Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease

Quantitative trait locus mapping in placenta: A comparative study of chorionic villus and birth placenta

The placenta, a pivotal player in the prenatal environment, holds crucial insights into early developmental pathways and future health outcomes. In this study, we explored genetic molecular regulation in chorionic villus samples (CVS) from the first trimester and placenta tissue at birth. We assessed quantitative trait locus (QTL) mapping on DNA methylation and gene expression data in a Finnish cohort of 574 individuals. We found more QTLs in birth placenta than in first-trimester placenta. Nevertheless, a substantial amount of associations overlapped in their effects and showed consistent direction in both tissues, with increasing molecular genetic effects from early pregnancy to birth placenta. The identified QTLs in birth placenta were most enriched in genes with placenta-specific expression. Conducting a phenome-wide-association study (PheWAS) on the associated SNPs, we observed numerous overlaps with genome-wide association study (GWAS) hits (spanning 57 distinct traits and 23 SNPs), with notable enrichments for immunological, skeletal, and respiratory traits. The QTL-SNP rs1737028 (chr6:29737993) presented with the highest number of GWAS hits. This SNP was related to HLA-G expression via DNA methylation and was associated with various immune, respiratory, and psychiatric traits. Our findings implicate increasing genetic molecular regulation during the course of pregnancy and support the involvement of placenta gene regulation, particularly in immunological traits. This study presents a framework for understanding placenta-specific gene regulation during pregnancy and its connection to health-related traits.

GWAShug: a comprehensive platform for decoding the shared genetic basis between complex traits based on summary statistics

The shared genetic basis offers very valuable insights into the etiology, diagnosis and therapy of complex traits. However, a comprehensive resource providing shared genetic basis using the accessible summary statistics is currently lacking. It is challenging to analyze the shared genetic basis due to the difficulty in selecting parameters and the complexity of pipeline implementation. To address these issues, we introduce GWAShug, a platform featuring a standardized best-practice pipeline with four trait level methods and three molecular level methods. Based on stringent quality control, the GWAShug resource module includes 539 high-quality GWAS summary statistics for European and East Asian populations, covering 54 945 pairs between a measurement-based and a disease-based trait and 43 902 pairs between two disease-based traits. Users can easily search for shared genetic basis information by trait name, MeSH term and category, and access detailed gene information across different trait pairs. The platform facilitates interactive visualization and analysis of shared genetic basic results, allowing users to explore data dynamically. Results can be conveniently downloaded via FTP links. Additionally, we offer an online analysis module that allows users to analyze their own summary statistics, providing comprehensive tables, figures and interactive visualization and analysis. GWAShug is freely accessible at http://www.gwashug.com.

Exploring the HLA complex in autoimmunity: From the risk haplotypes to the modulation of expression

The genes mapping at the HLA region show high density, strong linkage disequilibrium and high polymorphism, which affect the association of HLA class I and class II genes with autoimmunity. We focused on the HLA haplotypes, genomic structures consisting of an array of specific alleles showing some degrees of genetic association with different autoimmune disorders. GWASs in many pathologies have identified variants in either the coding loci or the flanking regulatory regions, both in linkage disequilibrium in haplotypes, that are frequently associated with increased risk and may influence gene expression. We discuss the relevance of the HLA gene expression because the level of surface heterodimers determines the number of complexes presenting self-antigen and, thus, the strength of pathogenic autoreactive T cells immune response.

Haplotype Analysis Reveals Pleiotropic Disease Associations in the HLA Region

The human leukocyte antigen (HLA) region plays an important role in human health through involvement in immune cell recognition and maturation. While genetic variation in the HLA region is associated with many diseases, the pleiotropic patterns of these associations have not been systematically investigated. Here, we developed a haplotype approach to investigate disease associations phenome-wide for 412,181 Finnish individuals and 2,459 traits. Across the 1,035 diseases with a GWAS association, we found a 17-fold average per-SNP enrichment of hits in the HLA region. Altogether, we identified 7,649 HLA associations across 647 traits, including 1,750 associations uncovered by haplotype analysis. We find some haplotypes show trade-offs between diseases, while others consistently increase risk across traits, indicating a complex pleiotropic landscape involving a range of diseases. This study highlights the extensive impact of HLA variation on disease risk, and underscores the importance of classical and non-classical genes, as well as non-coding variation.

