity and HLA allele frequencies in 123 populations worldwide. Our results show that HLA-A and HLA-B (but not HLA-C) molecules maintain considerable functional divergence in almost all populations, which likely plays an instrumental role in their immune defense. We also provide robust evidence of functional complementarity between HLA-A and HLA-B molecules, which display asymmetric relationships in terms of amino acid diversity at both inter- and intraprotein levels and in terms of promiscuous or fastidious peptide-binding specificities. Like two wings of a flying bird, the functional complementarity of HLA-A and HLA-B is a perfect example, in our genome, of duplicated genes sharing their capacity of assuming common vital functions while being submitted to complex and sometimes distinct environmental pressures.

Identification of the novel HLA-A*68:250 allele in a volunteer bone marrow donor from Sao Paulo, Brazil

The allele HLA-A*68:250 differs from HLA-A*68:27:01 by three nucleotides.

Molecular analysis of HLA Class I and Class II genes in five different South Indian linguistic groups

South Indians are a heterogeneous population who speak different languages and differ in their life style and physical appearance. Major population movements, social structure and caste endogamy have influenced the genetic structure of Indian populations. The human leukocyte antigen (HLA) system of populations is highly informative because of the high level of polymorphisms. Knowledge of allele and haplotype frequencies of the HLA system is important in the search for unrelated bone marrow donors. We investigated the distribution of HLA A, B, C, DRB1 and DQB1 loci in five linguistic groups from South India. HLA-A*01:01:01~B*57:01:01:01~C*06:02:01~DRB1*07:01:01~DQB1*03:03:02 was the common haplotype with highest frequency in all the five populations studied. A few relevant haplotypes were identified as most common haplotypes in each linguistic group. Comparison of HLA-A, -B and -DRB1 allele distribution in these five linguistic groups with the other Asian population showed that the South Indian populations were closely related to Sri Lankan populations. A large South Indian donor registry might serve as good source of donors for patients from Sri Lanka and vice versa.

HLA-A, -B, -C, -DRB1 allele and haplotype frequencies of the Korean population and performance characteristics of HLA typing by next-generation sequencing

INTRODUCTION

Human leukocyte antigen (HLA) identification at the allelic level is important for haematopoietic stem cell transplantation (HSCT). Next-generation sequencing (NGS) resolves ambiguous alleles by determining the phase of the polymorphisms. The aim of this study was to validate the software for HLA-SBT (sequence-based typing), assess Korean allele frequency, and characterise the performance of NGS-HLA typing.

METHODS

From the 2009 to 2016 registry, 1293 unrelated healthy donors with a complete dataset of previously characterised HLA-A, -B, -C, and -DRB1 loci were selected and assessed for frequency, haplotype inference, and relative linkage disequilibrium. For performance characteristics of NGS-HLA, alleles included in 1293 cases and ambiguous or alleles assigned as new by SBT-HLA software, or unassigned alleles were included. A total of 91 and 41 quality control samples resulted in 1056 alleles (132 samples × 4 loci × 2 diploid) for analysis. The GenDx NGSgo kit was used for NGS-HLA typing using the Illumina MiSeq platform.

RESULTS

A panel of 132 samples covered 231 alleles, including 53 HLA-A, 80 HLA-B, 43 HLA-C, and 55 HLA-DRB1 by HLA-SBT typing. Comparison of SBT-HLA and NGS-HLA typing showed 99.7% (1053/1056) concordance and discrepant cases were resolved by manual evaluation. Typing by NGS resulted in 67 HLA-A, 112 HLA-B, 71 HLA-C, and 72 HLA-DRB1 alleles. A total of 132 ambiguous, 4 new, and 1 unassigned alleles by HLA-SBT were resolved by NGS-HLA typing.

CONCLUSIONS

NGS-HLA typing provided robust and conclusive results without ambiguities, and its implementation could support HSCT in clinical settings.

