Evaluation of HLA-DRB1 imputation using a Finnish dataset

Schizophrenia, Human Leukocyte Antigen (HLA), and Herpes Viruses: Immunogenetic Associations at the Population Level

Several factors have been implicated in schizophrenia (SZ), including human herpes viruses (HHV) and the adaptive immunity Human Leukocyte Antigen (HLA) genes. Here we investigated these issues in 2 complementary ways. In one analysis, we evaluated SZ-HLA and HHV-HLA associations at the level of a single allele by computing (a) a SZ-HLA protection/susceptibility (P/S) score based on the covariance between SZ and 127 HLA allele prevalences in 14 European countries, (b) estimating in silico HHV-HLA best binding affinities for the 9 HHV strains, and (c) evaluating the dependence of P/S score on HHV-HLA binding affinities. These analyses yielded (a) a set of 127 SZ-HLA P/S scores, varying by >200× (maximum/minimum), which could not be accounted for by chance, (b) a set of 127 alleles × 9 HHV best-estimated affinities, varying by >600×, and (c) a set of correlations between SZ-HLA P/S scores and HHV-HLA binding which indicated a prominent role of HHV1. In a subsequent analysis, we extended these findings to the individual person by taking into account the fact that every individual carries 12 HLA alleles and computed (a) the average SZ-HLA P/S scores of 12 randomly chosen alleles (2 per gene), an indicator of HLA-based SZ P/S for an individual, and (b) the average of the corresponding HHV estimated affinities for those alleles, an indicator of overall effectiveness of HHV-HLA binding. We found (a) that HLA protection for SZ was significantly more prominent than susceptibility, and (b) that protective SZ-HLA scores were associated with higher HHV-HLA binding affinities, indicating that HLA binding and subsequent elimination of several HHV strains may confer protection against schizophrenia.

Blood donor biobank and HLA imputation as a resource for HLA homozygous cells for therapeutic and research use

Background

Allogeneic therapeutic cells may be rejected if they express HLA alleles not found in the recipient. As finding cell donors with a full HLA match to a recipient requires vast donor pools, the use of HLA homozygous cells has been suggested as an alternative. HLA homozygous cells should be well tolerated by those who carry at least one copy of donor HLA alleles. HLA-A-B homozygotes could be valuable for HLA-matched thrombocyte products. We evaluated the feasibility of blood donor biobank and HLA imputation for the identification of potential cell donors homozygous for HLA alleles.

Methods

We imputed HLA-A, -B, -C, -DRB1, -DQA1, -DQB1 and -DPB1 alleles from genotypes of 20,737 Finnish blood donors in the Blood Service Biobank. We confirmed homozygosity by sequencing HLA alleles in 30 samples and by examining 36,161 MHC-located polymorphic DNA markers.

Results

Three hundred and seventeen individuals (1.5%), representing 41 different haplotypes, were found to be homozygous for HLA-A, -B, -C, -DRB1, -DQA1 and -DQB1 alleles. Ten most frequent haplotypes homozygous for HLA-A to -DQB1 were HLA-compatible with 49.5%, and three most frequent homozygotes to 30.4% of the Finnish population. Ten most frequent HLA-A-B homozygotes were compatible with 75.3%, and three most frequent haplotypes to 42.6% of the Finnish population. HLA homozygotes had a low level of heterozygosity in MHC-located DNA markers, in particular in HLA haplotypes enriched in Finland.

Conclusions

The present study shows that HLA imputation in a blood donor biobank of reasonable size can be used to identify HLA homozygous blood donors suitable for cell therapy, HLA-typed thrombocytes and research. The homozygotes were HLA-compatible with a large fraction of the Finnish population. Regular blood donors reported to have positive attitude to research donation appear a good option for these purposes. Differences in population frequencies of HLA haplotypes emphasize the need for population-specific collections of HLA homozygous samples.