More evidence for widespread antagonistic pleiotropy in polymorphic disease alleles

Introduction

Many loci segregate alleles classified as "genetic diseases" due to their deleterious effects on health. However, some disease alleles have been reported to show beneficial effects under certain conditions or in certain populations. The beneficial effects of these antagonistically pleiotropic alleles may explain their continued prevalence, but the degree to which antagonistic pleiotropy is common or rare is unresolved. We surveyed the medical literature to identify examples of antagonistic pleiotropy to help determine whether antagonistic pleiotropy appears to be rare or common.

Results

We identified ten examples of loci with polymorphisms for which the presence of antagonistic pleiotropy is well supported by detailed genetic or epidemiological information in humans. One additional locus was identified for which the supporting evidence comes from animal studies. These examples complement over 20 others reported in other reviews.

Discussion

The existence of more than 30 identified antagonistically pleiotropic human disease alleles suggests that this phenomenon may be widespread. This poses important implications for both our understanding of human evolutionary genetics and our approaches to clinical treatment and disease prevention, especially therapies based on genetic modification.

The 18th International HLA & Immunogenetics workshop project report: Creating fully representative MHC reference haplotypes

A fundamental endeavor of the International Histocompatibility and Immunogenetics Workshop (IHIW) was assembling a collection of DNA samples homozygous through the MHC genomic region. This collection proved invaluable for assay development in the histocompatibility and immunogenetics field, for generating the human reference genome, and furthered our understanding of MHC diversity. Defined by their HLA-A, -B, -C and -DRB1 alleles, the combined frequency of the haplotypes from these individuals is ~20% in Europe. Thus, a significant proportion of MHC haplotypes, both common and rare throughout the world, and including many associated with disease, are not yet represented. In this workshop component, we are collecting the next generation of MHC -homozygous samples, to expand, diversify and modernize this critical community resource that has been foundational to the field. We asked laboratories worldwide to identify samples homozygous through all HLA class I and/or HLA class II genes, or through whole-genome SNP genotyping or sequencing, to have extensive homozygosity tracts within the MHC region. The focus is non-Europeans or those having HLA haplotypes less common in Europeans. Through this effort, we have obtained samples from 537 individuals representing 294 distinct haplotypes, as determined by their HLA class I and II alleles, and an additional 50 haplotypes distinct in HLA class I or II alleles. Although we have expanded the diversity, many populations remain underrepresented, particularly from Africa, and we encourage further participation. The data will serve as a resource for investigators seeking to characterize variation across the MHC genomic region for disease and population studies.

The effect of type 1 diabetes protection and susceptibility associated HLA class II genotypes on DNA methylation in immune cells

The HLA region, especially HLA class I and II genes, which encode molecules for antigen presentation to T cells, plays a major role in the predisposition to autoimmune disorders. To clarify the mechanisms behind this association, we examined genome-wide DNA methylation by microarrays to cover over 850,000 CpG sites in the CD4+ T cells and CD19+ B cells of healthy subjects homozygous either for DRB1*15-DQA1*01-DQB1*06:02 (DR2-DQ6, n = 14), associated with a strongly decreased T1D risk, DRB1*03-DQA1*05-DQB1*02 (DR3-DQ2, n = 19), or DRB1*04:01-DQA1*03-DQB1*03:02 (DR4-DQ8, n = 17), associated with a moderately increased T1D risk. In total, we discovered 14 differentially methylated CpG probes, of which 10 were located in the HLA region and six in the HLA-DRB1 locus. The main differences were between the protective genotype DR2-DQ6 and the risk genotypes DR3-DQ2 and DR4-DQ8, where the DR2-DQ6 group was hypomethylated compared to the other groups in all but four of the differentially methylated probes. The differences between the risk genotypes DR3-DQ2 and DR4-DQ8 were small. Our results indicate that HLA variants have few systemic effects on methylation and that their effect on autoimmunity is conveyed directly by HLA molecules, possibly by differences in expression levels or function.