Genetic-Code-Expansion Strategies for Vaccine Development

By providing long-term protection against infectious diseases, vaccinations have significantly reduced death and morbidity worldwide. In the 21st century, (bio)technological advances have paved the way for developing prophylactic vaccines that are safer and more effective as well as enabling the use of vaccines as therapeutics to treat human diseases. Here, we provide a focused review of the utility of genetic code expansion as an emerging tool for the development of vaccines. Specifically, we discuss how the incorporation of immunogenic noncanonical amino acids can aid in eliciting immune responses against adverse self-proteins and highlight the potential of an expanded genetic code for the construction of replication-incompetent viruses. We close the review by discussing the future prospects and remaining challenges for the application of these approaches in the development of both prophylactic and therapeutic vaccines in the near future.

The HLA diversity of the Anthony Nolan register

While the success of allogeneic stem cell transplantation depends on a high degree of HLA compatibility between donor and patient, finding a suitable donor remains challenging due to the hyperpolymorphic nature of HLA genes. We calculated high-resolution allele, haplotype and phenotype frequencies for HLA-A, -C, -B, -DRB1 and -DQB1 for 10 subpopulations of the Anthony Nolan (AN) register using an in-house expectation-maximisation (EM) algorithm run on mixed resolution HLA data, covering 676 155 individuals. Sample sizes range from 599 410 for British/Irish North West European (BINWE) individuals, the largest subpopulation in the United Kingdom to 1105 for the British Bangladeshi population. Calculation of genetic distance between the subpopulations based on haplotype frequencies shows three broad clusters, each following a major continental group: European, African and Asian. We further analysed the HLA haplotype and phenotype diversity of each subpopulation, and found that 35.52% of BINWE individuals ranging to 98.34% of Middle Eastern individuals on the register had a unique phenotype within their subpopulation. These analyses and the allele, haplotype and phenotype frequency data of the subpopulation on the AN register are a valuable resource in understanding the HLA diversity in the United Kingdom and can be used to improve the accuracy of match likelihoods and to inform future donor recruitment strategies.

How Ancestry Influences the Chances of Finding Unrelated Donors: An Investigation in Admixed Brazilians

A match of HLA loci between patients and donors is critical for successful hematopoietic stem cell transplantation. However, the extreme polymorphism of HLA loci - an outcome of millions of years of natural selection - reduces the chances that two individuals will carry identical combinations of multilocus HLA genotypes. Further, HLA variability is not homogeneously distributed throughout the world: African populations on average have greater variability than non-Africans, reducing the chances that two unrelated African individuals are HLA identical. Here, we explore how self-identification (often equated with "ethnicity" or "race") and genetic ancestry are related to the chances of finding HLA compatible donors in a large sample from Brazil, a highly admixed country. We query REDOME, Brazil's Bone Marrow Registry, and investigate how different criteria for identifying ancestry influence the chances of finding a match. We find that individuals who self-identify as "Black" and "Mixed" on average have lower chances of finding matches than those who self-identify as "White" (up to 57% reduction). We next show that an individual's African genetic ancestry, estimated using molecular markers and quantified as the proportion of an individual's genome that traces its ancestry to Africa, is strongly associated with reduced chances of finding a match (up to 60% reduction). Finally, we document that the strongest reduction in chances of finding a match is associated with having an MHC region of exclusively African ancestry (up to 75% reduction). We apply our findings to a specific condition, for which there is a clinical indication for transplantation: sickle-cell disease. We show that the increased African ancestry in patients with this disease leads to reduced chances of finding a match, when compared to the remainder of the sample, without the condition. Our results underscore the influence of ancestry on chances of finding compatible HLA matches, and indicate that efforts guided to increasing the African component of registries are necessary.