The lupus susceptibility allele DRB1*03:01 encodes a disease-driving epitope

The HLA-DRB1*03:01 allele is a major genetic risk factor in systemic lupus erythematosus (SLE), but the mechanistic basis of the association is unclear. Here we show that in the presence of interferon gamma (IFN-γ), a short DRB1*03:01-encoded allelic epitope activates a characteristic lupus transcriptome in mouse and human macrophages. It also triggers a cascade of SLE-associated cellular aberrations, including endoplasmic reticulum stress, unfolded protein response, mitochondrial dysfunction, necroptotic cell death, and production of pro-inflammatory cytokines. Parenteral administration of IFN-γ to naïve DRB1*03:01 transgenic mice causes increased serum levels of anti-double stranded DNA antibodies, glomerular immune complex deposition and histopathological renal changes that resemble human lupus nephritis. This study provides evidence for a noncanonical, antigen presentation-independent mechanism of HLA-disease association in SLE and could lay new foundations for our understanding of key molecular mechanisms that trigger and propagate this devastating autoimmune disease.

Novel Linkage Peaks Discovered for Diabetic Nephropathy in Individuals With Type 1 Diabetes

Genome-wide association studies (GWAS) and linkage studies have had limited success in identifying genome-wide significantly linked regions or risk loci for diabetic nephropathy (DN) in individuals with type 1 diabetes (T1D). As GWAS cohorts have grown, they have also included more documented and undocumented familial relationships. Here we computationally inferred and manually curated pedigrees in a study cohort of >6,000 individuals with T1D and their relatives without diabetes. We performed a linkage study for 177 pedigrees consisting of 452 individuals with T1D and their relatives using a genome-wide genotyping array with >300,000 single nucleotide polymorphisms and PSEUDOMARKER software. Analysis resulted in genome-wide significant linkage peaks on eight chromosomal regions from five chromosomes (logarithm of odds score >3.3). The highest peak was localized at the HLA region on chromosome 6p, but whether the peak originated from T1D or DN remained ambiguous. Of other significant peaks, the chromosome 4p22 region was localized on top of ARHGAP24, a gene associated with focal segmental glomerulosclerosis, suggesting this gene may play a role in DN as well. Furthermore, rare variants have been associated with DN and chronic kidney disease near the 4q25 peak, localized on top of CCSER1.

Increasing accuracy of HLA imputation by a population-specific reference panel in a FinnGen biobank cohort

The HLA genes, the most polymorphic genes in the human genome, constitute the strongest single genetic susceptibility factor for autoimmune diseases, transplantation alloimmunity and infections. HLA imputation via statistical inference of alleles based on single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with alleles is a powerful first-step screening tool. Due to different LD structures between populations, the accuracy of HLA imputation may benefit from matching the imputation reference with the study population. To evaluate the potential advantage of using population-specific reference in HLA imputation, we constructed an HLA reference panel consisting of 1150 Finns with 5365 major histocompatibility complex region SNPs consistent between genome builds. We evaluated the accuracy of the panel against a European panel in an independent test set of 213 Finnish subjects. We show that the Finnish panel yields a lower imputation error rate (1.24% versus 1.79%). More than 30% of imputation errors occurred in haplotypes enriched in Finland. The frequencies of imputed HLA alleles were highly correlated with clinical-grade HLA allele frequencies and allowed accurate replication of established HLA–disease associations in ∼102 000 biobank participants. The results show that a population-specific reference increases imputation accuracy in a relatively isolated population within Europe and can be successfully applied to biobank-scale genome data collections.