Immunotherapy for colorectal cancer: insight from inherited genetics

Immunotherapy shows efficacy for multiple cancer types and potential for expanded use. However, current immune checkpoint inhibitors (ICIs) are ineffective against microsatellite-stable colorectal cancer (CRC), which is more commonly diagnosed. Immunotherapy strategies for non-responsive CRC, including new targets and new combination therapies, are being tested to address this need. Importantly, a subset of inherited germline genetic variants associated with CRC risk are predicted to regulate genes with immune functions, including genes related to existing ICIs, as well as new potential targets in the major histocompatibility complex (MHC) region and immunoregulatory cytokines. We review discoveries in the inherited genetics of CRC related to the immune system and draw connections with ongoing developments and emerging immunotherapy targets.

Multi-omic QTL mapping in early developmental tissues reveals phenotypic and temporal complexity of regulatory variants underlying GWAS loci

Most GWAS loci are presumed to affect gene regulation, however, only ∼43% colocalize with expression quantitative trait loci (eQTLs). To address this colocalization gap, we identify eQTLs, chromatin accessibility QTLs (caQTLs), and histone acetylation QTLs (haQTLs) using molecular samples from three early developmental (EDev) tissues. Through colocalization, we annotate 586 GWAS loci for 17 traits by QTL complexity, QTL phenotype, and QTL temporal specificity. We show that GWAS loci are highly enriched for colocalization with complex QTL modules that affect multiple elements (genes and/or peaks). We also demonstrate that caQTLs and haQTLs capture regulatory variations not associated with eQTLs and explain ∼49% of the functionally annotated GWAS loci. Additionally, we show that EDev-unique QTLs are strongly depleted for colocalizing with GWAS loci. By conducting one of the largest multi-omic QTL studies to date, we demonstrate that many GWAS loci exhibit phenotypic complexity and therefore, are missed by traditional eQTL analyses.

Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a rare atopic disorder associated with esophageal dysfunction, including difficulty swallowing, food impaction, and inflammation, that develops in a small subset of people with food allergies. Genome-wide association studies (GWASs) have identified 9 independent EoE risk loci reaching genome-wide significance (p < 5 × 10-8) and 27 additional loci of suggestive significance (5 × 10-8 < p < 1 × 10-5). In the current study, we perform linkage disequilibrium (LD) expansion of these loci to nominate a set of 531 variants that are potentially causal. To systematically interrogate the gene regulatory activity of these variants, we designed a massively parallel reporter assay (MPRA) containing the alleles of each variant within their genomic sequence context cloned into a GFP reporter library. Analysis of reporter gene expression in TE-7, HaCaT, and Jurkat cells revealed cell-type-specific gene regulation. We identify 32 allelic enhancer variants, representing 6 genome-wide significant EoE loci and 7 suggestive EoE loci, that regulate reporter gene expression in a genotype-dependent manner in at least one cellular context. By annotating these variants with expression quantitative trait loci (eQTL) and chromatin looping data in related tissues and cell types, we identify putative target genes affected by genetic variation in individuals with EoE. Transcription factor enrichment analyses reveal possible roles for cell-type-specific regulators, including GATA3. Our approach reduces the large set of EoE-associated variants to a set of 32 with allelic regulatory activity, providing functional insights into the effects of genetic variation in this disease.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

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.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Simultaneous detection of DNA variation and methylation at HLA class II locus and immune gene promoters using targeted SureSelect Methyl-Sequencing