Demographic history and selection at HLA loci in Native Americans

The American continent was the last to be occupied by modern humans, and native populations bear the marks of recent expansions, bottlenecks, natural selection, and population substructure. Here we investigate how this demographic history has shaped genetic variation at the strongly selected HLA loci. In order to disentangle the relative contributions of selection and demography process, we assembled a dataset with genome-wide microsatellites and HLA-A, -B, -C, and -DRB1 typing data for a set of 424 Native American individuals. We find that demographic history explains a sizeable fraction of HLA variation, both within and among populations. A striking feature of HLA variation in the Americas is the existence of alleles which are present in the continent but either absent or very rare elsewhere in the world. We show that this feature is consistent with demographic history (i.e., the combination of changes in population size associated with bottlenecks and subsequent population expansions). However, signatures of selection at HLA loci are still visible, with significant evidence selection at deeper timescales for most loci and populations, as well as population differentiation at HLA loci exceeding that seen at neutral markers.

Similar patterns of genetic diversity and linkage disequilibrium in Western chimpanzees (Pan troglodytes verus) and humans indicate highly conserved mechanisms of MHC molecular evolution

BACKGROUND

Many species are threatened with extinction as their population sizes decrease with changing environments or face novel pathogenic threats. A reduction of genetic diversity at major histocompatibility complex (MHC) genes may have dramatic effects on populations' survival, as these genes play a key role in adaptive immunity. This might be the case for chimpanzees, the MHC genes of which reveal signatures of an ancient selective sweep likely due to a viral epidemic that reduced their population size a few million years ago. To better assess how this past event affected MHC variation in chimpanzees compared to humans, we analysed several indexes of genetic diversity and linkage disequilibrium across seven MHC genes on four cohorts of chimpanzees and we compared them to those estimated at orthologous HLA genes in a large set of human populations.

RESULTS

Interestingly, the analyses uncovered similar patterns of both molecular diversity and linkage disequilibrium across the seven MHC genes in chimpanzees and humans. Indeed, in both species the greatest allelic richness and heterozygosity were found at loci A, B, C and DRB1, the greatest nucleotide diversity at loci DRB1, DQA1 and DQB1, and both significant global linkage disequilibrium and the greatest proportions of haplotypes in linkage disequilibrium were observed at pairs DQA1 ~ DQB1, DQA1 ~ DRB1, DQB1 ~ DRB1 and B ~ C. Our results also showed that, despite some differences among loci, the levels of genetic diversity and linkage disequilibrium observed in contemporary chimpanzees were globally similar to those estimated in small isolated human populations, in contrast to significant differences compared to large populations.

CONCLUSIONS

We conclude, first, that highly conserved mechanisms shaped the diversity of orthologous MHC genes in chimpanzees and humans. Furthermore, our findings support the hypothesis that an ancient demographic decline affecting the chimpanzee populations - like that ascribed to a viral epidemic - exerted a substantial effect on the molecular diversity of their MHC genes, albeit not more pronounced than that experienced by HLA genes in human populations that underwent rapid genetic drift during humans' peopling history. We thus propose a model where chimpanzees' MHC genes regenerated molecular variation through recombination/gene conversion and/or balancing selection after the selective sweep.

The immunogenetic diversity of the HLA system in Mexico correlates with underlying population genetic structure

We studied HLA class I (HLA-A, -B) and class II (HLA-DRB1, -DQB1) allele groups and alleles by PCR-SSP based typing in a total of 15,318 mixed ancestry Mexicans from all the states of the country divided into 78 sample sets, providing information regarding allelic and haplotypic frequencies and their linkage disequilibrium, as well as admixture estimates and genetic substructure. We identified the presence of 4268 unique HLA extended haplotypes across Mexico and find that the ten most frequent (HF > 1%) HLA haplotypes with significant linkage disequilibrium (Δ'≥0.1) in Mexico (accounting for 20% of the haplotypic diversity of the country) are of primarily Native American ancestry (A*02~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*08~DQB1*04, A*68~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*14~DQB1*03:01, A*24~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*04~DQB1*03:02, A*02~B*40:02~DRB1*04~DQB1*03:02, A*68~B*35~DRB1*04~DQB1*03:02, A*02~B*15:01~DRB1*04~DQB1*03:02). Admixture estimates obtained by a maximum likelihood method using HLA-A/-B/-DRB1 as genetic estimators revealed that the main genetic components in Mexico as a whole are Native American (ranging from 37.8% in the northern part of the country to 81.5% in the southeastern region) and European (ranging from 11.5% in the southeast to 62.6% in northern Mexico). African admixture ranged from 0.0 to 12.7% not following any specific pattern. We were able to detect three major immunogenetic clusters correlating with genetic diversity and differential admixture within Mexico: North, Central and Southeast, which is in accordance with previous reports using genome-wide data. Our findings provide insights into the population immunogenetic substructure of the whole country and add to the knowledge of mixed ancestry Latin American population genetics, important for disease association studies, detection of demographic signatures on population variation and improved allocation of public health resources.