Clinical Diagnosis of the Dampness and Mold Hypersensitivity Syndrome: Review of the Literature and Suggested Diagnostic Criteria

A great variety of non-specific symptoms may occur in patients living or working in moisture-damaged buildings. In the beginning, these symptoms are usually reversible, mild, and present irritation of mucosa and increased morbidity due to respiratory tract infections and asthma-like symptoms. Later, the disease may become chronic and a patient is referred to a doctor where the assessment of dampness and mold hypersensitivity syndrome (DMHS) often presents diagnostic challenges. Currently, unanimously accepted laboratory tests are not yet available. Therefore, the diagnosis of DMHS is clinical and is based on the patient’s history and careful examination. In this publication, I reviewed contemporary knowledge on clinical presentations, laboratory methods, and clinical assessment of DMHS. From the literature, I have not found any proposed diagnostic clinical criteria. Therefore, I propose five clinical criteria to diagnose DMHS: (1) the history of mold exposure in water-damaged buildings, (2) increased morbidity to due infections, (3) sick building syndrome, (4) multiple chemical sensitivity, and (5) enhanced scent sensitivity. If all the five criteria are met, the patient has a very probable DMHS. To resolve the current problems in assigning correct DMHS diagnosis, we also need novel assays to estimate potential risks of developing DMHS.

HLA-check: evaluating HLA data from SNP information

Background

The major histocompatibility complex (MHC) region of the human genome, and specifically the human leukocyte antigen (HLA) genes, play a major role in numerous human diseases. With the recent progress of sequencing methods (eg, Next-Generation Sequencing, NGS), the accurate genotyping of this region has become possible but remains relatively costly. In order to obtain the HLA information for the millions of samples already genotyped by chips in the past ten years, efficient bioinformatics tools, such as SNP2HLA or HIBAG, have been developed that infer HLA information from the linkage disequilibrium existing between HLA alleles and SNP markers in the MHC region.

Results

In this study, we first used ShapeIT and Impute2 to implement an imputation method akin to SNP2HLA and found a comparable quality of imputation on a European dataset. More importantly, we developed a new tool, HLA-check, that allows for the detection of aberrant HLA allele calling with regard to the SNP genotypes in the region. Adding this tool to the HLA imputation software increases dramatically their accuracy, especially for HLA class I genes.

Conclusion

Overall, HLA-check was able to identify a limited number of implausible HLA typings (less than 10%) in a population, and these samples can then either be removed or be retyped by NGS for HLA association analysis.

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest

Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, <27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.

Comparison of HLA allelic imputation programs

Imputation of human leukocyte antigen (HLA) alleles from SNP-level data is attractive due to importance of HLA alleles in human disease, widespread availability of genome-wide association study (GWAS) data, and expertise required for HLA sequencing. However, comprehensive evaluations of HLA imputations programs are limited. We compared HLA imputation results of HIBAG, SNP2HLA, and HLA*IMP:02 to sequenced HLA alleles in 3,265 samples from BioVU, a de-identified electronic health record database coupled to a DNA biorepository. We performed four-digit HLA sequencing for HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1 using long-read 454 FLX sequencing. All samples were genotyped using both the Illumina HumanExome BeadChip platform and a GWAS platform. Call rates and concordance rates were compared by platform, frequency of allele, and race/ethnicity. Overall concordance rates were similar between programs in European Americans (EA) (0.975 [SNP2HLA]; 0.939 [HLA*IMP:02]; 0.976 [HIBAG]). SNP2HLA provided a significant advantage in terms of call rate and the number of alleles imputed. Concordance rates were lower overall for African Americans (AAs). These observations were consistent when accuracy was compared across HLA loci. All imputation programs performed similarly for low frequency HLA alleles. Higher concordance rates were observed when HLA alleles were imputed from GWAS platforms versus the HumanExome BeadChip, suggesting that high genomic coverage is preferred as input for HLA allelic imputation. These findings provide guidance on the best use of HLA imputation methods and elucidate their limitations.

Novel Associations Between Major Histocompatibility Complex and Pediatric-onset Inflammatory Bowel Disease

PURPOSE

Major histocompatibility complex (MHC) genes have been widely studied in adult inflammatory bowel disease (IBD), but data on MHC genes are scarce in pediatric IBD. This study focused on MHC association of genes with pediatric-onset IBD and its different phenotypes.