The Human Leukocyte Antigen (HLA) locus associates with a variety of complex diseases, particularly autoimmune and inflammatory conditions. The HLA-DR15 haplotype, for example, confers the major risk for developing Multiple Sclerosis in Caucasians, pinpointing an important role in the etiology of this chronic inflammatory disease of the central nervous system. In addition to the protein-coding variants that shape the functional HLA-antigen-T cell interaction, recent studies suggest that the levels of HLA molecule expression, that are epigenetically controlled, also play a role in disease development. However, deciphering the exact molecular mechanisms of the HLA association has been hampered by the tremendous genetic complexity of the locus and a lack of robust approaches to investigate it. Here, we developed a method to specifically enrich the genomic DNA from the HLA class II locus (chr6:32,426,802-34,167,129) and proximal promoters of 2,157 immune-relevant genes, utilizing the Agilent RNA-based SureSelect Methyl-Seq Capture related method, followed by sequencing to detect genetic and epigenetic variation. We demonstrated successful simultaneous detection of the genetic variation and quantification of DNA methylation levels in HLA locus. Moreover, by the detection of differentially methylated positions in promoters of immune-related genes, we identified relevant pathways following stimulation of cells. Taken together, we present a method that can be utilized to study the interplay between genetic variance and epigenetic regulation in the HLA class II region, potentially, in a wide disease context.

Genetic Modifiers of Cystic Fibrosis Lung Disease Severity: Whole-Genome Analysis of 7,840 Patients

Rationale: Lung disease is the major cause of morbidity and mortality in persons with cystic fibrosis (pwCF). Variability in CF lung disease has substantial non-CFTR (CF transmembrane conductance regulator) genetic influence. Identification of genetic modifiers has prognostic and therapeutic importance. Objectives: Identify genetic modifier loci and genes/pathways associated with pulmonary disease severity. Methods: Whole-genome sequencing data on 4,248 unique pwCF with pancreatic insufficiency and lung function measures were combined with imputed genotypes from an additional 3,592 patients with pancreatic insufficiency from the United States, Canada, and France. This report describes association of approximately 15.9 million SNPs using the quantitative Kulich normal residual mortality-adjusted (KNoRMA) lung disease phenotype in 7,840 pwCF using premodulator lung function data. Measurements and Main Results: Testing included common and rare SNPs, transcriptome-wide association, gene-level, and pathway analyses. Pathway analyses identified novel associations with genes that have key roles in organ development, and we hypothesize that these genes may relate to dysanapsis and/or variability in lung repair. Results confirmed and extended previous genome-wide association study findings. These whole-genome sequencing data provide finely mapped genetic information to support mechanistic studies. No novel primary associations with common single variants or rare variants were found. Multilocus effects at chr5p13 (SLC9A3/CEP72) and chr11p13 (EHF/APIP) were identified. Variant effect size estimates at associated loci were consistently ordered across the cohorts, indicating possible age or birth cohort effects. Conclusions: This premodulator genomic, transcriptomic, and pathway association study of 7,840 pwCF will facilitate mechanistic and postmodulator genetic studies and the development of novel therapeutics for CF lung disease.

Influence of polymorphic variations of IFNL, HLA, and IL-6 genes in severe cases of COVID-19

The administration of vaccination doses to the global population has led to a decrease in the incidence of COVID-19. However, the clinical picture developed by infected individuals remains extremely concerning due to the great variability in the severity of cases even in vaccinated individuals. The clinical progression of the pathology is characterized by various influential factors such as sex, age group, comorbidities, and the genetics of the individual. The immune response to viral infections can be strongly influenced by the genetics of individuals; nucleotide variations called single-nucleotide polymorphisms (SNPs) in structures involved in the innate and adaptive immune response such as interferon (IFN)-λ, human leukocyte antigen (HLA), and interleukin (IL)-6 are frequently associated with pathological progression. In this study, we conducted a review of the main SNPs of these structures that are associated with severity in COVID-19. Searches were conducted on some platforms of the National Center for Biotechnology and Information (NCBI), and 102 studies were selected for full reading according to the inclusion criteria. IFNs showed a strong association with antiviral function, specifically, IFN-λ3 (IL-28B) demonstrated genetic variants commonly related to clinical progression in various pathologies. For COVID-19, rs12979860 and rs1298275 presented frequently described unfavorable genotypes for pathological conditions of hepatitis C and hepatocellular carcinoma. The high genetic variability of HLA was reported in the studies as a crucial factor relevant to the late immune response, mainly due to its ability to recognize antigens, with the HLA-B*46:01 SNP being associated with susceptibility to COVID-19. For IL-6, rs1554606 showed a strong relationship with the clinical progression of COVID-19. In addition, rs2069837 was identified with possible host protection relationships when linked to this infection.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