The role of host genetics in the immune response to SARS-CoV-2 and COVID-19 susceptibility and severity

This article provides a review of studies evaluating the role of host (and viral) genetics (including variation in HLA genes) in the immune response to coronaviruses, as well as the clinical outcome of coronavirus-mediated disease. The initial sections focus on seasonal coronaviruses, SARS-CoV, and MERS-CoV. We then examine the state of the knowledge regarding genetic polymorphisms and SARS-CoV-2 and COVID-19. The article concludes by discussing research areas with current knowledge gaps and proposes several avenues for future scientific exploration in order to develop new insights into the immunology of SARS-CoV-2.

Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide

We report detailed peptide‐binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV‐1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide‐binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV‐1. Among the strong HLA binders (IC₅₀ ≤ 50), we uncovered 16 alleles (the top ones being A*02:02, B*15:03 and DRB1*01:02) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA‐A*68:01, B*15:25, C*03:02 and DRB1*07:01) binding all viruses except HIV‐1, and 15 (top ones A*02:01 and C*14:02) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level

In renal transplantation, polymorphic amino acids on mismatched donor HLA molecules can lead to the induction of de novo donor‐specific antibodies (DSA), which are associated with inferior graft survival. To ultimately prevent de novo DSA formation without unnecessarily precluding transplants it is essential to define which polymorphic amino acid mismatches can actually induce an antibody response. To facilitate this, we developed a user‐friendly software program that establishes HLA class I and class II compatibility between donor and recipient on the amino acid level. HLA epitope mismatch algorithm (HLA‐EMMA) is a software program that compares simultaneously the HLA class I and class II amino acid sequences of the donor with the HLA amino acid sequences of the recipient and determines the polymorphic solvent accessible amino acid mismatches that are likely to be accessible to B cell receptors. Analysis can be performed for a large number of donor‐recipient pairs at once. As proof of principle, a previously described study cohort of 191 lymphocyte immunotherapy recipients was analysed with HLA‐EMMA and showed a higher frequency of DSA formation with higher number of solvent accessible amino acids mismatches. Overall, HLA‐EMMA can be used to analyse compatibility on amino acid level between donor and recipient HLA class I and class II simultaneously for large cohorts to ultimately determine the most immunogenic amino acid mismatches.

Immunoinformatics and Vaccine Development: An Overview

The use of vaccines have resulted in a remarkable improvement in global health. It has saved several lives, reduced treatment costs and raised the quality of animal and human lives. Current traditional vaccines came empirically with either vague or completely no knowledge of how they modulate our immune system. Even at the face of potential vaccine design advance, immune-related concerns (as seen with specific vulnerable populations, cases of emerging/re-emerging infectious disease, pathogens with complex lifecycle and antigenic variability, need for personalized vaccinations, and concerns for vaccines' immunological safety -specifically vaccine likelihood to trigger non-antigen-specific responses that may cause autoimmunity and vaccine allergy) are being raised. And these concerns have driven immunologists toward research for a better approach to vaccine design that will consider these challenges. Currently, immunoinformatics has paved the way for a better understanding of some infectious disease pathogenesis, diagnosis, immune system response and computational vaccinology. The importance of this immunoinformatics in the study of infectious diseases is diverse in terms of computational approaches used, but is united by common qualities related to host–pathogen relationship. Bioinformatics methods are also used to assign functions to uncharacterized genes which can be targeted as a candidate in vaccine design and can be a better approach toward the inclusion of women that are pregnant into vaccine trials and programs. The essence of this review is to give insight into the need to focus on novel computational, experimental and computation-driven experimental approaches for studying of host–pathogen interactions and thus making a case for its use in vaccine development.