METHODS

Blood samples of 103 patients with pediatric IBD (Crohn disease or ulcerative colitis) were collected at Children's Hospital, University of Helsinki, Finland. HLA-A, -B, -DRB1 alleles and complement C4A and C4B gene copy numbers were determined and constructed into haplotypes by a Bayesian algorithm (PHASE). A general population cohort (n = 149) served as a control. HLA-alleles and C4 deficiency frequencies were compared between patients and controls with χ-squared and Fisher exact test with Bonferroni correction (Pcorr).

RESULTS

One MHC haplotype HLA-A03; HLA-B07; 1 C4A gene; 1 C4B gene; HLA-DRB115 was more common in Crohn disease and ulcerative colitis than in controls (7/61, 11.5%, 6/42, 14.3% and 1/149, 0.7%, respectively, odds ratio (OR) = 19.19, 95% CI 2.31-159.57, Pcorr = 0.004 for Crohn disease vs controls and OR = 24.67, 95% CI 2.88-211.36, Pcorr = 0.002 for ulcerative colitis vs controls). Two MHC markers were associated with clinical characteristics. HLA-DRB101 was more common in patients with milder disease course, that is, no need for anti-tumor necrosis factor (TNF)-α medication (18/32, 56.2% vs 19/71, 26.8% without and with anti-TNF-α medication, respectively, OR = 0.28, 95% CI 0.12-0.68, Pcorr = 0.032). C4B deficiency (<2 C4B genes) was associated with complicated recovery after surgery (12/16, 75.0% vs 4/16, 25.0%, respectively, OR = 9.00, 95% CI 1.82-44.59, Pcorr = 0.025).

CONCLUSIONS

One MHC haplotype is strongly linked with pediatric-onset IBD, whereas the need for immunomodulatory therapy and surgery outcome associates with other distinct MHC gene markers.

Novel 6p21.3 Risk Haplotype Predisposes to Acute Coronary Syndrome

BACKGROUND

The HLA-DRB1*01 allele of the human leukocyte antigen has been associated with acute coronary syndrome. Genome-wide association studies have revealed associations with human leukocyte antigen and non-human leukocyte antigen genes of 3 major histocompatibility complex gene classes but not at allelic level.

METHODS AND RESULTS

We conducted a large-scale genetic analysis on a case-control cohort comprising 5376 acute coronary syndrome cases and 4852 unrelated controls from 4 populations of 2 European countries. We analyzed the risk candidate allele of HLA-DRB1*01 by genomic real-time polymerase chain reaction together with high-density single nucleotide polymorphisms of the major histocompatibility complex to precisely identify risk loci for acute coronary syndrome with effective clinical implications. We found a risk haplotype for the disease containing single nucleotide polymorphisms from BTNL2 and HLA-DRA genes and the HLA-DRB1*01 allele. The association of the haplotype appeared in 3 of the 4 populations, and the direction of the effect was consistent in the fourth. Coronary samples from subjects homozygous for the disease-associated haplotype showed higher BTNL2 mRNA levels (r=0.760; P<0.00001).We localized, with immunofluorescence staining, BTNL2 in CD68-positive macrophages of the coronary artery plaques. In homozygous cases, BTNL2 blocking, in T-cell stimulation assays, enhanced CD4(+)FOXP3(+) regulatory T cell proliferation significantly (blocking versus nonblocking; P<0.05).

CONCLUSIONS

In cases with the risk haplotype for acute coronary syndrome, these results suggest involvement of enhanced immune reactions. BTNL2 may have an inhibitory effect on FOXP3(+) T cell proliferation, especially in patients homozygous for the risk alleles.

CLINICAL TRIAL REGISTRATION

https://www.clinicaltrials.gov; Unique Identifier: NCT00417534.