Characterization of the immunoglobulin lambda chain locus from diverse populations reveals extensive genetic variation

Immunoglobulins (IGs), crucial components of the adaptive immune system, are encoded by three genomic loci. However, the complexity of the IG loci severely limits the effective use of short read sequencing, limiting our knowledge of population diversity in these loci. We leveraged existing long read whole-genome sequencing (WGS) data, fosmid technology, and IG targeted single-molecule, real-time (SMRT) long-read sequencing (IG-Cap) to create haplotype-resolved assemblies of the IG Lambda (IGL) locus from 6 ethnically diverse individuals. In addition, we generated 10 diploid assemblies of IGL from a diverse cohort of individuals utilizing IG-Cap. From these 16 individuals, we identified significant allelic diversity, including 36 novel IGLV alleles. In addition, we observed highly elevated single nucleotide variation (SNV) in IGLV genes relative to IGL intergenic and genomic background SNV density. By comparing SNV calls between our high quality assemblies and existing short read datasets from the same individuals, we show a high propensity for false-positives in the short read datasets. Finally, for the first time, we nucleotide-resolved common 5-10 Kb duplications in the IGLC region that contain functional IGLJ and IGLC genes. Together these data represent a significant advancement in our understanding of genetic variation and population diversity in the IGL locus.

Human leukocyte antigen super-locus: nexus of genomic supergenes, SNPs, indels, transcripts, and haplotypes

The human Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) super-locus is a highly polymorphic genomic region that encodes more than 140 coding genes including the transplantation and immune regulatory molecules. It receives special attention for genetic investigation because of its important role in the regulation of innate and adaptive immune responses and its strong association with numerous infectious and/or autoimmune diseases. In recent years, MHC genotyping and haplotyping using Sanger sequencing and next-generation sequencing (NGS) methods have produced many hundreds of genomic sequences of the HLA super-locus for comparative studies of the genetic architecture and diversity between the same and different haplotypes. In this special issue on 'The Current Landscape of HLA Genomics and Genetics', we provide a short review of some of the recent analytical developments used to investigate the SNP polymorphisms, structural variants (indels), transcription and haplotypes of the HLA super-locus. This review highlights the importance of using reference cell-lines, population studies, and NGS methods to improve and update our understanding of the mechanisms, architectural structures and combinations of human MHC genomic alleles (SNPs and indels) that better define and characterise haplotypes and their association with various phenotypes and diseases.

A small-molecule inhibitor and degrader of the RNF5 ubiquitin ligase

RNF5 E3 ubiquitin ligase has multiple biological roles and has been linked to the development of severe diseases such as cystic fibrosis, acute myeloid leukemia, and certain viral infections, emphasizing the importance of discovering small-molecule RNF5 modulators for research and drug development. The present study describes the synthesis of a new benzo[b]thiophene derivative, FX12, that acts as a selective small-molecule inhibitor and degrader of RNF5. We initially identified the previously reported STAT3 inhibitor, Stattic, as an inhibitor of dislocation of misfolded proteins from the endoplasmic reticulum (ER) lumen to the cytosol in ER-associated degradation. A concise structure-activity relationship campaign (SAR) around the Stattic chemotype led to the synthesis of FX12, which has diminished activity in inhibition of STAT3 activation and retains dislocation inhibitory activity. FX12 binds to RNF5 and inhibits its E3 activity in vitro as well as promoting proteasomal degradation of RNF5 in cells. RNF5 as a molecular target for FX12 was supported by the facts that FX12 requires RNF5 to inhibit dislocation and negatively regulates RNF5 function. Thus, this study developed a small-molecule inhibitor and degrader of the RNF5 ubiquitin ligase, providing a chemical biology tool for RNF5 research and therapeutic development.

Fine-mapping studies distinguish genetic risks for childhood- and adult-onset asthma in the HLA region

BACKGROUND

Genome-wide association studies of asthma have revealed robust associations with variation across the human leukocyte antigen (HLA) complex with independent associations in the HLA class I and class II regions for both childhood-onset asthma (COA) and adult-onset asthma (AOA). However, the specific variants and genes contributing to risk are unknown.