Diversity of HLA Class I and Class II blocks and conserved extended haplotypes in Lacandon Mayans

Here we studied HLA blocks and haplotypes in a group of 218 Lacandon Maya Native American using a high-resolution next generation sequencing (NGS) method. We assessed the genetic diversity of HLA class I and class II in this population, and determined the most probable ancestry of Lacandon Maya HLA class I and class II haplotypes. Importantly, this Native American group showed a high degree of both HLA homozygosity and linkage disequilibrium across the HLA region and also lower class II HLA allelic diversity than most previously reported populations (including other Native American groups). Distinctive alleles present in the Lacandon population include HLA-A*24:14 and HLA-B*40:08. Furthermore, in Lacandons we observed a high frequency of haplotypes containing the allele HLA-DRB1*04:11, a relatively frequent allele in comparison with other neighboring indigenous groups. The specific demographic history of the Lacandon population including inbreeding, as well as pathogen selection, may have elevated the frequencies of a small number of HLA class II alleles and DNA blocks. To assess the possible role of different selective pressures in determining Native American HLA diversity, we evaluated the relationship between genetic diversity at HLA-A, HLA-B and HLA-DRB1 and pathogen richness for a global dataset and for Native American populations alone. In keeping with previous studies of such relationships we included distance from Africa as a covariate. After correction for multiple comparisons we did not find any significant relationship between pathogen diversity and HLA genetic diversity (as measured by polymorphism information content) in either our global dataset or the Native American subset of the dataset. We found the expected negative relationship between genetic diversity and distance from Africa in the global dataset, but no relationship between HLA genetic diversity and distance from Africa when Native American populations were considered alone.

Tumor suppressor genes and allele-specific expression: mechanisms and significance

Recent findings indicate that allele-specific expression (ASE) at specific cancer driver gene loci may be of importance in onset/progression of the disease. Of particular interest are loss-of-function (LOF) of tumor suppressor gene (TSGs) alleles. While LOF tumor suppressor mutations are typically considered to be recessive, if these mutant alleles can be significantly differentially expressed relative to wild-type alleles in heterozygotes, the clinical consequences could be significant. LOF TSG alleles are shown to be segregating at high frequencies in world-wide populations of normal/healthy individuals. Matched sets of normal and tumor tissues isolated from 233 cancer patients representing four diverse tumor types demonstrate functionally important changes in patterns of ASE in individuals heterozygous for LOF TSG alleles associated with cancer onset/progression. While a variety of molecular mechanisms were identified as potentially contributing to changes in ASE patterns in cancer, changes in DNA copy number and allele-specific alternative splicing possibly mediated by antisense RNA emerged as predominant factors. In conclusion, LOF TSGs are segregating in human populations at significant frequencies indicating that many otherwise healthy individuals are at elevated risk of developing cancer. Changes in ASE between normal and cancer tissues indicates that LOF TSG alleles may contribute to cancer onset/progression even when heterozygous with wild-type functional alleles.

The somatic mutation landscape of the human body

BACKGROUND

Somatic mutations in healthy tissues contribute to aging, neurodegeneration, and cancer initiation, yet they remain largely uncharacterized.

RESULTS

To gain a better understanding of the genome-wide distribution and functional impact of somatic mutations, we leverage the genomic information contained in the transcriptome to uniformly call somatic mutations from over 7500 tissue samples, representing 36 distinct tissues. This catalog, containing over 280,000 mutations, reveals a wide diversity of tissue-specific mutation profiles associated with gene expression levels and chromatin states. For example, lung samples with low expression of the mismatch-repair gene MLH1 show a mutation signature of deficient mismatch repair. In addition, we find pervasive negative selection acting on missense and nonsense mutations, except for mutations previously observed in cancer samples, which are under positive selection and are highly enriched in many healthy tissues.