Immunogenetics of type 1 diabetes: A comprehensive review

Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing beta cells in the pancreas. Prevention of T1D will require the ability to detect and modulate the autoimmune process before the clinical onset of disease. Genetic screening is a logical first step in identification of future patients to test prevention strategies. Susceptibility to T1D includes a strong genetic component, with the strongest risk attributable to genes that encode the classical Human Leukocyte Antigens (HLA). Other genetic loci, both immune and non-immune genes, contribute to T1D risk; however, the results of decades of small and large genetic linkage and association studies show clearly that the HLA genes confer the most disease risk and protection and can be used as part of a prediction strategy for T1D. Current predictive genetic models, based on HLA and other susceptibility loci, are effective in identifying the highest-risk individuals in populations of European descent. These models generally include screening for the HLA haplotypes "DR3" and "DR4." However, genetic variation among racial and ethnic groups reduces the predictive value of current models that are based on low resolution HLA genotyping. Not all DR3 and DR4 haplotypes are high T1D risk; some versions, rare in Europeans but high frequency in other populations, are even T1D protective. More information is needed to create predictive models for non-European populations. Comparative studies among different populations are needed to complete the knowledge base for the genetics of T1D risk to enable the eventual development of screening and intervention strategies applicable to all individuals, tailored to their individual genetic background. This review summarizes the current understanding of the genetic basis of T1D susceptibility, focusing on genes of the immune system, with particular emphasis on the HLA genes.

The immunogenetics of multiple sclerosis: A comprehensive review

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system and common cause of non-traumatic neurological disability in young adults. The likelihood for an individual to develop MS is strongly influenced by her or his ethnic background and family history of disease, suggesting that genetic susceptibility is a key determinant of risk. Over 100 loci have been firmly associated with susceptibility, whereas the main signal genome-wide maps to the class II region of the human leukocyte antigen (HLA) gene cluster and explains up to 10.5% of the genetic variance underlying risk. HLA-DRB1*15:01 has the strongest effect with an average odds ratio of 3.08. However, complex allelic hierarchical lineages, cis/trans haplotypic effects, and independent protective signals in the class I region of the locus have been described as well. Despite the remarkable molecular dissection of the HLA region in MS, further studies are needed to generate unifying models to account for the role of the MHC in disease pathogenesis. Driven by the discovery of combinatorial associations of Killer-cell Immunoglobulin-like Receptor (KIR) and HLA alleles with infectious, autoimmune diseases, transplantation outcome and pregnancy, multi-locus immunogenomic research is now thriving. Central to immunity and critically important for human health, KIR molecules and their HLA ligands are encoded by complex genetic systems with extraordinarily high levels of sequence and structural variation and complex expression patterns. However, studies to-date of KIR in MS have been few and limited to very low resolution genotyping. Application of modern sequencing methodologies coupled with state of the art bioinformatics and analytical approaches will permit us to fully appreciate the impact of HLA and KIR variation in MS.

The relevance of HLA sequencing in population genetics studies

Next generation sequencing (NGS) is currently being adapted by different biotechnological platforms to the standard typing method for HLA polymorphism, the huge diversity of which makes this initiative particularly challenging. Boosting the molecular characterization of the HLA genes through efficient, rapid, and low-cost technologies is expected to amplify the success of tissue transplantation by enabling us to find donor-recipient matching for rare phenotypes. But the application of NGS technologies to the molecular mapping of the MHC region also anticipates essential changes in population genetic studies. Huge amounts of HLA sequence data will be available in the next years for different populations, with the potential to change our understanding of HLA variation in humans. In this review, we first explain how HLA sequencing allows a better assessment of the HLA diversity in human populations, taking also into account the methodological difficulties it introduces at the statistical level; secondly, we show how analyzing HLA sequence variation may improve our comprehension of population genetic relationships by facilitating the identification of demographic events that marked human evolution; finally, we discuss the interest of both HLA and genome-wide sequencing and genotyping in detecting functionally significant SNPs in the MHC region, the latter having also contributed to the makeup of the HLA molecular diversity observed today.