METHODS

We used Bayesian approaches to perform genetic fine-mapping for COA and AOA (n=9432 and 21,556, respectively; n=318,167 shared controls) in White British individuals from the UK Biobank and to perform expression quantitative trait locus (eQTL) fine-mapping in immune (lymphoblastoid cell lines, n=398; peripheral blood mononuclear cells, n=132) and airway (nasal epithelial cells, n=188) cells from ethnically diverse individuals. We also examined putatively causal protein coding variation from protein crystal structures and conducted replication studies in independent multi-ethnic cohorts from the UK Biobank (COA n=1686; AOA n=3666; controls n=56,063).

RESULTS

Genetic fine-mapping revealed both shared and distinct causal variation between COA and AOA in the class I region but only distinct causal variation in the class II region. Both gene expression levels and amino acid variation contributed to risk. Our results from eQTL fine-mapping and amino acid visualization suggested that the HLA-DQA1*03:01 allele and variation associated with expression of the nonclassical HLA-DQA2 and HLA-DQB2 genes accounted entirely for the most significant association with AOA in GWAS. Our studies also suggested a potentially prominent role for HLA-C protein coding variation in the class I region in COA. We replicated putatively causal variant associations in a multi-ethnic cohort.

CONCLUSIONS

We highlight roles for both gene expression and protein coding variation in asthma risk and identified putatively causal variation and genes in the HLA region. A convergence of genomic, transcriptional, and protein coding evidence implicates the HLA-DQA2 and HLA-DQB2 genes and HLA-DQA1*03:01 allele in AOA.

PRINCESS: comprehensive detection of haplotype resolved SNVs, SVs, and methylation

Long-read sequencing has been shown to have advantages in structural variation (SV) detection and methylation calling. Many studies focus either on SV, methylation, or phasing of SNV; however, only the combination of variants provides a comprehensive insight into the sample and thus enables novel findings in biology or medicine. PRINCESS is a structured workflow that takes raw sequence reads and generates a fully phased SNV, SV, and methylation call set within a few hours. PRINCESS achieves high accuracy and long phasing even on low coverage datasets and can resolve repetitive, complex medical relevant genes that often escape detection. PRINCESS is publicly available at https://github.com/MeHelmy/princess under the MIT license.

Inference for High-Dimensional Censored Quantile Regression

With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes. To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression. This paper proposes a novel procedure to draw inference on all predictors within the framework of global censored quantile regression, which investigates covariate-response associations over an interval of quantile levels, instead of a few discrete values. The proposed estimator combines a sequence of low dimensional model estimates that are based on multi-sample splittings and variable selection. We show that, under some regularity conditions, the estimator is consistent and asymptotically follows a Gaussian process indexed by the quantile level. Simulation studies indicate that our procedure can properly quantify the uncertainty of the estimates in high dimensional settings. We apply our method to analyze the heterogeneous effects of SNPs residing in lung cancer pathways on patients' survival, using the Boston Lung Cancer Survivor Cohort, a cancer epidemiology study on the molecular mechanism of lung cancer.

Haplotype-Specific Expression Analysis of MHC Class II Genes in Healthy Individuals and Rheumatoid Arthritis Patients

HLA-DRB1 alleles have been associated with several autoimmune diseases. For anti-citrullinated protein antibody positive rheumatoid arthritis (RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to study the genetic regulation of major histocompatibility complex (MHC) Class II gene expression in immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles, thus HLA-DRB1 SE alleles have a strong cis effect on gene expression. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels.