CONCLUSIONS

These findings reveal fundamental patterns of tissue-specific somatic evolution and shed light on aging and the earliest stages of tumorigenesis.

SampPick: Selection of a Cohort of Subjects Matching a Population HLA Distribution

Immune responses to therapeutic proteins and peptides can adversely affect their safety and efficacy; consequently, immunogenicity risk-assessments are part of the development, licensure and clinical use of these products. In most cases the development of anti-drug antibodies is mediated by T cells which requires antigen presentation by Major Histocompatibility Complex Class II (MHCII) molecules (also called Human Leucocyte Antigen, HLA in humans). Immune responses to many protein therapeutics are thus HLA-restricted and it is important that the distribution of HLA variants used in the immunogenicity assessments provides adequate coverage of the target population. Due to biases inherent to the collection of samples in a blood bank or donor pool, simple random sampling will not achieve a truly representative sample of the population of interest. To help select a donor cohort we introduce SampPick, an implementation of simulated annealing which optimizes cohort selection to closely match the frequency distribution of a target population or subpopulation. With inputs of a target background frequency distribution for a population and a set of available, HLA-typed donors, the algorithm will iteratively create a cohort of donors of a user selected size that will closely match the target population rather than a random sample. In addition to optimizing the HLA types of donor cohorts, the software presented can be used to optimize donor cohorts for any other biallelic or monoallelic trait.

Immunity and mental illness: findings from a Danish population-based immunogenetic study of seven psychiatric and neurodevelopmental disorders

Human leukocyte antigen (HLA) genes encode proteins with important roles in the regulation of the immune system. Many studies have also implicated HLA genes in psychiatric and neurodevelopmental disorders. However, these studies usually focus on one disorder and/or on one HLA candidate gene, often with small samples. Here, we access a large dataset of 65,534 genotyped individuals consisting of controls (N = 19,645) and cases having one or more of autism spectrum disorder (N = 12,331), attention deficit hyperactivity disorder (N = 14,397), schizophrenia (N = 2401), bipolar disorder (N = 1391), depression (N = 18,511), anorexia (N = 2551) or intellectual disability (N = 3175). We imputed participants' HLA alleles to investigate the involvement of HLA genes in these disorders using regression models. We found a pronounced protective effect of DPB1*1501 on susceptibility to autism (p = 0.0094, OR = 0.72) and intellectual disability (p = 0.00099, OR = 0.41), with an increased protective effect on a comorbid diagnosis of both disorders (p = 0.003, OR = 0.29). We also identified a risk allele for intellectual disability, B*5701 (p = 0.00016, OR = 1.33). Associations with both alleles survived FDR correction and a permutation procedure. We did not find significant evidence for replication of previously-reported associations for autism or schizophrenia. Our results support an implication of HLA genes in autism and intellectual disability, which requires replication by other studies. Our study also highlights the importance of large sample sizes in HLA association studies.

Multiplicative fitness, rapid haplotype discovery, and fitness decay explain evolution of human MHC

The major histocompatibility complex (MHC) is a central component of the vertebrate immune system and hence evolves in the regime of a host-pathogen evolutionary race. The MHC is associated with quantitative traits which directly affect fitness and are subject to selection pressure. The evolution of haplotypes at the MHC HLA (HLA) locus is generally thought to be governed by selection for increased diversity that is manifested in overdominance and/or negative frequency-dependent selection (FDS). However, recently, a model combining purifying selection on haplotypes and balancing selection on alleles has been proposed. We compare the predictions of several population dynamics models of haplotype frequency evolution to the distributions derived from 6.59-million-donor HLA typings from the National Marrow Donor Program registry. We show that models that combine a multiplicative fitness function, extremely high haplotype discovery rates, and exponential fitness decay over time produce the best fit to the data for most of the analyzed populations. In contrast, overdominance is not supported, and population substructure does not explain the observed haplotype frequencies. Furthermore, there is no evidence of negative FDS. Thus, multiplicative fitness, rapid haplotype discovery, and rapid fitness decay appear to be the major factors shaping the HLA haplotype frequency distribution in the human population.