Tensin 1 (TNS1) is a modifier gene for low body mass index (BMI) in homozygous [F508del]CFTR patients

Cystic fibrosis (CF) is a life‐limiting autosomal recessive genetic disease caused by variants in the CFTR gene, most commonly by the [F508del] variant. Although CF is a classical Mendelian disease, genetic variants in several modifier genes have been associated with variation of the clinical phenotype for pulmonary and gastrointestinal function and urogenital development. We hypothesized that whole genome sequencing of a well‐phenotyped CF populations might identify novel variants in known, or hitherto unknown, modifier genes. Whole genome sequencing was performed on the Illumina HiSeq X platform for 98 clinically diagnosed cystic fibrosis patient samples from the Adult CF Clinic at the University of California San Diego (UCSD). We compared protein‐coding, non‐silent variants genome wide between CFTR [F508del] homozygotes vs CFTR compound heterozygotes. Based on a single variant score test, we found 3 SNPs in common variants (MAF >5%) that occurred at significantly different rates between homozygous [F508del]CFTR and compound heterozygous [F508del]CFTR patients. The 3 SNPs were all located in one gene on chromosome 2: Tensin 1 (TNS1: rs3796028; rs2571445: and rs918949). We observed significantly lower BMIs in homozygous [F508del]CFTR patients who were also homozygous for Tensin 1 rs918949 (T/T) (p = 0.023) or rs2571445 (G/G) (p = 0.02) variants. The Tensin 1 gene is thus a potential modifier gene for low BMI in CF patients homozygous for the [F508del]CFTR variant.

Global discovery of lupus genetic risk variant allelic enhancer activity

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Thousands of genetic variants have been associated with lupus, but causal variants and mechanisms are unknown. Here, the authors combine a massively parallel reporter assay with genome-wide ChIP experiments to identify risk variants with allelic enhancer activity mediated through transcription factor binding.

HLA RNA Sequencing With Unique Molecular Identifiers Reveals High Allele-Specific Variability in mRNA Expression

The HLA gene complex is the most important single genetic factor in susceptibility to most diseases with autoimmune or autoinflammatory origin and in transplantation matching. Most studies have focused on the vast allelic variation in these genes; only a few studies have explored differences in the expression levels of HLA alleles. In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology. Our method provides novel insights into HLA research, and it can be applied to quantify expression differences of HLA alleles in various tissues and to evaluate the role of this type of variation in transplantation matching and susceptibility to autoimmune diseases.

Understanding the genetic contribution of the human leukocyte antigen system to common major psychiatric disorders in a world pandemic context

The human leukocyte antigen (HLA) is a complex genetic system that encodes proteins which predominantly regulate immune/inflammatory processes. It can be involved in a variety of immuno-inflammatory disorders ranging from infections to autoimmunity and cancers. The HLA system is also suggested to be involved in neurodevelopment and neuroplasticity, especially through microglia regulation and synaptic pruning. Consequently, this highly polymorphic gene region has recently emerged as a major player in the etiology of several major psychiatric disorders, such as schizophrenia, autism spectrum disorder and bipolar disorder and with less evidence for major depressive disorders and attention deficit hyperactivity disorder. We thus review here the role of HLA genes in particular subgroups of psychiatric disorders and foresee their potential implication in future research. In particular, given the prominent role that the HLA system plays in the regulation of viral infection, this review is particularly timely in the context of the Covid-19 pandemic.

Gene expression variability in human and chimpanzee populations share common determinants

Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

Cystic Fibrosis and Genotype-Dependent Therapy: Is There a Need for a Sex-Specific Therapy?

Cystic fibrosis (CF) is an autosomal recessive genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulation (CFTR) anion channel. Loss of CFTR protein and/or function disrupts chloride, bicarbonate, and fluid transport and also impacts epithelial sodium transport. Such altered ion and fluid transport produces mucus obstruction, inflammation, pulmonary infection, and damage to multiple organs. Although an autosomal disease, it is apparent that gender differences in life expectancy and quality of life do exist. Conventionally established therapies have treated the downstream sequelae of CFTR dysfunction and have led to a steady increase in life expectancy. Physicians now have access to medications that treat the basic defect in CF, in the form of CFTR modulators. These drugs target the trafficking and/or function of CFTR to improve clinical outcomes for patients. This review summarizes the science behind CFTR modulators and shows how these drugs have dramatically changed how patients with CF are treated. Surprisingly, although the drug target(s) are identical in males and females, CF females seem to display a greater improvement than their male counterparts.